In-situ coating and surface partial protonation co-promoting performance of single-crystal nickel-rich cathode in all-solid-state batteries

The poor electrochemical performance of all-solid-state batteries(ASSBs),which is assemblied by Ni-rich cathode and poly(ethylene oxide)(PEO)-based electrolytes,can be attributed to unstable cathodic interface and poor crystal structure stability of Ni-rich cathode.Several coating strategies are previously employed to enhance the stability of the cathodic interface and crystal structure for Ni-rich cathode.However,these methods can hardly achieve simplicity and high efficiency simultaneously.In this work,polyacrylic acid(PAA)replaced traditional PVDF as a binder for cathode,which can achieve a uniform PAA-Li(LixPAA(0<x≤1))coating layer on the surface of single-crystal LiNi_(0.83)Co_(0.12)Mn_(0.05)O_(2)(SC-NCM83)due to H^(+)/Li^(+)exchange reaction during the initial charging-discharging process.The formation of PAA-Li coating layer on cathode can promote interfacial Li^(+)transport and enhance the stability of the cathodic interface.Furthermore,the partially-protonated surface of SC-NCM83 casued by H^(+)/Li^(+)exchange reaction can restrict Ni ions transport to enhance the crystal structure stability.The proposed SC-NCM83-PAA exhibits superior cycling performance with a retention of 92%compared with that(57.3%)of SC-NCM83-polyvinylidene difluoride(PVDF)after 200 cycles.This work provides a practical strategy to construct high-performance cathodes for ASSBs.

Structural regulation chemistry of lithium-ion solvation in nonflammable phosphate-based electrolytes for high interfacial compatibility with graphite anode

With the booming development of lithium-ion batteries,safety has become one of the most primary focuses of current researches.Although there are various approaches to enhance the safety of lithiumion batteries,phosphate-based electrolyte holds the greatest potential for practical application due to their non-flammability.Nonetheless,its compatibility issue with the graphite anode remains a significant obstacle to its widespread use.Herein,an effective method is proposed to improve the compatibility of electrolyte with graphite(Gr)anode by rationally adjusting the proportion of lithium salt and solvent components to optimize the Li^(+)solvation structure.By slightly increasing the Li^(+)/triethyl phosphate(TEP)ratio,TEP alone cannot fully occupy the inner solvation sheath and therefore less polar ethylene carbonate(EC)has to be recruited,and the solvation structure gradually changes from Li^(+)–[TEP]_(4)to Li^(+)–[TEP]_(3)[EC]with the coexistence of EC and TEP.Simultaneously,EC molecules in the Li^(+)–[TEP]_(3)[EC]could be preferentially reduced on graphite compared to the TEP molecules,resulting in the formation of a uniform and durable solid-electrolyte interphase(SEI)layer.Benefiting from the optimized phosphate-based electrolyte,the Gr|Li battery exhibits a capacity retention rate of 96.8%after stable cycling at 0.5 C for 470 cycles which shows a longer cycle life than the battery with carbonate electrolyte(cycling at 0.5 C for 450 cycles).Therefore,this work provides the guidance for designing a non-flammable phosphate-based electrolyte for high-safety and long cycling-life lithium-ion batteries.

Self-assembled three-dimensional carbon networks with accessorial Lewis base sites and variational electron characteristics as efficient oxygen reduction reaction catalysts for alkaline metal-air batteries

Heteroatom-doped carbon has been demonstrated to be one of the most promising non-noble metal catalysts with high catalytic activity and stability through the modification of the electronic and geometric structures.In this study,we develop a novel solvent method to prepare interconnected N,S co-doped three-dimensional（3D）carbon networks with tunable nanopores derived from an asso-ciated complex based on melamine and sodium dodecylbenzene sulfonate（SDBS）.After the intro-duction of silica templates and calcination,the catalyst exhibits 3D networks with interconnected 50-nm pores and partial graphitization.With the increase of the number of Lewis base sites caused by the N doping and change of the carbon charge and spin densities caused by the S doping,the designed N,S co-doped catalyst exhibits a similar electrochemical activity to that of the commercial 20-wt%Pt/C as an oxygen reduction reaction catalyst.In addition,in an aluminum-air battery,the proposed catalyst even outperforms the commercial 5-wt%Pt/C catalyst.Both interconnected porous structures and synergistic effects of N and S contribute to the superior catalytic perfor-mance.This study paves the way for the synthesis of various other N-doped and co-doped carbon materials as efficient catalysts in electrochemical energy applications.

新一代水文水资源监测卫星SWOT数据特征、应用与展望

水文水资源监测是对地观测系统的重要任务之一,是支撑新时代水利高质量发展、满足“三水”共治需求和践行“十六字”治水策略的直接有效途径,而卫星遥感技术提供了一种大范围、快速和高精度的数据获取渠道。但是现有卫星遥感在水文水资源应用上存在多星同步观测难、应急响应能力差和易受天气影响等问题,因此美国国家航空航天局于2022年12月发射了地表水和海洋地形卫星(SWOT),这是全球第一颗通过多传感器协同观测全球陆地和海洋水资源的卫星,预期将极大提升水文水资源监测的时空分辨率和精度。系统梳理了水文水资源监测卫星发展现状、应用和技术难点等概况,并分析了SWOT卫星的参数、科学任务、算法流程和应用产品等内容,对我国后续卫星设计规划和数据处理关键技术有一定的参考价值。

Annotating TSSs in Multiple Cell Types Based on DNA Sequence and RNA-seq Data via DeeReCT-TSS

The accurate annotation of transcription start sites(TSSs)and their usage are critical for the mechanistic understanding of gene regulation in different biological contexts.To fulfill this,specific high-throughput experimental technologies have been developed to capture TSSs in a genome-wide manner,and various computational tools have also been developed for in silico prediction of TSSs solely based on genomic sequences.Most of these computational tools cast the problem as a binary classification task on a balanced dataset,thus resulting in drastic false positive predictions when applied on the genome scale.Here,we present Dee Re CT-TSS,a deep learningbased method that is capable of identifying TSSs across the whole genome based on both DNA sequence and conventional RNA sequencing data.We show that by effectively incorporating these two sources of information,Dee Re CT-TSS significantly outperforms other solely sequence-based methods on the precise annotation of TSSs used in different cell types.Furthermore,we develop a meta-learning-based extension for simultaneous TSS annotations on 10 cell types,which enables the identification of cell type-specific TSSs.Finally,we demonstrate the high precision of DeeReCT-TSS on two independent datasets by correlating our predicted TSSs with experimentally defined TSS chromatin states.The source code for Dee Re CT-TSS is available at https://github.-com/Joshua Chou2018/Dee Re CT-TSS_release and https://ngdc.cncb.ac.cn/biocode/tools/BT007316.