Nuclear Magnetic Resonance Instrument Research Articles

Structural Analysis of Hyaluronic Acid Fillers Using Nuclear Magnetic Resonance: Implications for Quality Control and Clinical Performance.

Potential disruptions in the biocompatibility of hyaluronic acid (HA) fillers can arise with mono-linked 1,4-butanediol diglycidyl ether (BDDE) or unreacted (pendant) 1,4-butanediol di-(propan-2,3-diolyl) ether. Assessing the filler's degree of modification involves evaluating improperly cross-linked BDDE. This study analyzed commercially available HA fillers using nuclear magnetic resonance (NMR), focusing on key parameters, such as the degree of modification (MoD), the cross-linker ratio (CrR), and the degree of cross-linking. We assessed thirteen commercially available HA fillers using NMR. The samples were placed in an NMR instrument, and each sample was analyzed for 26 h, including MoD and CrR assessments. MoD 1H ranged from 17.065% to 2.239%, MoD 13C ranged from 12.567% to 1.947%, and CrR 13C ranged from 0.394 to 0.014. Significant distinctions were observed in the CrR 13C values when the MoD values of the products were similar. This study underscores the importance of considering the MoD and the CrR together to ensure optimal cross-linking and minimize the risks associated with residual BDDE impurities. Utilizing NMR for HA gel characterization provides valuable insights regarding product quality control, safety assessments, and clinical performance evaluations for esthetic interventions, contributing to filler product improvements. Further studies correlating NMR findings with real-world outcomes are essential for ensuring safety and efficacy.

A hybrid denoising method for low-field nuclear magnetic resonance data

Low-field nuclear magnetic resonance (NMR) has broad application prospects in the exploration and development of unconventional oil and gas reservoirs. However, NMR instruments tend to acquire echo signals with relatively low signal-to-noise ratio (SNR), resulting in poor accuracy of T2 spectrum inversion. It is crucial to preprocess the low SNR data with denoising methods before inversion. In this paper, a hybrid NMR data denoising method combining empirical mode decomposition-singular value decomposition (EMD-SVD) was proposed. Firstly, the echo data were decomposed with the EMD method to low- and high-frequency intrinsic mode function (IMF) components as well as a residual. Next, the SVD method was employed for the high-frequency IMF components denoising. Finally, the low-frequency IMF components, the denoised high-frequency IMF components, and the residual are summed to form the denoised signal. To validate the effectiveness and feasibility of the EMD-SVD method, numerical simulations, experimental data, and NMR log data processing were conducted. The results indicate that the inverted NMR spectra with the EMD-SVD denoising method exhibit higher quality compared to the EMD method and the SVD method.

Determination of Nicotine Protonation State in E-Liquids by Low-Resolution Benchtop NMR Spectroscopy.

Over several years, e-liquids with "nicotine salts" have gained considerable popularity. These e-liquids have a low pH, at which nicotine occurs mostly in its monoprotonated form. Manufacturers usually accomplish this by the addition of an organic acid, such as levulinic acid, benzoic acid, or lactic acid. Nicotine in its protonated form can be more easily inhaled, enhancing the addictiveness and attractiveness of products. Several techniques have been described for measuring the protonation state of nicotine in e-liquids. However, nuclear magnetic resonance (NMR) spectroscopy is particularly suited for this purpose because it can be performed on unaltered e-liquids. In this article, we demonstrate the suitability of a benchtop NMR (60 MHz) instrument for determining the protonation state of nicotine in e-liquids. The method is subsequently applied to measure the protonation state of 33 commercially available e-liquids and to investigate whether the vaping process alters the protonation state of nicotine. For this purpose, the protonation state in the condensed aerosol obtained by automated vaping of different e-liquids was compared with that of the original e-liquids. Two distinct populations were observed in the protonation state of nicotine in commercial e-liquids: free-base (fraction of free-base nicotine αfb > 0.80) and protonated (αfb < 0.40). For 30 e-liquids out of 33, the information on the packaging regarding the presence of nicotine salt was in agreement with the observed protonation state. Three e-liquids contained nicotine salt, even though this was not stated on the packaging. Measuring the protonation state of nicotine before and after (machine) vaping revealed that the protonation state of e-liquids is not affected by vaping. In conclusion, it is possible to determine the nicotine protonation state with the described method. Two clusters can be distinguished in the protonation state of commercial e-liquids, and the protonation state of nicotine remains unchanged after vaping.

A multi-technique based analytical platform for characterization and identification of a newly emerged steroid 6β-chlorotestosterone and its in-vivo epimeric metabolites

Doping athletes tend to use new and non-approved drugs in an attempt to circumvent the dope test. Recently, a package of unknown drug was obtained from black market claiming to contain steroid-like compound, which could not be readily identified due to the lack of commercially available reference standards. In order to characterize and identify the chemical structure of the unknown compound, ultra performance liquid chromatography high resolution mass spectrometry (UPLC-HRMS), high performance liquid chromatography tandem quadrupole mass spectrometry (HPLC-MS/MS), gas chromatography tandem quadrupole mass spectrometry (GC–MS/MS) and nuclear magnetic resonance (NMR) instruments were applied in this work. Based on the combined data, the unknown compound was identified as 6β-chlorotestosterone. The aim of this study was to find urinary metabolic biomarkers of 6β-chlorotestosterone for clinical research and doping control analysis. Ten in-vivo metabolites including four phase I metabolites and six phase II metabolites were characterized and potentially identified. The detailed structure of the phase I metabolite was successfully obtained by GC–MS/MS analysis of trimethylsilylation (TMS) released upon dissolution, overcoming the absence of useful fragment ions to demonstrate the structure of sulfate metabolites. Two strategies including metabolic mechanisms and retention time variation of steroids were introduced to determine and distinguish 3α/β- and 5α/β- epimeric metabolites. A comprehensive evaluation was conducted on time of appearance and detection of each metabolite. The sulfate metabolite 6β-chloro-5β-androstan-17-one-3β-O-sulfate (S1) could be detected up to 12 days after oral administration, which was considered to be the long term biomarker for 6β-chlorotestosterone abuse in clinical research and doping control analysis.

Thermal and Mechanical Investigations of (Bi, Pb)-2212 Superconductor Added with Different Oxide Nanoparticles

Abstract The current study reports the synthesis of nano-(CdO)x/Bi1.6Pb0.4Sr1.9Ca1.1Cu2.1Oy, nano-(Cd0.95Mn0.05O)x/Bi1.6Pb0.4Sr1.9Ca1.1Cu2.1Oy, and nano-(Cd0.95Fe0.05O)x/Bi1.6Pb0.4Sr1.9Ca1.1Cu2.1Oy composites, with x = 0.00, 0.01, 0.02, 0.05, and 0.10 wt. %, respectively, using the classical solid-state reaction technique. X-ray powder diffraction (XRD) confirmed the formation of an orthorhombic structure of the (Bi, Pb)-2212 as the major phase. Thermogravimetric analysis was utilized to evaluate the thermal stability of the pure sample throughout the different stages of phase formation and the effect of nanoparticle addition. The weight loss/gain from the three additions is related to the excess of oxygen, as confirmed via iodometric titration analysis and from the findings of oxygen diffusion energy. Room temperature Vickers microhardness (HV) measurements were conducted at various applied loads (0.49–9.8 N). Based on the Vickers microhardness (HV) measurements, the optimum addition of nanoparticles for increasing the microhardness of the (Bi, Pb)-2212 phase was at x = 0.05 wt. % for all superconducting composites. Iron doped Cadmium Oxide (CdFeO) nanoparticles have the greatest enhancement on the Vicker hardness values (HV) at the plateau region. Furthermore, various mechanical parameters for potential applications, such as elastic modulus (E), yield strength (Y), and fracture toughness (K) of the samples under study, were consequently extracted from HV as a function of nanoparticle addition. Moreover, CdFeO addition outperformed CdO and Manganese doped Cadmium Oxide (CdMnO) addition in improving the parameters of E, Y, K, and B, which display better ductility and an enhanced capacity to resist indentation fractures and facilitate (Bi-2212) manufactured in the form of round wires that can be used in high magnetic field magnets, nuclear magnetic resonance instruments, and large hadron colliders. Different models were theoretically used to analyze the measured HV data in the plateau limit regions. The indentation-induced cracking model offered the most accurate theoretical model at the plateau limit region based on Vickers microhardness (HV) observations.

Experimental Investigation on the Effect of Salt Solution on the Soil Freezing Characteristic Curve for Expansive Soils

With the development of the Belt and Road Initiative in China, high-speed railways are booming and inevitably pass through seasonal frost regions. In Nanyang basin, due to seasonal changes, railway subgrades will undergo frost heaving and thawing subsidence. The freezing characteristics of the soil are characterized by the freezing characteristic curve, and the important factors affecting the freezing characteristic curve are the content of expansive clay minerals in the soil and the salt solution. Therefore, three soil samples with different montmorillonite contents were saturated with salt solutions of different concentrations, and the freezing temperature of the soil samples was controlled by a cold bath. After the temperature equilibrium, the frozen stable soil samples were put into a nuclear magnetic resonance instrument to test the unfrozen water content, and the relationship between the freezing temperature and the unfrozen water content of expansive soil under different salt solution concentrations was obtained. Additionally, a unified model was used to simulate the test results. The results show that SFCC shifts to the left, that is, the sodium chloride salt solution reduces the freezing point of the soil sample so that it has more unfrozen water at the same temperature. At the same time, the soil’s freezing characteristic curves are closely related to content of expansive clay minerals in the soil. The more expansive clay mineral content, the greater the corresponding unfrozen water content. These results provide some basic insights for improving the frost heave and thaw subsidence problems of railway subgrades in seasonal permafrost regions, which will have a positive impact on promoting the management and rational application of land resources and the promotion of sustainable development.

Determination of self-diffusion coefficients in mixtures with benchtop 13C NMR spectroscopy via polarization transfer.

Nuclear magnetic resonance (NMR) is an established method to determine self-diffusion coefficients in liquids with high precision. The development of benchtop NMR spectrometers makes the method accessible to a wider community. In most cases, 1H NMR spectroscopy is used to determine self-diffusion coefficients due to its high sensitivity. However, especially when using benchtop NMR spectrometers for the investigation of complex mixtures, the signals in 1H NMR spectra can overlap, hindering the precise determination of self-diffusion coefficients. In 13C NMR spectroscopy, the signals of different compounds are generally well resolved. However, the sensitivity of 13C NMR is significantly lower than that of 1H NMR spectroscopy leading to very long measurement times, which makes diffusion coefficient measurements based on 13C NMR practically infeasible with benchtop NMR spectrometers. To circumvent this problem, we have combined two known pulse sequences, one for polarization transfer from 1H to the 13C nuclei (PENDANT) and one for the measurement of diffusion coefficients (PFG). The new method (PENPFG) was used to measure the self-diffusion coefficients of three pure solvents (acetonitrile, ethanol and 1-propanol) as well as in all their binary mixtures and the ternary mixture at various compositions. For comparison, also measurements of the same systems were carried out with a standard PFG-NMR routine on a high-field NMR instrument. The results are in good agreement and show that PENPFG is a useful tool for the measurement of the absolute value of the self-diffusion coefficients in complex liquid mixtures with benchtop NMR spectrometers.

Optimal control pulses for the 1.2-GHz (28.2-T) NMR spectrometers

The ability to measure nuclear magnetic resonance (NMR) spectra with a large sample volume is crucial for concentration-limited biological samples to attain adequate signal-to-noise (S/N) ratio. The possibility to measure with a 5-mm cryoprobe is currently absent at the 1.2-GHz NMR instruments due to the exceedingly high radio frequency power demands, which is four times compared to 600-MHz instruments. Here, we overcome the high-power demands by designing optimal control (OC) pulses with up to 20 times lower power requirements than currently necessary at a 1.2-GHz spectrometer. We show that multidimensional biomolecular NMR experiments constructed using these OC pulses can bestow improvement in the S/N ratio of up to 26%. With the expected power limitations of a 5-mm cryoprobe, we observe an enhancement in the S/N ratio of more than 240% using our OC sequences. This motivates the development of a cryoprobe with a larger volume than the current 3-mm cryoprobes.

Study of nuclear magnetic resonance response mechanism in shale oil and correction of petrophysical parameters

Shale oil reservoirs, characterized by a low porosity, complex mineral composition, and heterogeneity of organic matter distribution, are common unconventional oil and gas reservoirs. Nuclear magnetic resonance (NMR) methods have great potential for the evaluation of petrophysical parameters in porous rocks. However, it is challenging to characterize the petrophysical properties of shale oil due to the complex mineral composition and heterogeneity of organic matter distribution. In this paper, a new NMR relaxation theory for shale was proposed for the first time, and the frequency dependencies of transverse surface relaxivity and internal magnetic field gradient for pore fluids were presented. The accuracy was verified by the extraction experiments, gas chromatography experiments, and multi-frequency NMR experiments for the first time. These experiments were also utilized to determine the transverse surface relaxivity and the transverse bulk relaxation time. Subsequently, the effects of the pyrite and clay minerals on shale oil T2 distributions at different instrument frequencies were analyzed with random walk simulations based on digital core technology for the first time. The results show the echo spacing, instrument frequency, pyrite content, and clay minerals are important parameters affecting the NMR response. Compared with the oil in organic pore, these factors have a greater impact on the NMR response characteristics for water in inorganic pore. When the content of pyrite is 5.3 % and the echo spacing is 0.2 ms, the numerical simulation results show that the NMR porosity of water in inorganic pore is 65.3 %, 12.3 %, and 1.6 % of the real porosity at the instrument frequencies (IF) of 2 MHz, 21.36 MHz, and 200 MHz, respectively. When chlorite with high magnetic susceptibility exists near the formation pores, it can also affect the NMR response of shale oil. The results show the effects of these factors on porosity and T2ML are non-negligible. The cross-plots of petrophysical parameters correction from shale oil T2 distributions were established for the first time. This work provides a theoretical guide for the NMR-based shale oil evaluation, which may be helpful for petrophysical parameter conversion between downhole and laboratory NMR instruments.

The Effect of Thermal Maturity on the Pore Structure Heterogeneity of Xiamaling Shale by Multifractal Analysis Theory: A Case from Pyrolysis Simulation Experiments

Shale oil and gas, as source-reservoir-type resources, result from organic matter hydrocarbon generation, diagenesis, and nanoscale pore during the evolution processes, which are essential aspects of shale gas enrichment and reservoir formation. To investigate the impact of diagenetic hydrocarbons on shale pore heterogeneity, a thermal simulation of hydrocarbon formation was conducted on immature shale from the Middle Proterozoic Xiamaling Formation in the Zhangjiakou area, covering stages from mature to overmature. Nuclear magnetic resonance (NMR) instruments analyzed the microstructure of the thermally simulated samples, and the multifractal model quantitatively assessed pore development and heterogeneity in the experimental samples. The results reveal that the quartz and clay mineral contents show alternating trends with increasing temperature. Organic matter dissolution intensifies while unstable mineral content decreases, promoting clay mineral content development. Pyrolysis intensity influences Total Organic Carbon (TOC), which reduces as hydrocarbons are generated and released during simulation. Porosity exhibits a decreasing–increasing–decreasing trend during thermal evolution, peaking at high maturity. At maturity, hydrocarbon generation obstructs pore space, resulting in higher levels of bound fluid porosity than those of movable fluid porosity. Conversely, high maturity leads to many organic matter micropores, elevating movable fluid porosity and facilitating seepage. Shale pore heterogeneity significantly increases before 450 °C due to the dissolution of pores and the generation of liquid and gas hydrocarbons. In the highly overmature stage, pore heterogeneity tends to increase slowly, correlated with the generation of numerous micro- and nano-organic matter pores.

Investigating the Impact of Aqueous Phase on CO2 Huff ‘n’ Puff in Tight Oil Reservoirs Using Nuclear Magnetic Resonance Technology: Stimulation Measures and Mechanisms

Summary CO2 huff ‘n’ puff is a promising enhanced oil recovery (EOR) technique for tight/shale reservoirs, also enabling CO2 geological storage. However, the effectiveness of this method can be significantly affected by the aqueous phase resulting from connate water and hydraulic fracturing. The mechanism underlying the influence of the aqueous phase on oil recovery during CO2 huff ‘n’ puff, as well as the corresponding stimulation methods in such scenarios, remain unclear and warrant further study. To investigate this, we utilized a nuclear magnetic resonance (NMR) instrument to track the movement of fluids during CO2 huff ‘n’ puff under water invasion conditions. The impact of the invaded aqueous phase on oil recovery was examined, and the impact of different treatment parameters was explored. The results show that the aqueous barrier formed by water invasion alters the pathway of CO2 diffusion to matrix oil. This alteration leads to a diminished concentration of CO2 in the oil phase, which, in turn, results in a substantial reduction in oil recovery. Consequently, the performance of CO2 huff ‘n’ puff is highly sensitive to the water phase. Nevertheless, the oil recovery dynamics in cyclic CO2 huff ‘n’ puff under water invasion exhibit distinctive patterns compared with those without water invasion. These differences manifest as notable low oil recovery in the first cycle, followed by a rapid increase in the second cycle. This behavior primarily arises from the expulsion of a significant portion of the invaded water from the macropores after the first cycle. However, the effectiveness of this mechanism is limited in micropores due to the challenging displacement of trapped water in such pores. Raising the injection pressure mainly boosts oil recovery in macropores, with minimal response in micropores. Yet, the achievement of miscibility does not lead to a substantial improvement in the CO2 huff ‘n’ puff performance, primarily due to the constraints imposed by the limited CO2 dissolution through molecular diffusion Additionally, we have proposed three stimulation mechanisms achieved by lengthening the soaking time under water invasion conditions. First, the prolonged soaking time increases the concentration of CO2 molecules that diffuse into the matrix oil. Second, it promotes the imbibition of the trapped water on the fracture surface into the deeper matrix to alleviate water blockage. Finally, the invaded water in macropores displaces oil in micropores by capillary force during the soaking period.

Reaction monitoring via benchtop nuclear magnetic resonance spectroscopy: A practical comparison of on-line stopped-flow and continuous-flow sampling methods.

The ability for nuclear magnetic resonance (NMR) spectroscopy to provide quantitative, structurally rich information makes this spectroscopic technique an attractive reaction monitoring tool. The practicality of NMR for this type of analysis has only increased in the recent years with the influx of commercially available benchtop NMR instruments and compatible flow systems. In this study, we aim to compare 19F NMR reaction profiles acquired under both on-line continuous-flow and stopped-flow sampling methods, with modern benchtop NMR instrumentation, and two reaction systems: a homogeneous imination reaction and a biphasic activation of a carboxylic acid to acyl fluoride. Reaction trends with higher data density can be acquired with on-line continuous-flow analyses, and this work highlights that representative reaction trends can be acquired without any correction when monitoring resonances with a shorter spin-lattice relaxation time (T1), and with the used flow conditions. On-line stopped-flow analyses resulted in representative reaction trends in all cases, including the monitoring of resonances with a long T1, without the need of any correction factors. The benefit of easier data analysis, however, comes with the cost of time, as the fresh reaction solution must be flowed into the NMR system, halted, and time must be provided for spins to become polarized in the instrument's external magnetic field prior to spectral measurement. Results for one of the reactions were additionally compared with the use of a high-field NMR.

SOFNet: Optical-flow based large-scale slice augmentation of brain MRI

Brain magnetic resonance imaging (MRI) data from multiple centers often exhibit variations in imaging conditions, such as the types of nuclear magnetic resonance instruments used and the presence of random noise. Additionally, discrepancies in the gap between MRI slices further complicate the usability of the data for advanced artificial intelligence (AI) analysis. Deep learning-based methods have emerged as practical solutions to address the challenge. However, existing research has largely overlooked the augmentation of brain MRI data, particularly when confronted with significant slice gaps, such as around 6 mm observed in our clinical brain MRI slices. In response to this research gap, we aim to develop novel approaches for augmenting brain MRI data, focusing on more significant slice gaps. To achieve this, we propose SOFNet, which utilizes the optical flow-based and encoder–decoder backbone. The primary objective of our model is to interpolate MRI slices while preserving feature consistency. Leveraging the optical flow method, which has exhibited exceptional performance compared to other super-resolution algorithms, our proposed approach has been evaluated on three distinct brain MRI datasets, explicitly addressing the gap between 4.2 mm and 6.0 mm. The experimental results highlight the significant enhancement in super-resolution quality achieved by SOFNet in generating adapted brain MRI data, surpassing other single-image super-resolution (SISR) methods in feature completion. To ensure the credibility of the interpolated brain MRI slices, we conducted experiments on three axes of MRI based on metrics such as peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM). These experiments demonstrate the effectiveness of our approach in transforming low-resolution MRI data into clear and reliable brain MRIs, thereby enabling improved analysis using AI techniques.

High-Quality Reconstruction for Laplace NMR Based on Deep Learning.

Laplace nuclear magnetic resonance (NMR) exploits relaxation and diffusion phenomena to reveal information regarding molecular motions and dynamic interactions, offering chemical resolution not accessible by conventional Fourier NMR. Generally, the applicability of Laplace NMR is subject to the performance of signal processing and reconstruction algorithms involving an ill-posed inverse problem. Here, we propose a proof-of-concept of a deep-learning-based method for rapid and high-quality spectra reconstruction from Laplace NMR experimental data. This reconstruction method is performed based on training on synthetic exponentially decaying data, which avoids a vast amount of practically acquired data and makes it readily suitable for one-dimensional relaxation and diffusion measurements by commercial NMR instruments.

1618-P: Fasting Decreases Pyruvate Carboxylase Flux in the Perfused Exocrine Pancreas

The exocrine pancreas displays structural and functional abnormalities in type 1 diabetes, such as acinar atrophy and fibrosis. Metabolic dysfunction may occur alongside these changes. We established a method to investigate exocrine metabolism using nuclear magnetic resonance (NMR) and hyperpolarized (HP) substrates. This approach conserves the native environment while permitting analysis of metabolic flux in the living pancreas. Here, we compared exocrine pancreas metabolism in fed (n=4) and fasted (n=5) male C57BL/6J mice. Each pancreas was perfused for 30 minutes with oxygenated Krebs-Heinsleit buffer in a 14 T NMR instrument. NMR spectra were collected after injection of 4 mM HP [1-13C] pyruvate into the common bile duct. 13C signals from several central carbon metabolites were detected, such as alanine, malate, and fumarate. Pancreata from fasted mice produced less (p&amp;lt;0.05) fumarate and aspartate compared to those from the fed mice. After perfusion, all pancreata were analyzed by gas chromatography - mass spectrometry for metabolite quantification. Malate was significantly enriched (p&amp;lt;0.05) by 13C in the fed pancreas with similar total malate between groups. Overall, these results suggest that the exocrine pancreas displays higher pyruvate carboxylase (PC) flux in the fed state compared to the fasted state. The methodology presented here provides a unique avenue to assess pancreatic metabolism in real-time. Disclosure A.Rushin: None. M.Mcleod: None. M.Glanz: None. D.S.Graham: None. M.Merritt: None. Funding National Institutes of Health (T32DK10876); National Science Foundation (DMR-1644779)

Evolutionary Law of Pore Structure of Ion-Adsorbed Rare Earth Ore Leaching Process

In the process of ion-adsorbed rare earth (RE) ore leaching and mining, the injected chemical agent and rare earth particles have a strong chemical reaction, resulting in changes in the structure of the rare earth, and thus affecting the macroscopic mechanical properties and permeability of soil. To investigate the evolution of the pore structure during the leaching process, indoor leaching simulation experiments were used to compare and analyze the changes of Zeta potential during the leaching process with different concentrations of leaching solution, the process of the gradual change of the strong and weak combined water layer was analyzed, and a nuclear magnetic resonance (NMR) instrument was used to obtain the structural parameters such as the porosity, T2 spectrum and pore radius to analyze the evolution law of microscopic pore structure. The experimental results show that the deionized (DI) water leaching process has less effect on the pore structure of the ore body, and the pore structure inside the ore body evolves gradually from small and medium pore size pores to large pore size pores, while the pore structure of the ore body changes more during the leaching process of the MgSO4 leaching solution. In the initial leaching stage, the number of minimal pores (0–0.24 μm) and small pores (0.24–0.65 μm) of the ore body decreases rapidly, and the number of large pores (1.6–10 μm) increases. In the effective leaching stage, the number of minimal pores (0–0.24 μm), small pores (0.24–0.65 μm) and medium pores (0.65–1.6 μm) increases, while the number of large pores (1.6–10 μm) and mega pores (greater than 10 μm) decreases. At the end of leaching stage, the pore size evolves from medium pores (0.65–1.6 μm) and small pore (0.24–0.65 μm) to large pores (1.6–10 μm). Both chemical replacement reaction and solution percolation can induce changes in the pore structure of the ore body, and the influence of the chemical replacement reaction is higher than that of percolation in the leaching process. The evolution of pore structure during ion exchange is caused by the difference of ionic strength in leaching solution. RE ore particles are adsorbed or released to the solid phase, and the migration of particles leads to changes in the interface properties of RE particles, which affects the pore structural changes.

Variational Mode Decomposition for NMR Echo Data Denoising

Nuclear magnetic resonance (NMR) relaxometry, a noninvasive and nondestructive method, is a key technique for unconventional reservoir evaluation. Echo data detected from NMR instrument, a kind of weak signal, however, is characterized by a low signal-to-noise ratio (SNR). The achievement of NMR relaxation spectra inversion of a high precision, for echo data with a low SNR, is a challenge, which will also affect the unconventional reservoir evaluation of NMR logging. In this article, a variational mode decomposition (VMD) method was proposed for NMR echo data denoising. NMR echo data were decomposed into an ensemble of intrinsic mode functions (IMFs) by the VMD method. The IMF number is an important parameter for VMD, and VMD results are different with various IMF numbers. An optimal selection method for the IMF number was proposed. The decomposed IMFs compose of signals with different frequencies. Noise is from high-frequency signal, but valuable data are from low-frequency signal. The effective IMFs in VMD were selected and summed as the denoised echo data. Numerical simulations and field NMR logging data processing were undertaken to evaluate the NMR echo data denoising effectiveness and practicality of the proposed VMD-based method. The results showed that the inverted NMR spectra exhibit a higher quality after the VMD-based denoise, compared with those for raw echo data and after the empirical mode decomposition (EMD) denoise. This indicates that a higher denoising quality is achieved by the VMD-based method than by the EMD-based method for NMR echo data.

Determination of copolymer compositions in polyhydroxyalkanoates using 1H benchtop nuclear magnetic resonance spectroscopy.

Continuous research into polyhydroxyalkanoates (PHAs), biodegradable polymers which can be produced by, and harvested from, various bacteria has led to more cost-effective ways of isolating and commercializing them. As bio-based polymers, PHAs can be transformed into compostable bioplastics and utilized for a variety of applications. Often isolated as copolymers, the monomeric ratio compositions of these products greatly affect both the properties and consequently, possible end uses of these products. As such, methods of reliably characterizing these ratios are important for quality control and product development purposes. Herein, we discuss how 1H benchtop nuclear magnetic resonance (NMR) instruments can be used for the determination of monomeric ratio compositions in PHAs and compare results obtained at three different NMR field strengths: 1.40 T (60 MHz), 2.35 T (100 MHz), and 9.4 T (400 MHz).

Biological Magnetic Resonance Data Bank.

The Biological Magnetic Resonance Data Bank (BMRB, https://bmrb.io) is the international open data repository for biomolecular nuclear magnetic resonance (NMR) data. Comprised of both empirical and derived data, BMRB has applications in the study of biomacromolecular structure and dynamics, biomolecular interactions, drug discovery, intrinsically disordered proteins, natural products, biomarkers, and metabolomics. Advances including GHz-class NMR instruments, national and trans-national NMR cyberinfrastructure, hybrid structural biology methods and machine learning are driving increases in the amount, type, and applications of NMR data in the biosciences. BMRB is a Core Archive and member of the World-wide Protein Data Bank (wwPDB).

Usefulness of Applying Partial Least Squares Regression to T2 Relaxation Curves for Predicting the Solid form Content in Binary Physical Mixtures

This study applied partial least squares (PLS) regression to nuclear magnetic resonance (NMR) relaxation curves to quantify the free base of an active pharmaceutical ingredient powder. We measured the T2 relaxation of intact and moisture-absorbed physical mixtures of tetracaine free base (TC) and its hydrochloride salt (TC·HCl). The obtained T2 relaxation curves were analyzed by two methods, one using a previously reported T2 relaxation time (T2), and the other using PLS regression. The accuracy of estimating TC was inadequate when using previous T2 values because the moisture-absorbed physical mixtures showed biphasic T2 relaxation curves. By contrast, the entire measured whole of the T2 relaxation curves was used as input variables and analyzed by PLS regression to quantify the content of TC in the moisture-absorbed TC/TC·HCl. Based on scatterplots of theoretical versus predicted TC, the obtained PLS model exhibited acceptable coefficients of determination and relatively low root mean squared error values for calibration and validation data. The statistical values confirmed that an accurate and reliable PLS model was created to quantify TC in even moisture-absorbed TC/TC·HCl. The bench-top low-field NMR instrument used to apply PLS regression to the T2 relaxation curve may be a promising tool in process analytical technology.