Acquisition Of Spectra Research Articles

Vis-NIR spectroscopy based rapid and non-destructive method to quantitate microplastics: An emerging contaminant in farm soil

Microplastics (MPs) is the second most important environmental issue and can potentially enter into food chain through farmland contamination and other means. There are no standardized extraction methods for quantification of MPs in soil. The embedded errors and biases generated serious problems regarding the comparability of different studies and leading to erroneous estimation. To address this gap, present study was formulated to develop an efficient method for MPs analysis suitable for a wide range of soil and organic matrices. A method based on Vis-NIR (Visible-Near Infra Red) spectroscopy is developed for four different soil belonging to Alfisol, Inceptisol, Mollisol and Vertisol and two organic matter matrices (FYM and Sludge). The developed method was found as rapid, reproducible, non-destructive and accurate method for estimation of all three-density groups of MPs (Low, Medium and High) with a prediction accuracy ranging from 1.9 g MPs/kg soil (Vertisol) to 3.7 g MPs/kg soil (Alfisol). Two different regression models [Partial Least Square Regression (PLSR) and Principal Component Regression (PCR)] were assessed and PLSR was found to provide better information in terms of prediction accuracy and minimum quantification limit (MQL). However, PCR performed better for organic matter matrices than PLSR. The method avoids any complicated sample preparation steps except drying and sieving thus saving time and acquisition of reflectance spectrum for single sample is possible within 18 s. Owing to have the minimum quantification limit ranging from 1.9–3.7 g/kg soil, the vis-NIR based method is perfectly suitable for estimation of MPs in soil samples collected from plastic pollution hotspots like landfill sites, regular based sludge amended farm soils. Additionally, the method can be adapted by small scale compost industries for assessing MPs load in product like city compost which are applied at agricultural fields and will be helpful in quantifying possible MPs at the sources itself.

Identifying Exchangeable Protons in a 1D NMR Spectrum by Spatially Selective Exchange-Editing.

Signals undergoing chemical or conformational exchange in one-dimensional NMR spectra are often identified by deuterium exchange. In order to obtain quantitative information about the dynamic processes involved, one frequently used method is EXchange SpectroscopY (EXSY). To detect all exchange processes, the EXSY experiment requires the acquisition of time-consuming two-dimensional spectra. Here we report a faster alternative, an experiment which uses spatial encoding to extract similar information in a 1D exchange-edited experiment. Thereby, all protons are observed at once, but in different slices of the detection volume. The experiment can be carried out in a single scan to identify exchanging sites in a 1D spectrum by changes in signal intensity indicating exchange processes. If the exchanging partner, for example water is in molar excess the exchange-editing method easily identifies mobile protons by negative signals in the 1D 1H NMR spectrum.

Multimodal fiber probe for simultaneous mid-infrared and Raman spectroscopy

A fiber probe has been developed that enables simultaneous acquisition of mid-infrared (MIR) and Raman spectra in the region of 3100–2600 cm−1. Multimodal measurement is based on a proposed ZrO2 crystal design at the tip of an attenuated total reflection (ATR) probe. Mid-infrared ATR spectra are obtained through a pair of chalcogenide infrared (CIR) fibers mounted at the base of the crystal. The probe enables both excitation and acquisition of a weak Raman signal from a portion of the sample in front of the crystal using an additional pair of silica fibers located in a plane perpendicular to the CIR fibers. The advantages of combining MIR and Raman spectra in a single probe have been discussed.

RNA m6a Methylation Regulator Expression in Castration-Resistant Prostate Cancer Progression and Its Genetic Associations.

N6-methyladenosine (m6A) methylation, a prevalent epitranscriptomic modification, plays a crucial role in regulating mRNA expression, stability, and translation in mammals. M6A regulators have gained attention for their potential implications in tumorigenesis and clinical applications, such as cancer diagnosis and therapeutics. The existing literature predominantly addresses m6A regulators in the context of primary prostate cancer (PCa). However, a notable gap in the knowledge emerges regarding the dynamic expression patterns of these regulators as PCa progresses towards the castration-resistant stage (CRPC). Employing sequential window acquisition of all theoretical mass spectra (SWATH-MS) and RNAseq analysis, we comprehensively profiled the expression of 27 m6A regulators in hormone/androgen-dependent and -independent PCa cell lines, revealing distinct clustering between tumor and adjacent normal prostate tissues. High-grade PCa tumors demonstrated the upregulation of METTL3, RBM15B, and HNRNAPA2B1 and the downregulation of ZC3H13, NUDT21, and FTO. Notably, we identified six m6A regulators associated with PCa survival. Additionally, association analysis of the PCa-associated risk loci in the cancer genome atlas program (TCGA) data unveiled genetic variations near the WTAP, HNRNPA2B1, and FTO genes as significant expression quantitative trait loci. In summary, our study unraveled abnormalities in m6A regulator expression in PCa progression, elucidating their association with PCa risk loci. Considering the heterogeneity within the PCa phenotypes and treatment responses, our findings suggest that prognostic stratification based on m6A regulator expression could enhance PCa diagnosis and prognosis.

IMPORTANT-Net: Integrated MRI multi-parametric increment fusion generator with attention network for synthesizing absent data

Magnetic resonance imaging (MRI) is highly sensitive for lesion detection. Sequences obtained with different settings can capture specific characteristics of lesions. Such multi-parametric MRI information has been shown to aid radiologist performance in lesion classification, as well as improving the performance of artificial intelligence models in various tasks. However, obtaining multi-parametric MRI makes the examination costly from both financial and time perspectives, and there may also be safety concerns for special populations, thus making acquisition of the full spectrum of MRI sequences less durable. In this study, a sophisticated Integrated MRI Multi-Parametric increment fusiOn generatoR wiTh AtteNTion Network (IMPORTANT-Net) is developed to generate absent sequences/parameters. First, the parameter reconstruction module is used to encode and restore the existing MRI parameters to obtain the corresponding latent representation information at any scale level. Then the multi-parametric fusion with attention module enables the interaction of the encoded information from different parameters through a set of algorithmic strategies, and applies different weights to the information through the attention mechanism after information fusion to obtain refined representation information. Finally, a increment fusion scheme embedded in a V-shape generation module is used to combine the hierarchical representations to generate specified absent MRI parameter. Results showed that our IMPORTANT-Net is capable of synthesizing absent MRI, outperforms comparable state-of-the-art networks and more importantly benefit downstream tasks. The codes are available at https://github.com/Netherlands-Cancer-Institute/MRI_IMPORTANT_NET

Detection of endometrial cancer in cervico-vaginal fluid and blood plasma: leveraging proteomics and machine learning for biomarker discovery

The anatomical continuity between the uterine cavity and the lower genital tract allows for the exploitation of uterine-derived biomaterial in cervico-vaginal fluid for endometrial cancer detection based on non-invasive sampling methodologies. Plasma is an attractive biofluid for cancer detection due to its simplicity and ease of collection. In this biomarker discovery study, we aimed to identify proteomic signatures that accurately discriminate endometrial cancer from controls in cervico-vaginal fluid and blood plasma. Blood plasma and Delphi Screener-collected cervico-vaginal fluid samples were acquired from symptomatic post-menopausal women with (n=53) and without (n=65) endometrial cancer. Digitised proteomic maps were derived for each sample using sequential window acquisition of all theoretical mass spectra (SWATH-MS). Machine learning was employed to identify the most discriminatory proteins. The best diagnostic model was determined based on accuracy and model parsimony. A protein signature derived from cervico-vaginal fluid more accurately discriminated cancer from control samples than one derived from plasma. A 5-biomarker panel of cervico-vaginal fluid derived proteins (HPT, LG3BP, FGA, LY6D and IGHM) predicted endometrial cancer with an AUC of 0.95 (0.91-0.98), sensitivity of 91% (83%-98%), and specificity of 86% (78%-95%). By contrast, a 3-marker panel of plasma proteins (APOD, PSMA7 and HPT) predicted endometrial cancer with an AUC of 0.87 (0.81-0.93), sensitivity of 75% (64%-86%), and specificity of 84% (75%-93%). The parsimonious model AUC values for detection of stage I endometrial cancer in cervico-vaginal fluid and blood plasma were 0.92 (0.87-0.97) and 0.88 (0.82-0.95) respectively. Here, we leveraged the natural shed of endometrial tumours to potentially develop an innovative approach to endometrial cancer detection. We show proof of principle that endometrial cancers secrete unique protein signatures that can enable cancer detection via cervico-vaginal fluid assays. Confirmation in a larger independent cohort is warranted. Cancer Research UK, Blood Cancer UK, National Institute for Health Research.

NMR Analysis of Extra Virgin Olive Oil of the Epirus Region of Greece with Emphasis on Selected Phenolic Compounds.

Extra virgin olive oil (EVOO) is recognized for its numerous health benefits, attributed to its rich phenolic components. NMR has emerged as a prevalent technique for precisely identifying these compounds. Among Mediterranean countries, Greece stands as the third-largest producer of olives, with the Epirus region notably advancing in olive cultivation, contributing significantly to the dynamic growth of the region. In this study, an NMR method was employed based on the acquisition of a 1H NMR spectrum along with multiple resonant suppression in order to increase the sensitivity. Using the above method, 198 samples of extra virgin olive oil, primarily sourced from the Epirus region, were analyzed, and both the qualitative and quantitative aspects of the phenolic compounds were obtained. In addition, we examined the effects of various factors such as variety, harvest month, and region origin on the phenolic compounds' concentration. The results revealed an average total phenolic content of 246 mg/kg, closely approaching the EU health claim limit of 250 mg/kg. Approximately 15% of the samples were confidently characterized as high-phenolic olive oil. The highest concentrations were observed in the Thesprotia samples, with several Lianolia varieties exceeding the total phenolic content of 400 mg/kg. Statistical tests demonstrated a significant influence of the olive variety and the month of fruit harvest on phenolic component concentration, followed by the region of origin. A very strong correlation was noted between the total phenolics content and the levels of oleocanthal and oleacein, with a correlation coefficient (r) of 0.924. Upon optimization of all factors affecting olive oil quality, the majority of the EVOOs from the Epirus region have the potential to be characterized as high in phenolic content.

Electron knock-on damage effects on electron magnetic chiral dichroism of magnetic metals using cobalt as a model

Electron magnetic chiral dichroism (EMCD) is a high-resolution technique currently in development for quantitative magnetic measurements using transmitted electrons. However, the inevitable electron damage to materials can be a significant yet easily overlooked factor affecting the quantification accuracy. This work experimentally investigated the electron knock-on damage effects on EMCD of magnetic metals using metallic cobalt as a model. Three issues are involved in the metal-surface damage process. It was revealed that under sustained electron irradiation during spectra acquisition, gradual removal of the thin surface oxidation layer, rather than a simple continuous thickness reduction that changes the diffraction and plural scattering conditions, can lead to notable residual nonmagnetic components in EMCD spectra and may make the quantified result of the orbital-to-spin moment ratio remarkably higher than the actual value. It was, thus, proposed to pay great attention to the surface oxidation and to minimize the effect of the oxidation layer by performing electron irradiation on the target area prior to EMCD experiments. A further experiment was additionally proposed to quantify the impact of thickness reduction on the magnetic components of momentum-resolved electron energy-loss spectra and the EMCD quantification. This study advances the application of EMCD in magnetic metals.

Implantable theranostic device for in vivo real-time NMR evaluation of drug impact in brain tumors.

The evaluation of the efficacy of a drug is a fundamental step in the development of new treatments or in personalized therapeutic strategies and patient management. Ideally, this evaluation should be rapid, possibly in real time, easy to perform and reliable. In addition, it should be associated with as few adverse effects as possible for the patient. In this study, we present a device designed to meet these goals for assessing therapeutic response. This theranostic device is based on the use of magnetic resonance imaging and spectroscopy for the diagnostic aspect and on the application of the convection-enhanced delivery technique for the therapeutic aspect. The miniaturized device is implantable and can be used in vivo in a target tissue. In this study, the device was applied to rodent glioma models with local administration of choline kinase inhibitor and acquisition of magnetic resonance images and spectra at 7 Tesla. The variations in the concentration of key metabolites measured by the device during the administration of the molecules demonstrate the relevance of the approach and the potential of the device.

Solid Propellant Aging Detection Method Based on Impedance Spectroscopy

Aiming at the shortcomings of large volume, high cost and long detection cycle of traditional solid propellant aging detection methods, a solid propellant aging detection method based on impedance spectroscopy is proposed. Firstly, the internal impedance of the solid propellant changes after aging, and a portable solid propellant impedance spectrum acquisition system based on impedance spectroscopy is designed based on the principle of electrochemical impedance spectroscopy, and the real and imaginary parts of the impedance spectrum are obtained. Secondly, in order to reduce the data dimension of the classification algorithm, the KPCA (Nuclear Principal Component Analysis) feature extraction algorithm is used to extract the impedance spectrum features of the solid propellant. Then, according to the impedance spectrum characteristics, the BP neural network is used for classification training, and the correspondence between the impedance spectrum and the aging time is obtained. Finally, the feasibility and effectiveness of the proposed method are verified on the physical platform, and the results show that the proposed method has the advantages of high precision and accurate classification, and can effectively predict the aging degree of solid propellant.

Utilizing a Metal Inlet Coiled with Copper Wire as the Ion Source for Ambient Ionization Mass Spectrometry.

In ambient ionization mass spectrometry (MS), a customized metal inlet is typically adapted to the orifice of the mass spectrometer for ease of introduction of the sample. We herein explore that the metal inlet coiled with a copper wire (∼50 μm) can be directly used as an ion source to induce corona discharge-like processes for ionization of analytes in the gas phase. When the metal inlet is subjected to a high voltage in the mass spectrometer, the electric field provided by the mass spectrometer enables the generation of corona discharge to ionize volatile/semivolatile analytes derived from the sample in the condensed phase. The limit of detection for azulene derived from the aqueous sample was as low as ∼1 pM. Moreover, we also demonstrated the feasibility of coupling ultraviolet-visible absorption spectroscopy with MS by using the metal inlet coiled with a thin copper wire as the interface. Integration of these two techniques enables the simultaneous acquisition of spectra from both instruments for quantitative and qualitative analysis of the sample. Furthermore, we showed that polar and nonpolar analytes in a mixture can be acquired in the same mass spectrum by simply depositing a sample droplet (∼20 μL) on a dielectric substrate near the copper wire-coiled metal inlet of the mass spectrometer. The ionization processes involved both electrospray ionization and corona discharge. To demonstrate the applicability of our method for detecting nonpolar and polar analytes in complex samples, we spiked a nonpolar analyte, benzo[a]pyrene, to a spice sample and successfully detected analytes with different polarities using our approach.

Retention time-independent strategy for screening pesticide residues in herbs based on a fingerprint database and all ion fragmentation acquisition with LC-QTOF MS.

A retention time (RT)-independent strategy for nontargeted screening of pesticide residues in herbs was exploited using liquid chromatography-quadrupole time-of-flight mass spectrometry (LC-QTOF MS). The core of this strategy is a fingerprint database coupled with a data-independent acquisition (DIA) scan mode of all ion fragmentation (AIF). In the fingerprint database, a total of 150 pesticides with quasimolecular ions and fragment ions at five-level collision energies were collected as qualified ions for screening. During the data acquisition, the AIF scan was performed via real unbiased full-spectrum MS/MS acquisition. Six herb matrices spiked with 30 banned pesticides were used to evaluate the applicability of the strategy in real samples. The use of the narrow ion mass extraction window (10 mDa) and the narrow RT window (0.1 min) enabled the effective extraction of spectra from noisy backgrounds and the discovery of suspected pesticides via similarity matching of filtered qualified ions. On average, more than 11/30 of pesticides at 1 ng mL-1 and more than 23/30 of pesticides at 10 ng mL-1 or lower could be screened out in each matrix using at least two qualified ions. In addition, the AIF mode exhibited superior anti-interference capability compared to data-dependent acquisition (DDA) and sequential window acquisition of all theoretical mass spectra (SWATH), as determined by comparing the limits of screening (LOSs) of 30 banned pesticides spiked into Isatidis Folium. Finally, the developed strategy was applied to screen pesticide residues in extracts of Ganoderma and Foeniculi Fructus. Phorate-sulfone and phorate-sulfoxide were found in Ganoderma, as well as terbufos-sulfone and terbufos-sulfoxide were found in Foeniculi Fructus. In conclusion, the developed RT-independent strategy based on a fingerprint database and AIF acquisition with LC-QTOF MS seems to be one of the most efficient tools for the analysis of nontargeted pesticide residues in complicated matrices.

Structure and bonding in rhodium coordination compounds: a 103Rh solid-state NMR and relativistic DFT study.

This study demonstrates the application of 103Rh solid-state NMR (SSNMR) spectroscopy to inorganic and organometallic coordination compounds, in combination with relativistic density functional theory (DFT) calculations of 103Rh chemical shift tensors and their analysis with natural bond orbital (NBO) and natural localized molecular orbital (NLMO) protocols, to develop correlations between 103Rh chemical shift tensors, molecular structure, and Rh-ligand bonding. 103Rh is one of the least receptive NMR nuclides, and consequently, there are very few reports in the literature. We introduce robust 103Rh SSNMR protocols for stationary samples, which use the broadband adiabatic inversion-cross polarization (BRAIN-CP) pulse sequence and wideband uniform-rate smooth-truncation (WURST) pulses for excitation, refocusing, and polarization transfer, and demonstrate the acquisition of 103Rh SSNMR spectra of unprecedented signal-to-noise and uniformity. The 103Rh chemical shift tensors determined from these spectra are complemented by NBO/NLMO analyses of contributions of individual orbitals to the 103Rh magnetic shielding tensors to understand their relationship to structure and bonding. Finally, we discuss the potential for these experimental and theoretical protocols for investigating a wide range of materials containing the platinum group elements.

Accelerated acquisition of wideline solid-state NMR spectra of spin 3/2 nuclei by frequency-stepped indirect detection experiments.

73% of all NMR-active nuclei are quadrupolar nuclei with a nuclear spin I > 1/2. The broadening of the solid-state NMR signals by the quadrupolar interaction often leads to poor sensitivity and low resolution. In this work we present experimental and theoretical investigations of magic angle spinning (MAS) 1H{X} double-echo resonance-echo saturation-pulse double-resonance (DE-RESPDOR) and Y{X} J-resolved solid-state NMR experiments for the indirect detection of spin 3/2 quadrupolar nuclei (X = spin 3/2 nuclei, Y = spin 1/2 nuclei). In these experiments, the spectrum of the quadrupolar nucleus is reconstructed by plotting the observed dephasing of the detected spin as a function of the transmitter offset of the indirectly detected spin. Numerical simulations were used to investigate the achievable levels of dephasing and to predict the lineshapes of indirectly detected NMR spectra of the quadrupolar nucleus. We demonstrate 1H, 31P and 207Pb detection of 35Cl, 81Br, and 63Cu (I = 3/2) nuclei in trans-Cl2Pt(NH3)2 (transplatin), (CH3NH3)PbCl3 (methylammonium lead chloride, MAPbCl3), (CH3NH3)PbBr3 (methylammonium lead bromide, MAPbBr3) and CH3C(CH2PPh2)3CuI (1,1,1-tris(diphenylphosphinomethyl)ethane copper(I) iodide, triphosCuI), respectively. In all of these experiments, we were able to detect megahertz wide central transition or satellite transition powder patterns. Significant time savings and gains in sensitivity were attained in several test cases. Additionally, the indirect detection experiments provide valuable structural information because they confirm the presence of dipolar or scalar couplings between the detected nucleus and the quadrupolar nucleus of interest. Finally, numerical simulations suggest these methods are also potentially applicable to abundant spin 5/2 and spin 7/2 quadrupolar nuclei.

Characterisation of reproductive tract microbiome and immune biomarkers for bovine genital campylobacteriosis in vaccinated and unvaccinated heifers.

Bovine genital campylobacteriosis (BGC) is a globally important venereal disease of cattle caused by Campylobacter fetus subspecies venerealis. Diagnosis of BGC is highly challenging due to the lack of accurate diagnostic tests. To characterise the biomarkers for C. fetus venerealis infection, a total of twelve cycling heifers were selected and categorised as vaccinated (n = 6) with Vibrovax® (Zoetis™) and unvaccinated (n = 6). All heifers were oestrous synchronised with a double dose of prostaglandin (PGF2α) 11 days apart and when in oestrous intravaginally challenged with 2.7 x 109 CFU live C. fetus venerealis. DNA extracted from vaginal mucus samples was screened using a C. fetus qPCR and 16S rRNA was characterised using Illumina sequencing (V5-V8 region). Relative abundances of serum proteins were calculated using sequential window acquisition of all theoretical fragment ion spectra coupled to tandem mass spectrometry (SWATH-MS) for all heifers at three timepoints: pre-challenge, post-challenge and post-recovery. In 16S rRNA sequencing of vaginal mucus, Campylobacter spp. appeared two days following challenge in unvaccinated compared to 14 days in vaccinated animals, consistent with the qPCR results. Increased relative abundances of Firmicutes and Campylobacterota were identified after C. fetus venerealis challenge and were associated with C. fetus venerealis in vaccinated and unvaccinated heifers. Greater relative abundance of Streptococcus spp. was observed during oestrous rather than dioestrous. In both vaccinated and unvaccinated heifers, Acinetobacter spp. increased after challenge with higher abundance of Corynebacterium spp. in the vaccinated group. A total of 130 unique proteins were identified in SWATH analysis of the serum samples, and the number of differentially abundant proteins found was higher in the vaccinated group after recovery from infection compared to pre-and post-challenge (adjusted P < 0.05 and Log2FC > 0.2). Coglutinin, clusterin, HP homologs, vitamin D binding protein and fetuin B were identified as potential biomarkers for C. fetus venerealis infection and need further study to validate their efficiency as immune biomarkers for BGC.

Targeted retinal spectroscopy: Towards a localized assessment of biomarkers in the eye fundus

Aims/Purpose: The non‐invasive evaluation of biomarkers for the screening, diagnosis, and monitoring of ocular and neurological diseases is receiving increasing attention. Targeted retinal spectroscopy (TRS) enables simultaneous imaging and high‐quality spectral analysis from specific regions of the eye fundus. It offers valuable information on the structure, composition, and function of retinal tissues. This study demonstrates the capabilities of TRS and assesses its effectiveness in retinal oximetry.Methods: The Zilia Ocular TRS platform was developed and evaluated. First, a reference target and a model eye were used to demonstrate the targeted spectral analysis. Then, Monte Carlo simulations were used to identify crucial TRS parameters—such as spectral range, resolution, noise, and tissue scattering—for retinal oximetry. Simultaneous imaging of the eye fundus and diffuse reflectance spectra acquisitions were performed in two targeted regions of the eye fundus of eight healthy subjects to determine blood oxygen saturation (StO2).Results: Experiments performed with the reference target and model eye showed precise and distinct spectral signatures for each targeted region. Simulation results showed that highest StO2 accuracy was obtained with a spectral range between 530 nm and 585 nm, while a resolution below 4 nm compromised the accuracy. In addition, acquisition areas larger than blood vessels led to an underestimation of StO2, and a linear correlation was found between the additive noise level and the variability of StO2. In vivo oximetry measurements revealed significant differences in StO2 between the optic nerve head and the parafovea.Conclusions: TRS opens up new possibilities for disease screening, diagnosis and monitoring, including assessing oximetry in glaucoma, diabetic retinopathy, age‐related macular degeneration, etc. To account for confounding factors, careful selection of acquisition parameters is crucial, as emphasized in this study.

DrogoFinder: An open-source graphical user interface for the identification of illicit drugs using infrared spectroscopy

The development of Free and Open-Source Software (FOSS) is being increasingly recognized as an indispensable resource for the development, validation, and replication of analytical methodologies and tools. In this context, the use of Attenuated Total Reflectance Infrared (ATR-IR) spectroscopy for the in-situ identification of drugs requires software for the treatment of spectroscopic data, including spectral quality controls, the subtraction of possible excipients, and the comparison with well-defined libraries that can be complex and limits its application on the field analysis by non-expert users. Here we describe a user-friendly FOSS for drug identification that can be operated in an intuitive way, including automatic features such as i) quality controls that warn the user from possible technical problems during spectrum acquisition (e.g. water vapour, contaminated background), ii) the subtraction of the contribution of excipients and other substances present on the sample, and iii) the creation of custom and updated cloud-based libraries to deal with the great number of new psychoactive substances (NPS) that are constantly being developed and introduced for their consume. The proposed application was tested by expert and non-expert users with spectra from 42 drug samples measured in situ in a music festival and 39 seized samples measured in a laboratory. Non-expert users were able to flag technical problems in the spectra and to perform excipient subtractions automatically, obtaining drug identifications that matched those ones obtained by reference methods and dedicated commercial software. We share both, the code, and a standalone Windows app to reach worldwide users and scientists interested in the identification of drugs.

Novel Operando Nuclear Magnetic Resonance Approach for Tracking the Electrode State of Charge in Li/Na-Ion Batteries

Lithium and sodium-ion batteries have become the focal point of interest for the energy transition due to their promising applications for electric cars and energy grid storage. Operando characterization of batteries is critical to understand the degradation processes and increasing their electrochemical performance, especially in abusive conditions like during fast charges. Knowledge of the redox state of each electrode is essential to identify the origins of capacity loss in full batteries. Among the methods used for these investigations, operando Nuclear Magnetic Resonance (NMR) methods are promising since, without destroying the battery, they enable monitoring in real-time the electrochemical processes and the formation of short-lived metastable or reactive phases [1,2].Up to now, most operando NMR studies have focused on 7Li NMR spectroscopy to follow the lithiation and degradation processes in the solid electrodes of lithium-ion batteries. However, the large shifts and broadenings of the NMR spectra, which result from the redox-active paramagnetic ions (Ni2/3+, Co4+, Mn3/4+) or from the metallicity of the electrodes [3], complicate operando NMR spectra acquisition and interpretation for full batteries.Herein, we demonstrate that the 1H operando NMR signal of the liquid electrolyte solvent can be used to spy on the positive electrode evolution while benefitting from the high sensitivity of 1H liquid-state NMR compared to 7Li NMR. So far, operando NMR using the liquid electrolyte signal was mainly exploited to follow electrolyte decomposition [4] or to image indirectly dendrite formation [5]. Contrary to the lithium or sodium atoms composing the electrodes, hydrogen atoms in the electrolyte solvent are not a direct probe of the state of charge of the electrode. We demonstrate that the 1H NMR signal of the electrolyte molecules in the battery is, however, highly sensitive to the magnetic susceptibility (and therefore the redox state) of the neighboring particles of positive electrode active material.The state-of-charge (SOC) of the positive electrodes in the charging battery can be tracked indirectly through distortion in the spectrum of the dimethyl carbonate (DMC) solvent near the positive electrode. The effect of the other battery components such as current collectors, separators, or even negative electrodes is shown to be negligible compared to the perturbations induced by the positive electrode. We define specific descriptors to track the changes in the distorted 1H NMR spectrum of the battery and we correlate these changes with the state-of-charge of the positive electrode inside the battery as it is charged and discharged. This approach will enable measuring, operando, the redox state of positive electrodes in batteries, even when their 7Li signals cannot be detected by NMR. Exact knowledge of the redox state will contribute to a better exploitation of the electrochemical curves in full batteries.[1] Bagheri, K.; Deschamps, M.; Salager, E. Nuclear Magnetic Resonance for Interfaces in Rechargeable Batteries. Current Opinion in Colloid & Interface Science 2023, 64, 101675. https://doi.org/10.1016/j.cocis.2022.101675.[2] Liu, X.; Liang, Z.; Xiang, Y.; Lin, M.; Li, Q.; Liu, Z.; Zhong, G.; Fu, R.; Yang, Y. Solid‐State NMR and MRI Spectroscopy for Li/Na Batteries: Materials, Interface, and in Situ Characterization. Advanced Materials 2021, 33 (50), 2005878. https://doi.org/10.1002/adma.202005878.[3] Grey, C. P.; Dupré, N. NMR Studies of Cathode Materials for Lithium-Ion Rechargeable Batteries. Chemical Reviews 2004, 104 (10), 4493–4512. https://doi.org/10.1021/cr020734p.[4] Wiemers-Meyer, S.; Winter, M.; Nowak, S. NMR as a Powerful Tool to Study Lithium Ion Battery Electrolytes. Annual Reports on NMR Spectroscopy 2019, 121–162. https://doi.org/10.1016/bs.arnmr.2018.12.003.[5] Ilott, A. J.; Mohammadi, M.; Chang, H. J.; Grey, C. P.; Jerschow, A. Real-Time 3D Imaging of Microstructure Growth in Battery Cells Using Indirect MRI. Proceedings of the National Academy of Sciences 2016, 113 (39), 10779–10784. https://doi.org/10.1073/pnas.1607903113.

Development of in situ high resolution NMR: Proof-of-principle for a new (spinning) cylindrical mini-pellet approach applied to a Lithium ion battery

Solid-state nuclear magnetic resonance (ssNMR) spectroscopy is a powerful technique for characterizing the local structure and dynamics of battery and other materials. It has been widely used to investigate bulk electrode compounds, electrolytes, and interfaces. Beside common ex situ investigations, in situ and operando techniques have gained considerable importance for understanding the reaction mechanisms and cell degradation of electrochemical cells.Herein, we present the recent development of in situ magic angle spinning (MAS) NMR methodologies to study batteries with high spectral resolution, setting into context possible advances on this topic. A mini cylindrical cell type insert for 4 mm MAS rotors is introduced here, being demonstrated on a Li/VO2F electrochemical system, allowing the acquisition of high-resolution 7Li MAS NMR spectra, spinning the electrochemical cell up to 15 kHz.

Gold nanoparticles for surface-enhanced Raman scattering detection of benzyldimethyldodecylammonium chloride at low concentration

The oil and gas industry plays a vital role in the global economy. The production process has several critical conditions and can expose metals to corrosion. Surfactants like the quaternary ammonium salt Benzyldimethyldodecylammonium Bromide (BDAC) are currently used to prevent corrosions; classical methods for determining these surfactants have problems in saline samples and usually present high costs. In this context, spectroscopic techniques become an excellent alternative for quaternary ammonium salts detection. Here, a SERS (surface-enhanced Raman scattering) sensor based on gold nanoparticles (AuNPs) synthesized through chemical reduction was used as an alternative method for BDAC detection. We detected BDAC at low concentrations in water solutions: at 5 to 30 ppm (1.47 × 10−5 mol L−1 to 8.82 × 10−5 mol L−1); and had the vibration attempt attribute analyzed. A new study of quaternary ammonium compounds using AuNPs and SERS with a different, easy, and repeatable approach to spectra acquisition is presented and shows to be a promising method applied in quaternary ammonium salt compounds detection for the oil and gas industry.