Recovery of isolated lithium through discharged state calendar ageing.

Rechargeable Li-metal batteries have the potential to more than double the specific energy of the state-of-the-art rechargeable Li-ion batteries, making Li-metal batteries a prime candidate for next-generation high-energy battery technology1-3. However, current Li-metal batteries suffer from fast cycle degradation compared with their Li-ion battery counterparts2,3, preventing their practical adoption. A main contributor to capacity degradation is the disconnection of Li from the electrochemical circuit, forming isolated Li4-8. Calendar ageing studies have shown that resting in the charged state promotes further reaction of active Li with the surrounding electrolyte9-12. Here we discover that calendar ageing in the discharged state improves capacity retention through isolated Li recovery, which is in contrast with the well-known phenomenon of capacity degradation observed during the charged state calendar ageing. Inactive capacity recovery is verified through observation of Coulombic efficiency greater than 100% on both Li||Cu half-cells and anode-free cells using a hybrid continuous-resting cycling protocol and with titration gas chromatography. An operando optical setup further confirms excess isolated Li reactivation as the predominant contributor to the increased capacity recovery. These insights into a previously unknown pathway for capacity recovery through discharged state resting emphasize the marked impact of cycling strategies on Li-metal battery performance.

Data-driven electrolyte design for lithium metal anodes.

Improving Coulombic efficiency (CE) is key to the adoption of high energy density lithium metal batteries. Liquid electrolyte engineering has emerged as a promising strategy for improving the CE of lithium metal batteries, but its complexity renders the performance prediction and design of electrolytes challenging. Here, we develop machine learning (ML) models that assist and accelerate the design of high-performance electrolytes. Using the elemental composition of electrolytes as the features of our models, we apply linear regression, random forest, and bagging models to identify the critical features for predicting CE. Our models reveal that a reduction in the solvent oxygen content is critical for superior CE. We use the ML models to design electrolyte formulations with fluorine-free solvents that achieve a high CE of 99.70%. This work highlights the promise of data-driven approaches that can accelerate the design of high-performance electrolytes for lithium metal batteries.

TimeTector: A Twin-Branch Approach for Unsupervised Anomaly Detection in Livestock Sensor Noisy Data (TT-TBAD).

Unsupervised anomaly detection in multivariate time series sensor data is a complex task with diverse applications in different domains such as livestock farming and agriculture (LF&A), the Internet of Things (IoT), and human activity recognition (HAR). Advanced machine learning techniques are necessary to detect multi-sensor time series data anomalies. The primary focus of this research is to develop state-of-the-art machine learning methods for detecting anomalies in multi-sensor data. Time series sensors frequently produce multi-sensor data with anomalies, which makes it difficult to establish standard patterns that can capture spatial and temporal correlations. Our innovative approach enables the accurate identification of normal, abnormal, and noisy patterns, thus minimizing the risk of misinterpreting models when dealing with mixed noisy data during training. This can potentially result in the model deriving incorrect conclusions. To address these challenges, we propose a novel approach called "TimeTector-Twin-Branch Shared LSTM Autoencoder" which incorporates several Multi-Head Attention mechanisms. Additionally, our system now incorporates the Twin-Branch method which facilitates the simultaneous execution of multiple tasks, such as data reconstruction and prediction error, allowing for efficient multi-task learning. We also compare our proposed model to several benchmark anomaly detection models using our dataset, and the results show less error (MSE, MAE, and RMSE) in reconstruction and higher accuracy scores (precision, recall, and F1) against the baseline models, demonstrating that our approach outperforms these existing models.

In Situ Prelithiation by Direct Integration of Lithium Mesh into Battery Cells.

Silicon (Si)-based anodes are promising for next-generation lithium (Li)-ion batteries due to their high theoretical capacity (∼3600 mAh/g). However, they suffer quantities of capacity loss in the first cycle from initial solid electrolyte interphase (SEI) formation. Here, we present an in situ prelithiation method to directly integrate a Li metal mesh into the cell assembly. A series of Li meshes are designed as prelithiation reagents, which are applied to the Si anode in battery fabrication and spontaneously prelithiate Si with electrolyte addition. Various porosities of Li meshes tune prelithiation amounts to control the degree of prelithiation precisely. Besides, the patterned mesh design enhances the uniformity of prelithiation. With an optimized prelithiation amount, the in situ prelithiated Si-based full cell shows a constant >30% capacity improvement in 150 cycles. This work presents a facile prelithiation approach to improve battery performance.

Proximity Matters: Interfacial Solvation Dictates Solid Electrolyte Interphase Composition.

The composition of the solid electrolyte interphase (SEI) plays an important role in controlling Li-electrolyte reactions, but the underlying cause of SEI composition differences between electrolytes remains unclear. Many studies correlate SEI composition with the bulk solvation of Li ions in the electrolyte, but this correlation does not fully capture the interfacial phenomenon of SEI formation. Here, we provide a direct connection between SEI composition and Li-ion solvation by forming SEIs using polar substrates that modify interfacial solvation structures. We circumvent the deposition of Li metal by forming the SEI above Li+/Li redox potential. Using theory, we show that an increase in the probability density of anions near a polar substrate increases anion incorporation within the SEI, providing a direct correlation between interfacial solvation and SEI composition. Finally, we use this concept to form stable anion-rich SEIs, resulting in high performance lithium metal batteries.

Dissolution of the Solid Electrolyte Interphase and Its Effects on Lithium Metal Anode Cyclability.

At >95% Coulombic efficiencies, most of the capacity loss for Li metal anodes (LMAs) is through the formation and growth of the solid electrolyte interphase (SEI). However, the mechanism through which this happens remains unclear. One property of the SEI that directly affects its formation and growth is the SEI's solubility in the electrolyte. Here, we systematically quantify and compare the solubility of SEIs derived from ether-based electrolytes optimized for LMAs using in-operando electrochemical quartz crystal microbalance (EQCM). A correlation among solubility, passivity, and cyclability established in this work reveals that SEI dissolution is a major contributor to the differences in passivity and electrochemical performance among battery electrolytes. Together with our EQCM, X-ray photoelectron spectroscopy (XPS), and nuclear magnetic resonance (NMR) spectroscopy results, we show that solubility depends on not only the SEI's composition but also the properties of the electrolyte. This provides a crucial piece of information that could help minimize capacity loss due to SEI formation and growth during battery cycling and aging.

Suspension electrolyte with modified Li+ solvation environment for lithium metal batteries.

Designing a stable solid-electrolyte interphase on a Li anode is imperative to developing reliable Li metal batteries. Herein, we report a suspension electrolyte design that modifies the Li+ solvation environment in liquid electrolytes and creates inorganic-rich solid-electrolyte interphases on Li. Li2O nanoparticles suspended in liquid electrolytes were investigated as a proof of concept. Through theoretical and empirical analyses of Li2O suspension electrolytes, the roles played by Li2O in the liquid electrolyte and solid-electrolyte interphases of the Li anode are elucidated. Also, the suspension electrolyte design is applied in conventional and state-of-the-art high-performance electrolytes to demonstrate its applicability. Based on electrochemical analyses, improved Coulombic efficiency (up to ~99.7%), reduced Li nucleation overpotential, stabilized Li interphases and prolonged cycle life of anode-free cells (~70 cycles at 80% of initial capacity) were achieved with the suspension electrolytes. We expect this design principle and our findings to be expanded into developing electrolytes and solid-electrolyte interphases for Li metal batteries.

Underpotential lithium plating on graphite anodes caused by temperature heterogeneity.

Rechargeability and operational safety of commercial lithium (Li)-ion batteries demand further improvement. Plating of metallic Li on graphite anodes is a critical reason for Li-ion battery capacity decay and short circuit. It is generally believed that Li plating is caused by the slow kinetics of graphite intercalation, but in this paper, we demonstrate that thermodynamics also serves a crucial role. We show that a nonuniform temperature distribution within the battery can make local plating of Li above 0 V vs. Li0/Li+ (room temperature) thermodynamically favorable. This phenomenon is caused by temperature-dependent shifts of the equilibrium potential of Li0/Li+ Supported by simulation results, we confirm the likelihood of this failure mechanism during commercial Li-ion battery operation, including both slow and fast charging conditions. This work furthers the understanding of nonuniform Li plating and will inspire future studies to prolong the cycling lifetime of Li-ion batteries.

Pig Movement Estimation by Integrating Optical Flow with a Multi-Object Tracking Model.

Pig husbandry constitutes a significant segment within the broader framework of livestock farming, with porcine well-being emerging as a paramount concern due to its direct implications on pig breeding and production. An easily observable proxy for assessing the health of pigs lies in their daily patterns of movement. The daily movement patterns of pigs can be used as an indicator of their health, in which more active pigs are usually healthier than those who are not active, providing farmers with knowledge of identifying pigs' health state before they become sick or their condition becomes life-threatening. However, the conventional means of estimating pig mobility largely rely on manual observations by farmers, which is impractical in the context of contemporary centralized and extensive pig farming operations. In response to these challenges, multi-object tracking and pig behavior methods are adopted to monitor pig health and welfare closely. Regrettably, these existing methods frequently fall short of providing precise and quantified measurements of movement distance, thereby yielding a rudimentary metric for assessing pig health. This paper proposes a novel approach that integrates optical flow and a multi-object tracking algorithm to more accurately gauge pig movement based on both qualitative and quantitative analyses of the shortcomings of solely relying on tracking algorithms. The optical flow records accurate movement between two consecutive frames and the multi-object tracking algorithm offers individual tracks for each pig. By combining optical flow and the tracking algorithm, our approach can accurately estimate each pig's movement. Moreover, the incorporation of optical flow affords the capacity to discern partial movements, such as instances where only the pig's head is in motion while the remainder of its body remains stationary. The experimental results show that the proposed method has superiority over the method of solely using tracking results, i.e., bounding boxes. The reason is that the movement calculated based on bounding boxes is easily affected by the size fluctuation while the optical flow data can avoid these drawbacks and even provide more fine-grained motion information. The virtues inherent in the proposed method culminate in the provision of more accurate and comprehensive information, thus enhancing the efficacy of decision-making and management processes within the realm of pig farming.

Correlating Kinetics to Cyclability Reveals Thermodynamic Origin of Lithium Anode Morphology in Liquid Electrolytes.

The rechargeability of lithium metal batteries strongly depends on the electrolyte. The uniformity of the electroplated Li anode morphology underlies this dependence, so understanding the main drivers of uniform plating is critical for further electrolyte discovery. Here, we correlate electroplating kinetics with cyclability across several classes of electrolytes to reveal the mechanistic influence electrolytes have on morphology. Fast charge-transfer kinetics at fresh Li-electrolyte interfaces correlate well with uniform morphology and cyclability, whereas the resistance of Li+ transport through the solid electrolyte interphase (SEI) weakly correlates with cyclability. These trends contrast with the conventional thought that Li+ transport through the electrolyte or SEI is the main driver of morphological differences between classes of electrolytes. Relating these trends to Li+ solvation, Li nucleation, and the charge-transfer mechanism instead suggests that the Li/Li+ equilibrium potential and the surface energy─thermodynamic factors modulated by the strength of Li+ solvation─underlie electrolyte-dependent trends of Li morphology. Overall, this work provides an insight for discovering functional electrolytes, tuning kinetics in batteries, and explaining why weakly solvating fluorinated electrolytes favor uniform Li plating.

Correlating Li-Ion Solvation Structures and Electrode Potential Temperature Coefficients.

Temperature coefficients (TCs) for either electrochemical cell voltages or potentials of individual electrodes have been widely utilized to study the thermal safety and cathode/anode phase changes of lithium (Li)-ion batteries. However, the fundamental significance of single electrode potential TCs is little known. In this work, we discover that the Li-ion desolvation process during Li deposition/intercalation is accompanied by considerable entropy change, which significantly contributes to the measured Li/Li+ electrode potential TCs. To explore this phenomenon, we compare the Li/Li+ electrode potential TCs in a series of electrolyte formulations, where the interaction between Li-ion and solvent molecules occurs at varying strength as a function of both solvent and anion species as well as salt concentrations. As a result, we establish correlations between electrode potential TCs and Li-ion solvation structures and further verify them by ab initio molecular dynamics simulations. We show that measurements of Li/Li+ electrode potential TCs provide valuable knowledge regarding the Li-ion solvation environments and could serve as a screening tool when designing future electrolytes for Li-ion/Li metal batteries.

Potentiometric Measurement to Probe Solvation Energy and Its Correlation to Lithium Battery Cyclability.

The electrolyte plays a critical role in lithium-ion batteries, as it impacts almost every facet of a battery's performance. However, our understanding of the electrolyte, especially solvation of Li+, lags behind its significance. In this work, we introduce a potentiometric technique to probe the relative solvation energy of Li+ in battery electrolytes. By measuring open circuit potential in a cell with symmetric electrodes and asymmetric electrolytes, we quantitatively characterize the effects of concentration, anions, and solvents on solvation energy across varied electrolytes. Using the technique, we establish a correlation between cell potential (Ecell) and cyclability of high-performance electrolytes for lithium metal anodes, where we find that solvents with more negative cell potentials and positive solvation energies-those weakly binding to Li+-lead to improved cycling stability. Cryogenic electron microscopy reveals that weaker solvation leads to an anion-derived solid-electrolyte interphase that stabilizes cycling. Using the potentiometric measurement for characterizing electrolytes, we establish a correlation that can guide the engineering of effective electrolytes for the lithium metal anode.

Steric Effect Tuned Ion Solvation Enabling Stable Cycling of High-Voltage Lithium Metal Battery.

1,2-Dimethoxyethane (DME) is a common electrolyte solvent for lithium metal batteries. Various DME-based electrolyte designs have improved long-term cyclability of high-voltage full cells. However, insufficient Coulombic efficiency at the Li anode and poor high-voltage stability remain a challenge for DME electrolytes. Here, we report a molecular design principle that utilizes a steric hindrance effect to tune the solvation structures of Li+ ions. We hypothesized that by substituting the methoxy groups on DME with larger-sized ethoxy groups, the resulting 1,2-diethoxyethane (DEE) should have a weaker solvation ability and consequently more anion-rich inner solvation shells, both of which enhance interfacial stability at the cathode and anode. Experimental and computational evidence indicates such steric-effect-based design leads to an appreciable improvement in electrochemical stability of lithium bis(fluorosulfonyl)imide (LiFSI)/DEE electrolytes. Under stringent full-cell conditions of 4.8 mAh cm-2 NMC811, 50 µm thin Li, and high cutoff voltage at 4.4 V, 4 M LiFSI/DEE enabled 182 cycles until 80% capacity retention while 4 M LiFSI/DME only achieved 94 cycles. This work points out a promising path toward the molecular design of non-fluorinated ether-based electrolyte solvents for practical high-voltage Li metal batteries.

Companilactobacillus pabuli sp. nov., a lactic acid bacterium isolated from animal feed.

A Gram-positive, facultative anaerobic, catalase-negative, non-motile, non-spore-forming and rod-shaped lactic acid bacterium strain, denoted as NFFJ11T and isolated from total mixed fermentation feed in the Republic of Korea, was characterized through polyphasic approaches, including sequence analyses of the 16S rRNA gene and housekeeping genes (rpoA and pheS), determination of average nucleotide identity and in silico DNA-DNA hybridization, fatty acid methyl ester analysis, and phenotypic characterization. Phylogenetic analyses based on 16S rRNA, rpoA and pheS gene sequences revealed that strain NFFJ11T belonged to the genus Companilactobacillus. The 16S rRNA gene sequence of strain NFFJ11T exhibited high similarity to Companilactobacillus formosensis S215T (99.66 %), Companilactobacillus farciminis Rv4 naT (99.53 %), Companilactobacillus crustorum LMG 23699T (99.19 %), Companilactobacillus futsaii YM 0097T (99.06 %), Companilactobacillus zhachilii HBUAS52074T (98.86 %) and Companilactobacillus heilongiiangensis S4-3T (98.66 %). However, average nucleotide identity and in silico DNA-DNA hybridization values for these type strains were in the range of 79.90-92.93 % and 23.80-49.30 %, respectively, which offer evidence that strain NFFJ11T belongs to a novel species of the genus Companilactobacillus. The cell-wall peptidoglycan type was A4α (l-Lys-d-Asp) and the G+C content of the genomic DNA was 35.7 mol%. The main fatty acids of strain NFFJ11T were C18 : 1 ω9c (43.3 %), C16 : 0 (20.1 %) and summed feature 7 (18.3 %; comprising any combination of C19 : 1 ω7c, C19 : 1 ω6c and C19 : 0 cyclo ω10c). Through polyphasic taxonomic analysis, it was observed that strain NFFJ11T represents a novel species belonging to the genus Companilactobacillus, for which the name Companilactobacillus pabuli sp. nov. is proposed. The type strain is NFFJ11T (= KACC 21771T= JCM 34088T).

An Aqueous Extract from Batillus Cornutus Meat Protects Against H2O2-Mediated Cellular Damage via Up-Regulation of Nrf2/HO-1 Signal Pathway in Chang Cells.

In this study, we evaluated the protective effects of an aqueous extract from Batillus cornutus meat (BM) against cellular oxidative damage caused by hydrogen peroxide (H2O2) in human hepatocyte, Chang cells. First, we prepared an aqueous extract of BM meat (BMW) showing the highest taurine content among free amino acid contents. BMW led to high antioxidant activity showing 2,2-azino-bis(3-ethylbenzthiazoline)-6-sulfonic acid (ABTS) radical scavenging activity, good reducing power and an oxygen radical absorbance capacity (ORAC) value. Also, BMW improved cell viability that was diminished by H2O2 exposure, as it reduced the generation of intracellular reactive oxygen species (ROS) in Chang cells. In addition, BMW up-regulated the production of antioxidant enzymes, such as catalase and superoxide dismutase (SOD), compared to H2O2-treated Chang cells lacking BMW. Moreover, BMW induced the expressions of nuclear Nrf2 and cytosolic HO-1 in H2O2-treated Chang cells. Interestingly, the treatment of ZnPP, HO-1 inhibitor, abolished the improvement in cell viability and intracellular ROS generation mediated by BMW treatment. In conclusion, this study suggests that BMW protects hepatocytes against H2O2-mediated cellular oxidative damage via up-regulation of the Nrf2/HO-1 signal pathway.

Antioxidant Effects of an Alcalase Hydrolysate from Batillus cornutus Meat.

Batillus cornutus (B. cornutus) is one of the gastropoda, which are distributed along the coast of China, Japan and South Korea and northeast area. In this study, we first identified the antioxidant effects of a B. cornutus meat (BM) enzymatic hydrolysate in H2O2-treated Vero cells. First of all, we prepared an Alcalase hydrolysate from BM (BMA) and revealed a high taurine content. Also, taurine rich BMA dose-dependently increased 2,2-azino-bis(3-ethylbenzthiazoline)-6-sulfonic acid (ABTS) radical scavenging activity, reducing power and the higher oxygen radical absorbance capacity (ORAC) value. In addition, BMA significantly increased the cell viability via the down-regulation of intracellular reactive oxygen species (ROS) production, as well as the decreased formation of apoptotic bodies and sub-G1 DNA population in H2O2-treated Vero cells. Furthermore, BMA increased the expression of the anti-apoptotic molecule, Bcl-2, and decreased the expressions of Bax, p53 and cleaved PARP, all of which are pro-apoptotic molecules, in H2O2-treated Vero cells. Based on these results, this study suggests that BMA may be used as a potential protector on damage caused by oxidative stress.

Cytoprotective Effects of an Aqueous Extracts from Atrina Pectinate Meat in H2O2-Induced Oxidative Stress in a Human Hepatocyte.

In the present study, we investigated the antioxidant activity of an aqueous extract from Atrina pectinate meat (APW) against H2O2-induced oxidative stress in a human hepatocyte. The extraction yield of APW was 30.01 ± 0.83% and which contained the highest taurine content among free amino acid contents. APW led to the high antioxidant activity showing 2,2-azino-bis(3-ethylbenzthiazoline)-6-sulfonic acid (ABTS) radical scavenging activity, good reducing power and oxygen radical absorbance capacity (ORAC) value. Also, the results showed that APW improved the cell viability decreased by H2O2 stimulation as well as the reduction of intracellular reactive oxygen species (ROS) generation in hepatocytes. Additionally, APW up-regulated the production of antioxidant mechanisms related enzymes such as catalase and superoxide dismutase (SOD), compared to the only H2O2-treated hepatocytes. Moreover, APW increased the expressions of nuclear Nrf2 and cytosolic HO-1 in H2O2-treated hepatocytes. Interestingly, the treatment of ZnPP, a HO-1 inhibitor abolished the cell viability and intracellular ROS generation induced by APW treatment. In conclusion, this study suggests that APW protects H2O2 induced oxidative stress via up-regulating of Nrf2/HO-1 signal pathway in hepatocytes.

Radio-Protective Effects of Loliolus beka Gray Meat Consisted of a Plentiful Taurine Against Damages Caused by Gamma Ray Irradiation.

Gamma ray irradiation causes immune suppression, in which oxidative stress reduces cell viability and damages immune cells. In the present study, we investigated whether Loliolus beka gray meat (LBM), which contains large amounts of taurine, protects against damage of murine splenocytes by oxidative stress. An aqueous extract of LBM (LBMW) was prepared, which contained plentiful levels of taurine. LBMW improved cell viability of gamma ray-irradiated murine splenocytes, an effect that was associated with significant reduction in the production of reactive oxygen species (ROS). We also showed that the production of nitric oxide (NO) and ROS in gamma ray-irradiated zebrafish embryos, as well as the death of the embryos, were diminished by LBMW. These data suggest that the consumption of taurine-rich foods, such as LBM, may be used in the protection of cells against oxidative stress.

Evaluation of somatic copy number estimation tools for whole-exome sequencing data.

Whole-exome sequencing (WES) has become a standard method for detecting genetic variants in human diseases. Although the primary use of WES data has been the identification of single nucleotide variations and indels, these data also offer a possibility of detecting copy number variations (CNVs) at high resolution. However, WES data have uneven read coverage along the genome owing to the target capture step, and the development of a robust WES-based CNV tool is challenging. Here, we evaluate six WES somatic CNV detection tools: ADTEx, CONTRA, Control-FREEC, EXCAVATOR, ExomeCNV and Varscan2. Using WES data from 50 kidney chromophobe, 50 bladder urothelial carcinoma, and 50 stomach adenocarcinoma patients from The Cancer Genome Atlas, we compared the CNV calls from the six tools with a reference CNV set that was identified by both single nucleotide polymorphism array 6.0 and whole-genome sequencing data. We found that these algorithms gave highly variable results: visual inspection reveals significant differences between the WES-based segmentation profiles and the reference profile, as well as among the WES-based profiles. Using a 50% overlap criterion, 13-77% of WES CNV calls were covered by CNVs from the reference set, up to 21% of the copy gains were called as losses or vice versa, and dramatic differences in CNV sizes and CNV numbers were observed. Overall, ADTEx and EXCAVATOR had the best performance with relatively high precision and sensitivity. We suggest that the current algorithms for somatic CNV detection from WES data are limited in their performance and that more robust algorithms are needed.

Integrated genomic analysis of recurrence-associated small non-coding RNAs in oesophageal cancer.

OBJECTIVE: Oesophageal squamous cell carcinoma (ESCC) is a heterogeneous disease with variable outcomes that are challenging to predict. A better understanding of the biology of ESCC recurrence is needed to improve patient care. Our goal was to identify small non-coding RNAs (sncRNAs) that could predict the likelihood of recurrence after surgical resection and to uncover potential molecular mechanisms that dictate clinical heterogeneity. DESIGN: We developed a robust prediction model for recurrence based on the analysis of the expression profile data of sncRNAs from 108 fresh frozen ESCC specimens as a discovery set and assessment of the associations between sncRNAs and recurrence-free survival (RFS). We also evaluated the mechanistic and therapeutic implications of sncRNA obtained through integrated analysis from multiple datasets. RESULTS: We developed a risk assessment score (RAS) for recurrence with three sncRNAs (microRNA (miR)-223, miR-1269a and nc886) whose expression was significantly associated with RFS in the discovery cohort (n=108). RAS was validated in an independent cohort of 512 patients. In multivariable analysis, RAS was an independent predictor of recurrence (HR, 2.27; 95% CI, 1.26 to 4.09; p=0.007). This signature implies the expression of ΔNp63 and multiple alterations of driver genes like PIK3CA. We suggested therapeutic potentials of immune checkpoint inhibitors in low-risk patients, and Polo-like kinase inhibitors, mammalian target of rapamycin (mTOR) inhibitors, and histone deacetylase inhibitors in high-risk patients. CONCLUSION: We developed an easy-to-use prognostic model with three sncRNAs as robust prognostic markers for postoperative recurrence of ESCC. We anticipate that such a stratified and systematic, tumour-specific biological approach will potentially contribute to significant improvement in ESCC treatment.