Presenting Author: Stacey Althaus
Title: NMR Imaging Elucidates Flow Paths of Hydrocarbon and Brine in Source Rocks
During hydraulic fracturing a large amount of fracturing fluid is retained in source rock reservoirs, yet the fate of this fluid and its effects on hydrocarbon production are still unclear. It has been suggested that imbibed hydraulic fracturing fluid may damage the formation and impact the efficiency of hydrocarbon production from source rock reservoirs. Alternatively, others have reported that short enhanced early hydrocarbon production after periods of shut-in time after hydraulic fracturing in some unconventional reservoirs. This study aims to shed light on the effect of hydraulic fracturing fluids by elucidating hydrocarbon and brine flow paths in a carbonaceous source rock reservoir using nuclear magnetic resonance (NMR) spectroscopy and magnetic resonance imaging (MRI) to track the spatial and temporal process of fluid during spontaneous imbibition of oil or brine into core plugs. In this study the fluids are introduced separately to the core plugs and the behavior of each is monitored by NMR. Large amounts of oil were found to rapidly imbibe into the studied plugs, whether it was conducted before or after brine imbibition, suggesting that imbibed brine does not block the oil imbibition. A smaller amount of brine, approximately 1 pu in most samples, imbibed into the plugs, regardless if oil had imbibed first or not. It was also found that the majority of brine imbibed only into the fractures. Overall, this NMR study revealed that the flow paths for water and oil appear to be independent in the studied reservoir rocks, with the exception of fractures, which appear to allow either fluid to flow through. This information can be used in reservoir planning and management as it gives us further insight into water blocking and flowback in reservoir production.
Presenting Author: Dr. Ombeline Danton, University of Basel
Title: Saponins from saffron corms inhibit the secretion of pro-inflammatory cytokines
Corms are obtained as a by-product during the cultivation of saffron (Crocus sativus). In a project aimed at the valorization of this waste product, we observed that a 70% EtOH extract of the corms and particularly a Diaion HP-20 methanolic fraction thereof inhibited the TNF-a/IFN-g-induced secretion and gene expression of the chemokines IL-8, MCP-1 and RANTES in human HaCaT cells. The effects were partly stronger than those of the positive control hydrocortisone. After semi-preparative HPLC separation of the methanolic fraction, the activity could be assigned to a major broad peak in the ELSD trace. For preparative isolation, the 70% EtOH extract was partitioned between n-butanol and water. Separation of the n-butanol-soluble fraction by centrifugal partition chromatography (CPC), followed by preparative HPLC on RP-18 and HILIC columns afforded eight bidesmosidic glycosides of echinocystic acid bearing a fatty acid residue attached to the glycosidic moiety at C-28. The two main components were identified as azafrines 1 and 2 , while the other compounds were previously unreported congeners. Saffron saponins significantly inhibited TNF-a/IFN-g-induced secretion of RANTES in human HaCaT cells at 1 M (p < 0.001). Some of them further lowered TNF-a/IFN-g-induced gene expression. Saffron corm extracts and their saponin constituents may have a potential for the development of new cosmetic and/or medicinal products against inflammatory skin conditions.  Rubio-Moraga H, Gerwig GJ, Castro-Diaz, NC, Jimeno ML, Escribano J, Fernandez JA, Kamerling JP. Triterpenoid saponins from corms of Cro
Presenting Author: Dr. Lauren Lytwak, MilliporeSigma
Title: Use of Quantitative NMR for the Certification of Reference Materials
Determining a material's content, purity factor, or mass purity is critical to the production of Certified Reference Materials (CRMs) with a certified concentration. Depending upon the properties of the material, purity factor can be determined by different methods, such as assay to a known, like substance or mass balance certification. Assays are limited by the availability of a suitable certified assay standard. The mass balance approach is derived independently of comparison to a like substance and primarily utilizes chromatography (liquid or gas) with detection by UV absorbance or flame ionization detection (FID) for quantification of organic impurities, Karl Fischer titration for the determination of residual water, gas chromatography-FID for quantification of residual organic solvents, and residue on ignition (ROI) analysis for determination of residual inorganic content. Metrological traceability and measurement uncertainty of mass balance determinations are dependent on the calibration and traceability of all the component tests. Mass balance is versatile, but has limitations related to detector response and resolution. Quantitative 1H NMR (qNMR) has emerged as an orthogonal mass purity technique to the traditional mass balance approach. qNMR provides independent determination of content by comparison to an unrelated NMR standard and is directly traceable to SI units of mass and mole. qNMR offers advantages over the mass balance approach in terms of efficiency and impurity selectivity but exhibits some limitations related to spectral resolution, material properties, and technical expertise. Mass purity, as determined by mass balance and qNMR, has been compiled for a library of materials with a wide variety of material properties. Comparison of the benefits and challenges associated with these techniques will be discussed.
Presenting Author: Dr. Leonid Grunin, Resonance Systems
Title: Up-to-date Industrial Applications of Time-Domain NMR
Avalanche-like explosion of digitalization and cloud technologies of the Internet of Things (IoT) nowadays embrace nearly every branch of human activity starting from intelligent kitchenettes, amateur DIY by microcontrollers, wireless remote car maintenance and ending up at total automation of factory mass production, logistics and artificial intelligence in companies' boards of directors. According to forecasts of experts the market of sensors that are involved in digital life flow will be increased in a geometrical progression for the upcoming decade. This fact is bringing up new requirements for every analytical technique to migrate from stationary laboratory setups to inexpensive robust miniature modular sensors that can be immersed in standardized online solutions.
There is a good chance for the Time-Domain NMR (TD-NMR) to merge into this trend involving recent progress in permanent magnets, microelectronics and embedded software technologies. The presented talk is uncovering some aspects of the marked issue:
1. Development of miniaturized and cost effective hardware;
2. Easiness of installation;
3. Very robust, accurate and fast measurement techniques;
4. Reliable models of Sensor+Sample (development of Digital Twins)
5. Accessibility for online performance control and data analyzing/storing via Application Programming Interface (API) of IoT systems.
The following measurement techniques of TD-NMR will be discussed:
• Solid Fat Content (SFC) and Total Fat Content (TFC) - mostly in food products
• Oil content - in food, seeds, artificial tissues (Spin Finish)
• Sugar content - in food and dairy products
• Moisture - in food, gun powders, sand, fuels (calorific value)…
• 1H (proton) density - for fuels, polymers…
• Na, Fe, Al, P, Ca, F, N… content
• Droplet size distribution - oil and water droplet sizes in emulsions
• Specific Area - for particles dispersions and sorbents
• Particles size - for particles dispersions
• Pores volume - for adsorbent, construction materials
• Molecular weight and chain length - for medium size oligomers and fats
• Crystallinity - from sugars and celluloses to artificial polymers, their solubility and density
• Crosslinking - for elastic polymers network
• Purity of water and paramagnetic ions in trace concentrations for environmental research
With special attention to Double Quantum NMR relaxation measured by a TD-NMR instrument.
Presenting Author: Dr. Thorsten Maly, Bridge12, Technologies, Inc.
Title: High-Resolution, Solution-State ODNP-enhanced NMR Spectroscopy at Low Magnetic F
Dynamic Nuclear Polarization (DNP) is a technique capable of boosting the sensitivity of an NMR experiment by two to three orders of magnitude. Currently, the method is mostly used in solid-state NMR experiments to enhance signal intensities at magnetic fields strengths corresponding to NMR frequencies up to 900 MHz. As a result, DNP enables scientists to conduct experiments that were unthinkable even a decade ago. DNP for solution-state NMR experiments is a much more challenging task, due to the high dielectric losses of the solvent, which leads to microwave induced sample heating. Solution-state DNP, based on the Overhauser effect (ODNP), is therefore typically performed at low magnetic field strengths. At 0.35 T, corresponding to a proton Larmor frequency of 14.5 MHz, many concepts from X-band EPR spectroscopy can be applied to build efficient ODNP resonators with minimal sample heating. However, at this low magnetic field the overall sensitivity is low, especially for low-gamma nuclei, and the resolution is often poor. Here, we demonstrate high-resolution, ODNP-enhanced NMR spectroscopy at 0.35 T on samples of small molecules such as ethyl crotonate and aspirin (see Figure 1). Even at a polarizing agent concentration of 10 mM TEMPO we are able to resolve the J-coupling and many features of the NMR spectrum. Until now, X-band ODNP spectroscopy has been typically used to study hydration dynamics of water molecules of bio-macromolecular surfaces. Here we demonstrate in-situ ODNP to enhance NMR signals at low magnetic fields. The application to reaction monitoring of small molecules and studies of crude oil samples will be discussed along with its application to enhance NMR signals of different nuclei such as 19F and 31P and two-dimensional NMR spectroscopy.
Presenting Author: Dr. Dimitris Argyropoulos, Advanced Chemistry Development UK Ltd
Title: Efficient Approaches for Addressing Spectral Ambiguities in CASE Systems
Computer Assisted Structure Elucidation (CASE) systems (or expert systems, ES) have been around for more than 50 years and have helped tremendously in the elucidation of structures of new organic compounds, both natural products and synthesized ones, that were very difficult or even impossible to solve with the traditional (manual) methods [1,2]. Contemporary ES are based on the utilization of 1D and 2D NMR spectra, given that the molecular formula is determined from HR-MS. Today there are several free and commercial CASE systems. The main advantages  of these ES are: i) ES deliver all (without any exception) structures which can be deduced from a given set of NMR data; ii) Application of fast empirical methods for NMR chemical shift prediction allows the program to select the most probable structure; iii) If necessary, DFT based chemical shift calculations are used to confirm the selected structure; iiii) ES are now capable of suggesting a 3D model of the elucidated structure. However advanced, expert systems are still susceptible to a series of limitations which impede structure elucidation by a human expert. These limitations are mainly associated with the ambiguity of the experimental data, as well as with intersection of chemical shift characteristic ranges in NMR spectra. An experimental ambiguity can result from the lower resolution of the 2D spectra, which prohibits proper assignment of peaks to closely spaced signals. Ambiguity of a second kind is often present in the hybridization state of carbon atoms that show signals in the same regions of NMR spectra. For instance, a 13C NMR signal observed at 90 ppm can be assigned either to an sp2-hybridized carbon or to an sp3 carbon connected to one or two oxygen atoms. If a molecule contains atoms of variable valence (for instance N and/or P) then, strictly speaking, all possible valences of these atoms should be searched during structure generation. It can happen also that some carbon atoms have no HMBC or COSY correlations at all; this is especially probable for molecules with severe deficit of hydrogen atoms, and consequently such atoms appear as "floating", i.e. could potentially be connected to any other atom. The presence of "floating" atoms increases significantly both the size of the output and the time of structure generation. To remove uncertainty in spectroscopic data, additional experiments are usually carried out; for example a higher resolution 2D spectrum, in the form of either a highly inflated NUS or a band selective one, could help with reliably assigning the correlation. Additional spectroscopic data (IR, Raman, UV-Vis,) could help with identifying characteristic groups and resolving hybridization or valence problems. However these will not help in all cases. The only method that remains if the above fail is the exhaustive investigation of all alternatives ensuing from the presence of any ambiguity. For instance, if there are five carbon atoms showing signals in the range of 70-120 ppm of the 13C NMR spectrum, then 25=32 combinations of hybridization (sp3 or sp2) have to be checked during structure generation, which significantly extends the structure generation time. In this poster we will consider approaches which were developed in order to get a solution to the problem of structure elucidation as fast as possible under condition that the initial data contain many ambiguous assumptions, taking advantage of modern programming developments. Examples will be presented, showing the strength of the techniques, together with analysis of the limitations of each approach.  Blinov, K.A.; Elyashberg, M.E.; Martirosian, E.R.; Molodtsov, S.G.; Williams, A. J.; Sharaf, M. M. H.; Schiff, P. L. Jr.; Crouch, R.C.; Martin, G. E.; Hadden, C.E.; Guido J.E.; Mills, K.A., Quindolinocryptotackieine: the Elucidation of a Novel Indoloquinoline Alkaloid Structure Through the Use of Computer-Assisted Structure Elucidation and 2D NMR. Magn. Reson. Chem., 41, 577-584 (2003)  M.E. Elyashberg, K.A. Blinov, S.G. Molodtsov, A.J. Williams., Elucidating "Undecipherable" Chemical Structures Using Computer Assisted Structure Elucidation Approaches, Magn. Reson. Chem., 2012, 50, 22-27  M. Elyashberg, D. Argyropoulos. NMR-based Computer-assisted Structure Elucidation (CASE) of Small Organic Molecules in Solution: Recent Advances. eMagRes, 2019, Vol 8: 239-254
Presenting Author: Jonathan Farjon, University of Nantes
Title: Benchtop NMR spectroscopy with advanced pulse sequences, a sensor for processes
ABSTRACT Emerging benchtop NMR instruments are attractive analytical tools for routine industrial applications because they are low-cost, transportable and robust . However, at lower magnetic fields NMR spectra suffer from a low sensitivity and a weak spectral resolution. In order to circumvent these limitations, we recently implemented advanced high-resolution NMR techniques on a 1T benchtop NMR instrument equipped with a gradient coil. Recent advances include tailored solvent suppression , DOSY , pure-shift methods  and ultrafast 2D NMR . Thanks to these developments, we have been able to tackle exciting industrial challenges. We focused on microalgae since they have a tremendous potential for a variety of applications in the fields of food and energy. Several microalgae species present the ability to produce lipids thanks to a metabolic shift provoked by nitrogen starvation cultivation conditions . In order to better understand these phenomena and optimize the lipid production, biological and process research works are carried out by a substantial research community. In this context, we developed an on-line and real-time approach for the monitoring of lipids in microalgae cultures . A 43 MHz NMR spectrometer was used for the first time for the non-invasive monitoring of the entire living microalgae without major bioprocess adjustments. Thanks to the implementation of a gradient coil in the hardware, the dominating water peak could be efficiently removed through an excitation-sculpting pulse sequence . The main peak from in vivo lipids (1.2 ppm) thus provided a measurement of total lipids, allowing to monitor the biological process in real time  which is not possible with other analytical methods primarily because of the water contribution on the global NMR signal. In order to move these developments towards an industrial scale, this benchtop spectrometer was coupled to a photobioreactor, an automated device for microalgae cultivation. For the first time, the real time, in vivo access to lipid production kinetics were monitored over 3 weeks with this NMR hyphenated apparatus (publication in preparation). Our recent results in monitoring a cell-based bioprocess demonstrates one of the possibilities of benchtop NMR as an online sensor. The adaptive feature of NMR thanks to the wide range of pulse sequence approaches and its inherent reproducibility make it a suitable device for the monitoring of different kind of industrial processes. ACKNOWLEDGMENTS The National Center for Scientific Research and Région Pays de la Loire are acknowledged for funds.
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Presenting Author: Dr. Hilary Fabich, ABQMR Inc.
Title: Imaging sorghum roots in natural soil
It is relatively easy to measure the parts of crop plants that are above ground to improve agricultural procedures and plant genetics. Nonetheless, the roots are important parts and the world lacks a good way to measure their configuration in situ. One typically digs the roots up and washes off the soil (shovelomics), meaning it is impossible to preserve the root configuration in the ground. During this project, a field-deployable MR imaging system was developed to image the roots of energy sorghum (Sorghum bicolor) in natural soils. Previous plant-root MRI pursuits were complicated by the fact that almost all natural soils have high magnetic susceptibility and researchers used their existing high-field laboratory MRI systems. Either high-susceptibility soils distorted the images or the water in special synthetic or low-susceptibility soils had similar relaxation to the water in roots and the two were difficult to separate. First we constructed a prototype 47 mT (2 MHz proton resonance) electromagnet, magnetic field gradient coils, and a quadrature, double-saddle RF coil to image 250 ml samples. At this lower field, water in roots in natural soils has T1 about 1 s, and T2 about 300 ms. Water in natural soils has T1 about 4 ms and T2 about 1 ms. By using a 16-echo, spin-warp sequence with 7 ms echo spacing, we avoid signal from soil water and make images of roots alone. After the successful application of the prototype to root imaging, we built a full scale model with a 1700 ml sample volume (27 cm diameter נ27 cm height cylinder). The signal-to-noise ratio (SNR) is expectedly low compared to higher-field systems. It currently takes about 9 hours to make a fully sampled 3D image. Alternatively, in a bit under 2 hours we take 8 2D spin-warp images (third dimension is unresolved) with equally-spaced view angles that rotate 180 degrees around the vertical axis. When the images are played as frames in a video, the roots appear to rotate about the vertical axis; the mind's eye constructs a 3D image of the roots. One can stop the video at appropriate views to measure branching angles and one can extract root diameters. Thus, we gain the necessary biological information without a full 3D image in about 20% of the scan time. We also take advantage of the fact that the roots are sparse and appear as light streaks against a dark background. We can detect roots smaller than the voxel size and ascertain the partial volume they fill by pixel brightness. Thus, we can use coarse-resolution images that deliver relatively high SNR in short scan times. In the field-deployable system, the roots remain in situ but the soil around them is excavated to make room for the MRI system. Before soil excavation, a 244 mm ID, 267 mm OD PVC pipe is pressed into the ground around the chosen plant roots to maintain them in their natural configuration. An approximately 700 mm diameter annular hole is excavated around the sample and the MRI system (620 mm OD and 279 mm clear bore) is lowered in place for imaging.
Presenting Author: Henry R.N.B. Enninful
Title: Development of a novel NMR Cryoporometry technique for characterizing mesoporous solids
Liquid-solid phase transitions in porous materials exhibit behaviors with marked changes from their bulk forms. These distinct properties have direct applications in reservoir rock characterization, drug delivery, preservation of food and historical artifacts, among others. Strong confinement effects, which are responsible for the aforementioned alterations of the fluid properties, are still not fully understood with aspects remaining as matters of debate. The NMR cryoporometry technique employs the melting and freezing point depression of liquids in pores to predict the distribution of pores in a given porous solid. Presumed to occur under thermodynamic equilibrium, melting is treated as a pore-independent phenomenon. Compounded by another assumption of a constant non-frozen (NFL) layer thickness, over-estimated pore sizes are obtained, which can be detrimental in drawing a suitable catalysis or filtration program for industrial purposes. In this work, we apply the recently developed serially-connected pore (SCPM) model, which takes into account the complex phase transitions arising from pore interconnectivity. Herein, both equilibrium and metastable thermodynamic conditions for different parts of the system are considered. In implementation, we introduce kernels which incorporate a variable NFL thickness with pore size and temperature relation and a pore transition which accounts for the elimination of metastability in very small pores. These modifications offer a more accurate characterization toolbox for NMR cryoporometry. For validation, we perform NMR cryoporometry studies of water in MCM-41 and SBA-15 porous materials to validate this approach and provide useful insights into the structure of the materials. References  Kondrashova, D., and Valiullin, R. (2013)., Microporous Mesoporous Mater. 178, 15-19.  Schneider D., Kondrashova D., and Valiullin, R. (2017), Sci. Rep. 7:7216.  Enninful H.R.N.B., Schneider D, Hoppe A, König S, Fröba M, Enke D. and Valiullin R., (2019), Front. Chem. 7:230.  Schneider D., Valiullin R., (2019), J. Phys. Chem. C, DOI:10.1021/acs.jpcc.9b03626  Enninful H.R.N.B., Schneider D, Kohns Richard, Enke D. and Valiullin R., (2020), Microporous Mesoporous Mater., 110534.
Presenting Author: Jessica Litman, ACD/Labs
Title: Detection of Multiplets in 13C Spectra Using Structure Aware Algorithms
Software that is capable of Automatic interpretation of NMR spectra is highly demanded in the modern chemical and pharmaceutical industry. Every day scientists record hundreds of NMR spectra that need to be interpreted. Interpretation of such large numbers of spectra can be quite daunting and prone to human error, which makes it a good candidate for automation. The first step is the reliable detection of the peaks and multiplets in the recorded spectra. This seemingly simple task can become quite complicated if the structures contain heteroatoms such as 19F and 31P that give rise to additional peak splittings in the 1D 13C and heteronuclear 2D spectra. With up to 30% of the commercial pharmaceutical APIs and agrochemicals containing either a 19F and/or a 31P atom, the need for a reliable peak detection algorithm in these chemicals is quite clear. The traditional way of accomplishing this task is to select all the visible peaks in the 1D 13C spectrum and define them as singlets. For specific patterns, for example three evenly spaced peaks with a 1:2:1 intensity ratio, a triplet will be defined and treated as a single multiplet. A similar procedure is followed for patterns that fit into quartets, however, there is no reliable method for doublets. Moreover, the whole procedure fails when the two outer peaks of the multiplet with lower intensities are not observed at all. Another common problem is the overlapping of multiplets, since these are usually quite broad and the 19F and 31P nuclei are usually coupled to more than one carbon. In this latter case, the procedure will fail as well. Peak interpretations can become even more complicated in 2D spectra with characteristic diagonal peak patterns causing confusion even to some experts. Even though for F-containing chemicals the problem can be alleviated by using costly required hardware and recording a spectrum with additional 19F decoupling, there is no such practical option for 31P. Here we present a more generalized method for multiplet detection in such spectra, which resembles the way a human analyst would follow. Since a proposed structure usually exists with the positions of the fluorine and phosphorus atoms defined, the human expert would specifically know what to look for, instead of starting from zero. The way this can be implemented in software is by predicting the spectrum of the proposed structure and then looking for similar patterns in the experimental spectra. If such patterns are found then the multiplets are defined correctly and the analysis can proceed without getting a false negative result, and need for manual inspection. This study will demonstrate examples of overlapped and low-intensity multiplets arising from 19F and/or 31P couplings and how these are consistently detected using this approach, as well as characteristic 2D spectra with the associated problems completely resolved.
Presenting Author: Dr. Padmanava Pradhan, City College of CUNY
Title: Study of diastereoselective addition reactions to polycyclic aromatic hydrocarbons
Polycyclic aromatic hydrocarbons (PAHs) are widespread environmental contaminants formed due to incomplete combustion of organic matter and activities of a modern society (1). Metabolism of PAH in mammalian cells results in the formation of vicinal diol epoxides, considered as ultimate carcinogens, if the oxirane ring is located in a bay- or fjord-region of the parent compound (2). The mutagenicity of the stereoisomers of the fjord-region diol epoxides of benzo[c]phenanthrene (BcPh), and as well as of the diol epoxides of benzo[a]pyrene (BaP) is due to the formation of several isomeric adducts formed by covalent bonding to nucleophilic external amino groups of deoxyguanosine and deoxyadenosine (3). Biological and structural studies rely on the availability of chemical routes to PAH derivatives (4, 5). In this context, a series of interesting but poorly understood stereoselective reactions are used as lynchpin conversions. Chemically synthesized dihydrodiols are converted to series 1 (syn) diol epoxides via intermediate bromohydrins, which are formed via a single facial addition of Br+. Synthesis of the series 2 (anti) diol epoxides relies on a similar highly facial epoxidation by mCPBA. However, in this case hydroxyl-group directed epoxidation could be contributing. Interestingly, dihydroxylation of dihydrodiols by stoichiometric OsO4 also occurs in a highly face selective manner. These reactions for BcPh and BaP are summarized in Scheme 1 and a possible position intermediates for the former have been shown in Scheme 2. In order to study the mechanism, transition states, and stereochemistry of diastereoselective addition of dihydrodiols of PAH, DFT and other quantum computations will be carried out. During the ground state optimization of the dihydrodiols (1-2 and 7-8), we will incorporate dihedral constraints obtained from the analysis of the 1HNMR spin-spin coupling.
Presenting Author: Alexander Rueck, Sigma-Aldrich Production GmbH
Title: Development of a novel Proficiency Testing (PT) material for quantitative NMR (qNMR)
Development of a novel Proficiency Testing (PT) material for quantitative NMR (qNMR). Quantitative NMR (qNMR) spectroscopy has evolved to become one of the most important tools for content determination of organic substances and for the quantitative evaluation of impurities in various industries such as chemistry, food and pharmacy. Since the signal intensity is directly proportional to the number of protons contributing to the resonance, qNMR is considered as a relative primary method [1-3], and the validity, robustness and precision of the 1H qNMR technique has been demonstrated . While there is a comprehensive portfolio of (certified) reference materials available for qNMR calibration and method validation from various producers and vendors, up to now, there have only been limited possibilities for laboratories to participate in proficiency testing (PT) schemes. While there have been interlaboratory comparison studies conducted by various organizations, these were either only available for a regionally restricted participant circle or only for certain labs. In order to ensure easy worldwide availability of interlaboratory comparisons in the field of qNMR, a PT material for performance evaluation of qNMR analysis has been developed . The main component, which needs to be determined by a qNMR experiment, has a =90% content of the analyte. This covers a typical range in the determination of pure neat materials. The product is set up as a quick-turn study material, which means that it can be ordered any time. This leads to the advantage that the laboratory does not have to wait for a Proficiency Testing campaign to start. Analytical results can be submitted online by the user, and the result (given as Acceptable or Not Acceptable according to the statistical z-scores) will be provided shortly thereafter. The material is available worldwide to ensure that a better comparability of all the labs performing qNMR is made possible. The PT material is produced and sold under ISO/IEC 17043, ISO/IEC 17025 and ISO 17034 accreditations.  Malz F, Jancke H, Journal of Pharmaceutical and Biomedical Analysis, 38(5), 813-823, 2005  Saito T, Ihara T, Koike M, Kinugasa S, Fujimine Y, Nose K, Hirai T, Accreditation and Quality Assurance, 14(2), 79-86, 2009  De Bievre P, Dybkaer R, Fajgelj A, Hibbert BD, Pure and Applied Chemistry, 83(10), 1873-1935, 2011  Weber M, Hellriegel C, Rueck A, Sauermoser R, Wuethrich J, Accreditation and Quality Assurance, 18(2), 91-98, 2013 
Presenting Author: Alexander Rueck, Sigma-Aldrich Production GmbH
Title: Development of Certified Reference Material (CRM) solutions for quantitative Nuclear Magnetic Resonance (qNMR) and quantitative Performance Qualification (qPQ)
Development of Certified Reference Material (CRM) solutions for quantitative Nuclear Magnetic Resonance (qNMR) and quantitative Performance Qualification (qPQ). Certified Reference Material (CRM) is characterized by specific requirements, such as traceability, measurement uncertainty, homogeneity-assessment, stress- and stability-tests, expiry date, certificate and others. All these items are defined in ISO/IEC 17025 and ISO 17034 [1,2]. Through the last years, we have been working on the development of neat CRM for use in 1H, 31P and 19F qNMR [3,4]. Here we present the development of CRM solutions for qNMR, dissolved in different deuterated solvents with a certain concentration and filled into ampules. Traceability to the SI was achieved using primary reference material from the National Institute of Standards and Technology (NIST) or the National Metrology Institute of Japan (NMIJ). Working with ready-to-use solutions can be time saving for particular qNMR applications working either with internal or external standard. Especially in regulated environments, also the performance of the NMR instrument has to be demonstrated continuously according to the requirements given e.g. by the authorities or guidelines. Through a collaboration between Bruker and Sigma-Aldrich, a new CRM solution has been developed for its use as qNMR performance qualification test (qPQ) . It is a binary mixture, which consists of two common CRM for qNMR, dissolved in DMSO-d6 and delivered in ampules. The certified mass fraction values result from a combination of gravimetry and qNMR according to ISO/IEC 17025 and ISO 17034.  ISO/IEC 17025:2005, "General requirements for the competence of testing and calibration laboratories"  ISO 17034:2016, "General requirements for the competence of reference material producers"  Weber M, Hellriegel C, Rueck A, Wuethrich J, Jenks P, Obkircher M, Analytical and Bioanalytical Chemistry, 407(11), 3115-3123, 2015  Rigger R, Hellriegel C, Rueck A, Sauermoser R, Morf F, Breitruck K, Obkircher M, Journal of AOAC International, 100(5), 1365-1375, 2017 
Presenting Author: Dr. Michael Dada, Federal University of Technology, Minna, Nigeria
Title: Radiofrequency (RF) Controlled Computatioal Theranostics for Neurodegenerative Diseases
Awojoyogbe O. Bamidele, Dada O. Michael : Department of Physics, Federal University of Technology, Minna, Niger State, Nigeria Email: INTRODUCTION We have developed a Wolfram Mathematica computer program for therapeutic hypothermia to resolve the challenge of temperature monitoring which has placed limitations on the current clinical applications of state-of-the-art methods in therapeutic hypothermia. This has been achieved with the exploration of the unique tissue pathology usually embedded in NMR T1 and T2 relaxation times. In fact, the grey brain matter thermal response could help in better monitoring of hippocampal neuron temperature and thermal response of ventricular muscle. The selective thermal deposition feature of our method could prove to be an interesting addition to this monitoring such that the temperatures of ischemic volume centroid can easily be compared during reperfusion as well as rewarming. The diagnostic ability of our method could prove to be helpful in the determination of severity of injury during and after treatment. T1 and T2 could help indicate the commencement of ischemia and nature of the injury. The relaxation times also contain molecular information and hence, they could help in the use of this technique for monitoring cellular events that are affected during ischemia and assessment of protection mechanisms after reperfusion. It is important to note that this study has opened a window into the future to explore further the treatment of patients suffering from cardiac arrest and a few other clinical syndromes that feature ischemic injury. This is also true for patients who are suffering from various types of tumours. METHOD Using the Penne's Bioheat equation  and NMR relaxation parameters developed in the Bloch NMR flow equation [2-5], we show that it is possible to perform hyperthermia treatment of tumours and monitor temperature changes without the usual concern for safety of normal tissues. At the same time, it is demonstrated that by modifying the nature of the applied RF field, significant temperature reduction could be induced in order to conduct hypothermia treatment. Appropriate values of SAR ware shown to induce considerably high thermal response in tumours and very low thermal response towards neuroprotection treatment. It is observed with keen interest that time does not significantly influence the values of the temperature but x does between few millimetres to few micrometre ranges. Consequently, we presented thermal profiles when the sampled regions are within clinical limits. INNOVATIONS In comparison to most state-of-the-art methods of therapeutic hypothermia, our method has been able to achieve a drastic reduction in the time required to attain the desired tissue temperature from hours and minutes to microseconds (a time of 3s has been used in the hypothermia) . This would be helpful in the significant reduction of heat loads on tissues. Secondly, this study uses radiofrequency pulses which rely on tissue spin magnetic resonance and hence, able to penetrate deep organs. The RF penetration is selective able to provide thermal profiles of white brain matter and gray brain matter. Our technique is able to provide hypothermia treatment to deep organs and do so selectively to components of organs. This technique is able to achieve an impressive temperature monitoring and feedback with the incorporation of NMR relaxation times and control parameters such that thermal response monitoring problems associated with current state-of-the-art methods are resolved. This is cheaper to implement for clinical applications. The method is less cumbersome, not limited to the in-hospital environment and does not have stringent surroundings clean requirements. This is due to its portability and non-invasiveness and could open immense opportunities for use during clinical emergencies. CONCLUSION In comparison with other state-of-the-art methods, we have presented a radiofrequency ablation method, which uses a relatively lower frequency (64MHz), specifically targeted only to the tumour while keeping the temperature of surrounding normal tissues relatively normal and gives feedback on tissue state via the T1 and T2 relaxation times. These features have been demonstrated clearly with experimental data. Unlike other methods, which require other clinical techniques to observe tissue response after treatment, our theranostic method could simultaneously treat tumours with thermal deposition while monitoring the tissue response through NMR relaxation times and thermal conductivity. This feature could be used for local hyperthermia in order to treat superficial, intracavital, intraluminal and intracranial tumours with sizes even smaller than 3cm. Comparably, the same RF energy used for normal tissue produced high temperature levels (11oC increase) in cancer tissue for hyperthermia therapy subject to the controlled parameters. This may play an increasingly important therapeutic and palliative role as a minimally invasive alternative to surgery. FURTHER INVESTIGATIONS In our current investigations, we study practical ways that radiofrequency (RF) controlled computational MRI theranostics based on Penne's Bioheat equation and Bloch NMR flow equations [1-5] can be used to provide innovative data-driven solutions for the prediction, simplification, and characterization of brain tumor and its intrinsic mechanisms to promote new data-intensive, accurate diagnostics and therapeutics for neurocomputing such that all information on diagnosis, therapy, recovery, inventory, medication can be collected managed and shared effectively by using deep learning, Artificial intelligent and Internet of Things (IoT) based systems with a global connectivity.
Presenting Author: Dr. Tim Bays, Pacific Northwest National Laboratory
Title: Fuel Property Modeling from Chemical Structures Identified using 13C NMR
Determining the properties of biofuels during early-stages of development is difficult because of the small sample volumes that are typically produced. 13C NMR offers a low-volume analytical technique for quantifying the various chemical substructures within a complex fuel mixture, providing a formulation based upon the relative populations of each carbon type, averaged together from the hundreds to thousands of unique chemicals making up a fuel. These carbon type distributions can be empirically correlated to fuel properties, like octane or cetane number, through relatively simple models. In this work, models for derived cetane number and key points in the simulated distillation curve, T10, T50, and T90, were built using fuel blendstocks derived from thermochemical conversion of biomass. These models are comprised of 5-7 terms representing the most influential chemical substructures for a property. Differences among models within a set for each fuel property show the complex interactions among chemical substructures that impact fuel properties. Further refinement of the substructures and models should more fully describe these interactions. The tool allows properties to be predicted from only 50 - 200 L of blendstock, and will accelerate early-stage blendstock development. Fuel blends optimized using chemical structures identified with these models will advance new formulations from both fossil and renewable sources having fuel properties tailored for future engine designs.
Presenting Author: Igor Savukov, Los Alamos National Laboratory
Title: Development of multi-channel parallel atomic magnetometer MRI
Ultra-low field (ULF) magnetic resonance imaging (MRI) can supplement conventional several-Tesla MRI to reduce cost and realize portability, when the use of such MRI is limited. ULF MRI, for example, may be the only option for MRI in developing countries in Africa. Advantages of ULF MRI include allowed combination of magnetoencephalography (MEG) and MRI in a single instrument at the same place, installation in airport checkpoints for screening liquid explosives, deployment to detect water or oil at substantial depths with one-sided coils. However, ULF MRI has low sensitivity. Low-temperature superconducting quantum interference devices (SQUIDs) were used as the magnetic-field sensors to solve the sensitivity problem, but the cryogenic operation increases cost and limits applicability. These technological challenges can be addressed by replacing SQUIDs with atomic magnetometers (AMs) that are currently the most sensitive non-cryogenic magnetic-field sensors. Over the years we have used AMs for nuclear magnetic resonance (NMR) detection and ULF MRI. Recently we started a project for developing a parallel ULF MRI system with a single-module multi-channel AM sensor. Our approach brings the advantage of improving signal-to-noise ratio and accelerating imaging. At the meeting, we will present the description of our approach and first preliminary results.
Presenting Author: Dr. Michael Dada, Federal University of Technology, Minna, Nigeria
Title: Implementation of a Neural Network for Predicting NMR Hydrocarbon Fluid Typing
Over the past decade, we have relied on oil and gas resources found in large sedimentary reservoirs (conventional oil). However, due to ever increasing energy requirements, conventional reserves are dwindling giving way to new attention towards unconventional natural gas and oil. In order to develop these resources, new exploration methods need to be developed since the physical and chemical properties of unconventional reservoirs are significantly different from those of conventional reservoirs. Unconventional formations are usually fine-grained, organic carbon-rich strata that are both the source of and the reservoir for oil and natural gas. Furthermore, these formations are pervasive throughout over large area, and are thus known as continuous-type deposits or tight formations. Also, unconventional reservoirs may have extremely small pore sizes and lack of permeability make them resistant to hydrocarbon flow. Consequently, hydrocarbons typically remain in the source rock unless natural or induced fractures occur. The recovery of oil from these reservoirs has been helped by current developments in NMR logging through which the properties of both the fluids (oil, water or brine, miscible or immiscible gas) present in the reservoir and the rock matrix (pore network, mineral composition and their mechanical performance) can be assessed to predict remaining oil reserves and potential recovery accurately. Recently, a computational method has been developed for identifying the fluids in these restricted geometries using NMR logging data. To further this study, development of machine learning algorithms for predicting the fluid type in these unconventional reservoirs could constitute a great help in industrial applications of hydrocarbon fluid typing. In order to address this problem, the current study has implemented Python-based neural network with kernel using multilayer perceptrons to predict the type of hydrocarbon fluid found within the rock formation according to their magnetic resonance and fluid dynamic properties. These data were then distributed over all possible scenarios consistent with measurements made at B0=0.0176T. The data were then imported into a Jupyter Notebook using TensorFlow backend. In order to maintain a good accuracy, the feature of each dataset has been normalized to a range of 0-1 for processing. The data is then used to train the network which makes use of Adam Optimization Algorithm, and softmax activation function. A visualization of the dataset showing classifications of the fluids according to their measured properties is given in Figure 1 while the model summary is given in Table 1. Within the dataset, we have 300 samples in which training was performed on 240 samples while 60 samples were used for validation. Fortunately, the model returned 100% accuracy. This implies our model is perfect for predicting hydrocarbon fluid type by using the NMR relaxation and fluid dynamic properties. This results show that for each epoch, the neural network is trying to learn from its existing feature so as to predict it by its weights and biases. This model is the necessary backend needed for a system consisting NMR logging equipment to make automatic fluid prediction with minimum human intervention. The essence of this is that amount of energy and time spent on logging results interpretation would be drastically reduced. In addition to this, cost would be reduced as well.
Presenting Author: Dr. Olaf Kohlmann, Lexmar Global Inc.
Title: Study of Semicrystalline Polymer Aging by TD-NMR
Low field time-domain NMR is an analytical tool frequently used for process and quality control in polyolefin plants. One application of TD-NMR is the prediction of xylene soluble (XS) fractions in polypropylene. Due to its simplicity, shorter length of experiment and no use of hazardous chemicals compared to standard wet chemistry methods, time-domain NMR is an advantageous method for XS fraction determination. It is well known that semi-crystalline polymers exhibit morphology changes with age, often becoming more crystalline over time. A collaborative study by UMass Amherst and the LexMar Global Innovation Lab is aimed at quantifying these morphology changes with age in order to understand how they impact TD-NMR measurements. 16 random copolymer (RACO) polypropylene powder samples were heat treated (annealed) to erase prior age-induced crystallization. The samples were cooled, then analyzed at five different age intervals between several minutes and one month. Free Induction Decay signals were collected on a MagStation II laboratory NMR analyzer. Each of the FID's were fit with a regression model to quantify the crystalline, amorphous, and interphase domains. A Gaussian-Exponential-Exponential function was shown to have the most accurate fit of any of the investigated models. It was found that both phase fractions and relaxation rates changed with sample age for all investigated samples. In addition, a predictive model of XS was generated using a transformation of the extracted fit parameters of least aged samples. This model was then applied to the other samples to quantify the impact sample age would have on time-domain NMR XS measurement accuracy.
Presenting Author: Yiyong He, DuPont
Title: Cr(acac)3 Effects on 13C NMR Experiments under Various Conditions
Cr(acac)3 is a well recognized relaxation reagent for NMR experiments. However, there is always a comprise between time saving and spectral quality. In this work, the effects of the relaxation reagent Cr(acac)3 on 13C NMR spectral resolution and spin-lattice relaxation times (T1) have been systematically investigated in common NMR solvents. Optimum Cr(acac)3 concentrations were recommended for each solvent, which corresponds to a desired 1 Hz spectral resolution. The effect of Cr(acac)3 on 13C NMR data at different temperatures was studied as well. This report provides a detailed guidance for using Cr(acac)3 in 13C NMR experiments. It demonstrated that the appropriate use of Cr(acac)3 will significantly reduce 13C NMR data acquisition time without compromising data quality too much.
Presenting Author: Lewis Robertson, CSIRO
Title: Enhanced Methods of Nuclear Quadrupole Resonance for 14N Detection in Sodium Nitrite FROM An Enhanced Method of Nuclear Quadrupole Resonance for 14N Detection in Explosives and Narcotics
The capability to efficiently identify security-sensitive substances is a tool of paramount importance in defence and security industries all over the world. Various technologies that are (or have been) developed for this purpose include scent and chemical based methods, X-ray and UV spectrometry and even neutron activation. These techniques are characterised by high rates of false positive results, require time consuming preparation of the sample material or are unsuitable when applied in the field (outside of the laboratory). Nuclear Quadrupole Resonance (NQR) is a radio frequency (RF) spectroscopic technique that probes the nuclear spin states of a material and is uniquely felicitous to the prompt detection of explosive substances. This is because the technique does not demand any sample preparation and is extremely sensitive to the electronic environment of the target nucleus, facilitating the specific identification of various substances. My research involves performing, designing and modelling magnetic resonance (MR) experiments on a custom built NQR spectrometer at CSIRO, Lucas Heights. In particular, my preliminary PhD work is focused on investigating the response of Sodium Nitrite (an explosive precursor and test substance) to multi-pulse excitation. This research has a broader purpose of contributing to the characteristation of Sodium Nitrite as a quadrupolar material and explosive precursor as well as attempting to discern the nature of the observed spin dynamics. Multi-pulse excitation techniques involve the repeated application of a radio frequency pulse of magnetisation to the sample in order to induce a steady-state signal, causing the spin system to 'lock' itself in place. These sequences drastically reduce the signal acquisition time needed to detect a substance. However, the most commonly used sequences are observed to respond extremely inconsistently to variations in the transmission frequency of the RF pulse, which is unpropitious due to the sensitivity of the quadrupolar resonance to temperature changes. There is currently no pulse sequence in existence that can account for the temperature instability of the NQR resonance line. An optimised SORC sequence was found to significantly lessen oscillations in the standard multi-pulse frequency response of 14N in Sodium Nitrite. This was achieved through the utilisation of peculiar phase reversals and signal resurgence effects in the analysis of each response that had a net effect of increasing SNR. This phenomena has not been previously observed in our laboratory or the available literature.
Presenting Author: Lauren Switala, Lonza
Title: Solid State NMR as an Orthogonal Technique for Crystallization Detection in Amorphous Dispersions
This work explored the use of solid state proton NMR to detect crystallinity in otherwise amorphous solids. Studying the relaxometry of nuclear spins can indicate differences in chemical environment and/or phase state. Generally, amorphous materials exhibit higher mobility than crystalline solids, resulting in shorter relaxation times. The local molecular motion controls the rate of magnetic field fluctuations which are responsible for T1? relaxation. By observing how NMR signals decay differently with varying relaxation delay time in the experiment's pulse sequence, phase separation can be detected, and, ultimately, quantified. Here, a spray-dried dispersion (SDD) of 25% sulfasalazine and 75% polymer (PVPVA-64) was examined by solid state NMR as a case study for low-level crystallinity detection. A series of crystalline-spiked physical mixtures were analyzed and their phases were successfully identified by proton ssNMR by using a T1? filter experiment. In this pulse sequence, a single long delay time is applied, thereby selectively detecting the crystalline signal with a long delay time, and filtering the amorphous content with a short relaxation time. This work presents a streamlined, orthogonal method of crystallization detection to complement traditional methods such as PXRD and DSC. Results are promising, with the current LOQ being 0.16wt% crystals and linearity established from 0.16 - 3wt%. Future work will aim to identify API characteristics that will allow for routine use of this method.
Presenting Author: Mingzhang Wang, Pfizer
Title: Characterization of Protein Deamidation by NMR
Chemical and post translational modifications can potentially modulate protein properties including folding, conformation, stability and function. Characterizing these modifications is a crucial component of biotherapeutic development and production. There is a growing demand for new analytical techniques to complement the existing characterization methods. Protein deamidation is one of the most common modifications during the manufacturing and storage of protein therapeutics. Asparagine (Asn) deamidation leads to the formation of aspartate and isoaspartate, and some other minor species, and these species can affect protein function. Here, we employed 2D high-resolution NMR spectroscopy to characterize Asn deamidation in a 33 kDa intact protein (protein A) under thermal stress. By collecting 2D homo- and heteronuclear correlation experiments, we observed new peaks corresponding to the deamidated products, and assessed their abundance. Our results demonstrated the potential application of NMR spectroscopy for deamidation characterization in biotherapeutic proteins to complement other analytical tools such as mass spectrometry.
Presenting Author: Massimiliano La Colla, WAVEGUIDE CORPORATION
Title: Tool for Monitoring Viscosity Content and Brand Authentication of Petroleum Products
Time-domain nuclear magnetic resonance (TD-NMR) represents an attractive alternative method for analyzing petroleum products such as motor oil and diesel fuel. This is due to its ability to analyze samples with little or no sample preparation, allowing fast data collection, and being a nondestructive and noninvasive method. Current TD-NMR methods that have been developed to analyze petroleum product samples utilize very large and expensive TD-NMR benchtop equipment. WaveGuide is developing a portable TD-?NMR (time-domain micro-NMR) that can be utilized in the field to determine the viscosity and authenticity of branded petroleum products. TD-NMR was explored as a rapid method for simultaneous assessment of the quality parameters in conventional and synthetic motor oil samples. Data obtained with the relaxation decay curves employing a Carr-Purcell-Meiboom-Gill (CPMG) pulse sequence revealed tight and well-separated clusters of the motor oils, allowing discrimination of the motor oil samples according to their viscosity content and brand: 0W-30, 5W-30, 10W-30 and 10W-40. A set of 10 ASI standards for sulfur in diesel fuel was also analyzed, using a CPMG pulse sequence. The resulting data also showed well-separated clusters, allowing discrimination among the standards with sulfur weight percentage (wt %): 0, 0.1, 0.25, 0.5, 1, 1.5, 2, 3, 4, 5). WaveGuide's portable TD-NMR is the first battery powered instrument that is fully automated and robust enough to operate in the field without the need for a trained NMR technician. The device is 22x smaller, ~80x lighter, and 30x lower cost than contemporary commercial analytical systems.
Presenting Author: Dr. Robert Marti, PPG
Title: Streamlining Structure Identification and Improving Acquisition Time
Abstract: Solution-state NMR is a powerful analytical tool for structure elucidation of small molecules. Many times the structures we analyze are analogs of a parent structure and thus, have many of the same resonances, which could be assigned in an automated fashion. Utilizing ACD Labs NMR Workbook a database was created to enable inputting several pieces of data (1D and 2D) and linking them together for the purpose of structure assignment. To aid in these structure assignments, non-uniform sampling (NUS) was implemented for an HSQC experiment, which only takes 15 minutes to acquire high quality data. Implementing this HSQC-NUS experiment allowed the use of 13C chemical shifts for structure assignments, which tend to be less susceptible to its environment. Automating this process saves time for us to focus our attention on other projects.
Presenting Author: Ken Skidmore, Genentech
Title: A Comparison of CRAFT, qGSD, and Traditional Integration Methods for Quantitation of Excipients and Trace Impurities by NMR
Quantitative analysis of excipients and trace impurities can be challenging due to complex matrices, low analyte concentrations, or large dynamic ranges. In addition, the people time needed to properly process and analyze NMR data can be quite high due to the need to manually correct the phase and baseline of each spectrum, as well as the slope and bias of each integral. In extreme situations, where the phase is not consistent across the entire spectral width, a single spectrum may need to be processed multiple times, namely once for each peak of interest. Where significant peak overlap exists, traditional integration is ineffective. Selection of the proper processing approach helps address these challenges. Previously, we presented preliminary results demonstrating that, in many cases, CRAFT processing provides a route to faster, more objective data processing for impurity analysis. Recently, we acquired an in-house license for CRAFT 1D processing. As a result, we now have a sizeable collection of CRAFT processed data. Our experience shows that in many cases CRAFT is an ideal processing method for impurity analysis. CRAFT does not require phase adjustment nor baseline correction, so trace impurities can be measured accurately with relative ease. For example, in one study an analyte was quantitated in 80 samples of cell culture media. The total processing time was just a few minutes by CRAFT, whereas integration required manual adjustment of integrals and took an experienced analyst several hours to complete. In another study, CRAFT was able to isolate and accurately provide the amplitude of the resonance of a trace leachable, even though it was completely overlapped by a broad and heterogeneous signal. This feat was not possible with any other processing method. qGSD can also provide advantages in terms of automated processing and crowded spectra, so in some cases it is an effective tool. However, it cannot always overcome all signal overlap problems adequately, and is still partially sensitive to baseline imperfections, phase, and spectra with signals that span a wide dynamic range. In situations where the analyte concentrations are not trace, signal overlap is minimal, and the number of spectra to be processed are fairly small, traditional integration can be the most straightforward approach. Therefore, depending on the user's particular workflow, traditional integration should not be dismissed. Below, we share a comparison of a variety of quantitative results produced from data using CRAFT, qGSD, and traditional integration. These comparisons are designed to provide practical examples addressing accuracy, precision, the ability to revolve overlapping peaks, and reproducibility, with the goal of allowing the reader to evaluate which method might benefit their particular use case and workflow.
Presenting Author: Aaron Tang, Health Canada
Title: Automated Analysis and Quantitation of Complex Forensic Drug Mixtures by qNMR and a Multi-Component, Multi-Resonance Algorithm
Quantitative nuclear magnetic resonance (qNMR) spectroscopy is a powerful analytical technique in the identification and quantitation of components present in a sample. However, the interpretation of even simple one-dimensional proton spectra requires experience, expertise, and can ultimately be time-consuming, especially if the sample is a complex mixture. This obstacle provides a significant challenge for the implementation of NMR as a routine, high-throughput instrument in a forensic laboratory. We present a novel multi-component, multi-resonance algorithm that provides the means to an automated workflow to analyzing complex drug mixtures. Written in the programming language Julia, the "NMRquant" algorithm was developed in Health Canada's Drug Analysis Service to address the challenge of identifying and separating overlapping resonances from different components in commonly encountered drug matrices. The algorithm evaluates the correlation coefficients of the sample spectrum against a library of reference spectra to identify the contributing components, and subtracts these resonance contributions from the sample spectrum in order to perform further iterations of analyses. The program can also identify areas of overlapping resonances and avoid using them for quantitation. A complete identification and quantitation of components in an unknown sample can be performed in seconds. Combined with spectrum acquisition under quantitative conditions, the total time required from sample injection into the NMR magnet to the generation of a complete quantitation report is approximately seven minutes. The ease of use, speed, and accuracy of the NMRquant program has led to its successful implementation in the Drug Analysis Lab for the analysis of hard drugs and cannabis resin.
Presenting Author: Thilini Oshadhi Senarath Ukwaththage, Louisiana State University
Title: The 3D Structure Determination of Scc4 in Chlamydia trachomatis using NMR Spectroscopy
Chlamydia trachomatis (CT) is an obligate intracellular bacterial pathogen with adverse effects on both humans and animals. This is the most common, sexually transmitted bacterial disease (STD) with 90 million infections worldwide including 2.8 million infections in the United States annually. Due to a lack of efficient treatments, investigating novel drug candidates for CT is important. In the developmental cycle of CT, Scc4 is a small, cytosolic protein that has dual functions. In the early stages of the developmental cycle, it functions as a type III secretion system (T3SS) chaperone. The Scc4 will interact with Scc1 protein and then binds with CopN, which is an essential effector for virulence. This interaction will stabilize CopN inside the bacterial cell and allow releasing to the host cytosol. Also, the Scc4 modulates transcription in CT, by interacting with s66 region 4 (s66R4) and the ß subunit of RNA polymerase (RNAP) later in the developmental cycle. This s66RNAP•Scc4 complex can inhibit the s66-dependent transcription which helps the transition of metabolically active reticulate bodies (RB) to inactive elementary bodies (EB), the form which is important for the infection/re-infection. Due to the essential and multiple roles of Scc4, this is a significant virulence target for therapeutic approaches for treating CT. However, the lack of structural details of Scc4 will prevent the discovery of new drugs that can inhibit the function of Scc4. The determination of the 3D structure of Scc4 will lead to revealing the mechanisms of these protein:protein interactions as well as the screening of small molecular inhibitors for novel drug discovery.
The experiments to purify Scc4 with GST tag was unsuccessful due to less solubility of the protein. The purified protein yields of Scc4 with 6XHistidine tag (affinity chromatography) and tag free Scc4 (ion exchange chromatography) were lower. However, with the comparison of 2D- 1H- 15N HSQC of 6XHis-Scc4 and Scc4 (tag free) showed that the Scc4 (tag free) has a better peak dispersion with 90% of amide peaks visible which allows the 3D structure determination of Scc4. Hence, a new strategy was developed to achieve a higher yield of purified protein with tag free Scc4. In this strategy, Scc4 was co-transformed and co-expressed with Scc1-6XHis in E. coli BL21 (DE3) gold cells. The proteins were isotopically labeled with 15N ammonium chloride as the sole nitrogen source and 13C glucose as the carbon source. By using the strong interactions of Scc1:Scc4, the protein complex was captured on the nickel affinity chromatography with the 6XHis tag and Scc4 was cleaved with a mild detergent (Sarkosyl). The purified Scc4 yield was 10-12 mgs which is six times higher than the yields with 6XHis-Scc4 purification. The buffer conditions were optimized to obtain a better peak dispersion and uniform peak intensities. With Scc4, 50 mM sodium phosphate, pH 7.3 gave optimum results. Since Scc4 has higher water solubility, long time stability, and proper protein folding, the triple resonance experiments were carried out to determine the Scc4 structure in NMRFAM at University of Wisconsin-Madison.
In order to acquire the 3D structure, first backbone assignments were obtained using 2D- 1H- 15N HSQC, CBCA(CO)NH HNCACB, HNCO, NHCA and HNCOCA with sequence assisted method. The aliphatic side chain assignments were done using 3D experiments of CBCA(CO)NH, C(CO)NH, HC(CO)NH, HBHA(CO)NH, HCCH-TOCSY and 2D-1H-13C HSQC. The aromatic side chain assignments were analyzed with aliphatic and aromatic 2D- 1H- 13C HSQC, 2D-(HB)CB(CGCD)HD, 2D-(HB)CB(CGCDCE)HE, aromatic 3D HCCH-TOCSY and NOESY. Furthermore, 3D 13C NOESY and 3D 15N NOESY spectra were obtained to achieve the NOE constraints to complete the 3D structure in the future.
Presenting Author: Jason Ewanicki, Pfizer Worldwide R&D
Title: 2H SOLCOR: A novel tool for reducing volume variation as a source of error in external standard quantitative NMR
Tube to tube volume difference presents a challenge in obtaining correct external standard quantitative NMR (esqNMR) results. Deuterium (2H) is easily observable, intrinsically quantitative, present in all samples, free of interfering signals, insensitive to probe tune/match and sample saltiness. These properties make 2H SOLCOR (2H observed SOLvent CORrected) an ideal tool for volume correction whenever difference exist between reference standard and analyte, such as esqNMR. We demonstrate a technique where 2H peak integrals from the solvent are used as a universal internal standard to correct volume variations in NMR tubes, thereby improving the accuracy and precision of esqNMR method. This simple yet effective technique is described in this talk. Practical considerations for successful implementation are investigated. 2H SOLCOR can be applied anywhere esqNMR is used, including where precious samples need to be accurately quantified for qualification as an authentic analytical standard.
Presenting Author: Kelly Sackett, Pfizer
Title: Toward better characterized glycoconjugate vaccines: Analysis of S. aureus CP5 steps of chemical activation and model conjugation
Development of glycoconjugate vaccines that target capsular polysaccharide antigens on the surface of bacterial pathogens is an effective approach for preventing infections such as pneumococcal, meningococcal and HIB that can be life threatening. To make the vaccine the purified bacterial polysaccharide antigen is typically chemically modified to introduce highly reactive moieties in a process termed activation, for the purpose of conjugating it to a carrier protein. Understanding the extent and regioselectivity of the polysaccharide chemical modification is important for process control and for predicting the downstream steps involving conjugation of the modified polysaccharide to a carrier protein. Optimization of the activation and conjugation steps are critical for consistent production of glycoconjugate drug substances that meet targeted physicochemical properties and retain epitope-relevant functional groups. We present structural characterization of a candidate vaccine antigen, the capsular polysaccharide 5 (CP5) from S. aureus before and after carbonylditriazole (CDT) activation and mock conjugation using a model small molecule. Our structural understanding of CP5 activation and conjugation is further supported by the corollary structural characterization of a synthetic CP5 model oligosaccharide. These findings articulate the specificity of CP5 activation by CDT, the fate of labile functional groups during activation and conjugation steps, and reveal structural details of the preferred conjugation site for the CP5 glycoconjugate.
Presenting Author: Derrick Kaseman, Los Alamos National Laboratory
Title: Portable Earth's Field NMR Systems for the Detection of Chemical Warfare Agents
Organophosphorus nerve agents, such as sarin and VX, are a deadly class of materials which comprise thousands of unique chemical structures. However, less than 1200 of these compounds have been measured by analytical methods, including NMR. Identification of these compounds in the field is paramount for remediation efforts and remains a considerable challenge. While high resolution Nuclear Magnetic Resonance (NMR) can be employed to identify these small organic molecules, the high magnetic field (tesla regime) super-conducting NMR magnets are not suitable for use as a fieldable or portable unit. On the other hand, using Earth's magnetic field (50 ?T) is more feasible for a fieldable unit, but also eliminates the chemical shift information, which is the primary metric used to identify small molecules by NMR. We show that measuring organophosphorus compounds at Earth's magnetic field provides unique signatures based on the heteronuclear 1H-31P J-coupling. At this magnetic field, the spin systems are in the strong-coupling regime and therefore have additional heteronuclear J-coupling transitions not observable at high field (weak coupling). Furthermore, the presence of a heteronucleus lifts the degeneracy of the equivalent spins resulting in observable homonuclear J-couplings. These "J-coupled" spectra provide distinct structural fingerprints for organophosphorus compounds. We leverage J-coupled spectroscopy and identify organophosphorus nerve agent surrogates, precursors, and decomposition products using two home-built spectrometers. The first spectrometer utilizes a linear actuator to shuttle the sample from an external prepolarization source to the detector. This system is ideal for solid samples. Furthermore, due to the requirement of a heteronuclear coupling to observe the J-coupled spectra, the system exhibits no background signal from organic matter. The second system uses a fluidics based approach to shuttle the sample to the detector, which increases the overall portability of the system. The systems provide quantitative results that allow for the stoichiometry of the molecule to be determined. Experimental J-coupled spectra show close agreement to theoretically calculated J-coupled spectra. Furthermore, the calculated J-coupled spectra of several organophosphorus nerve agents show unique J-coupled spectroscopic signatures, indicating the feasibility of using a fieldable unit for the detection of nerve agents. This document has been approved for public release LA-UR-20-20657
Presenting Author: Dr. Caiyu Zhang, National Institutes for Food and Drug Control
Title: Application of qNMR in drug quliaty control in China
Quantitative nuclear magnetic resonance (qNMR) is a powerful tool in measuring drug content because of its high speed, sensitivity and precision. This method has been widely utilized in chemical drug quality control within National Institutes for Food and Drug Control (NIFDC), China. Our study includes several fields: 1) Application of proton qNMR in characterizing the assay of chemical reference substances 2) Application of 19F qNMR in characterizing fluoro-containing APIs and drug products 3) Application of 13C qNMR in characterizing long chain fatty-acids
Presenting Author: Dr. Klas Meyer, Bundesanstalt fr Materialforschung und -prfung (BAM)
Title: Industrial Applications of Low-Field NMR Spectroscopy for Process and Quality Control of Silanes
The combination of different silanes as starting materials and as a product of hydrolysis by several alcohols or water creates a range of hundreds of technical products for a wide range of applications. In recent years, functional trialkoxysilanes have proven to be multi-purpose organosilanes. Applications range from weather protection of buildings to additives for glass fiber industry, sealants, adhesives, coatings and paints to the modification of polymers. Commercial benchtop NMR spectrometers have the potential to be used in silane chemistry as an online method for reaction monitoring and quality control . NMR nuclei of interest for silane products are 1H and 29Si. In a joint research cooperation between EVONIK and BAM, the applicability of low-field NMR spectroscopy for the chemical analysis of silanes was evaluated. It was shown how it can extend the application range where existing technologies like NIR, Raman, UV/VIS, etc. cannot be used quantitatively due to a lack of reference data. In a first case study the process of hydrolysis and condensation was observed using online NMR analysis. For this purpose, the substituents of a trialkoxysilane are first hydrolyzed by adding water and corresponding silanols are formed, which can then bind to materials via SiOH functions and crosslink to form siloxane units . Another case study was dealing with the kinetics of the cleavage of a cyclic silane compound. Online NMR analysis was used both in the laboratory and in the manufacturing plant. For this purpose, a fully automated containment system was used, which enables the use of a commercial NMR spectrometer in ATEX-environments. In the third case study presented, quantitative 1H-NMR spectra were acquired on product mixtures of a trialkoxysilane and other components such as organic stabilizers, organotin compounds, an aromatic amine and organic peroxides. An automatic evaluation method based on Indirect Hard Modeling (IHM) was developed. References:  K. Meyer et al., Process control with compact NMR, TrAC Trends Anal Chem. 83a (2016), 39-52  M. Brand et al., NMR-spektroskopische Untersuchungen zur Hydrolyse von funktionellen Trialkoxysilanen, Z. Naturforsch. 54 b (1999), 155-164
Presenting Author: Daniel Holland, University of Canterbury
Title: Applications of a Quantum Mechanical Model in qNMR
Many industrial applications of NMR require quantitative analysis of the composition of mixtures. These measurements are becoming increasingly accessible with the advent of relatively low-cost, portable benchtop NMR systems. These benchtop systems provide the same functionality as conventional high field instruments. However, the chemical shift dispersion in benchtop spectra is much lower, and high order coupling effects are more prevalent; this reduces the effective spectral resolution and makes the resulting spectra significantly more crowded and challenging to analyse. Over the last few years quantum mechanical models have been developed that provide a field-invariant method of characterizing NMR spectra [1,2]. This poster will present results from several qNMR applications we have investigated using our quantum mechanical model. We demonstrate the effectiveness of our method experimentally on a range of problems, such as the characterization of juices, adulteration of honeys, analysis of mixtures in forensic applications, mineral processing and thermodynamics. We demonstrate our analysis on both conventional high field spectrometers and benchtop NMR systems, where analysis of benchtop spectra benefits from the field invariant nature of the model. References:  Matviychuk, Yevgen, Jet Yeo, and Daniel J. Holland. "A field-invariant method for quantitative analysis with benchtop NMR." Journal of Magnetic Resonance 298 (2019): 35-47.  Tiainen, Mika, Pasi Soininen, and Reino Laatikainen. "Quantitative quantum mechanical spectral analysis (qQMSA) of 1H NMR spectra of complex mixtures and biofluids." Journal of Magnetic Resonance 242 (2014): 67-78.
Presenting Author: Dr. Anna Codina, Bruker
Title: Analysis of Biologics and Biosimilars by Magnetic Resonance - A Review
High-resolution NMR is a key technology that provides critical information about protein structure and dynamics. It also has the popularity of being difficult to use, expensive, size limited and to require labelled molecules, which leads to lengthy studies. These hindered the adoption of the technique for the characterization of biotherapeutic drugs in the pharmaceutical industry. Recent advances in acquisition and analysis changed the situation . We are now able to see intact antibodies at natural abundance. NMR is especially sensitive to changes to higher order structure at atomic resolution, making it ideally suited for similarity assessment of biologics and biosimilars . NMR also allows for intact protein analysis, enabling evaluation of the structure of therapeutic drugs without modification, in conditions that are physiologically relevant. Because of its intrinsically high information content NMR has the potential to reduce the number of techniques needed to characterize therapeutic drugs. Due to the quantitative nature of magnetic resonance and its selectivity, potency determination , impurity profiling  and degradation studies (e.g. polysorbates) are performed directly enabling fast and easy testing without the need of response factor calculations, or the method redevelopment activities required by traditional LC methods, thereby saving time and reducing costs. In these last examples size is not an issue because we either look at the small molecules or specifically at radicals. Another way to overcome the molecular size threshold is to approach the problems from a completely different angle. There have been several publications in the last 2-3 year on the use of time-domain NMR (TD-NMR) to determine aggregation  and moisture  in biologics. TD-NMR has the great advantage of being truly non-destructive, allowing the analysis of drugs in their container (vials and syringes) and maintaining the sterility of the product. This, together with the speed of the measurements, enables 100% testing, which is a requirement for highly potent drugs. NMR is also being used in bio-production understanding  and culture media screening and quality control. Current applications of magnetic resonance (NMR, EPR, TD-NMR) for the analysis of biotherapeutic drugs will be reviewed. 1. Arbogast L., Delaglio F., Tolman J.R., J Biomol NMR, 72: 149-161 (2018) 2. Haxhom G.W., Bent O., Malmstrom J., J Pharm Sci, 108: 3029 (2019) 3. Bradley S. A., Jackson W. C., Mahoney P. P., Anal Chem. 91(3):1962-1967 (2019) 4. Skidmore K, Hewitt D, Kao Y.H., Biotechnol Prog. 28(6):1526-33 (2012) 5. Taraban M.B., Briggs K.T., Merkel P., Anal Chem. 91: 13538-13546 (2019) 6. Abraham A, Elkassabany O., Krause M.E., Ott A., Magn Reson Chem, 1-5 (2019) 7. Bradley S. A., et al, J. Am. Chem. Soc., 132 (28): 9531-9533 (2010)
Presenting Author: Dr. Frank Delaglio, NIST
Title: Chemometric Outlier Detection and Classification of 2D-NMR Spectra to Enable Higher Order Structure Characterization of Protein Therapeutics
Protein therapeutics are increasingly important, both clinically and commercially, with monoclonal antibody therapeutic sales alone accounting for $115 billion in revenue for 2018, a year-on-year increase of 11%. In order for these therapeutics to be safe and efficacious, their protein components must maintain their three-dimensional fold and not aggregate. Analytical methods to characterize this higher order structure (HOS) can help establish comparability between drug products, and provide impact throughout the life cycle of the therapeutic, from development to manufacturing. As demonstrated in the recent NISTmAb Interlaboratory NMR Study, nuclear magnetic resonance (NMR) spectroscopy is a robust and precise approach for assessment of the HOS at residue-specific resolution. In the study, peak positions show reproducibility of better than 6 parts per billion, over a collection of more than 350 two-dimensional 1H,13C spectra measured on 39 different instruments in nine countries. However, the peak table approach requires interactive analysis of each individual spectrum, including subjective decisions about spectral quality and peak identification. Therefore, to take best advantage of NMR for HOS, alternative analysis methods that are automated and objective are desirable. Using the study data, we benchmark a method for automated outlier detection that aims to identify spectra that are not of sufficient quality for further automated analysis. The outlier detection uses the symmetric Kullback-Leibler divergence as a metric of spectral similarity, and identifies outliers according to the average value of this metric between a given spectrum and all others in its related group (here, spectra measured with similar acquisition details and NMR field strength). When applied to a collection of all 252 1H,13C gHSQC spectra from the study, a recursive version of the automated outlier detection performed comparably to visual analysis, identifying three outlier cases that were missed by the human analyst. In total, this method represents a distinct advance in chemometric detection of outliers due to both measurement and sample.
Presenting Author: Dr. Amy Freund, Bruker BioSpin
Title: Single sample test for the calibration of NMR systems
There is an increased awareness by both spectroscopists and regulating bodies that NMR instrument tests should be done regularly in order to validate the readiness of an NMR spectrometer to generate valid data. This is especially important when running analyses requiring a high degree of system reproducibility, or those where data comparisons are made between instruments. These inter-instrument comparisons are difficult when systems vary in their inherent stability over time. There are many tests available for monitoring individual aspects of performance (shimming, sensitivity, quality) each requiring their own dedicated sample. However, we see benefits from running as many tests as possible on a single sample (2mM sucrose in H2O:D2O (9:1) (99.9aton % D), DSS 0.5 mM). We will highlight the benefit of using this single sample to test multiple aspects of performance; shimming, pulse calibration, sensitivity, and quantitation. Results of each test can be viewed individually, but also in conjunction with other tests. This single sample, multiple test setup allows access to test results that improves our ability to troubleshoot discrepancies found when using multiple samples to test these parameters. We will show results from a variety of systems, spanning a few months to nearly a year of continuous running. From the data collected we will show the cross-test analysis results and dive into what they reveal about the system state.
Presenting Author: Dr. James Sagar, Oxford Instruments
Title: Broadband, variable temperature benchtop NMR for industrial and research applications
Benchtop NMR spectroscopy is in its relative infancy as a technique, with the first commercial instruments having been introduced less than a decade ago. Initially, benchtop instruments offered limited capabilities, only producing 1D 1H and 19F NMR spectra at a fixed temperature, restricting their usage largely to basic educational applications and limiting their usefulness in research and industrial settings. However, the field has seen significant interest and development in the last five years, with more modern benchtop NMR spectrometers offering many capabilities of high-field instruments, such as 2D spectra, multinuclear spectra, and gradient-selected experiments. Still, due in large part to engineering challenges posed by the properties of rare-earth permanent magnets, capabilities such as stable variable-temperature operation and true broadband NMR has previously remained out of reach. To increase the utility and broaden the scope of benchtop NMR, a newly developed, highly flexible spectrometer has extended the capabilities of this technique. New flow cell and variable-temperature probe designs provide stable operation, providing the ability to analyse samples that were previously inaccessible to benchtop instruments, as well as allowing the performance of kinetic and thermodynamic studies. In addition, novel electronics and probe designs have allowed nuclei ranging in frequency from 29Si to 31P to be acquired on the same broadband channel allowing the analysis of many nuclei on a single benchtop NMR instrument for the first time. This opens up new applications in industrial and academic research and development, as well as in QC and process control. Moreover, new database software, applying machine learning techniques, identifies compounds, even in multi-component mixtures, or low concentration adulterants, allowing casual users to produce meaningful results without expert intervention. The flexibility in measurement temperature, choice of nucleus, and operation modes provides the potential for additional industrial applications to move to the benchtop while also increasing the usefulness of benchtop NMR spectroscopy in educational and research settings.
Presenting Author: Dr. Karl Stupic, National Institute of Standards and Technology
Title: Challenges in Low Field Magnetic Resonance: Transmit/Receive, RF, and more
While high-field magnetic resonance continuously pushes the envelope of new technology, the essential hardware has been relatively unchanged for decades. Technology, such as PIN diodes, are commonly used for transmit/receive switches in in high field nuclear magnetic resonance (NMR) or magnetic resonance imaging (MRI) but not at low frequencies due to carrier lifetime issues. Discussed here are a series of challenges we have faced in developing quantitative very low field magnetic resonance systems. Many of these challenges are unique to the very low field / low field area as the decrease in frequency, and typically lower required power, result in situations outside of the normal operating conditions of NMR/MRI spectrometers. At low frequencies transmit/receive switches are typically constructed with arrays of crossed diodes which require a certain voltage to switch between transmit and receive. This causes a situation where significant power is necessary to transmit RF pulses to the NMR coils. However, in MRI, commonly using shaped pulses, fidelity is lost due to the shapes having under powered regions for the switches. Additionally, the diodes draw power from the RF pulse resulting in slightly lower powers delivered to the coils expected. One possible solution is the use of active transmit/receive switches with either complementary metal-oxide-semiconductor (CMOS) or micro-electromechanical system (MEMS) technology. These active switches impose slightly more complex pulse sequences necessary to activate the switches but resolve several issues from the passive switches. Another issue that uniquely arises at very low fields/frequencies is an issue of radiofrequency (RF) efficiency. It is typical to consider the use of very short RF pulses in NMR to prevent significant decay of processes with 90-degree times on the order of 5-15 microseconds. However, at lower frequencies where the period of one oscillation can be measured in microseconds, the efficiency of these RF pulses could be problematic. We explore this behavior both experimentally via inversion recovery experiments as well as Bloch simulations to ensure efficient RF pulses.
Presenting Author: Dr. Michael Dada, Federal University of Technology, Minna, Nigeria
Title: Application of Computational MRI Modelling and Machine Learning to Fluid Typing in Shale
The recent emphasis on developing shale reservoirs has presented interesting alternatives to meeting the ever increasing worldwide energy demands. In order to evaluate these reservoirs, nuclear magnetic resonance (NMR) technique is becoming one of the preferred techniques for the determination of shale fluid typing and fluid properties estimation due to their successful application in conventional reservoirs. However, the characteristics of these reservoirs such as pore size, mineralogy, organic matter, wettability, adsorption and clay content have presented challenges because models taken these features into consideration under the condition of fast relaxation are limited. Furthermore, the overlap of various fluids peaks has made fluid properties estimation in shale quite challenging. In addition to this, shale reservoir is made up of complicated pore networks, within which various pore fluids including unrecoverable fluid, capillary bound fluid and movable fluid can be found. Although a lot of studies have investigated pore structure of gas shale with the use of various laboratory testing techniques, only a handful provided quantified model that be used to delineate different types of shale fluids according to their corresponding pore types. To address this problem, we shall apply a computational model developed for identifying the fluids in restricted geometries (based on the Bloch NMR flow equation)  and machine learning algorithm for classification of pore fluids according to NMR relaxation features and signal response. For a cylindrical-like pore system, the diffusion-NMR based signal from the restricted geometries has been derived as a function of the porosity of the geometry . Without recourse to the boundary and initial conditions (since these are difficult to define in shale reservoirs), the general expression for the NMR signal is employed in computing the transverse magnetization signal based on the geometrical and NMR relaxation features of the shale reservoir. Using this expression, a unique dataset has been generated for use in Python-based neural networks has been implemented for classification of shale reservoir porous system. The T2 relaxation times measured at B0 = 0.55T for unrecoverable fluid pore, capillary bound fluid pore and movable fluid pore, pore features and shale diffusion coefficients were obtained from a recent studies. T1 relaxation times were calculated based on the experimental results obtained by Mehana and El-monier (2016). These data were then distributed over all possible situations at this value of uniform magnetic field and then used to compute the MR signal values. These dataset is then used to train a deep neural network for classification of shale reservoir. Visualizations of the dataset showing classifications of the pores according to their measured properties are given in the following figures. A decision tree summarizing how a computer is to solve the problem is also demonstrated. In the dataset developed for this study, we have 300 samples in which training was performed on 210 samples while 90 samples were employed for validation. It is very interesting to note that most classification algorithms performed impressively on our dataset. SVM, Naïve Bayes, Decision tree, Random forest, Extra tree classifier and XGB all returned 100% accuracy. Logistic regression returned 97.8% accuracy while KNN returned 80% accuracy. Since these models has performed very well, it follows that the challenges of interpreting magnetic resonance results from NMR logs can now be solved with the help of machine learning. In this direction, we developed a decision tree with which computers can address this problem. The advantage of the computational approach used in this study is that data from different magnetic fields can be incorporated and since NMR relaxation times are very sensitive to pore structures, we can always measure these relaxation times to delineate complicated pore networks usually encountered in shale reservoirs.
Presenting Author: Sophia Hayes, Washington University
Title: The Materials Project Database of NMR Tensors for 29Si and 27Al - VASP versus CASTEP Systematic Differences
New computational methods have generated opportunities to reveal structural information available from chemical shielding (shift) tensors in solid-state NMR. The ability to predict NMR parameters and connect them to 3-dimensional local environments is critical for extracting perturbations to the tensor that arise from more distant (2nd- or 3rd-shell) species. In this study we have used 42 silicon sites as a benchmarking set to compare experimentally-reported 29Si solid-state NMR tensors with those computed by CASTEP-NMR and Vienna Ab Initio Simulation Program (VASP). Individual tensor elements have been both validated, and in some cases corrected in an effort to catalogue these for the Local Spectroscopy Database Infrastructure (LSDI), where over 10,000 29Si tensors for crystalline materials have been computed. 29Si was selected as a starting point for computation of additional species, with 27Al under validation now, and work on diverse additional species, including 51V, and 17O at preliminary stages. Critically, a systematic difference between CASTEP and VASP has been discovered, enabled by looking at such large datasets. This difference is evident when examining correlations between tensor elements and could be one of the (inadvertent) major findings of this study. Such tensors are useful for identification of new silicon-containing species, serving as a starting point for determination of the local environments present in amorphous silicon-containing structures. With knowledge of these predicted values, NMR experiments can be executed with precision, optimizing conditions to capture the individual tensor elements accurately under both static and magic-angle spinning experiments.
Presenting Author: Kristie Adams, Steelyard Analytics, Inc.
Title: Determination of Cannabidiol and other Cannabinoids in CBD Products using 1H-qNMR Spectroscopy
Cannabidiol-infused products are flooding the market worldwide, as the regulations surrounding growth of industrial hemp are relaxed. Currently, the analysis of such products relies on mostly chromatographic methods, some which destroy the easily decarboxylated cannabinoids. This analysis can also be performed using quantitative 1H-NMR spectroscopy, which has clear advantages over chromatographic methods: faster run times, no destruction of the sample components, and no need of reference material(s). We have developed a 1H-qNMR method enables simultaneous determination of various cannabinoids in Cannabis sativa plant material and CBD-infused products, like oils, tinctures, gummies and so on. With chemical shifts assigned for the 1H NMR signals of various cannabinoids and after considering influences on the quantification process (e.g., solvent-based shifting effects), a parallel quantification of 16 cannabinoids (potentially more) can be done with one 1H qNMR measurement. Sample preparation for oils is as simple as it gets, and the initial composition of the cannabinoids can be obtained directly. Additional information can be obtained from the NMR spectrum, enabling determination of several parameters related to oil quality, like peroxide and anisidine value(s), fatty acid distribution, amount of ?-3 fatty acids and more within the same experiment. Furthermore, the non-destructive nature of NMR analysis allows application of subsequent analytical methods if necessary. This work demonstrates the application of the above-described 1H-qNMR method to CBD-infused products from a wide range of product categories, showing 1H-qNMR to be a reliable and quick method for cannabinoid analysis in routine quality control analytics of cannabinoid products.
Presenting Author: Samuel Kotler
Title: Use of EXSIDE NMR to Determine the E/Z-Conformation for 5-Methylene Substituted Hydantoins
The determination of stereochemistry within a compound is critical for the development of small molecule therapeutics as structure is highly involved in a drug's activity. Nuclear magnetic resonance (NMR) spectroscopy is a primary method for the determination of molecular structure and configuration, especially when acquiring an x-ray crystal structure is hindered by the inability to obtain well-diffracting crystals. However, NMR can often provide data that are difficult to interpret or inaccessible due to molecular flexibility or complexities in 3D configuration. As such, the development and application of analytical techniques to expeditiously acquire quantitative markers for structural deconvolution of small molecules is essential. Six1-Eya2 transcription factor has been implicated in diverse tumor types such as Wilms' tumor, ovarian cancer, and breast cancer and overexpression is associated with shortened relapse and survival times. Inhibition of the protein-protein interaction (PPI) with a small molecule is a potential therapy and high-throughput screening (HTS) identified an inhibitor class containing a 5-methylene substituted hydantoin core, which exhibits low micromolar activity. It was observed that the E/Z-stereochemistry of the exocyclic double bond is significant as only one conformation had biological activity. However, the application of 1D NOE and NOESY experiments to determine stereochemistry were unsuccessful as NOE interactions were not detected between the hydantoin NH and the methine proton of the double bond for either conformation. It was therefore necessary to develop an NMR protocol that could rapidly and easily identify stereoisomers of these small molecules through easy-to-interpret NMR parameters such as chemical shift and long-range 1H, 13C coupling constants (3JCH), the latter of which can distinctly identify E/Z-conformation. We utilized Excitation-Sculptured Indirect-Detection Experiment (EXSIDE), a band-selective variation of the gradient HSQC experiment, for this purpose and demonstrated the viability of the approach for nearly 40 different 5-methylene substituted hydantoins. After structural assignment for each compound by the straightforward measurement of chemical shifts (1H and 13C) and homonuclear coupling constants (3JHH) with a standard suite of 1D and 2D NMR experiments, the EXSIDE was used to measure long-range heteronuclear coupling constants (3JCH) to accurately identify the E/Z-conformation. The implementation of non-uniform sampling (NUS) reduced data acquisition time for a single compound from 12 hours to as little as 2 hours. Application of the EXSIDE coupled with NUS enabled us to expediently identify the Z-stereoisomer as the active conformation for inhibition of the Six1-Eya2 PPI and helped guide future structure design. During the course of this work, we also discovered the compounds were thermally stable but photoisomerization of the double bond can occur, which has large implications for storage and usage.
Presenting Author: Yui Otagaki
Title: Improving detection of nuclear quadrupole resonance signals in humanitarian demining using a machine learning based approach
This work presents an overview of recent advances in improving landmine detection with a portable nuclear quadrupole resonance (NQR) system using machine learning (ML) techniques. NQR technique is widely used to search for substances such as explosives, petroleum, and pharmaceuticals. The NQR apparatus has been designed and developed to be low-cost and suitable for deployment in humanitarian demining. To this end, the system uses an FPGA and a self-made transmission/ reception circuit, and requires power that can be supplied by portable batteries. This design approach results inevitably in a weaker NQR signal from the target, and thus a low signal to noise ratio (SNR). By employing machine learning (ML) techniques, we are able to increase the system's detection accuracy. This is demonstrated with tests of conventional thresholding and ML methods applied to the NQR signal from RDX acquired by the developed device, which shows that ML methods can indeed improve the detection accuracy of the NQR device
Presenting Author: Stephen Russek
Title: NIST Diffusion Coefficient Calibration Service for MRI Phantom Materials: Measurement Protocol and Uncertainty Analysis
Quantitative diffusion mapping is extensively used in MRI for tumor delineation, tumor phenotyping, and neurological imaging for traumatic brain injury and neurologic disorders such as Alzheimer's disease and Parkinson's disease. NIST, in conjunction with the Radiological Society of North America, the National Cancer Institute, the National Institute of Child Health and Human Development, and the Department of Veterans Affairs developed an isotropic diffusion phantom which has been commercialized and widely disseminated. This phantom, and others being developed, require traceable calibration to ensure their accuracy and to define the uncertainty in the diffusion parameters. NIST has a measurement service, to provide traceable calibration of spin relaxation time measurements. We are currently extending this service to include measurement of water diffusion coefficients over a range of temperature, 0 C to 50 C, and at clinical field values of 1.5 T, 3 T, and 7 T. Here we describe the measurement procedure, the custom designed diffusion cell, the NMR calibration procedures, and the uncertainty analysis. The diffusion cell is a precision machined polyphenylene sulfide NMR tube with sample dimensions accurate to 0.03 mm and an embedded fiberoptic thermometer. The diffusion cell, in addition to having precise dimensions, must be susceptibility matched to tissue and tissue mimics, have good thermal properties, and must be easy to load with tissues and tissue mimics. The system calibration requires calibration of the time base to the US time standard, gradient calibration via microCT using a precision sphere (3.000 mm ± 0.0025 mm) with traceable dimensions, and temperature calibration against NIST traceable thermometers. The most significant and time-consuming component of the calibration service is the uncertainty analysis. The NMR system and data processing uncertainties are characterized, including time base calibration error and jitter; thermometer calibration errors, temperature fluctuations and spatial variation; B0, B1, and gradient inhomogeneities; sample misalignment; environmental and electronic noise, and data processing parameter choices. These uncertainties are then entered into a Monte Carlo calculation which integrates Bloch-Torrey equations for a large ensemble of spin packets with the pulse sequences used in the measurements. The synthetic data is processed using the same analysis pipeline as the real data. The distributions in apparent diffusion coefficients are compared to and validated against real measurements taken over an extended period of time. The statistical distributions obtained from the Monte Carlo calculations are then used to specify the 3-sigma uncertainties. This type of uncertainty analysis accounts for the fact that many of the system nonidealities give rise to correlated errors that cannot be evaluated independently. We actively solicit community input to provide and improve calibration services for NMR-based medical measurements.  Palacios EM, Martin AJ, Boss MA, Ezekiel F, Chang YS, Yuh EL, Vassar MJ, Schnyer DM, MacDonald CL, Crawford KL, Irimia A, Toga AW, Mukherjee P, Investigators T-T (2017) Toward Precision and Reproducibility of Diffusion Tensor Imaging: A Multicenter Diffusion Phantom and Traveling Volunteer Study. AJNR American journal of neuroradiology 38(3):537-545.  CaliberMRI (Available at  Boss MA, Dienstfrey AM, Gimbutas Z, Keenan KE, Splett JD, Stupic KF, Russek SE (2018) Magnetic Resonance Imaging Biomarker Calibration Service: Proton Spin Relaxation Times (NIST).