Recent progress on two-dimensional ferroelectrics:Material systems and device applications

Ferroelectrics are a type of material with a polar structure and their polarization direction can be inverted reversibly by applying an electric field.They have attracted tremendous attention for their extensive applications in non-volatile memory,sensors and neuromorphic computing.However,conventional ferroelectric materials face insulating and interfacial issues in the commercialization process.In contrast,two-dimensional(2D)ferroelectric materials usually have excellent semiconductor performance,clean van der Waals interfaces and robust ferroelectric order in atom-thick layers,and hold greater promise for constructing multifunctional ferroelectric optoelectronic devices and nondestructive ultra-high-density memory.Recently,2D ferroelectrics have obtained impressive breakthroughs,showing overwhelming superiority.Herein,firstly,the progress of experimental research on 2D ferroelectric materials is reviewed.Then,the preparation of 2D ferroelectric devices and their applications are discussed.Finally,the future development trend of 2D ferroelectrics is looked at.

A Reverse Numerical Approach to Determine Elastic-plastic Properties of Multi-layer Material Systems with Flat Cylindrical Indenters

In the present study, the indentation testing with a flat cylindrical indenter on typical multi-layer material systems was simulated successfully by finite element method. The emphasis was put on the methods of extracting the yield stresses and strain-hardening modulus of upper and middle-layers of three-layer material systems from the indentation testing. The slope of the indentation depth to the applied indentation stress curve was found to have a turning point, which can be used to determine the yield stress of the upper-layer. Then, a different method was also presented to determine the yield stress of the middle-layer. This method was based on a set of assumed applied indentation stresses which were to be intersected by the experimental results in order to meet the requirement of having the experimental indentation depth. At last, a reverse numerical algorithm was explored to determine the yield stresses of upper and middle-layers simultaneously by using the indentation testing with two different size indenters. This method assumed two ranges of yield stresses to simulate the indentation behavior. The experimental depth behavior was used to intersect the simulated indentation behavior. And the intersection corresponded to the values of yield stresses of upper and middle-layers. This method was also used further to determine the strain-hardening modulus of upper and middle-layers simultaneously.

Data Centric Design:A New Approach to Design of Microstructural Material Systems

Building processing,structure,and property(PSP)relations for computational materials design is at the heart of the Materials Genome Initiative in the era of high-throughput computational materials science.Recent technological advancements in data acquisition and storage,microstructure characterization and reconstruction(MCR),machine learning(ML),materials modeling and simulation,data processing,manufacturing,and experimentation have significantly advanced researchers’abilities in building PSP relations and inverse material design.In this article,we examine these advancements from the perspective of design research.In particular,we introduce a data-centric approach whose fundamental aspects fall into three categories:design representation,design evaluation,and design synthesis.Developments in each of these aspects are guided by and benefit from domain knowledge.Hence,for each aspect,we present a wide range of computational methods whose integration realizes data-centric materials discovery and design.

Enhanced entropy generation and heat transfer characteristics of magnetic nano-encapsulated phase change materials in latent heat thermal energy storage systems

The objective of the current study is to investigate the importance of entropy generation and thermal radiation on the patterns of velocity,isentropic lines,and temperature contours within a thermal energy storage device filled with magnetic nanoencapsulated phase change materials(NEPCMs).The versatile finite element method(FEM)is implemented to numerically solve the governing equations.The effects of various parameters,including the viscosity parameter,ranging from 1 to 3,the thermal conductivity parameter,ranging from 1 to 3,the Rayleigh parameter,ranging from 102 to 3×10^(2),the radiation number,ranging from 0.1 to 0.5,the fusion temperature,ranging from 1.0 to 1.2,the volume fraction of NEPCMs,ranging from 2%to 6%,the Stefan number,ranging from 1 to 5,the magnetic number,ranging from 0.1 to 0.5,and the irreversibility parameter,ranging from 0.1 to 0.5,are examined in detail on the temperature contours,isentropic lines,heat capacity ratio,and velocity fields.Furthermore,the heat transfer rates at both the cold and hot walls are analyzed,and the findings are presented graphically.The results indicate that the time taken by the NEPCMs to transition from solid to liquid is prolonged inside the chamber region as the fusion temperatureθf increases.Additionally,the contours of the heat capacity ratio Cr decrease with the increase in the Stefan number Ste.

Porous framework materials for energy&environment relevant applications:A systematic review

Carbon peaking and carbon neutralization trigger a technical revolution in energy&environment related fields.Development of new technologies for green energy production and storage,industrial energy saving and efficiency reinforcement,carbon capture,and pollutant gas treatment is in highly imperious demand.The emerging porous framework materials such as metal–organic frameworks(MOFs),covalent organic frameworks(COFs)and hydrogen-bonded organic frameworks(HOFs),owing to the permanent porosity,tremendous specific surface area,designable structure and customizable functionality,have shown great potential in major energy-consuming industrial processes,including sustainable energy gas catalytic conversion,energy-efficient industrial gas separation and storage.Herein,this manuscript presents a systematic review of porous framework materials for global and comprehensive energy&environment related applications,from a macroscopic and application perspective.

Nondestructive and active interrogation system for special nuclear material:proof of principle and initial results

Herein,we employ the threshold energy neutron analysis(TENA)technique to introduce the world's first active interrogation system to detect special nuclear materials(SNMs),including U-235 and Pu-239.The system utilizes a DD neutron generator based on inertial electrostatic confinement(IEC)to interrogate suspicious objects.To detect secondary neutrons produced during fission reactions induced in SNMs,a tensioned metastable fluid detector(TMFD)is employed.The current status of the system's development is reported in this paper,accompanied by the results from experiments conducted to detect 10 g of highly enriched uranium(HEU).Notably,the experimental findings demonstrate a distinct difference in the count rates of measurements with and without HEU.This difference in count rates surpasses two times the standard deviation,indicating a confidence level of more than 96% for identifying the presence of HEU.The paper presents and extensively discusses the proof-of-principle experimental results,along with the system's planned trajectory.

Sound Transmission Loss Analysis of a Double Plate-Acoustic Cavity Coupling System with In-Plane Functionally Graded Materials

In this paper, the isogeometric analysis (IGA) is employed to develop an acoustic radiation model for a double plate-acoustic cavity coupling system, with a focus on analyzing the sound transmission loss (STL). The functionally graded (FG) plate exhibits a different material properties in-plane, and the power-law rule is adopted as the governing principle for material mixing. To validate the harmonic response and demonstrate the accuracy and convergence of the isogeometric modeling, ANASYS is utilized to compare with numerical examples. A plane wave serves as the acoustic excitation, and the Rayleigh integral is applied to discretize the radiated plate. The STL results are compared with the literature, confirming the reliability of the coupling system. Finally, the investigation is conducted to study impact of cavity depth and power-law parameter on the STL.

Research on Performance Optimization of Liquid Cooling and Composite Phase Change Material Coupling Cooling Thermal Management System for Vehicle Power Battery

The serpentine tube liquid cooling and composite PCM coupled cooling thermal management system is designed for 18650 cylindrical power batteries,with the maximum temperature and temperature difference of the power pack within the optimal temperature operating range as the target.The initial analysis of the battery pack at a 5C discharge rate,the influence of the single cell to cooling tube distance,the number of cooling tubes,inlet coolant temperature,the coolant flow rate,and other factors on the heat dissipation performance of the battery pack,initially determined a reasonable value for each design parameter.A control strategy is used to regulate the inlet flow rate and coolant temperature of the liquid cooling system in order to make full use of the latent heat of the composite PCM and reduce the pump’s energy consumption.The simulation results show that the maximum battery pack temperature of 309.8 K and the temperature difference of 4.6 K between individual cells with the control strategy are in the optimal temperature operating range of the power battery,and the utilization rate of the composite PCM is up to 90%.

Materials,preparation,performances and mechanism of polyurethane modified asphalt and its mixture:A systematic review

With the rapid development of asphalt pavement technology,it has attracted considerable attention to improving the durability of asphalt pavement.An effective action is to use modified asphalt with high performance and durability.Polyurethane(PU)has been used in asphalt pavement engineering to enhance the durability and service life of asphalt pavement because of its excellent high-temperature performance,toughness,wear resistance,aging resistance and oil resistance.However,PU modified asphalt technology is still in the exploratory stage.The preparation,modification mechanism and working performances of PU modified asphalt need to be further clarified.Therefore,this paper summarized the research progress of PU modified asphalt and its mixture.The composition of PU modified asphalt was introduced.The addition methods of PU materials and preparation process parameters of the PU modified asphalt were determined.The modification mechanism of PU on asphalt was discussed.The effects of polyurethane on asphalt were analyzed and the road performances of its mixture were evaluated.Finally,the development tendency towards PU modified asphalt and its mixture were forecasted.

Heat transfer enhanced inorganic phase change material compositing carbon nanotubes for battery thermal management and thermal runaway propagation mitigation

Developing technologies that can be applied simultaneously in battery thermal management(BTM)and thermal runaway(TR)mitigation is significant to improving the safety of lithium-ion battery systems.Inorganic phase change material(PCM)with nonflammability has the potential to achieve this dual function.This study proposed an encapsulated inorganic phase change material(EPCM)with a heat transfer enhancement for battery systems,where Na_(2)HPO_(4)·12H_(2)O was used as the core PCM encapsulated by silica and the additive of carbon nanotube(CNT)was applied to enhance the thermal conductivity.The microstructure and thermal properties of the EPCM/CNT were analyzed by a series of characterization tests.Two different incorporating methods of CNT were compared and the proper CNT adding amount was also studied.After preparation,the battery thermal management performance and TR propagation mitigation effects of EPCM/CNT were further investigated on the battery modules.The experimental results of thermal management tests showed that EPCM/CNT not only slowed down the temperature rising of the module but also improved the temperature uniformity during normal operation.The peak battery temperature decreased from 76℃to 61.2℃at 2 C discharge rate and the temperature difference was controlled below 3℃.Moreover,the results of TR propagation tests demonstrated that nonflammable EPCM/CNT with good heat absorption could work as a TR barrier,which exhibited effective mitigation on TR and TR propagation.The trigger time of three cells was successfully delayed by 129,474 and 551 s,respectively and the propagation intervals were greatly extended as well.

Deformable Catalytic Material Derived from Mechanical Flexibility for Hydrogen Evolution Reaction

Deformable catalytic material with excellent flexible structure is a new type of catalyst that has been applied in various chemical reactions,especially electrocatalytic hydrogen evolution reaction(HER).In recent years,deformable catalysts for HER have made great progress and would become a research hotspot.The catalytic activities of deformable catalysts could be adjustable by the strain engineering and surface reconfiguration.The surface curvature of flexible catalytic materials is closely related to the electrocatalytic HER properties.Here,firstly,we systematically summarized self-adaptive catalytic performance of deformable catalysts and various micro–nanostructures evolution in catalytic HER process.Secondly,a series of strategies to design highly active catalysts based on the mechanical flexibility of lowdimensional nanomaterials were summarized.Last but not least,we presented the challenges and prospects of the study of flexible and deformable micro–nanostructures of electrocatalysts,which would further deepen the understanding of catalytic mechanisms of deformable HER catalyst.

Valorization of Camellia oleifera oil processing byproducts to value-added chemicals and biobased materials: A critical review

The C.oleifera oil processing industry generates large amounts of solid wastes,including C.oleifera shell(COS)and C.oleifera cake(COC).Distinct from generally acknowledged lignocellulosic biomass(corn stover,bamboo,birch,etc.),Camellia wastes contain diverse bioactive substances in addition to the abundant lignocellulosic components,and thus,the biorefinery utilization of C.oleifera processing byproducts involves complicated processing technologies.This reviewfirst summarizes various technologies for extracting and converting the main components in C.oleifera oil processing byproducts into value-added chemicals and biobased materials,as well as their potential applications.Microwave,ultrasound,and Soxhlet extractions are compared for the extraction of functional bioactive components(tannin,flavonoid,saponin,etc.),while solvothermal conversion and pyrolysis are discussed for the conversion of lignocellulosic components into value-added chemicals.The application areas of these chemicals according to their properties are introduced in detail,including utilizing antioxidant and anti-in-flammatory properties of the bioactive substances for the specific application,as well as drop-in chemicals for the substitution of unrenewable fossil fuel-derived products.In addition to chemical production,biochar fabricated from COS and its applications in thefields of adsorption,supercapacitor,soil remediation and wood composites are comprehensively reviewed and discussed.Finally,based on the compositions and structural characteristics of C.oleifera byproducts,the development of full-component valorization strategies and the expansion of the appli-cationfields are proposed.

Multi-Material Topology Optimization for Spatial-Varying Porous Structures

This paper aims to propose a topology optimization method on generating porous structures comprising multiple materials.The mathematical optimization formulation is established under the constraints of individual volume fraction of constituent phase or total mass,as well as the local volume fraction of all phases.The original optimization problem with numerous constraints is converted into a box-constrained optimization problem by incorporating all constraints to the augmented Lagrangian function,avoiding the parameter dependence in the conventional aggregation process.Furthermore,the local volume percentage can be precisely satisfied.The effects including the globalmass bound,the influence radius and local volume percentage on final designs are exploited through numerical examples.The numerical results also reveal that porous structures keep a balance between the bulk design and periodic design in terms of the resulting compliance.All results,including those for irregular structures andmultiple volume fraction constraints,demonstrate that the proposedmethod can provide an efficient solution for multiple material infill structures.

Radiofrequency sensing systems based on emerging two-dimensional materials and devices

As one of the most promising platforms for wireless communication,radiofrequency(RF)electronics have been widely advocated for the development of sensing systems.In particular,monolayer and few-layer two-dimensional(2D)materials exhibiting extraordinary electrical properties not only can be integrated to improve the performance of RF circuits,but also to display exceptional sensing capabilities.This review provides an in-depth perspective of current trends and challenges in the application of 2D materials for RF biochemical sensing,including:(i)theoretical bases to achieve different sensing schemes;(ii)unique properties of 2D materials for reasoning their applications in RF sensing;(iii)developments in 2D RF sensors to facilitate the practice of biochemical sensors with ever-demanding sensitivities,as well as their potential uses in meeting the requirements and challenges of biochemical sensors in the Internet-of-Things era.

Numerical Investigation of the Thermal Behavior of a System with a Partition Wall Incorporating a Phase Change Material

The work deals with the thermal behavior of a conventional partition wall incorporating a phase change material(PCM).The wall separates two environments with different thermal properties.The first one is conditioned,while the adjacent space is characterized by a temperature that changes sinusoidally in time.The effect of the PCM is assessed through a comparative analysis of the cases with and without PCM.The performances are evaluated in terms of dimensionless energy stored within the wall,comfort temperature and variations of these quantities as a function of the amount of PCM and its emplacement.

Certification of a Multicomponent Reference Material from Natural Gas Mixture by Gravimetry and Dual GC-FID/TCD System

Natural gas (NG) is one of the most important sources of energy for industrial and domestic consumption in the present era because it is cheap and free from sulfur impurities. Therefore, accurate and precise measurement of its composition is of fundamental importance for trade reasons. To improve the quality of NG gas measurements, certified reference materials (CRMs) should be used for calibration of measuring equipment in order to ensure the traceability of the measurement results to the SI units. For the traceability purpose, a multicomponent natural gas mixture was prepared gravimetrically as a reference material according to ISO 6142 from pure helium, hydrogen, n-pentane, i-pentane, n-butane, i-butane, propane, ethane, hexane, methane and nitrogen. The preparation was done in two dilution steps in 5 L aluminum cylinders. The calculated mole fractions and associated uncertainties of natural gas components were verified by a dual GC-FID/TCD system in accordance with ISO 6143 calibrated by a series of primary gas mixtures (CRMs) produced by an NMI. The results obtained by gravimetry and by GC measurements have been checked for compatibility as required by ISO 6142 and were found in very good agreement. Details of the preparation and calculation of the mole fractions and uncertainties of all gas components are explained in this article.

人工智能背景下Materials Project数据库在计算材料学课程教学中的应用

该文探讨了在人工智能背景下,Materials Project数据库在计算材料学课程教学中的应用和影响。Materials Project数据库是一个集成了AI和大数据技术的开放获取的材料库,能为学生提供海量的材料晶体结构和物性数据,使教学内容更为丰富,让学生能通过亲自操作获取和分析数据,深入理解微观结构与物性之间的关系。这一新兴的教学模式不仅提升了学生的科研能力和创新思维能力,还有助于培养具备计算材料专业知识和多学科交叉的复合型人才。总体来说,人工智能时代下,大数据的引入为计算材料学课程带来新的活力,并对未来教育改革和实践产生了积极影响。

A thermodynamics-based three-scale constitutive model for partially saturated granular materials

A three-scale constitutive model for unsaturated granular materials based on thermodynamic theory is presented.The three-scale yield locus,derived from the explicit yield criterion for solid matrix,is developed from a series of discrete interparticle contact planes.The three-scale yield locus is sensitive to porosity changes;therefore,it is reinterpreted as a corresponding constitutive model without phenomenological parameters.Furthermore,a water retention curve is proposed based on special pore morphology and experimental observations.The features of the partially saturated granular materials are well captured by the model.Under wetting and isotropic compression,volumetric compaction occurs,and the degree of saturation increases.Moreover,the higher the matric suction,the greater the strength,and the smaller the volumetric compaction.Compared with the phenomenological Barcelona basic model,the proposed three-scale constitutive model has fewer parameters;virtually all parameters have clear physical meanings.

Actively tuning anisotropic light-matter interaction in biaxial hyperbolic materialα-MoO_(3) using phase change material VO_(2) and graphene

Anisotropic hyperbolic phonon polaritons(PhPs)in natural biaxial hyperbolic materialα-MoO_(3) has opened up new avenues for mid-infrared nanophotonics,while active tunability ofα-MoO_(3) PhPs is still an urgent problem necessarily to be solved.In this study,we present a theoretical demonstration of actively tuningα-MoO_(3) PhPs using phase change material VO_(2) and graphene.It is observed thatα-MoO_(3) PhPs are greatly dependent on the propagation plane angle of PhPs.The insulator-to-metal phase transition of VO_(2) has a significant effect on the hybridization PhPs of theα-MoO_(3)/VO_(2) structure and allows to obtain actively tunableα-MoO_(3) PhPs,which is especially obvious when the propagation plane angle of PhPs is 900.Moreover,when graphene surface plasmon sources are placed at the top or bottom ofα-MoO_(3) inα-MoO_(3)/VO_(2)structure,tunable coupled hyperbolic plasmon-phonon polaritons inside its Reststrahlen bands(RB s)and surface plasmonphonon polaritons outside its RBs can be achieved.In addition,the above-mentionedα-MoO_(3)-based structures also lead to actively tunable anisotropic spontaneous emission(SE)enhancement.This study may be beneficial for realization of active tunability of both PhPs and SE ofα-MoO_(3),and facilitate a deeper understanding of the mechanisms of anisotropic light-matter interaction inα-MoO_(3) using functional materials.

Application of deep learning for informatics aided design of electrode materials in metal-ion batteries

To develop emerging electrode materials and improve the performances of batteries,the machine learning techniques can provide insights to discover,design and develop battery new materials in high-throughput way.In this paper,two deep learning models are developed and trained with two feature groups extracted from the Materials Project datasets to predict the battery electrochemical performances including average voltage,specific capacity and specific energy.The deep learning models are trained with the multilayer perceptron as the core.The Bayesian optimization and Monte Carlo methods are applied to improve the prediction accuracy of models.Based on 10 types of ion batteries,the correlation coefficients are maintained above 0.9 compared to DFT calculation results and the mean absolute error of the prediction results for voltages of two models can reach 0.41 V and 0.20 V,respectively.The electrochemical performance prediction times for the two trained models on thousands of batteries are only 72.9 ms and 75.7 ms.Besides,the two deep learning models are applied to approach the screening of emerging electrode materials for sodium-ion and potassium-ion batteries.This work can contribute to a high-throughput computational method to accelerate the rational and fast materials discovery and design.