Dual Modification Strategy for Enhanced Cycling and Rate Performance of Ni-Rich Cathode Materials in Lithium-Ion Batteries.

A great challenge in the commercialization process of layered Ni-rich cathode material LiNixCoyMn1-x-yO2 (NCM, x ≥ 80%) for lithium-ion batteries is the surface instability, which is exacerbated by the increase in nickel content. The high surface alkalinity and unavoidable cathode/electrolyte interface side reactions result in significant decrease for the capacity of NCM material. Surface coating and doping are common and effective ways to improve the electrochemical performance of Ni-rich cathode material. In this study, an in situ reaction is induced on the surface of secondary particles of NCM material to construct a stable lithium sulfate coating, while achieving sulfur doping in the near surface region. The synergistic modification of lithium sulfate coating and lattice sulfur doping significantly reduced the content of harmful residual lithium compounds (RLCs) on the surface of NCM material, suppressed the side reactions between the cathode material surface and electrolyte and the degradation of surface structure of the NCM material, effectively improved the rate capability and cycling stability of the NCM material.

Tailoring Electric Double Layer by Cation Specific Adsorption for High-Voltage Quasi-Solid-State Lithium Metal Batteries.

The interfacial instability of high-nickel layered oxides severely plagues practical application of high-energy quasi-solid-state lithium metal batteries (LMBs). Herein, a uniform and highly oxidation-resistant polymer layer within inner Helmholtz plane is engineered by in situ polymerizing 1-vinyl-3-ethylimidazolium (VEIM) cations preferentially adsorbed on LiNi0.83Co0.11Mn0.06O2 (NCM83) surface, inducing the formation of anion-derived cathode electrolyte interphase with fast interfacial kinetics. Meanwhile, the copolymerization of [VEIM][BF4] and vinyl ethylene carbonate (VEC) endows P(VEC-IL) copolymer with the positively-charged imidazolium moieties, providing positive electric fields to facilitate Li+ transport and desolvation process. Consequently, the Li||NCM83 cells with a cut-off voltage up to 4.5 V exhibit excellent reversible capacity of 130 mAh g-1 after 1000 cycles at 25 °C and considerable discharge capacity of 134 mAh g-1 without capacity decay after 100 cycles at -20 °C. This work provides deep understanding on tailoring electric double layer by cation specific adsorption for high-voltage quasi-solid-state LMBs.

Low-Solvent-Coordination Solvation Structure for Lithium-Metal Batteries via Electric Dipole-Dipole Interaction.

Unveiling inherent interactions among solvents, Li+ ions, and anions are crucial in dictating solvation-desolvation kinetics at the electrode/electrolyte interface. Developing an electrolyte with a low ion-transport barrier and minimal solvent coordination in its interfacial solvation structure is essential for forming an anion-derived solid-electrolyte interface, a key component for high-performance Li-metal batteries. In this study, we harness electric dipole-dipole synergistic interactions to formulate an electrolyte with significantly reduced interfacial solvent coordination. Operando characterization and theoretical analysis reveal that 2-fluoropyridine (FPy) with high dipole preferentially adsorbs onto the Li metal surface. The adsorbed FPy molecule squeezes succinonitrile in the primary solvation sheath through steric hindrance, leading to the formation of an inorganic-rich interphase. Consequently, the introduction of FPy enhances the reversible capacity of the LiCoO2||Li cell, which maintains a capacity of 143 mAh g-1 after 500 cycles at a 1C rate. Moreover, the cycle life of LiCoO2 batteries with a limited supply of lithium extends from 120 cycles to over 200 cycles. These findings offer a strategy that can be applied broadly to design interfacial solvation structures for various metal-ion/metal-based batteries.

Ion-Dipole-Interaction-Induced Encapsulation of Free Residual Solvent for Long-Cycle Solid-State Lithium Metal Batteries.

Owing to high ionic conductivity and mechanical strength, poly(vinylidene fluoride) (PVDF) electrolytes have attracted increasing attention for solid-state lithium batteries, but highly reactive residual solvents severely plague cycling stability. Herein, we report a free-solvent-capturing strategy triggered by reinforced ion-dipole interactions between Li+ and residual solvent molecules. Lithium difluoro(oxalato)borate (LiDFOB) salt additive with electron-withdrawing capability serves as a redistributor of the Li+ electropositive state, which offers more binding sites for residual solvents. Benefiting from the modified coordination environment, the kinetically stable anion-derived interphases are preferentially formed, effectively mitigating the interfacial side reactions between the electrodes and electrolytes. As a result, the assembled solid-state battery shows a lifetime of over 2000 cycles with an average Coulombic efficiency of 99.9% and capacity retention of 80%. Our discovery sheds fresh light on the targeted regulation of the reactive residual solvent to extend the cycle life of solid-state batteries.

d-p Hybridization-Induced "Trapping-Coupling-Conversion" Enables High-Efficiency Nb Single-Atom Catalysis for Li-S Batteries.

Single-atom catalysts have been paid more attention to improving sluggish reaction kinetics and anchoring polysulfide for lithium-sulfur (Li-S) batteries. It has been demonstrated that d-block single-atom elements in the fourth period can chemically interact with the local environment, leading to effective adsorption and catalytic activity toward lithium polysulfides. Enlightened by theoretical screening, for the first time, we design novel single-atom Nb catalysts toward improved sulfur immobilization and catalyzation. Calculations reveal that Nb-N4 active moiety possesses abundant unfilled antibonding orbitals, which promotes d-p hybridization and enhances anchoring capability toward lithium polysulfides via a "trapping-coupling-conversion" mechanism. The Nb-SAs@NC cell exhibits a high capacity retention of over 85% after 1000 cycles, a superior rate performance of 740 mA h g-1 at 7 C, and a competitive areal capacity of 5.2 mAh cm-2 (5.6 mg cm-2). Our work provides a new perspective to extend cathodes enabling high-energy-density Li-S batteries.

DNA Helix Structure Inspired Flexible Lithium-Ion Batteries with High Spiral Deformability and Long-Lived Cyclic Stability.

With the development of flexible devices, it is necessary to design high-performance power supplies with superior flexibility, durability, safety, etc., to ensure that they can be deformed with the device while retaining their electrochemical functions. Herein, we have designed a flexible lithium-ion battery inspired by the DNA helix structure. The battery structure is mainly composed of multiple thick energy stacks for energy storage and some grooves for stress buffers, which realized the spiral deformation of batteries. According to the results, the batteries exhibit less than 3% capacity degradation even after more than 31000 times of in situ dynamic mechanical loadings. Moreover, the mechanism of the battery with spiral deformability is further revealed. It is anticipated that this bioinspired design strategy could create unique opportunities for the commercialization of flexible batteries and fill the current gap in realizing battery-specific deformations to meet various requirements for future complex device designs.

Kirigami-Inspired Flexible Lithium-Ion Batteries via Transformation of Concentrated Stress into Segmented Strain.

Emerging directions in the growing wearable electronics market have spurred the development of flexible energy storage systems that require deformability while maintaining electrochemical performance. However, the traditional fabrication approaches of lithium-ion batteries (LIBs) are challenging to withstand long-cycle bending alternating loads due to the stress concentration caused by the nonuniformity of the actual deformation. Herein, inspired by kirigami, a segmented deformation design of full-cell scale thin-type flexible lithium-ion batteries (FLIBs) with large-scale manufacturing characteristics via the current collector's mechanical blanking process is reported. This strategy allows the battery's elliptical deformation of the actual state to be transformed into the circular strain of the ideal configuration, thereby dispersing the stress concentration on the top of the battery. According to the results, the designed battery maintains >95% capacity after >20 000 harsh in situ dynamic tests. In addition, finite element analysis further reveals the mechanism that the segmented deformation strategy bears the mechanical stress. This work can enlighten the rational design and customization of electrode patterns for high compatibility with various devices, thereby providing potential opportunities for the application of FLIBs.

Asprosin is associated with anorexia and body fat mass in cancer patients.

PURPOSE: Increasing evidence suggests that many adipokines are involved in cancer-related anorexia and cachexia syndrome (CACS), although the underlying mechanism remains to be clarify. Asprosin is a new peptide hormone mainly secreted by white adipose tissues that can increase appetite and body weight. In this cross-sectional study, we tested whether asprosin may intervene in the development of CACS. METHODS: The fasting plasma asprosin levels were determined via enzyme-linked immune-sorbent assay. Anorexia was determined using the anorexia/cachexia subscale (A/CS) of the functional assessment of anorexia/cachexia therapy (FAACT) questionnaire. The body composition was assessed using bioelectrical impedance analysis. The association of plasma asprosin with anorexia, cachexia, and nutritional status was analyzed. RESULTS: One hundred twenty treatment-naïve patients with pathological confirmed gastrointestinal or lung cancer and 14 mild gastritis patients were recruited. We found no significant difference in asprosin levels between subgroups of patients by age, sex, cancer types or stage. Correlation analysis suggested that asprosin levels were positively associated with body fat mass (r = 0.248, p = 0.043). No correlations were found between asprosin levels and hemoglobin, white blood cell count, blood platelet count, albumin, C-reactive protein, glucose, cholesterol, triglyceride, high density lipoprotein, low density lipoprotein, body mass index, body fat percentage, protein, skeletal muscle, muscle mass, lean body mass, and basal metabolic rate. Furthermore, asprosin levels were not significantly different between patients with or without cachexia. However, patients with anorexia had significantly lower asprosin levels compared with patients without anorexia. No significant difference in asprosin levels between gastritis and gastric cancer patients. Similarly, no significant change of asprosin levels occurred postoperatively in 10 gastric cancer patients. CONCLUSIONS: Patients with anorexia had significantly lower asprosin levels compared with patients without anorexia. We therefore speculated that asprosin might intervene in the development of cancer anorexia and serve as a potential therapeutic target.

Old yellow enzymes: structures and structure-guided engineering for stereocomplementary bioreduction.

Since the first discovery of old yellow enzyme 1 (OYE1) from Saccharomyces pastorianus in 1932, biocatalytic asymmetric reduction of activated alkenes by OYEs has become a valuable reaction in organic synthesis. To access stereocomplementary C=C-bond bioreduction, the mining of novel OYEs and especially the protein engineering of existing OYEs have been performed, which successfully achieved the stereocomplementary reduction in several cases and further raise the potential of applications. In this review, we analyzed the structures, active sites, and substrate recognition of OYEs, which are the bases for their substrate specificity and stereospecificity. Sequence similarity network of OYEs superfamily was also constructed to investigate the scope of characterized OYEs. The structure-guided engineering to switch the stereoselectivity of OYEs and thus access stereocomplementary bioreduction over the last decade (2009-2020) was then reviewed and discussed, which might give new insights into the mining and engineering of related biocatalysts. KEY POINTS: • The sequence similarity network of OYEs superfamily was constructed and annotated. • The structures and active sites of OYEs from different classes were compared. • "Left/right" binding mode was used to explain the stereopreferences of OYEs. • Structure-guided engineering of OYEs to switch their stereoselectivity was reviewed.

Preexisting Cerebral Abnormalities and Functional Outcomes After Acute Ischemic Stroke.

PURPOSE: The aim of this study was to investigate the association between preexisting cerebral abnormalities in patients with acute ischemic stroke upon their functional outcomes. METHODS: We recruited 272 patients with first-ever acute ischemic stroke. Cerebral abnormalities on magnetic resonance imaging included infarction, silent brain infarcts (SBI), enlarged perivascular spaces, white matter lesions (WMLs), global brain atrophy, and medial temporal lobe atrophy (MTLA). Functional outcomes were assessed using the instrumental activities of daily living (IADL) scale and basic activities of daily living (BADL) scale, at 3 and 6 months after the index stroke. RESULTS: Two hundred and fifty patients completed the 3-month follow-up and 246 patients completed the 6-month follow-up. Univariate analyses showed that patients with poor IADL and BADL were older, more likely to be men, had higher National Institutes of Health Stroke Scale (NIHSS) score on admission, more frequent atrial fibrillation, and large artery atherosclerosis subtypes. They also had more frequent cortical infarcts, subcortical infarcts, infratentorial infarcts, larger infarct volume, more frequent presence of SBI, severe WMLs, and MTLA. In multiple regression analyses, NIHSS on admission, subcortical region infarct and MTLA were significant predictors of poor IADL at 3 months. National Institutes of Health Stroke Scale on admission, SBI and MTLA were significant predictors of poor IADL at 6 months. National Institutes of Health Stroke Scale on admission and MTLA were significant predictors of poor BADL at 3 months. National Institutes of Health Stroke Scale on admission and SBI were significant predictors of poor BADL at 6 months. CONCLUSIONS: In patients with acute ischemic stroke, the presence of SBI, and severe MTLA represent significant predictors of poorer functional outcomes, thus highlighting the importance of preexisting cerebral abnormalities.

Severe Lesions Involving Cortical Cholinergic Pathways Predict Poorer Functional Outcome in Acute Ischemic Stroke.

Background and Purpose- The aim of the study was to assess the effect of lesion severity in cortical cholinergic pathways in acute ischemic stroke patients on functional outcomes. Methods- The study sample consisted of 214 men (70.9%) and 88 women (29.1%) with acute ischemic stroke. We used the Cholinergic Pathways Hyperintensities Scale (CHIPS) to assess the severity of lesions in cortical cholinergic pathways using brain magnetic resonance imaging. The other magnetic resonance imaging parameters included infarction, white matter lesions, and medial temporal lobe atrophy. Functional outcome was assessed using the Lawton activities of daily living (ADL) scale at 3 and 6 months after the index stroke. We also assessed disability status using the modified Rankin Scale. Results- Univariate analysis showed that patients with poor functional outcomes were older, more likely to be men, had a higher National Institutes of Health Stroke Scale (NIHSS) score on admission, and had more frequent histories of previous stroke and infection complications. They also had significantly more frequent cortical infarcts, left subcortical infarcts, a larger infarct volume, more severe medial temporal lobe atrophy, and periventricular hyperintensities, and higher CHIPS scores. In the multiple regression analysis, model 1 showed that age and NIHSS score on admission were significant predictors of poor ADL at 3 months, with an R2 of 45.4% fitting the model. Age, NIHSS score on admission and stroke subtype were also significant predictors of poor ADL at 6 months, with an R2 of 37.9% fitting the model. In model 2, sex, previous stroke, NIHSS score on admission, right cortical infarcts, left subcortical infarcts and CHIPS score were significant predictors for poor ADL at 3 months, with an R2 of 53.5%. NIHSS score on admission, stroke subtype, and CHIPS score were significant predictors for poor ADL at 6 months, with an R2 of 40.2%. After adjustment for confounders, CHIPS score was also a significant predictor for poor modified Rankin Scale, both at 3 and 6 months. Even after removing patients with moderate-to-severe white matter lesions, higher CHIPS scores still correlated with poorer ADL and modified Rankin Scale both at both 3 and 6 months. Conclusions- In patients with acute ischemic stroke, cortical cholinergic pathways impairment is common, and the severity of lesions in the cortical cholinergic pathways may significantly predict a poorer functional outcome. Clinical Trial Registration- URL: http://www.chictr.org.cn/index.aspx . Unique identifier: ChiCTR1800014982.

Automated thorax disease diagnosis using multi-branch residual attention network.

Chest X-ray (CXR) is an extensively utilized radiological modality for supporting the diagnosis of chest diseases. However, existing research approaches suffer from limitations in effectively integrating multi-scale CXR image features and are also hindered by imbalanced datasets. Therefore, there is a pressing need for further advancement in computer-aided diagnosis (CAD) of thoracic diseases. To tackle these challenges, we propose a multi-branch residual attention network (MBRANet) for thoracic disease diagnosis. MBRANet comprises three components. Firstly, to address the issue of inadequate extraction of spatial and positional information by the convolutional layer, a novel residual structure incorporating a coordinate attention (CA) module is proposed to extract features at multiple scales. Next, based on the concept of a Feature Pyramid Network (FPN), we perform multi-scale feature fusion in the following manner. Thirdly, we propose a novel Multi-Branch Feature Classifier (MFC) approach, which leverages the class-specific residual attention (CSRA) module for classification instead of relying solely on the fully connected layer. In addition, the designed BCEWithLabelSmoothing loss function improves the generalization ability and mitigates the problem of class imbalance by introducing a smoothing factor. We evaluated MBRANet on the ChestX-Ray14, CheXpert, MIMIC-CXR, and IU X-Ray datasets and achieved average AUCs of 0.841, 0.895, 0.805, and 0.745, respectively. Our method outperformed state-of-the-art baselines on these benchmark datasets.

Automatic diagnosis of depression based on attention mechanism and feature pyramid model.

Currently, most diagnoses of depression are evaluated by medical professionals, with the results of these evaluations influenced by the subjective judgment of physicians. Physiological studies have shown that depressed patients display facial movements, head posture, and gaze direction disorders. To accurately diagnose the degree of depression of patients, this paper proposes a comprehensive framework, Cross-Channel Attentional Depression Detection Network, which can automatically diagnose the degree of depression of patients by inputting information from the facial images of depressed patients. Specifically, the comprehensive framework is composed of three main modules: (1) Face key point detection and cropping for video images based on Multi-Task Convolutional Neural Network. (2) The improved Feature Pyramid Networks model can fuse shallow features and deep features in video images and reduce the loss of miniscule features. (3) A proposed Cross-Channel Attention Convolutional Neural Network can enhance the interaction between tensor channel layers. Compared to other methods for automatic depression identification, a superior method was obtained by conducting extensive experiments on the depression dataset AVEC 2014, where the Root Mean Square Error and the Mean Absolute Error were 8.65 and 6.66, respectively.

Advancements and Challenges in Organic-Inorganic Composite Solid Electrolytes for All-Solid-State Lithium Batteries.

To address the limitations of contemporary lithium-ion batteries, particularly their low energy density and safety concerns, all-solid-state lithium batteries equipped with solid-state electrolytes have been identified as an up-and-coming alternative. Among the various SEs, organic-inorganic composite solid electrolytes (OICSEs) that combine the advantages of both polymer and inorganic materials demonstrate promising potential for large-scale applications. However, OICSEs still face many challenges in practical applications, such as low ionic conductivity and poor interfacial stability, which severely limit their applications. This review provides a comprehensive overview of recent research advancements in OICSEs. Specifically, the influence of inorganic fillers on the main functional parameters of OICSEs, including ionic conductivity, Li+ transfer number, mechanical strength, electrochemical stability, electronic conductivity, and thermal stability are systematically discussed. The lithium-ion conduction mechanism of OICSE is thoroughly analyzed and concluded from the microscopic perspective. Besides, the classic inorganic filler types, including both inert and active fillers, are categorized with special emphasis on the relationship between inorganic filler structure design and the electrochemical performance of OICSEs. Finally, the advanced characterization techniques relevant to OICSEs are summarized, and the challenges and perspectives on the future development of OICSEs are also highlighted for constructing superior ASSLBs.

Microbial transformation of acetyl-11-keto-boswellic acid by Cunninghamella elegans.

Microbial biotransformation of acetyl-11-keto-boswellic acid by Cunninghamella elegans AS 3.1207 was carried out, and totally four transformed products were isolated. On the basis of the extensive spectral data, their structures were characterized as 7ß-hydroxy-11-keto-boswellic acid (1), 7ß,30-dihydroxy-11-keto-boswellic acid (2), 7ß,16α-dihydroxy-3-acetyl-11-keto-boswellic acid (3), and 7ß,15α,21ß-trihydroxy-3-acetyl-11-keto-boswellic acid (4), respectively. Among them, products 1 and 2 are the new compounds.

Facial expression recognition based on improved depthwise separable convolutional network.

A single network model can't extract more complex and rich effective features. Meanwhile, the network structure is usually huge, and there are many parameters and consume more space resources, etc. Therefore, the combination of multiple network models to extract complementary features has attracted extensive attention. In order to solve the problems existing in the prior art that the network model can't extract high spatial depth features, redundant network structure parameters, and weak generalization ability, this paper adopts two models of Xception module and inverted residual structure to build the neural network. Based on this, a face expression recognition method based on improved depthwise separable convolutional network is proposed in the paper. Firstly, Gaussian filtering is performed by Canny operator to remove noise, and combined with two original pixel feature maps to form a three-channel image. Secondly, the inverted residual structure of MobileNetV2 model is introduced into the network structure. Finally, the extracted features are classified by Softmax classifier, and the entire network model uses ReLU6 as the nonlinear activation function. The experimental results show that the recognition rate is 70.76% in Fer2013 dataset (facial expression recognition 2013) and 97.92% in CK+ dataset (extended Cohn Kanade). It can be seen that this method not only effectively mines the deeper and more abstract features of the image, but also prevents network over-fitting and improves the generalization ability.

COVID-Related Perceptions of the Future and Purpose in Life Among Older Canadian Women.

Global events that prime thoughts of proximity to death (e.g., the COVID-19 pandemic) can compress individuals' perceptions of future time horizons, and previous studies have found that compressed time horizons can be beneficial for older adults' well-being. However, findings from recent studies are mixed, and studies of well-being during the early months of COVID-19 show that older adults have fared comparatively well. The current study examines relationships between Future Time Perspective (FTP), COVID-19 impact, and purpose in life (PIL) among older Canadian women (N = 190; ages 59+). We expected that total FTP would be positively associated with PIL but that FTP subscales would be associated with PIL in different ways; COVID-19 impact would not be associated with PIL, but COVID-19 impact would moderate the FTP-PIL relationship. We found partial support for these hypotheses, as well as prevalence of social connection themes in open-ended question responses regarding COVID-19 impact.

Secular Trends in Gastric and Esophageal Cancer Attributable to Dietary Carcinogens From 1990 to 2019 and Projections Until 2044 in China: Population-Based Study.

BACKGROUND: Little is known about trends in or projections of the disease burden of dietary gastric and esophageal cancer (GEC) in China. OBJECTIVE: We aim to report GEC deaths and disability-adjusted life years (DALYs) from 1990 to 2019, predict them through 2044, and decompose changes in terms of population growth, population aging, and epidemiological changes. METHODS: We retrieved dietary GEC data from the Global Burden of Disease (GBD) online database and used joinpoint regression and age-period-cohort models to analyze trends in dietary GEC deaths and DALYs from 1990 to 2019 in China. We used a Bayesian age period cohort model of integrated nested Laplace approximations to predict the disease burden of GEC through 2044 and obtained the estimated population of China from 2020 to 2050 from the Global Health Data Exchange website. Finally, we applied a recently developed decomposition method to attribute changes between 2019 and 2044 to population growth, population aging, and epidemiological changes. RESULTS: The summary exposure values and age-standardized rates decreased significantly from 1990 to 1999, with percentage changes of -0.06% (95% CI -0.11% to -0.02%) and -0.05% (95% CI -0.1% to -0.02%), respectively. From 1990 to 2019, for dietary esophageal cancer, the percentage change in age-standardized mortality rate (ASMR) was -0.79% (95% CI -0.93% to -0.58%) and the percentage change in age-standardized DALY rate (ASDR) was -0.81% (95% CI -0.94% to -0.61%); these were significant decreases. For dietary stomach cancer, significant decreases were also observed for the percentage change in ASMR (-0.43%, 95% CI -0.55% to -0.31%) and the percentage change in ASDR (-0.47%, 95% CI -0.58% to -0.35%). In addition, data from both the joinpoint regression and annual percentage change analyses demonstrated significantly decreasing trends for the annual percentage change in ASMR and ASDR for GEC attributable to dietary carcinogens. The overall annual percentage change (net drift) was -5.95% (95% CI -6.25% to -5.65%) for dietary esophageal cancer mortality and -1.97% (95% CI -2.11% to -1.83%) for dietary stomach cancer mortality. Lastly, in 2044, dietary esophageal cancer deaths and DALYs were predicted to increase by 192.62% and 170.28%, respectively, due to age structure (121.58% and 83.29%), mortality change (76.81% and 92.43%), and population size (-5.77% and -5.44%). In addition, dietary stomach cancer deaths and DALYs were predicted to increase by 118.1% and 54.08%, with age structure, mortality rate change, and population size accounting for 96.71% and 53.99%, 26.17% and 3.97%, and -4.78% and -3.88% of the change, respectively. CONCLUSIONS: Although the predicted age-standardized rates of mortality and DALYs due to dietary GEC show downward trends, the absolute numbers are still predicted to increase in the next 25 years due to rapid population aging in China.

Long-sequence voltage series forecasting for internal short circuit early detection of lithium-ion batteries.

Accurate early detection of internal short circuits (ISCs) is indispensable for safe and reliable application of lithium-ion batteries (LiBs). However, the major challenge is finding a reliable standard to judge whether the battery suffers from ISCs. In this work, a deep learning approach with multi-head attention and a multi-scale hierarchical learning mechanism based on encoder-decoder architecture is developed to accurately forecast voltage and power series. By using the predicted voltage without ISCs as the standard and detecting the consistency of the collected and predicted voltage series, we develop a method to detect ISCs quickly and accurately. In this way, we achieve an average percentage accuracy of 86% on the dataset, including different batteries and the equivalent ISC resistance from 1,000 Ω to 10 Ω, indicating successful application of the ISC detection method.

Solid-state MAS NMR studies of Brønsted acid sites in zeolite H-Mordenite.

(17)O-(1)H double resonance NMR spectroscopy was used to study the local structure of zeolite H-Mordenite. Different contact times were used in cross-polarization magic angle spinning (CPMAS) NMR, CP rotational-echo double resonance (CP-REDOR) NMR, and heteronuclear correlation (HETCOR) NMR spectroscopy to distinguish between Brønsted acid sites with different O-H distances. The accessibility of the various Brønsted acid sites was quantified by adsorbing the basic probe molecule trimethylphosphine in known amounts. On the basis of these experiments, locations of different Brønsted acid sites in H-Mordenite (H-MOR) were proposed. The use of (17)O chemical shift correlations to help assign sites is discussed.