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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 55 records · Page 3

Neural Network Analysis of Nuclear Magnetic Resonance and Infrared Spectra

Nuclear magnetic resonance (NMR) spectroscopy and infrared (IR) spectroscopy are powerful chemical characterization techniques with broad general usage. However, the manual evaluation of the resulting spectra is time-consuming and requires significant expertise, preventing insights from being used in real-time applications. With recent advances in computation and artificial intelligence (AI), new tools are available for automating spectral interpretation. In this work, machine learning (ML) algorithms using 1-dimensional convolutional neural networks (CNNs) were applied to identify common functional groups from spectral information. Raw spectra were collected virtually from the Human Metabolome Database (HMDB) and National Institute of Standards and Technology (NIST) Chemistry WebBook and processed into a suitable standard. Algorithm design was tailored to best fit the nature of the problem, with built-in flexibility to accommodate relevant parameters beyond the raw spectral input, specifically solvent identity and magnetic frequency for NMR. The predictive capability of the algorithm in identifying functional groups is displayed in several examples. This methodology has been compiled into a code repository and could easily be modified to adapt alternative data sources, including other spectrum types. To mitigate overfitting, a common problem in mathematical modeling where overfamiliarity with training data produces trends that are not representative of the general data, a novel metric was developed, referred to as Accufit. Accufit includes a parameter that penalizes substantial differences in the training accuracy and the accuracy of an independent validation set. Examples are presented showing the effectiveness of Accufit in maintaining the model’s predictive capability while controlling the overfitting when used as a custom metric for hyperparameter tuning.

Sturgill, James↗

Measurements of nematic susceptibility with phase sensitive nuclear magnetic resonance in pulsed strain fields

Here, we present nuclear magnetic resonance data in BaFe 2 As 2 in the presence of pulsed strain fields that are interleaved in time with the radio frequency excitation pulses. In this approach, the preceding nuclear magnetization acquires a phase shift that is proportional to the strain and pulse time. The sensitivity of this approach is limited by the homogeneous decoherence time, T 2 , rather than the inhomogeneous linewidth. We measure the nematic susceptibility as a function of temperature and demonstrate a three orders of magnitude improvement in sensitivity. This approach will enable studies of the strain response in a broad range of materials that previously were inaccessible due to inhomogeneous broadening.

36 MATERIALS SCIENCE↗

Understanding generalized inversions of nuclear magnetic resonance transverse relaxation time in porous media

The nuclear magnetic resonance transverse relaxation time T{sub 2}, measured using the Carr-Purcell-Meiboom-Gill (CPMG) experiment, is a powerful method for obtaining unique information on liquids confined in porous media. Furthermore, T{sub 2} provides structural information on the porous material itself and has many applications in petrophysics, biophysics, and chemical engineering. Robust interpretation of T{sub 2} distributions demands appropriate processing of the measured data since T{sub 2} is influenced by diffusion through magnetic field inhomogeneities occurring at the pore scale, caused by the liquid/solid susceptibility contrast. Previously, we introduced a generic model for the diffusion exponent of the form −ant{sub e}{sup k} (where n is the number and t{sub e} the temporal separation of spin echoes, and a is a composite diffusion parameter) in order to distinguish the influence of relaxation and diffusion in CPMG data. Here, we improve the analysis by introducing an automatic search for the optimum power k that best describes the diffusion behavior. This automated method is more efficient than the manual trial-and-error grid search adopted previously, and avoids variability through subjective judgments of experimentalists. Although our method does not avoid the inherent assumption that the diffusion exponent depends on a single k value, we show through simulation and experiment that it is robust in measurements of heterogeneous systems that violate this assumption. In this way, we obtain quantitative T{sub 2} distributions from complicated porous structures and demonstrate the analysis with examples of ceramics used for filtration and catalysis, and limestone of relevance to the construction and petroleum industries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Operando nuclear magnetic resonance rotor insert

A magic angle sample spinning nuclear magnetic resonance system including a housing, a cryogenic fluid in the housing, a magnet in the housing, a probe in the housing, a magic angle sample spinning insert in the probe, a sample battery in the magic angle sample spinning insert, a photovoltaic cell in the magic angle sample spinning insert wherein the photovoltaic cell is connected to the sample battery, an optic fiber operatively connected to the photovoltaic cell, and a laser operatively connected to the optic fiber wherein the laser provides power to charge the sample battery during the magic angle sample spinning nuclear magnetic resonance.

Marple, Maxwell↗

Wide-range nuclear magnetic resonance detector

Compact and easy to use solid state nuclear magnetic resonance detector is designed for measuring field strength to 20 teslas in cryogenically cooled magnets. Extremely low noise and high sensitivity make detector applicable to nearly all types of analytical nuclear magnetic resonance measurements and can be used in high temperature and radiation environments.

Sturman, J. C.↗

Opportunities and Limitations of Nuclear Magnetic Resonance Spectroscopy in Astrobiology

For decades, Nuclear Magnetic Resonance (NMR) spectroscopy has been utilized as a powerful tool in various scientific disciplines, most prominently in chemistry, to determine molecular structures or monitor reactions. While well established in various fields, NMR applications in astrobiology are still unclear. This work aims to explore the potential of NMR in astrobiology, highlighting strengths but also weaknesses. We illustrate capabilities of NMR with two applications: (1) recently developed methods for position-specific carbon isotope analysis of complex organics; and (2) well-established tools for performing quantitative compositional analysis of complex organic mixtures. By utilizing samples relevant to astrobiology, specifically the amino acid valine and analogue mixtures of organics, we showcase that molecules retain a source dependent and distinct intramolecular carbon isotope fingerprint. We demonstrate that compositional sample analysis provides an independent and complementary line of evidence pointing towards the origin of a molecule or mixture. Together, these NMR tools have the potential to support life detection efforts, and aid in distinguishing between biotic and abiotic samples. Finally, we discuss sensitivity, detection limits, the portability of NMR, and propose how integration with mass-spectrometry techniques will be imperative to enable more targeted and comprehensive analyses relevant to astrobiology, including in-situ analysis but also sample return missions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The effect of magnetic susceptibility and magnetic field strength on porosity estimates determined from low-field nuclear magnetic resonance

The presence of materials with high magnetic susceptibility are known to have an impact on 1H nuclear magnetic resonance (NMR) measurements and in laboratory data this often results in poor estimates of porosity from NMR data. To quantify and understand the cause of the poor NMR porosity estimations, in this laboratory study, we examine the effect of magnetic susceptibility, NMR measurement parameters, and NMR instrument design on NMR measurements. Data were collected with two instruments, each with a different Larmor frequency (2 MHz and 485 kHz), on water-saturated unconsolidated sediments with magnetic susceptibility values ranging from 3.6 × 10 -6 to 7020 × 10 -6 SI. The results show that for materials with low magnetic susceptibility (<378 × 10 -6 SI), the gravimetric porosity is accurately predicted from the NMR measurements. For the samples with high magnetic susceptibility (>987 × 10 -6 SI) the gravimetric porosity is poorly predicted from the 2 MHz NMR measurements made at all echo times (from 0.2 to 3.0 ms). In contrast, the gravimetric porosity is more accurately predicted at an echo time of 0.2 ms for measurements made using the 485 kHz instrument, although at larger echo times (>1.0 ms), the porosity estimate becomes poor. The 485 kHz NMR instrument has non-zero internal magnetic field gradients, similar to those found in borehole instruments, in contrast to the 2 MHz NMR instrument, which has a homogeneous applied magnetic field. Finally, we conclude that differences is the magnetic field strength and higher magnetic field inhomogeneities in the 485 kHz NMR instrument contribute to a reduction of the impact of inhomogeneities in the magnetic field caused by materials with high magnetic susceptibility, allowing for improved porosity estimation. These results indicate that NMR measurements collected at short echo times in low, inhomogeneous static fields, e.g., borehole instruments, may provide accurate estimates of porosity in water saturated sediments, even in the presence of magnetic minerals.

58 GEOSCIENCES↗

Nuclear magnetic resonance in Kondo lattice systems

Nuclear magnetic resonance has emerged as a vital tool to explore the fundamental physics of Kondo lattice systems. Because nuclear spins experience two different hyperfine couplings to the itinerant conduction electrons and to the local f moments, the Knight shift can probe multiple types of spin correlations that are not accessible via other techniques. Furthermore, the Knight shift provides direct information about the onset of heavy electron coherence and the emergence of the heavy electron fluid.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NMR (Nuclear Magnetic Resonance) and macromolecular migration in a melt or in concentrated solutions

The purpose of this paper is to analyze the migration process of long polymer molecules in a melt or in concentrated solutions as it may be observed from the dynamics of the transverse magnetization of nuclear spins linked to these chains. The low frequency viscoelastic relaxation of polymer systems is known to be mainly controlled by the mechanism of dissociation of topological constraints excited on chains and which are called entanglements. This mechanism exhibits a strong dependence upon the chain molecular weight. These topological constraints also govern the diffusion process of polymer chains. So, the accurate description of the diffusion motion of a chain may be a convenient way to characterize disentanglement processes necessarily involved in any model proposed to explain viscoelastic effects.

Addad, J. P. C.↗

Nuclear magnetic resonance properties of lunar samples.

Nuclear magnetic resonance spectra of Na-23, Al-27, and P-31 in fines samples 10084,60 and 14163,168 and in crystalline rock samples 12021,55 and 14321,166, have been recorded over a range of frequencies up to 20 MHz. A shift in the field at which maximum absorption occurs for all of the spectra relative to the field at which maximum absorption occurs for terrestrial analogues is attributed to a sample-dependent magnetic field at the Na, Al, and P sites opposing the laboratory field. The magnitude of these fields internal to the samples is sample dependent and varies from 5 to 10 G. These fields do not correlate with the iron content of the samples. However, the presence of single-domain particles of iron distributed throughout the plagioclase fraction that contains the principal fraction of Na and Al is inferred from electron magnetic resonance spectra shapes.

Kline, D.↗

Discrete decoding based ultrafast multidimensional nuclear magnetic resonance spectroscopy

The three-dimensional (3D) nuclear magnetic resonance (NMR) spectroscopy constitutes an important and powerful tool in analyzing chemical and biological systems. However, the abundant 3D information arrives at the expense of long acquisition times lasting hours or even days. Therefore, there has been a continuous interest in developing techniques to accelerate recordings of 3D NMR spectra, among which the ultrafast spatiotemporal encoding technique supplies impressive acquisition speed by compressing a multidimensional spectrum in a single scan. However, it tends to suffer from tradeoffs among spectral widths in different dimensions, which deteriorates in cases of NMR spectroscopy with more dimensions. In this study, the discrete decoding is proposed to liberate the ultrafast technique from tradeoffs among spectral widths in different dimensions by focusing decoding on signal-bearing sites. For verifying its feasibility and effectiveness, we utilized the method to generate two different types of 3D spectra. The proposed method is also applicable to cases with more than three dimensions, which, based on the experimental results, may widen applications of the ultrafast technique.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

On the Possibility of Express Recording of Nuclear Magnetic Resonance Spectra of Liquid Media in Weak Fields

The necessity of recording nuclear magnetic resonance (NMR) spectra in weak magnetic fields during the express control of liquid media has been substantiated, and the conditions in which such recording is possible have been determined. A new scheme of a compact NMR spectrometer intended for such measurements has been proposed. The results of experimental investigation of some substances based on the developed technologies are reported.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Coaxial probe for nuclear magnetic resonance diffusion and relaxation correlation experiments

A coaxial nuclear magnetic resonance (NMR) probe is built to measure diffusion and relaxation properties of liquid samples. In particular, we demonstrate the acquisition of two-dimensional (2D) distribution functions (T{sub 1}-T{sub 2} and diffusion–T{sub 2}), essential for fluids characterization. The compact design holds promise for miniaturization, thus enabling the measurement of molecular diffusion that is inaccessible to conventional micro-NMR setups. Potential applications range from crude oil characterization to biomolecular screening and detections.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

In situ nuclear magnetic resonance microimaging of live biofilms in a microchannel

Nuclear magnetic resonance (NMR) microimaging and spectroscopy was used to interrogate fluids of biological importance (e.g., water, buffer, medium solution) and live biofilms in a microchannel compatible for analyses at ambient pressure and under vacuum. Studies using buffer, growth medium, and actively growing Shewanella oneidensis biofilms were used to demonstrate in situ NMR microimaging measurement capabilities including velocity mapping, diffusion coefficient mapping, relaxometry, localized spectroscopy, and 2D and 3D imaging within a microchannel suitable for different analytical platforms. This technique is promising for diverse applications of correlative imaging using a portable microfluidic platform.

biofilm↗

Polarized target nuclear magnetic resonance measurements with deep neural networks

Continuous-wave Nuclear Magnetic Resonance (CW-NMR) operated in constant-current mode has served as a foundational technique for polarization measurement in solid-state dynamically polarized targets within nuclear and high-energy physics experiments for several decades, and it remains an essential tool. Conventional Q-meter-based phase-sensitive detection is critical for precise real-time determination of target polarization during scattering runs. However, the accuracy and reliability of these measurements are frequently compromised by elevated noise levels, baseline drift, and systematic uncertainties arising from signal isolation and fitting, ultimately degrading the overall experimental figure of merit. In this work, we report the first successful application of neural network architectures to continuous-wave NMR polarization metrology. By leveraging advanced machine learning techniques for signal extraction and denoising, we achieve a substantial reduction of fitting uncertainties under a variety of realistic simulated and experimental conditions. These improvements translate directly into more robust real-time (online) polarization monitoring and higher precision in subsequent offline analysis. By reducing analysis-induced uncertainty, the resulting methodology can improve the effective figure of merit for scattering experiments employing dynamically polarized targets and provides a new toolset for NMR-based polarimetry in high-energy and nuclear physics.

Metrology↗

Measuring surface-area-to-volume ratios in soft porous materials using laser-polarized xenon interphase exchange nuclear magnetic resonance

We demonstrate a minimally invasive nuclear magnetic resonance (NMR) technique that enables determination of the surface-area-to-volume ratio (S/V) of soft porous materials from measurements of the diffusive exchange of laser-polarized 129Xe between gas in the pore space and 129Xe dissolved in the solid phase. We apply this NMR technique to porous polymer samples and find approximate agreement with destructive stereological measurements of S/V obtained with optical confocal microscopy. Potential applications of laser-polarized xenon interphase exchange NMR include measurements of in vivo lung function in humans and characterization of gas chromatography columns.

Non-NASA Center↗