Ab Initio Design of Ni-Rich Cathode Material with Assistance of Machine Learning for High Energy Lithium-Ion Batteries

With the widespread use of lithium-ion batteries in electric vehicles,energy storage,and mobile terminals,there is an urgent need to develop cathode materials with specific properties.However,existing material control synthesis routes based on repetitive experiments are often costly and inefficient,which is unsuitable for the broader application of novel materials.The development of machine learning and its combination with materials design offers a potential pathway for optimizing materials.Here,we present a design synthesis paradigm for developing high energy Ni-rich cathodes with thermal/kinetic simulation and propose a coupled image-morphology machine learning model.The paradigm can accurately predict the reaction conditions required for synthesizing cathode precursors with specific morphologies,helping to shorten the experimental duration and costs.After the model-guided design synthesis,cathode materials with different morphological characteristics can be obtained,and the best shows a high discharge capacity of 206 mAh g^(−1)at 0.1C and 83%capacity retention after 200 cycles.This work provides guidance for designing cathode materials for lithium-ion batteries,which may point the way to a fast and cost-effective direction for controlling the morphology of all types of particles.

Lithiophilic Li-Si alloy-solid electrolyte interface enabled by high-concentration dual salt-reinforced quasi-solid-state electrolyte

Solid polymer electrolytes(SPEs)are urgently required to achieve practical solid-state lithium metal batteries(LMBs)and lithium-ion batteries(LIBs),Herein,we proposed a mechanism for modulating interfacial conduction and anode interfaces in high-concentration SPEs by LiDFBOP.Optimized electrolyte exhibits superior ionic conductivity and remarkable interface compatibility with salt-rich clusters:(1)polymer-plastic crystal electrolyte(P-PCE,TPU-SN matrix)dissociates ion pairs to facilitate Li+transport in the electrolyte and regulates Li^(+)diffusion in the SEI.The crosslinking structure of the matrix compensates for the loss of mechanical strength at high-salt concentrations;(2)dual-anion TFSI^(-)_(n)-DFBOP^(-)_(m)in the Li^(+)solvation sheath facilitates facile Li^(+)desolvation and formation of salt-rich clusters and is conducive to the formation of Li conductive segments of TPU-SN matrix;(3)theoretical calculations indicate that the decomposition products of LiDFBOP form SEI with lower binding energy with LiF in the SN system,thereby enhancing the interfacial electrochemical redox kinetics of SPE and creating a solid interface SEI layer rich in LiF.As a result,the optimized electrolyte exhibits an excellent ionic conductivity of9.31×10^(-4)S cm^(-1)at 30℃and a broadened electrochemical stability up to 4.73 V.The designed electrolyte effectively prevents the formation of Li dendrites in Li symmetric cells for over 6500 h at0.1 mA cm^(-2).The specific Li-Si alloy-solid state half-cell capacity shows 711.6 mAh g^(-1)after 60 cycles at 0.3 A g^(-1).Excellent rate performance and cycling stability are achieved for these solid-state batteries with Li-Si alloy anodes and NCM 811 cathodes.NCM 811‖Prelithiated silicon-based anode solid-state cell delivers a discharge capacity of 195.55 mAh g^(-1)and a capacity retention of 97.8%after 120 cycles.NCM 811‖Li solid-state cell also delivers capacity retention of 84.2%after 450 cycles.

Magnetic Field Controllable Photocurrent Properties in BiFe_(0.9)Ni_(0.1)O_(3)/La_(0.7)Sr_(0.3)MnO_(3) Laminate Thin Film

This paper reports a multifunctional magnetic-photoelectric laminate device based on the integration of spintronic material(La_(0.7)Sr_(0.3)MnO_(3))and multiferroic(Ni-doped BiFeO_(3)),in which the repeatable modulation effect on the photoelectric properties were achieved by applying external magnetic fields.More obviously,photocurrent density(J)of the laminate was largely enhanced,the change rate of J up to 287.6%is obtained.This sensing function effect should be attributed to the low-field magnetoresistance effect in perovskite manganite and the scattering of spin photoelectron in multiferroic material.The laminate perfectly combines the functions of sensor and controller,which can not only reflect the intensity of environmental magnetic field,but also modulate the photoelectric conversion performance.This work provides an alternative and facile way to realize multi-degree-of-freedom control for photoelectric conversion performances and lastly miniaturize multifunction device.

组蛋白去甲基化酶KDM7家族在脑疾病中研究进展

组蛋白去甲基化酶KDM7家族包括KDM7A、KDM7B、KDM7C三种蛋白,主要通过去除与转录沉默相关的特定组蛋白赖氨酸甲基化修饰,进而对基因转录发挥调控作用。目前,对KDM7家族的研究主要集中于其在神经分化、肿瘤发生发展等过程中的作用,而对其在脑神经疾病中的作用却知之甚少。本文从该蛋白家族表观遗传调控机制、结构生物学及其在脑神经疾病中的作用等方面进行了综述,以期为研究其在脑神经疾病中的功能机制提供参考,为理解脑神经疾病分子病理机制以及探索基于该机制的有效治疗靶点带来新的启示。

Channel Measurement and Path Loss Modeling from 220 GHz to 330 GHz for 6G Wireless Communications

Terahertz(THz)communication has been envisioned as a key enabling technology for sixthgeneration(6G).In this paper,we present an extensive THz channel measurement campaign for 6G wireless communications from 220 GHz to 330 GHz.Furthermore,the path loss is analyzed and modeled by using two single-frequency path loss models and a multiplefrequencies path loss model.It is found that at most frequency points,the measured path loss is larger than that in the free space.But at around 310 GHz,the propagation attenuation is relatively weaker compared to that in the free space.Also,the frequency dependence of path loss is observed and the frequency exponent of the multiple-frequencies path loss model is 2.1.Moreover,the cellular performance of THz communication systems is investigated by using the obtained path loss model.Simulation results indicate that the current inter-site distance(ISD)for the indoor scenario is too small for THz communications.Furthermore,the tremendous capacity gain can be obtained by using THz bands compared to using microwave bands and millimeter wave bands.Generally,this work can give an insight into the design and optimization of THz communication systems for 6G.

The Way to Apply Machine Learning to IoT Driven Wireless Network from Channel Perspective

Internet of Things(IoT) is one of the targeted application scenarios of fifth generation(5 G) wireless communication.IoT brings a large amount of data transported on the network.Considering those data,machine learning(ML) algorithms can be naturally utilized to make network efficiently and reliably.However,how to fully apply ML to IoT driven wireless network is still open.The fundamental reason is that wireless communication pursuits the high capacity and quality facing the challenges from the varying and fading wireless channel.So in this paper,we explore feasible combination for ML and IoT driven wireless network from wireless channel perspective.Firstly,a three-level structure of wireless channel fading features is defined in order to classify the versatile propagation environments.This three-layer structure includes scenario,meter and wavelength levels.Based on this structure,there are different tasks like service prediction and pushing,self-organization networking,self adapting largescale fading modeling and so on,which can be abstracted into problems like regression,classification,clustering,etc.Then,we introduce corresponding ML methods to different levelsfrom channel perspective,which makes their interdisciplinary research promisingly.

Implementation Framework and Validation of Cluster-Nuclei Based Channel Model Using Environmental Mapping for 6G Communication Systems

With the research of the upcoming sixth generation(6 G) systems, new technologies will require wider bandwidth, larger scale antenna arrays and more diverse wireless communication scenarios on the future channel modeling. Considering channel model is prerequisite for system design and performance evaluation of 6 G technologies, we face a challenging task: how to accurately and efficiently model 6 G channel for various scenarios? This paper tries to answer it. Firstly, the features of cluster-nuclei(CN) and principle of cluster-nuclei based channel model(CNCM) are introduced. Then, a novel modeling framework is proposed to implement CNCM,which consists four steps: propagation environment reconstruction, cluster-nuclei identification, multipath parameters generation, and channel coefficients generation. Three-dimensional environment with material information is utilized to map CN with scatterers in the propagation pathway. CN are identified by geometrical and electric field calculation based on environmental mapping, and multipath components within CN are calculated by statistical characteristics of angle, power and delay domains. Finally, we present a three-level verification structure to investigate the accuracy and complexity of channel modeling comprehensively. Simulation results reveal that CNCM can perform higher accuracy than geometrybased stochastic model while lower complexity compared with ray-tracing model for practical propagation environment.

A Predictive 6G Network with Environment Sensing Enhancement:From Radio Wave Propagation Perspective

In order to support the future digital society,sixth generation(6G)network faces the challenge to work efficiently and flexibly in a wider range of scenarios.The traditional way of system design is to sequentially get the electromagnetic wave propagation model of typical scenarios firstly and then do the network design by simulation offline,which obviously leads to a 6G network lacking of adaptation to dynamic environments.Recently,with the aid of sensing enhancement,more environment information can be obtained.Based on this,from radio wave propagation perspective,we propose a predictive 6G network with environment sensing enhancement,the electromagnetic wave propagation characteristics prediction enabled network(EWave Net),to further release the potential of 6G.To this end,a prediction plane is created to sense,predict and utilize the physical environment information in EWave Net to realize the electromagnetic wave propagation characteristics prediction timely.A two-level closed feedback workflow is also designed to enhance the sensing and prediction ability for EWave Net.Several promising application cases of EWave Net are analyzed and the open issues to achieve this goal are addressed finally.

Adversarial Training-Aided Time-Varying Channel Prediction for TDD/FDD Systems

In this paper, a time-varying channel prediction method based on conditional generative adversarial network(CPcGAN) is proposed for time division duplexing/frequency division duplexing(TDD/FDD) systems. CPc GAN utilizes a discriminator to calculate the divergence between the predicted downlink channel state information(CSI) and the real sample distributions under a conditional constraint that is previous uplink CSI. The generator of CPcGAN learns the function relationship between the conditional constraint and the predicted downlink CSI and reduces the divergence between predicted CSI and real CSI.The capability of CPcGAN fitting data distribution can capture the time-varying and multipath characteristics of the channel well. Considering the propagation characteristics of real channel, we further develop a channel prediction error indicator to determine whether the generator reaches the best state. Simulations show that the CPcGAN can obtain higher prediction accuracy and lower system bit error rate than the existing methods under the same user speeds.

Subway Embedded Track Geometric Irregularity Safety Limits

A coupling dynamic model of a subway train and an embedded track is established to study the safety limits of track irregularities.The simulated vehicle system was a 74-degrees of freedom multi-rigid body model,and the rail was a Timoshenko beam.The slab was a three-dimensional solid finite element model.The sensitive wavelength irregularity was first studied,and then the safety limit of the sensitive wavelength was analyzed.The wheel-rail lateral force exhibited a substantial effect on the track alignment and gauge irregularity safety limit.The wheel-rail vertical force and the rate of wheel load reduction significantly affected the height and cross-level irregularity safety limit.The results demonstrate that the safety limits of the alignment,gauge,height,and cross-level embedded track geometric irregularity are 5.3 mm,[−10.5,8]mm,5.6 mm,and 6 mm,respectively.

Stable cycling of LiNi_(0.9)Co_(0.05)Mn_(0.05)O_(2)/lithium metal batteries enabled by synergistic tuning the surface stability of cathode/anode

Ni-rich layered oxides(LiNi_(0.9)Co_(0.05)Mn_(0.05)O_(2))show great potential in long-range and low-cost lithiumion batteries.However,due to the high surface sensitivity,their practical application is hindered by interfacial instability with electrolytes under high voltage for long cyclic life.Herein,by combining both firstprinciple calculations and time-of-flight secondary ion mass spectrometry(TOF-SIMS),a novel surface fluorinated reconstruction(SFR)mechanism is proposed to improve the interfacial stability under high voltage,which could effectively regulate the surface fluoride species to desensitize the LiNi_(0.9)Co_(0.05)Mn_(0.05)O_(2)interface.We demonstrate here that by tuning the ratio of fluoride species,the LiNi_(0.9)Co_(0.05)Mn_(0.05)O_(2)/Li battery could achieve excellent long-term and high voltage performance(163.5 mA h g^(-1)at 0.5 C for 300 cycles under 4.4 V),while the controlled sample decayed to 125.4 mA h g^(-1)after 300 cycles.Moreover,the favorable cross-talk effect induced by SFR further facilitates the incorporation of suitable amounts of Ni ions into the construction of stable solid electrolyte interface(SEI)layer for anode surface.Therefore,the ultra-long cycling stability under high voltage can be achieved by the robust cathode/electrolyte and Li/electrolyte interfaces,which results in excellent interfacial stability after long cycling.This work provides new insights into the surface design of cathode materials and improves the stability of the electrode-electrode interface under high voltage.

Asymmetric acidic/alkaline N_(2)electrofixation accelerated by high-entropy metal-organic framework derivatives

High-entropy materials are composed of five or more metal elements with equimolar or near-equimolar concentrations within one crystal structure,which offer remarkable structural properties for many applications.Despite previously reported entropy-driven stabilization mechanisms,many high-entropy materials still tend to decompose to produce a variety of derivatives under operating conditions.In this study,we use transition-metal(Ni,Co,Ni,Zn,V)-based high-entropy metal-organic frameworks(HE-MOFs)as the precursors to produce different derivatives under acidic/alkaline treatment.We have shown that HE-MOFs and derivatives have shown favorable kinetics for N_(2)electrofixation in different pH electrolytes,specifically cathodic nitrogen reduction reaction in acidic media and anodic oxygen evolution reaction in alkaline media.To buffer the pH mismatch,we have further constructed an asymmetric acidic/alkaline device prototype by using bipolar membranes.As expected,the prototype showed remarkable activities,with an NH_(3)yield rate of 42.76μg h^(−1)mg^(−1),and Faradaic efficiency of 14.75%and energy efficiency of 2.59%,which are 14.4 and 4.4 times larger than those of its symmetric acidic and alkaline counterparts,respectively.

Environment Information-Based Channel Prediction Method Assisted by Graph Neural Network

Recently,whether the channel prediction can be achieved in diverse communication scenarios by directly utilizing the environment information gained lots of attention due to the environment impacting the propagation characteristics of the wireless channel.This paper presents an environment information-based channel prediction(EICP)method for connecting the environment with the channel assisted by the graph neural networks(GNN).Firstly,the effective scatterers(ESs)producing paths and the primary scatterers(PSs)generating single propagation paths are detected by building the scatterercentered communication environment graphs(SCCEGs),which can simultaneously preserve the structure information and highlight the pending scatterer.The GNN-based classification model is implemented to distinguish ESs and PSs from other scatterers.Secondly,large-scale parameters(LSP)and small-scale parameters(SSP)are predicted by employing the GNNs with multi-target architecture and the graphs of detected ESs and PSs.Simulation results show that the average normalized mean squared error(NMSE)of LSP and SSP predictions are 0.12 and 0.008,which outperforms the methods of linear data learning.

Topology and Semantic Information Fusion Classification Network Based on Hyperspectral Images of Chinese Herbs

Most methods for classifying hyperspectral data only consider the local spatial relation-ship among samples,ignoring the important non-local topological relationship.However,the non-local topological relationship is better at representing the structure of hyperspectral data.This paper proposes a deep learning model called Topology and semantic information fusion classification network(TSFnet)that incorporates a topology structure and semantic information transmis-sion network to accurately classify traditional Chinese medicine in hyperspectral images.TSFnet uses a convolutional neural network(CNN)to extract features and a graph convolution network(GCN)to capture potential topological relationships among different types of Chinese herbal medicines.The results show that TSFnet outperforms other state-of-the-art deep learning classification algorithms in two different scenarios of herbal medicine datasets.Additionally,the proposed TSFnet model is lightweight and can be easily deployed for mobile herbal medicine classification.

6G信道新特性与建模研究:挑战、进展与展望

随着第六代移动通信(the six generation,6G)的前沿研究在全球范围内陆续开展,工业界和学术界提出了多种新技术、新频段和新应用,如通信感知一体化(integrated sensing and communication,ISAC)、超大规模多输入多输出天线阵列(extra-large-scale massive multiple-input multiple-output,XLMIMO)、多频段通信、可重构智能超表面(reconfigurable intelligent surface,RIS)和空-天-地-海通信等,旨在提供更高速率、更低时延、更广覆盖的高可靠移动通信服务.信道是移动通信系统收发端之间信号承载的媒介,其深入的传播特性发现与精确的建模对6G系统的研发、评估和优化至关重要.因此本文首先回顾了第一代到第五代移动通信的信道研究发展趋势,指出了多频段、多场景和多种新技术趋势下6G信道研究面临的挑战.随后,详细总结了6G信道新特性研究的最新进展,包括ISAC信道的共享性、XL-MIMO信道的近场和空间非平稳性、RIS信道的级联特性,以及多频段信道频率依赖性等.然后,本文提出了一种面向6G标准的扩展几何统计性信道模型,将所发现的信道新特性纳入统一建模框架,所提模型后向兼容主流的高精度5G标准模型,便于代际更迭的信道仿真器实现.最后,指出了面向6G演进的信道特性与建模方法研究有待深入的问题,并聚焦6G网络自治化的未来愿景,展望了一种基于环境感知重构和人工智能预测技术的信道数字孪生新范式.

MXene-based all-solid flexible electrochromic microsupercapacitor

With the increasing demand for multifunctional optoelectronic devices,flexible electrochromic energy storage devices are being widely recognized as promising platforms for diverse applications.However,simultaneously achieving high capacitance,fast color switching and large optical modulation range is very challenging.In this study,the MXenebased flexible in-plane microsupercapacitor was fabricated via a mask-assisted spray coating approach.By adding electrochromic ethyl viologen dibromide(EVB)into the electrolyte,the device showed a reversible color change during the charge/discharge process.Due to the high electronic conductivity of the MXene flakes and the fast response kinetics of EVB,the device exhibited a fast coloration/bleaching time of 2.6 s/2.5 s,a large optical contrast of 60%,and exceptional coloration efficiency.In addition,EVB acted as a redox additive to reinforce the energy storage performance;as a result,the working voltage window of the Ti_(3)C_(2)-based symmetric aqueous microsupercapacitor was extended to 1 V.Moreover,the device had a high areal capacitance of 12.5 mF cm^(−2)with superior flexibility and mechanical stability and showed almost 100%capacitance retention after 100 bending cycles.The as-prepared device has significant potential for a wide range of applications in flexible and wearable electronics,particularly in the fields of camouflage,anticounterfeiting,and displays.

Clinical characteristics and risk factors for mortality in Candida auris infections

Background:Candida auris infections pose a threat to public health,necessitating increased awareness in China.This study aimed to analyze the strains of C.auris,assess the infection status,and investigate clinical characteristics and risk factors for mortality.Methods:A retrospective analysis was conducted on 18 patients with Candida auris infection.We focused on evaluating basic characteristics,strain sources,and antibacterial susceptibility test results.Statistical methods were used to determine clinical features and identify risk factors for death.Results:The strain type,composition ratio,and specimen source of C.auris were not associated with mortality.Neither the infection index nor the length of hospitalization showed an association with the prognosis.However,significant risk factors for mortality included cerebral infarction,cardiac disease,renal dysfunction,hypoproteinemia,and anemia(all p<0.05).Conclusions:Cerebral infarction,cardiac disease,renal dysfunction,hypoproteinemia,and anemia are significant risk factors for death in C.auris infections.These findings indicate the importance of recognizing and addressing these factors in the clinical management of C.auris infection.

BZR1 Family Transcription Factors Function Redundantly and Indispensably in BR Signaling but Exhibit BRI1-Independent Function in Regulating Anther Development in Arabidopsis

BRASSINAZOLE-RESISTANT 1 family proteins(BZRs)are central transcription factors that govern brassinosteroid(BR)-regulated gene expression and plant growth.However,it is unclear whether there exists a BZR-independent pathway that mediates BR signaling.In this study,we found that disruption of all BZRs in Arabidopsis generated a hextuple mutant(bzr-h)displaying vegetative growth phenotypes that were almost identical to those of the null mutant of three BR receptors,bri1brl1brl3(bri-t).By RNA sequencing,we found that global gene expression in bzr-h was unaffected by 2 h of BR treatment.The anthers of bzr-h plants were loculeless,but a similar phenotype was not observed in bri-t,suggesting that BZRs have a BR signaling-independent regulatory role in anther development.By real-time PCR and in situ hybridization,we found that the expression of SPOROCYTELESS(SPL),which encodes a transcription factor essential for anther locule development,was barely detectable in bzr-h,suggesting that BZRs regulate locule development by affecting SPL expression.Our findings reveal that BZRs are indispensable transcription factors required for both BR signaling and anther locule development,providing new insight into the molecular mechanisms underlying the microsporogenesis in Arabidopsis.

O型口蹄疫病毒衣壳蛋白VP1的可溶表达及抗原活性鉴定

口蹄疫(Foot-and-mouth Disease,FMD)是由口蹄疫病毒(Foot-and-mouth Disease Virus,FMDV)引起的急性、高度传染性疾病,一旦大规模爆发会给畜牧业造成巨大的经济损失。接种灭活病毒疫苗是目前防控口蹄疫的最有效手段,但传统灭活疫苗存在病毒逃逸、生产成本高等诸多局限。重组亚单位蛋白疫苗免疫原性好且安全性高,是发展新型口蹄疫疫苗的重要方向。口蹄疫病毒结构蛋白VP1因含主要抗原表位,而成为口蹄疫亚单位疫苗及诊断试剂的开发热点。与真核系统相比,原核表达系统生产周期短、易于放大生产、成本低廉,更适于动物疫苗的开发,但VP1采用原核系统表达会形成无活性的不溶包涵体。本工作中首次同时融合小分子泛素相关修饰物(Small Ubiquitin-related Modifier,SUMO)和RNA作用结构域(RNA-interacting Domain,RID)两种助溶标签来实现FMDV VP1(O型/MYA/98)在原核系统中的高效可溶表达。首先采用PCR(聚合酶链反应)重叠技术,以p ET-28a(+)为载体构建了RID-SUMO-VP1重组质粒,将重组质粒转化至E.coli BL21(DE3),在18℃下通过1 mmol/L IPTG(异丙基-β-D-硫代半乳糖苷)诱导4 h后,融合蛋白RID-SUMO-VP1高效表达,可溶表达比例达79%,而融合SUMO或RID单一标签的VP1仍主要表达为不溶的包涵体。然后采用硫酸铵两步沉淀法对工程菌的破碎上清进行纯化,得到纯度为93%的RID-SUMO-VP1,酶联免疫吸附测定(ELISA)实验表明其能够与O型FMDV阳性小鼠血清反应。研究结果表明,采用RID及SUMO双标签融合策略能极大提高VP1在原核系统中的可溶表达效率,且表达的VP1具备良好的抗原性,这为开发新型FMDV免疫诊断试剂和安全高效的亚单位疫苗奠定了良好基础。

rhIFN-κ包涵体的氧化复性与纯化

干扰素卡帕(Interferon-Kappa, IFN-κ)是一种具有抗病毒、抗肿瘤及免疫调节等重要功能的蛋白质,独特的分泌方式和生理功能使其在临床上具有良好的应用前景。通过大肠杆菌以包涵体形式表达的重组人干扰素卡帕(rhIFN-κ)需要经过体外折叠复性才能获得生物活性,由于IFN-κ含两对二硫键,因此复性时面临易生成沉淀和二硫键难以正确氧化等双重挑战。本研究采用强阴离子表面活性剂十二烷基硫酸钠(SDS)溶解包涵体,并在复性过程添加多元醇2-甲基-2,4-戊二醇(MPD)逐渐剥离与蛋白质紧密结合的SDS,实现rhIFN-κ的氧化复性。研究发现,rhIFN-κ复性后主要形成了二硫键不同氧化程度的三种结构,包括完全氧化的正确结构、部分氧化的中间体和完全未氧化的变性蛋白。在SDS/MPD复性体系中,rhIFN-κ完全氧化的复性收率与两者浓度及比例密切相关。SDS浓度过低或MPD浓度过高易导致蛋白质沉淀或聚集,SDS浓度过高或MPD浓度过低则会抑制二硫键的正确氧化。进一步对氧化还原体系及pH值进行优化,确定了最优的复性缓冲液:添加0.05wt%SDS, 1 mol/L MPD, 0.2 mmol/L氧化型谷胱甘肽(GSSG), 0.1 mmol/L还原型谷胱甘肽(GSH)的20 mmol/L Tris, pH=9.5。且在此条件下,蛋白质浓度提高至2.0 mg/mL时,rhIFN-κ复性收率基本不变。室温复性24 h,rhIFN-κ的复性收率达66%。利用制备反相高效液相色谱一步纯化,可有效去除杂质及复性中间体等错误结构,获得非还原电泳为单一条带的纯度90%的rhIFN-κ。结果表明,SDS/MPD体系能抑制包涵体复性时沉淀形成的同时还能有效提高二硫键的正确氧化,该结果可为rhIFN-κ的规模化生产奠定良好的基础。