Synergetic Dual-Additive Electrolyte Enables Highly Stable Performance in Sodium Metal Batteries.

Sodium (Na)-metal batteries (SMBs) are considered one of the most promising candidates for the large-scale energy storage market owing to their high theoretical capacity (1,166 mAh g-1) and the abundance of Na raw material. However, the limited stability of electrolytes still hindered the application of SMBs. Herein, sulfolane (Sul) and vinylene carbonate (VC) are identified as effective dual additives that can largely stabilize propylene carbonate (PC)-based electrolytes, prevent dendrite growth, and extend the cycle life of SMBs. The cycling stability of the Na/NaNi0.68Mn0.22Co0.1O2 (NaNMC) cell with this dual-additive electrolyte is remarkably enhanced, with a capacity retention of 94% and a Coulombic efficiency (CE) of 99.9% over 600 cycles at a 5 C (750 mA g-1) rate. The superior cycling performance of the cells can be attributed to the homogenous, dense, and thin hybrid solid electrolyte interphase consisting of F- and S-containing species on the surface of both the Na metal anode and the NaNMC cathode by adding dual additives. Such unique interphases can effectively facilitate Na-ion transport kinetics and avoid electrolyte depletion during repeated cycling at a very high rate of 5 C. This electrolyte design is believed to result in further improvements in the performance of SMBs.

Effects of fluorinated solvents on electrolyte solvation structures and electrode/electrolyte interphases for lithium metal batteries.

Electrolyte is very critical to the performance of the high-voltage lithium (Li) metal battery (LMB), which is one of the most attractive candidates for the next-generation high-density energy-storage systems. Electrolyte formulation and structure determine the physical properties of the electrolytes and their interfacial chemistries on the electrode surfaces. Localized high-concentration electrolytes (LHCEs) outperform state-of-the-art carbonate electrolytes in many aspects in LMBs due to their unique solvation structures. Types of fluorinated cosolvents used in LHCEs are investigated here in searching for the most suitable diluent for high-concentration electrolytes (HCEs). Nonsolvating solvents (including fluorinated ethers, fluorinated borate, and fluorinated orthoformate) added in HCEs enable the formation of LHCEs with high-concentration solvation structures. However, low-solvating fluorinated carbonate will coordinate with Li+ ions and form a second solvation shell or a pseudo-LHCE which diminishes the benefits of LHCE. In addition, it is evident that the diluent has significant influence on the electrode/electrolyte interphases (EEIs) beyond retaining the high-concentration solvation structures. Diluent molecules surrounding the high-concentration clusters could accelerate or decelerate the anion decomposition through coparticipation of diluent decomposition in the EEI formation. The varied interphase features lead to significantly different battery performance. This study points out the importance of diluents and their synergetic effects with the conductive salt and the solvating solvent in designing LHCEs. These systematic comparisons and fundamental insights into LHCEs using different types of fluorinated solvents can guide further development of advanced electrolytes for high-voltage LMBs.

Dynamic Molecular Investigation of the Solid-Electrolyte Interphase of an Anode-Free Lithium Metal Battery Using In Situ Liquid SIMS and Cryo-TEM.

We use in situ liquid secondary ion mass spectroscopy, cryogenic transmission electron microscopy, and density functional theory calculation to delineate the molecular process in the formation of the solid-electrolyte interphase (SEI) layer under the dynamic operating conditions. We discover that the onset potential for SEI layer formation and the thickness of the SEI show dependence on the solvation shell structure. On a Cu film anode, the SEI is noticed to start to form at around 2.0 V (nominal cell voltage) with a final thickness of about 40-50 nm in the 1.0 M LiPF6/EC-DMC electrolyte, while for the case of 1.0 M LiFSI/DME, the SEI starts to form at around 1.5 V with a final thickness of about 20 nm. Our observations clearly indicate the inner and outer SEI layer formation and dissipation upon charging and discharging, implying a continued evolution of electrolyte structure with extended cycling.

Role of inner solvation sheath within salt-solvent complexes in tailoring electrode/electrolyte interphases for lithium metal batteries.

Functional electrolyte is the key to stabilize the highly reductive lithium (Li) metal anode and the high-voltage cathode for long-life, high-energy-density rechargeable Li metal batteries (LMBs). However, fundamental mechanisms on the interactions between reactive electrodes and electrolytes are still not well understood. Recently localized high-concentration electrolytes (LHCEs) are emerging as a promising electrolyte design strategy for LMBs. Here, we use LHCEs as an ideal platform to investigate the fundamental correlation between the reactive characteristics of the inner solvation sheath on electrode surfaces due to their unique solvation structures. The effects of a series of LHCEs with model electrolyte solvents (carbonate, sulfone, phosphate, and ether) on the stability of high-voltage LMBs are systematically studied. The stabilities of electrodes in different LHCEs indicate the intrinsic synergistic effects between the salt and the solvent when they coexist on electrode surfaces. Experimental and theoretical analyses reveal an intriguing general rule that the strong interactions between the salt and the solvent in the inner solvation sheath promote their intermolecular proton/charge transfer reactions, which dictates the properties of the electrode/electrolyte interphases and thus the battery performances.

A Systematic Study on the Effects of Solvating Solvents and Additives in Localized High-Concentration Electrolytes over Electrochemical Performance of Lithium-Ion Batteries.

Localized high-concentration electrolytes (LHCEs) based on five different types of solvents were systematically studied and compared in lithium (Li)-ion batteries (LIBs). The unique solvation structure of LHCEs promotes the participation of Li salt in forming solid electrolyte interphase (SEI) on graphite (Gr) anode, which enables solvents previously considered incompatible with Gr to achieve reversible lithiation/delithiation. However, the long cyclability of LIBs is still subject to the intrinsic properties of the solvent species in LHCEs. Such issue can be readily resolved by introducing a small amount of additive into LHCEs. The synergetic decompositions of Li salt, solvating solvent and additive yield effective SEIs and cathode electrolyte interphases (CEIs) in most of the studied LHCEs. This study reveals that both the structure and the composition of solvation sheaths in LHCEs have significant effect on SEI and CEI, and consequently, the cycle life of energetically dense LIBs.

Graphical Gaussian process regression model for aqueous solvation free energy prediction of organic molecules in redox flow batteries.

The solvation free energy of organic molecules is a critical parameter in determining emergent properties such as solubility, liquid-phase equilibrium constants, pKa and redox potentials in an organic redox flow battery. In this work, we present a machine learning (ML) model that can learn and predict the aqueous solvation free energy of an organic molecule using the Gaussian process regression method based on a new molecular graph kernel. To investigate the performance of the ML model for electrostatic interaction, the nonpolar interaction contribution of the solvent and the conformational entropy of the solute in the solvation free energy, three data sets with implicit or explicit water solvent models, and contribution of the conformational entropy of the solute are tested. We demonstrate that our ML model can predict the solvation free energy of molecules at chemical accuracy with a mean absolute error of less than 1 kcal mol-1 for subsets of the QM9 dataset and the Freesolv database. To solve the general data scarcity problem for a graph-based ML model, we propose a dimension reduction algorithm based on the distance between molecular graphs, which can be used to examine the diversity of the molecular data set. It provides a promising way to build a minimum training set to improve prediction for certain test sets where the space of molecular structures is predetermined.

High-sensitivity determination of available cobalt in soil using laser-induced breakdown spectroscopy assisted with laser-induced fluorescence.

Conventional laser-induced breakdown spectroscopy could not conduct high-sensitivity determination of available cobalt due to spectral interference and weak spectral intensity. To improve the poor detection sensitivity of available cobalt in soil, available cobalt was extracted from soil and prepared. Laser-induced breakdown spectroscopy assisted with laser-induced fluorescence was introduced to excite and detect the cobalt element. The results showed that coefficients of the calibration curve for the available cobalt element could reach 0.9991, and the limits of detection could reach 0.005 mg/kg in soil under optimized conditions, which were all much better than conventional LIBS and reach the international minimum detection standards. This work provides a possible approach for detecting available trace elements in soil.

Double Feature Extraction Method of Ship-Radiated Noise Signal Based on Slope Entropy and Permutation Entropy.

In order to accurately identify various types of ships and develop coastal defenses, a single feature extraction method based on slope entropy (SlEn) and a double feature extraction method based on SlEn combined with permutation entropy (SlEn&PE) are proposed. Firstly, SlEn is used for the feature extraction of ship-radiated noise signal (SNS) compared with permutation entropy (PE), dispersion entropy (DE), fluctuation dispersion entropy (FDE), and reverse dispersion entropy (RDE), so that the effectiveness of SlEn is verified, and SlEn has the highest recognition rate calculated by the k-Nearest Neighbor (KNN) algorithm. Secondly, SlEn is combined with PE, DE, FDE, and RDE, respectively, to extract the feature of SNS for a higher recognition rate, and SlEn&PE has the highest recognition rate after the calculation of the KNN algorithm. Lastly, the recognition rates of SlEn and SlEn&PE are compared, and the recognition rates of SlEn&PE are higher than SlEn by 4.22%. Therefore, the double feature extraction method proposed in this paper is more effective in the application of ship type recognition.

Advanced Low-Flammable Electrolytes for Stable Operation of High-Voltage Lithium-Ion Batteries.

Despite being an effective flame retardant, trimethyl phosphate (TMPa ) is generally considered as an unqualified solvent for fabricating electrolytes used in graphite (Gr)-based lithium-ion batteries as it readily leads to Gr exfoliation and cell failure. In this work, by adopting the unique solvation structure of localized high-concentration electrolyte (LHCE) to TMPa and tuning the composition of the solvation sheaths via electrolyte additives, excellent electrochemical performance can be achieved with TMPa -based electrolytes in Gr∥LiNi0.8 Mn0.1 Co0.1 O2 cells. After 500 charge/discharge cycles within the voltage range of 2.5-4.4 V, the batteries containing the TMPa -based LHCE with a proper additive can achieve a capacity retention of 85.4 %, being significantly higher than cells using a LiPF6 -organocarbonates baseline electrolyte (75.2 %). Meanwhile, due to the flame retarding effect of TMPa , TMPa -based LHCEs exhibit significantly reduced flammability compared with the conventional LiPF6 -organocarbonates electrolyte.

Optimization of Magnesium-Doped Lithium Metal Anode for High Performance Lithium Metal Batteries through Modeling and Experiment.

Lithium (Li)-magnesium (Mg) alloy with limited Mg amount, which can also be called Mg-doped Li (Li-Mg), has been considered as a potential alternative anode for high energy density rechargeable Li metal batteries. However, the optimum doping-content of Mg in Li-Mg anode and the mechanism of the improved performance are not well understood. Herein, density functional theory (DFT) calculations are used to investigate the effect of Mg amount in Li-Mg anode. The Li-Mg with about 5 wt. % Mg (abbreviated as Li-Mg5) has the lowest absorption energy of Li, thus all the surface area can be "controlled" by Mg atoms, leading to the smooth and continuous deposition of Li on the surface around the Mg center. A localized high concentration electrolyte enables Li-Mg5 to exhibit the best cycling stability in Li metal batteries with high-loading cathode and lean electrolyte under 4.4 V high-voltage, which is approaching the demand of practical application. This electrolyte also helps generate an inorganic-rich solid electrolyte interphase, which leads to smooth, compact and less corrosion layer on the Li-Mg5 surface. Both theoretical simulations and experimental results prove that Li-Mg5 has optimum Mg content and gives best battery cycling performance.

Learning Coarse-Grained Potentials for Binary Fluids.

For a multiple-fluid system, CG models capable of accurately predicting the interfacial properties as a function of curvature are still lacking. In this work, we propose a new probabilistic machine learning (ML) model for learning CG potentials for binary fluids. The water-hexane mixture is selected as a typical immiscible binary liquid-liquid system. We develop a new CG force field (FF) using the Shinoda-DeVane-Klein (SDK) FF framework and compute parameters in this CG FF using the proposed probabilistic ML method. It is shown that a standard response-surface approach does not provide a unique set of parameters, as it results in a loss function with multiple shallow minima. To address this challenge, we develop a probabilistic ML approach where we compute the probability density function (PDF) of parameters that minimize the loss function. The PDF has a well-defined peak corresponding to a unique set of parameters in the CG FF that reproduces the desired properties of a liquid-liquid interface. We compare the performance of the new CG FF with several existing FFs for the water-hexane mixture, including two atomistic and three CG FFs with respect to modeling the interface structure and thermodynamic properties. It is demonstrated that the new FF significantly improves the CG model prediction of both the interfacial tension and structure for the water-hexane mixture.

A data-driven framework for sparsity-enhanced surrogates with arbitrary mutually dependent randomness.

The challenge of quantifying uncertainty propagation in real-world systems is rooted in the high-dimensionality of the stochastic input and the frequent lack of explicit knowledge of its probability distribution. Traditional approaches show limitations for such problems, especially when the size of the training data is limited. To address these difficulties, we have developed a general framework of constructing surrogate models on spaces of stochastic input with arbitrary probability measure irrespective of the mutual dependencies between individual components of the random inputs and the analytical form. The present Data-driven Sparsity-enhancing Rotation for Arbitrary Randomness (DSRAR) framework includes a data-driven construction of multivariate polynomial basis for arbitrary mutually dependent probability measures and a sparsity enhancement rotation procedure. This sparsity-enhancing rotation method was initially proposed in our previous work [1] for Gaussian density distributions, which may not be feasible for non-Gaussian distributions due to the loss of orthogonality after the rotation. To remedy such difficulties, we developed a new data-driven approach to construct orthonormal polynomials for arbitrary mutually dependent randomness, ensuring the constructed basis maintains the orthogonality/near-orthogonality with respect to the density of the rotated random vector, where directly applying the regular polynomial chaos including arbitrary polynomial chaos (aPC) [2] shows limitations due to the assumption of the mutual independence between the components of the random inputs. The developed DSRAR framework leads to accurate recovery, with only limited training data, of a sparse representation of the target functions. The effectiveness of our method is demonstrated in challenging problems such as partial differential equations and realistic molecular systems within high-dimensional (O(10)) conformational spaces where the underlying density is implicitly represented by a large collection of sample data, as well as systems with explicitly given non-Gaussian probabilistic measures.

Determination of antimony in soil using laser-induced breakdown spectroscopy assisted with laser-induced fluorescence.

Antimony (Sb) in soil is attracting attention in the research community due to its potential toxicity and carcinogenicity. Traditional methods of detecting Sb lack the ability of rapid and nondigestion analysis, which hinders their development and application. Moreover, it is still a challenge for laser-induced breakdown spectroscopy (LIBS) to detect Sb in soil due to the weak intensities and intense interference of spectral lines. Here, LIBS, assisted with laser-induced fluorescence (LIBS-LIF), was used to selectively enhance the Sb's characteristic spectral lines under optimal parameters. The quantitative analysis performance was notably improved with a determination coefficient (R2) of 0.991, the limit of detection of 0.221 µg/g, and root mean square error of cross validation of 3.592 µg/g. These results demonstrate that LIBS-LIF has the potential to realize the rapid and accurate analysis of Sb in soil.

Fabrication of pH-Responsive Nanoparticles with an AIE Feature for Imaging Intracellular Drug Delivery.

Here we have demonstrated a facile method for construction of self-assembled nanoparticles with excellent fluorescent properties by the synergetic combination of unique AIE effects and tadpole-shaped polymers. The introduction of acid-sensitive Schiff base bonds furnished the polymeric vesicles and micelles with unique pH responsiveness that can possess maximal drug-release controllability inside tumor cells upon changes in physical and chemical environments, but present good stability under physiological conditions. Having benefited from the efficient fluorescence resonance energy transfer (FRET), the DOX-loaded fluorescent aggregates were employed for intracellular imaging and self-localization in surveillance of systemic DOX delivery. Cytotoxicity assay of the DOX-loaded aggregates indicated a fast internalization and a high cellular proliferation inhibition to MCF-7 cells while the PEG-POSS-(TPE)7 nanoparticles displayed no cytotoxicity, exhibiting excellent biocompatibility and biological imaging properties. These results indicated that these biodegradable nanoparticles, as a class of effective pH-responsive and visible nanocarriers, have the potential to improve smart drug delivery and enhance the antitumor efficacy for biomedical applications.

Comparison of the effects of propofol and emulsified isoflurane alone or combined with dexmedetomidine on induction of anesthesia in dogs.

OBJECTIVE: To compare the respective effects of propofol and emulsified isoflurane administered alone and in combination with dexmedetomidine on the quality of induction of anesthesia, physiological variables and recovery in dogs. STUDY DESIGN: Prospective, randomized, experimental trial. ANIMALS: Thirty-six adult mixed-breed dogs. METHODS: Animals were randomly assigned to one of four induction protocols: propofol alone (group P); emulsified isoflurane alone (group EI); both propofol and dexmedetomidine (group PD), or both emulsified isoflurane and dexmedetomidine (group EID). Pulse rate (PR), respiratory rate (fR ), non-invasive arterial blood pressure and arterial blood gases were measured at baseline, before induction, immediately after intubation (time 0), and at 5 minute intervals until the dog began to swallow and the trachea was extubated. The quality of induction and recovery, and degree of ataxia were scored by a single investigator unaware of group assignment. The durations of anesthesia and recovery, and the incidence of adverse events were recorded. RESULTS: There were no clinically significant differences among the groups in induction quality. Systolic arterial pressure was lower in EID compared with P at 5 minutes. PR and fR were lower in PD and EID compared with P after induction. The PaCO2 at 5 minutes was higher than at baseline in group P. Ataxia score was lower in EID than in P. Time from induction to extubation and time from extubation to sternal recumbency were lower in EID compared with PD. CONCLUSIONS AND CLINICAL RELEVANCE: There were no clinically significant differences among the groups in induction quality. In PD and EID, but not in P, PR and fR were decreased after induction. The EID combination resulted in smooth and rapid induction and recovery and thus may be useful clinically for induction of anesthesia.

Transferability of the coarse-grained potentials for trans-1,4-polybutadiene.

In this paper, we evaluate the transferability of the coarse-grained (CG) force field (FF) of trans-1,4-polybutadiene which was built via a combined structure-based and thermodynamic quantity-based CG method at 413 K and 1 atm by systematically examining CG simulated structural and thermodynamic properties against the underlying atomistic simulation results at different temperatures. Interestingly, the derived CG force field exhibits good "state-point transferability" to some extent. For example, when applying this CG FF to the nearby state point (e.g., amorphous phase at 500 K), the resulting local conformation statistics, chain size, and local packing properties as well as density values for the CG models closely match the atomistic simulated data. When further applying this CG force field to the crystalline state at 300 K, the structural and thermodynamic properties of the crystalline phase formed for these CG and atomistic MD simulations still match within a certain level of accuracy. Furthermore, the CG torsion potential has a dual effect: for the amorphous state, the presence of an intramolecular energy barrier against rotation improves the capability of CG models to more precisely reproduce the structural properties, while in the crystalline state this CG torsion barrier suppresses the formation of the more fully stretched chain with a higher trans content. As a result, in the crystalline phase the CG model chains without torsion potentials possess a more stretched chain conformation, pack more efficiently, and have a higher crystallinity degree than its counterpart with CG torsion potentials as well as its underlying atomistic model. However, the dual effect of CG torsion potentials does not mean that we have to use different dihedral parameters to describe different state points. Both CG FFs, one with and another without torsion potentials, are able to represent the melt and the crystalline states. Overall, the phase and its structural consistency between the CG and atomistic models over other state points (e.g., crystalline phase) for which CG FFs were not explicitly parameterized very encouraging such that the combined structure-based and thermodynamic quantity-based CG method can be used to derive an optimized CG FF for multi-scale simulation of polymer systems under different thermodynamic conditions.

Tailoring Solvation Solvent in Localized High-Concentration Electrolytes for Lithium||Sulfurized Polyacrylonitrile.

Sulfurized polyacrylonitrile (SPAN) is a promising cathode material for lithium-sulfur (Li-S) batteries due to its significantly reduced polysulfide (PS) dissolution compared to that of elemental S cathodes. Although conventional carbonate-based electrolytes are stable with SPAN electrodes, they are unstable with Li metal anodes. Recently, localized high-concentration electrolytes (LHCEs) have been developed to improve the stability of Li anodes. Here, we report a new strategy to further improve the performance of Li||SPAN batteries by replacing the conventional solvating solvent 1,2-dimethoxyethane (DME) in LHCEs with a new solvating solvent, 1,2-diethoxyethane (DEE). The new optimal DEE-LHCE exhibits less reactivity against Li2S2, alleviates PS dissolution, forms a better cathode-electrolyte interphase layer on the SPAN cathode, and enhances SPAN structural reversibility even at elevated temperatures (45 °C). Compared to DME-LHCE, DEE-LHCE with the same salt and diluent leads to better performance in Li||SPAN batteries (with 82.9% capacity retention after 300 cycles at 45 °C), preservation of the SPAN cathode structure, and suppression of volume change of the Li metal anode. A similar strategy on tailoring the solvating solvents in LHCEs can also be used in other rechargeable batteries to improve their electrochemical performances.

Important Role of Ion Flux Regulated by Separators in Lithium Metal Batteries.

Polyolefin separators are the most common separators used in rechargeable lithium (Li)-ion batteries. However, the influence of different polyolefin separators on the performance of Li metal batteries (LMBs) has not been well studied. By performing particle injection simulations on the reconstructed three-dimensional pores of different polyethylene separators, it is revealed that the pore structure of the separator has a significant impact on the ion flux distribution, the Li deposition behavior, and consequently, the cycle life of LMBs. It is also discovered that the homogeneity factor of Li-ion toward Li metal electrode is positively correlated to the longevity and reproducibility of LMBs. This work not only emphasizes the importance of the pore structure of polyolefin separators but also provides an economic and effective method to screen favorable separators for LMBs.

Seroprevalence of five diarrhea-related pathogens in bovine herds of scattered households in Inner Mongolia, China between 2019 and 2022.

Bovine diarrhea is a multi-factorial disease and remains one of the biggest health problems in animal husbandry. The endemic trends of the main pathogens responsible for bovine diarrhea in Inner Mongolia have not been analyzed systematically before. Therefore, the purpose of this study was to estimate the prevalence of bovine diarrhea pathogens found in the scattered households of Inner Mongolia in China. Additionally, we assessed for differences in the prevalence of infection based on age and region, as well as determined local prevalence rates and the rates of mixed infections. Using a two-stage random sampling strategy, 3,050 serum samples were collected from 72 bovine herds in 11 leagues and cities in Inner Mongolia, and the positive rates of BVDV, BRV, BCoV, K99, and Mycobacterium paratuberculosis (M. paratuberculosis) antibodies in the samples were detected by ELISA to determine the epidemic trends and epidemic differences of the five pathogens in Inner Mongolia. The positive rates of antibodies based on serum samples were: BVDV, 18.79% (95% CI [17.44-20.22]); BRV, 12.39% (95% CI [11.27-13.61]); BCoV, 12.82% (95% CI [11.68-14.05]); K99, 13.80% (95% CI [12.62-15.07]); and M. paratuberculosis, 10.79% (95% CI [9.74-11.94]). The prevalence rates of BRV, BCoV and K99 at 0-2 months were significantly different from that at 2-6 months, 6-18 months and adult cattle (P < 0.05). The prevalence of BVDV and M. paratuberculosis was the highest in adult cattle, which was significantly different from that in other age groups (P < 0.05). Furthermore, obvious regional epidemiological differences among the five diseases were observed. There was a mixed infection of BRV+BCoV in each age stage, the highest mixed infection being BVDV+BRV+K99 at 0-2 months of age. Our results showed that the cattle of scattered households in the Inner Mongolia of China were endemicly infected with several important cattle pathogens. Most of the pathogens studied occurred between 0-2 months of age and were mixed infections, which greatly influences the health of the cattle and leads to economic loss. These findings are of practical significance for the future prevention and control of bovine diarrhea in the Inner Mongolia or other regions of China.