Cooperative structure of Li/Ni mixing and stacking faults for achieving high-capacity Co-free Li-rich oxides

Co-free Li-rich layered oxides(LLOs)are emerging as promising cathode materials for Li-ion batteries due to their low cost and high capacity.However,they commonly face severe structural instability and poor electrochemical activity,leading to diminished capacity and voltage performance.Herein,we introduce a Co-free LLO,Li_(1.167)Ni_(0.222)Mn_(0.611)O_(2)(Cf-L1),which features a cooperative structure of Li/Ni mixing and stacking faults.This structure regulates the crystal and electronic structures,resulting in a higher discharge capacity of 300.6 mA h g^(-1)and enhanced rate capability compared to the typical Co-free LLO,Li_(1.2)Ni_(0.2)Mn_(0.6)O_(2)(Cf-Ls).Density functional theory(DFT)indicates that Li/Ni mixing in LLOs leads to increased Li-O-Li configurations and higher anionic redox activities,while stacking faults further optimize the electronic interactions of transition metal(TM)3d and non-bonding O 2p orbitals.Moreover,stacking faults accommodate lattice strain,improving electrochemical reversibility during charge/discharge cycles,as demonstrated by the in situ XRD of Cf-L1 showing less lattice evolution than Cf-Ls.This study offers a structured approach to developing Co-free LLOs with enhanced capacity,voltage,rate capability,and cyclability,significantly impacting the advancement of the next-generation Li-ion batteries.

Constraints on symmetry energy and n/p effective mass splitting with improved quantum molecular dynamics model

A new version of improved quantum molecular dynamics model that includes standard Skyrme interactions has been developed.Based on the new code,four commonly used parameter sets,SLy4,SkI2,SkM*and Gs are adopted in the improved quantum molecular dynamics model and the isospin sensitive observables,namely isospin transport ratios,single and double ratios of the yields of neutrons and protons are investigated.The isospin transport ratios are strongly sensitive to the slope of symmetry energy,and are not very sensitive to the nucleon effective mass splitting.On the other hand,the high energy neutrons and protons yields ratios from reactions at different incident energies provide a good observable to the momentum dependence of nucleon effective mass splitting.By comparing our calculations with the data,we find that the constrained L value(the slope of density dependence of symmetry energy) is about ~46 MeV when the Skyrme type interaction is considered in transport models,and the isospin diffusion data prefer to mn*>mp*,but it is not a strong constraint with deep χ2minimum.

Modeling Structures and Spectra of Fluorescent Proteins in the Coordinate-Locking Cluster Approach: Application to the Photoswitchable Protein AsFP595

An interest in the fluorescent protein asFP595 is due to unexplained puzzles in its photophysical behavior. We report the results of calculations of structures, absorption, and emission bands in asFP595 by considering model molecular clusters in the coordinate-locking scheme. Both trans and cis conformations of the anionic chromophore are considered. Equilibrium geometry coordinates on the ground potential energy surface were optimized in the density functional theory approaches by considering both large- and reduced-size clusters. The cluster size was reduced to locate positions of the minimum energy points on the excited-state potential surface by using the configuration interaction singles approach. Vertical excitation energies and oscillator strengths were computed by using the ZINDO method. We show that consideration of large clusters mimicking the protein-containing pocket is an essential issue to calculate positions of absorption and emission bands with the accuracy compatible to experiments.

Comparing biomarkers and proteomic fingerprints for classification studies

Early disease detection is extremely important in the treatment and prognosis of many diseases, especially cancer. Often, proteomic fingerprints and a pattern recognition algorithm are used to classify the pathological condition of a given individual. It has been argued that accurate classification of the existing data implies an underlying biological significance. Two fingerprint-based classifiers, decision tree and medoid classification algorithm, and a biomarker-based classifier were examined using a published dataset of mass spectral peaks from 81 healthy individuals and 78 individuals with benign prostate hyperplasia (BPH). For all three methods, classifiers were constructed using the original data and the data after permuting the labels of the samples (BPH and healthy). The fingerprint-based classifiers produced accurate results for the original data, though the peaks used in a given classifier depended upon which samples were placed in the training set. Accurate results were also obtained for the dataset with permuted labels. In contrast, only three unique peaks were identified as putative biomarkers, producing a small number of reasonably accurate biomarker-based classifiers. The dataset with permuted labels was poorly classified. Since fingerprint-based classifiers accurately classified the dataset with permuted labels, the argument for biological significance from a fingerprint-based classifier must be questioned.

Ab Initio Investigations for the Role of Compositional Complexities in Affecting Hydrogen Trapping and Hydrogen Embrittlement:A Review

ydrogen embrittlement(HE)seriously restricts the service safety of structural metallic materials applicate in aerospace,ocean,and transportation.Recent studies aiming at increasing the HE-resistance have been focusing on trapping diffusible H atoms by inherent microstructural features in materials.Alloying-induced compositional complexities,including different types of solute atoms,lattice chemical heterogeneities,and carbide precipitates,have attracted research efforts regarding the H trapping capabilities and potential to reduce the susceptibility to HE.In this paper,we review recent progress in exploiting compositional complexities to regulate the hydrogen trapping characteristics and mechanical properties in H-containing environments.The focus is placed on results and insights from ab initio calculations based on density functional theory(DFT).Quantitative predictions of trapping parameters and atomic scale details that are hardly to be gained through traditional experimental characterizations are provided.Additionally,we overview the electronic/atomistic mechanisms of H trapping energetics in metallic materials.Finally,we propose some key challenges and prospects in simulation of defect interactions,interpretation of experimental characterizations,and developing microstructure-based H diffusion prediction models.For the applications of first principle calculations,we illustrate how the DFT data can complement experimental characterizations to guide composition and microstructure design for better HE-resistant materials.

Frist-principles prediction of elastic, electronic,and thermodynamic properties of high entropy carbide ceramic (TiZrNbTa)C

High-entropy carbide ceramics (HECs) have drawn increasing attention as their excellent mechanical and thermal properties. In this work, the crystal stability,mechanical behavior, electronic and thermodynamic properties of (TiZrNbTa)C HEC are investigated by the first-principles calculations. Obtained results reveal that the disordered transition-metal (TM) atoms result in serious local lattice distortion within the crystal. The lattice distortion plays a key role for the structural stabilization,mechanical anisotropy and thermodynamic behaviors of(TiZrNbTa)C. Increasing pressure leads to decrease the lattice parameter, volume and brittleness, meanwhile increase the elastic constants, elastic moduli, mechanical anisotropy, sound velocity, and Debye temperature. It is also discovered that charge delocalization occurs with the increase in pressure. The mechanical stability and anisotropy of (TiZrNbTa)C are attributed primarily to TM-C bonding.

Antimicrobial power of biosynthesized Ag nanoparticles using refined Ginkgo biloba leaf extracts

Silver nanoparticles(Ag NPs),relative to existing antibacterial agents,are more effective,less toxic and more economical,and have shown enormous potential for the nanomedicine application.In this work,we report a‘green’method for the rapid and efficient synthesis of Ag NPs using Ginkgo biloba extracts as reducing agent and capping agent.The properties of Ag NPs against fungi and bacteria were investigated.The results showed that the Ginkgo biloba extracts are crucial for the preparation of uniform and monodispersed Ag NPs.The prepared Ag NPs exhibited remarkable antibacterial activities.The minimum inhibitory concentrations of Ag NPs for Escherichia coli and Pseudomonas aeruginosa were 0.044 and 0.088μg·mL−1,respectively.Moreover,Ag NPs exhibited excellent bactericidal performance against MDR-Pseudomonas aeruginosa.It was found that the effect of the antibacterial activity of Ag NPs on Escherichia coli and Staphylococcus aureus was tightly related to the reactive oxygen species accumulation.This research provides guidelines for the efficient green synthesis of Ag NPs and its antibacterial applications.

Disaster Risk Management Through the Design Safe Cyberinfrastructure

Design Safe addresses the challenges of supporting integrative data-driven research in natural hazards engineering.It is an end-to-end data management,communications,and analysis platform where users collect,generate,analyze,curate,and publish large data sets from a variety of sources,including experiments,simulations,field research,and post-disaster reconnaissance.DesignSafe achieves key objectives through:(1)integration with high performance and cloud-computing resources to support the computational needs of the regional risk assessment community;(2)the possibility to curate and publish diverse data structures emphasizing relationships and understandability;and(3)facilitation of real time communications during natural hazards events and disasters for data and information sharing.The resultant services and tools shorten data cycles for resiliency evaluation,risk modeling validation,and forensic studies.This article illustrates salient features of the cyberinfrastructure.It summarizes its design principles,architecture,and functionalities.The focus is on case studies to show the impact of Design Safe on the disaster risk community.The Next Generation Liquefaction project collects and standardizes case histories of earthquake-induced soil liquefaction into a relational database—Design Safe—to permit users to interact with the data.Researchers can correlate in Design Safe building dynamic characteristics based on data from building sensors,with observed damage based on ground motion measurements.Reconnaissance groups upload,curate,and publish wind,seismic,and coastal damage data they gather during field reconnaissance missions,so these datasets are available shortly after a disaster.As a part of the education and community outreach efforts of Design Safe,training materials and collaboration space are also offered to the disaster risk management community.

Single-cell Long Non-coding RNA Landscape of T Cells in Human Cancer Immunity

The development of new biomarkers or therapeutic targets for cancer immunotherapies requires deep understanding of Tcells.To date,the complete landscape and systematic characterization of long noncoding RNAs(lncRNAs)in T cells in cancer immunity are lacking.Here,by systematically analyzing full-length single-cell RNA sequencing(scRNA-seq)data of more than 20,000 libraries of T cells across three cancer types,we provided the first comprehensive catalog and the functional repertoires of lncRNAs in human T cells.Specifically,we developed a custom pipeline for de novo transcriptome assembly and obtained a novel lncRNA catalog containing 9433 genes.This increased the number of current human lncRNA catalog by 16%and nearly doubled the number of lncRNAs expressed in T cells.We found that a portion of expressed genes in single T cells were lncRNAs which had been overlooked by the majority of previous studies.Based on metacell maps constructed by the MetaCell algorithm that partitions scRNA-seq datasets into disjointed and homogenous groups of cells(metacells),154 signature lncRNA genes were identified.They were associated with effector,exhausted,and regulatory T cell states.Moreover,84 of them were functionally annotated based on the co-expression networks,indicating that lncRNAs might broadly participate in the regulation of T cell functions.Our findings provide a new point of view and resource for investigating the mechanisms of T cell regulation in cancer immunity as well as for novel cancer-immune biomarker development and cancer immunotherapies.

A cyberGIS-enabled multi-criteria spatial decision support system: A case study on flood emergency management

With the increased frequency of natural hazards and disasters and consequent losses,it is imperative to develop efficient and timely strategies for emergency response and relief operations.In this paper,we propose a cyberGIS-enabled multi-criteria spatial decision support system for supporting rapid decision making during emergency management.It combines a high-performance computing environment(cyberGIS-Jupyter)and multi-criteria decision analysis models(Weighted Sum Model(WSM)and Technique for Order Preference by Similarity to Ideal Solution Model(TOPSIS))with various types of social vulnerability indicators to solve decision problems that contain conflicting evaluation criteria in a flood emergency situation.Social media data(e.g.Twitter data)was used as an additional tool to support the decision-making process.Our case study involves two decision goals generated based on a past flood event in the city of Austin,Texas,U.S.A.As our result shows,WSM produces more diverse values and higher output category estimations than the TOPSIS model.Finally,the model was validated using an innovative questionnaire.This cyberGIS-enabled spatial decision support system allows collaborative problem solving and efficient knowledge transformation between decision makers,where different emergency responders can formulate their decision objectives,select relevant evaluation criteria,and perform interactive weighting and sensitivity analyses.