Large Room-Temperature Magnetoresistance in van der Waals Ferromagnet/Semiconductor Junctions

A magnetic tunnel junction(MTJ)is the core component in memory technologies,such as the magnetic random-access memory,magnetic sensors and programmable logic devices.In particular,MTJs based on twodimensional van der Waals(vd W)heterostructures offer unprecedented opportunities for low power consumption and miniaturization of spintronic devices.However,their operation at room temperature remains a challenge.Here,we report a large tunnel magnetoresistance(TMR)of up to 85%at room temperature(T=300 K)in vdW MTJs based on a thin(<10 nm)semiconductor spacer WSe_(2)layer embedded between two Fe_(3)GaTe_(2e)lectrodes with intrinsic above-room-temperature ferromagnetism.The TMR in the MTJ increases with decreasing temperature up to 164%at T=10 K.The demonstration of TMR in ultra-thin MTJs at room temperature opens a realistic and promising route for next-generation spintronic applications beyond the current state of the art.

Renewable biomass reinvigorates sustainable water-energy nexus

The water-energy nexus has garnered worldwide interest.Current dual-functional research aimed at coproducing freshwater and electricity faces significant challenges,including sub-optimal capacities("1+1<2"),poor inter-functional coordination,high carbon footprints,and large costs.Mainstream water-toelectricity conversions are often compromised owing to functionality separation and erratic gradients.Herein,we present a sustainable strategy based on renewable biomass that addresses these issues by jointly achieving competitive solar-evaporative desalination and robust clean electricity generation.Using hydrothermally activated basswood,our solar desalination exceeded the 100% efficiency bottleneck even under reduced solar illumination.Through simple size-tuning,we achieved a high evaporation rate of 3.56 kg h^(-1)m^(-2)and an efficiency of 149.1%,representing 128%-251% of recent values without sophisticated surface engineering.By incorporating an electron-ion nexus with interfacial Faradaic electron circulation and co-ion-predominated micro-tunnel hydrodynamic flow,we leveraged free energy from evaporation to generate long-term electricity(0.38 W m^(-3)for over 14 d),approximately 322% of peer performance levels.This inter-functional nexus strengthened dual functionalities and validated general engineering practices.Our presented strategy holds significant promise for global human–society–environment sustainability.

Generative artificial intelligence and its applications in materials science:Current situation and future perspectives

Generative Artificial Intelligence(GAI)is attracting the increasing attention of materials community for its excellent capability of generating required contents.With the introduction of Prompt paradigm and reinforcement learning from human feedback(RLHF),GAI shifts from the task-specific to general pattern gradually,enabling to tackle multiple complicated tasks involved in resolving the structure-activity relationships.Here,we review the development status of GAI comprehensively and analyze pros and cons of various generative models in the view of methodology.The applications of task-specific generative models involving materials inverse design and data augmentation are also dissected.Taking ChatGPT as an example,we explore the potential applications of general GAI in generating multiple materials content,solving differential equation as well as querying materials FAQs.Furthermore,we summarize six challenges encountered for the use of GAI in materials science and provide the corresponding solutions.This work paves the way for providing effective and explainable materials data generation and analysis approaches to accelerate the materials research and development.

Advances in the study of directed evolution for cellulases

If cellulose can be effectively hydrolyzed intoglucose by cellulase,the production costs of hydrogen,ethanol or other chemicals from cellulosic materials will begreatly decreased,and economically viable production ofbiohydrogen and bioethanol will become feasible.Celluloseis degraded into glucoses by multi-component enzymesystems.Nowadays cellulases are widely used in brewing,food,bioenergy,fodder,textiles,paper,pharmaceuticals,environmental protection and other industries.However,existing cellulases have several problems that limit theirwider applications,including the low turnover number forsolid cellulosic materials,and low stability in adapting tovarious application conditions.For example,high temperature,low pH,and so on.Application of directedevolution technology may be one of the most effectiveways for improving the characteristics of cellulases.Thispaper presents a brief review of the cellulases hydrolysismechanism by cellulase,advances in cellulases(endoglucanaseandβ-glucosidase)improvement by directedevolution for several characteristics(for instance,thermalstability,pH adaptability and enzyme activity),limitationsof directed evolution for cellulases,and the outlook fordirected evolution for cellulase.

基于SSAE-FCM的燃料乙醇分批发酵关键时间节点自动识别

生物工程日趋复杂化和智能化,其生产过程也从实验室向工业化规模快速发展,给生物工程过程控制优化带来了新的挑战。本工作以燃料乙醇分批发酵这一复杂过程为研究对象,提出了一种基于堆叠稀疏自编码器(SSAE)和模糊C均值聚类(FCM)相结合的燃料乙醇分批发酵关键时间节点自动识别方法。通过SSAE由低到高逐层提取发酵过程原始数据中更能反映数据本质属性的各级高层特征,并将其作为FCM算法的输入数据,最终构建燃料乙醇分批发酵关键时间节点自动识别模型。为评估模型性能,以国投生物燃料乙醇发酵过程为应用对象,结果表明,本工作所提出的方法具有可操作性。同时,与基于动力学模型和过程多参数相关性分析方法对比,本工作所提方法具有更优的识别性能。