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.

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.

Emerging two-dimensional Mo-based materials for rechargeable metal-ion batteries:Advances and perspectives

With the rapid development of rechargeable metal-ion batteries(MIBs)with safety,stability and high energy density,significant efforts have been devoted to exploring high-performance electrode materials.In recent years,two-dimensional(2D)molybdenum-based(Mo-based)materials have drawn considerable attention due to their exceptional characteristics,including low cost,unique crystal structure,high theoretical capacity and controllable chemical compositions.However,like other transition metal compounds,Mo-based materials are facing thorny challenges to overcome,such as slow electron/ion transfer kinetics and substantial volume changes during the charge and discharge processes.In this review,we summarize the recent progress in developing emerging 2D Mo-based electrode materials for MIBs,encompassing oxides,sulfides,selenides,carbides.After introducing the crystal structure and common synthesis methods,this review sheds light on the charge storage mechanism of several 2D Mo-based materials by various advanced characterization techniques.The latest achievements in utilizing 2D Mo-based materials as electrode materials for various MIBs(including lithium-ion batteries(LIBs),sodium-ion batteries(SIBs)and zinc-ion batteries(ZIBs))are discussed in detail.Afterwards,the modulation strategies for enhancing the electrochemical performance of 2D Mo-based materials are highlighted,focusing on heteroatom doping,vacancies creation,composite coupling engineering and nanostructure design.Finally,we present the existing challenges and future research directions for 2D Mo-based materials to realize high-performance energy storage systems.

Patterning single-layer materials by electrical breakdown using atomic force microscopy

The development of nanoelectronics and nanotechnologies has been boosted significantly by the emergence of 2D materials because of their atomic thickness and peculiar properties,and developing a universal,precise patterning technology for single-layer 2D materials is critical for assembling nanodevices.Demonstrated here is a nanomachining technique using electrical breakdown by an AFM tip to fabricate nanopores,nanostrips,and other nanostructures on demand.This can be achieved by voltage scanning or applying a constant voltage while moving the tip.By measuring the electrical current,the formation process on single-layer materials was shown quantitatively.The present results provide evidence of successful pattern fabrication on single-layer MoS2,boron nitride,and graphene,although further confirmation is still needed.The proposed method holds promise as a general nanomachining technology for the future.

Exploring the potential of olivine-containing copper-nickel slag for carbon dioxide mineralization in cementitious materials

Water-quenched copper-nickel metallurgical slag enriched with olivine minerals exhibits promising potential for the production of CO_(2)-mineralized cementitious materials.In this work,copper-nickel slag-based cementitious material(CNCM)was synthesized by using different chemical activation methods to enhance its hydration reactivity and CO_(2) mineralization capacity.Different water curing ages and carbonation conditions were explored related to their carbonation and mechanical properties development.Meanwhile,thermogravimetry differential scanning calorimetry and X-ray diffraction methods were applied to evaluate the CO_(2) adsorption amount and carbonation products of CNCM.Microstructure development of carbonated CNCM blocks was examined by backscattered electron imaging(BSE)with energy-dispersive X-ray spectrometry.Results showed that among the studied samples,the CNCM sample that was subjected to water curing for 3 d exhibited the highest CO_(2) sequestration amount of 8.51wt%at 80℃and 72 h while presenting the compressive strength of 39.07 MPa.This result indicated that 1 t of this CNCM can sequester 85.1 kg of CO_(2) and exhibit high compressive strength.Although the addition of citric acid did not improve strength development,it was beneficial to increase the CO_(2) diffusion and adsorption amount under the same carbonation conditions from BSE results.This work provides guidance for synthesizing CO_(2)-mineralized cementitious materials using large amounts of metallurgical slags containing olivine minerals.

MXene-based hybrid materials for electrochemical and photoelectrochemical H_(2) generation

The conversion of solar energy to produce clean hydrogen fuel through water splitting is an emerging strategy for efficiently storing solar energy in the form of solar fuel.This aligns with the increasing global demand for the development of an ideal energy alternative to fossil fuels that does not emit greenhouse gases.Electrochemical(EC) and photoelectrochemical(PEC) water splitting technologies have garnered significant attention worldwide for advanced hydrogen solar fuel production in recent decades.To achieve sustainable green H_(2) production,it is essential to create efficient catalyst materials that are low-cost and can replace expensive noble metal-based catalysts.These characteristics make them an ideal catalyst material for the process.Two-dimensional MXenes with M_(n+1)X_(n) structure have been identified as a promising option for EC and PEC water splitting due to their superior hydrophilicity,metal-like conductivity,large surface area,and adjustable surface chemistry.Here,we present a summary of recent advancements in the synthesis and performance enhancement methods for MXene hybrid materials in hydrogen production through EC and PEC water splitting.Furthermore,we examine the challenges and insights associated with the rational design of MXene-based hybrid materials to facilitate efficient water splitting for sustainable solar fuel production.

Experimental study on the influences of cutter geometry and material on scraper wear during shield TBM tunnelling in abrasive sandy ground

When shield TBM tunnelling in abrasive sandy ground,the rational design of cutter parameters is critical to reduce tool wear and improve tunnelling efficiency.However,the influence mechanism of cutter parameters on scraper wear remains unclear due to the lack of a reliable test method.Geometry and material optimisation are often based on subjective experience,which is unfavourable for improving scraper geological adaptability.In the present study,the newly developed WHU-SAT soil abrasion test was used to evaluate the variation in scraper wear with cutter geometry,material and hardness.The influence mechanism of cutter parameters on scraper wear has been revealed according to the scratch characteristics of the scraper surface.Cutter geometry and material parameters have been optimised to reduce scraper wear.The results indicate that the variation in scraper wear with cutter geometry is related to the cutting resistance,frictional resistance and stress distribution.An appropriate increase in the front angle(or back angle)reduces the cutting resistance(or frictional resistance),while an excessive increase in the front angle(or back angle)reduces the edge angle and causes stress concentration.The optimal front angle,back angle and edge angle for quartz sand samples areα=25°,β=10°andγ=55°,respectively.The wear resistance of the modelled scrapers made of different metal materials is related to the chemical elements and microstructure.The wear resistances of the modelled scrapers made of 45#,06Cr19Ni10,42CrMo4 and 40CrNiMoA are 0.569,0.661,0.691 and 0.728 times those made of WC-Co,respectively.When the alloy hardness is less than 47 HRC(or greater than 58 HRC),scraper wear decreases slowly with increasing alloy hardness as the scratch depth of the particle asperity on the metal surface stabilizes at a high(or low)level.However,when the alloy hardness is between 47 HRC and 58 HRC,scraper wear decreases rapidly with increasing alloy hardness as the scratch depth transitions from high to low levels.The sensitive hardness interval and recommended hardness interval for quartz sand are[47,58]and[58,62],respectively.The present study provides a reference for optimising scraper parameters and improving cutterhead adaptability in abrasive sandy ground tunnelling.

Enhanced structural damage behavior of liquid-filled tank by reactive material projectile impact

A series of ballistic experiments were performed to investigate the damage behavior of high velocity reactive material projectiles(RMPs) impacting liquid-filled tanks,and the corresponding hydrodynamic ram(HRAM) was studied in detail.PTFE/Al/W RMPs with steel-like and aluminum-like densities were prepared by a pressing/sintering process.The projectiles impacted a liquid-filled steel tank with front aluminum panel at approximately 1250 m/s.The corresponding cavity evolution characteristics and HRAM pressure were recorded by high-speed camera and pressure acquisition system,and further compared to those of steel and aluminum projectiles.Significantly different from the conical cavity formed by the inert metal projectile,the cavity formed by the RMP appeared as an ellipsoid with a conical front.The RMPs were demonstrated to enhance the radial growth velocity of cavity,the global HRAM pressure amplitude and the front panel damage,indicating the enhanced HRAM and structural damage behavior.Furthermore,combining the impact-induced fragmentation and deflagration characteristics,the cavity evolution of RMPs under the combined effect of kinetic energy impact and chemical energy release was analyzed.The mechanism of enhanced HRAM pressure induced by the RMPs was further revealed based on the theoretical model of the initial impact wave and the impulse analysis.Finally,the linear correlation between the deformation-thickness ratio and the non-dimensional impulse for the front panel was obtained and analyzed.It was determined that the enhanced near-field impulse induced by the RMPs was the dominant reason for the enhanced structural damage behavior.

Friction Characteristics Between Marine Clay and Construction Materials

Structure-soil interface friction characteristics is of importance to investigate the interaction between engineering structures and soils,especially for offshore structures.The interface friction behavior between marine clay and structural materials with different roughness was studied in this paper by using 3D optical scanning tests,a modified direct shear device and numerical simulation.Relationships between the surface roughness of structures,water content and interface friction angle were presented by model tests.The increase of water contents decreased the interface friction angles.For interfaces with different roughness,the interface friction angles will be smaller than that of the soil when the water content exceeds a certain value.The roughness of the interface and the water content of the soil are mutually coupled to influence the coefficient of friction(COF).This paper proposed a Finite Element Method(FEM)to simulate the interface direct shear tests of structures with different roughness.The surface models with different roughness are established based on the structure data obtained by 3D scanning.The Coupled Eulerian-Lagrangian(CEL)approach was employed to analyse soils sheared by irregular surfaces.The interface behavior for interfaces with different roughness under cyclic shear stresses was analyzed by FEM.

Databases of 2D material-substrate interfaces and 2D charged building blocks

Discovery of materials using“bottom-up”or“top-down”approach is of great interest in materials science.Layered materials consisting of two-dimensional(2D)building blocks provide a good platform to explore new materials in this respect.In van der Waals(vdW)layered materials,these building blocks are charge neutral and can be isolated from their bulk phase(top-down),but usually grow on substrate.In ionic layered materials,they are charged and usually cannot exist independently but can serve as motifs to construct new materials(bottom-up).In this paper,we introduce our recently constructed databases for 2D material-substrate interface(2DMSI),and 2D charged building blocks.For 2DMSI database,we systematically build a workflow to predict appropriate substrates and their geometries at substrates,and construct the 2DMSI database.For the 2D charged building block database,1208 entries from bulk material database are identified.Information of crystal structure,valence state,source,dimension and so on is provided for each entry with a json format.We also show its application in designing and searching for new functional layered materials.The 2DMSI database,building block database,and designed layered materials are available in Science Data Bank at https://doi.org/10.57760/sciencedb.j00113.00188.

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.

Fracture sealing performance of granular lost circulation materials at elevated temperature:A theoretical and coupled CFD-DEM simulation study

Lost circulation is a common downhole problem of drilling in geothermal and high-temperature,high-pressure(HTHP)formations.Lost circulation material(LCM)is a regular preventive and remedial measure for lost circulation.However,conventional LCMs seem ineffective in high-temperature formations.This may be due to the changes in the mechanical properties of LCMs and their sealing performance under high-temperature conditions.To understand how high temperature affects the fracture sealing performance of LCMs,we developed a coupled computational fluid dynamics-discrete element method(CFD-DEM)model to simulate the behavior of granular LCMs in fractures.We summarized the literature on the effects of high temperature on the mechanical properties of LCMs and the rheological properties of drilling fluid.We conducted sensitivity analyses to investigate how changing LCM slurry properties affected the fracture sealing efficiency at increasing temperatures.The results show that high temperature reduces the size,strength,and friction coefficient of LCMs as well as the drilling fluid viscosity.Smaller,softer,and less frictional LCM particles have lower bridging probability and slower bridging initiation.Smaller particles tend to form dual-particle bridges rather than single-particle bridges.These result in a deeper,tighter,but unstable sealing zone.Reduced drilling fluid viscosity leads to faster and shallower sealing zones.

Advancements in machine learning for material design and process optimization in the field of additive manufacturing

Additive manufacturing technology is highly regarded due to its advantages,such as high precision and the ability to address complex geometric challenges.However,the development of additive manufacturing process is constrained by issues like unclear fundamental principles,complex experimental cycles,and high costs.Machine learning,as a novel artificial intelligence technology,has the potential to deeply engage in the development of additive manufacturing process,assisting engineers in learning and developing new techniques.This paper provides a comprehensive overview of the research and applications of machine learning in the field of additive manufacturing,particularly in model design and process development.Firstly,it introduces the background and significance of machine learning-assisted design in additive manufacturing process.It then further delves into the application of machine learning in additive manufacturing,focusing on model design and process guidance.Finally,it concludes by summarizing and forecasting the development trends of machine learning technology in the field of additive manufacturing.

Existence and numerical approximation of a solution to frictional contact problem for electro-elastic materials

In this paper,a frictional contact problem between an electro-elastic body and an electrically conductive foundation is studied.The contact is modeled by normal compliance with finite penetration and a version of Coulomb’s law of dry friction in which the coefficient of friction depends on the slip.In addition,the effects of the electrical conductivity of the foundation are taken into account.This model leads to a coupled system of the quasi-variational inequality of the elliptic type for the displacement and the nonlinear variational equation for the electric potential.The existence of a weak solution is proved by using an abstract result for elliptic variational inequalities and a fixed point argument.Then,a finite element approximation of the problem is presented.Under some regularity conditions,an optimal order error estimate of the approximate solution is derived.Finally,a successive iteration technique is used to solve the problem numerically and a convergence result is established.

Al/Hf ratio-dependent mechanisms of microstructure and mechanical property of nearly fully dense Al—Hf reactive material

This study proposed three types of Al—Hf reactive materials with particle size ratios(a),which were almost completely dense(porosity of<5.40%)owing to their preparation using hot-pressing technology.Microstructure characteristics and phase composition were analyzed,and the influence of particle size ratios on dynamic mechanical behavior and damage mechanism were investigated.The prepared sample with a=0.1 exhibited continuous wrapping of the Hf phase by the Al phase.Hf—Hf contact(continuous Hf phase)within the sample gradually increased with increasing a,and a small amount of fine Hf appeared for the sample with a=1.The reactive materials exhibited clear strain-rate sensitivity,with flow stressσ0.05and failure strainεfincreasing approximately linearly with increasing strain rate.ε.It is found that the plastic deformation of the material increased with increasing strain rate.As a increased from 0.1 to 1,the flow stress gradually increased.Impact failure of the material was dominated by ductile fracture with a large Al phase plastic deformation band for lower a,while brittle fracture with crushed Hf particles occurred at higher a.Finally,a constitutive model based on BP neural network was proposed to describe the stress-strain relationships of the materials,with an average relative error of 2.22%.

Influence of substrate effect on near-field radiative modulator based on biaxial hyperbolic materials

Relative rotation between the emitter and receiver could effectively modulate the near-field radiative heat transfer(NFRHT)in anisotropic media.Due to the strong in-plane anisotropy,natural hyperbolic materials can be used to construct near-field radiative modulators with excellent modulation effects.However,in practical applications,natural hyperbolic materials need to be deposited on the substrate,and the influence of substrate on modulation effect has not been studied yet.In this work,we investigate the influence of substrate effect on near-field radiative modulator based onα-MoO_(3).The results show that compared to the situation without a substrate,the presence of both lossless and lossy substrate will reduce the modulation contrast(MC)for different film thicknesses.When the real or imaginary component of the substrate permittivity increases,the mismatch of hyperbolic phonon polaritons(HPPs)weakens,resulting in a reduction in MC.By reducing the real and imaginary components of substrate permittivity,the MC can be significantly improved,reaching 4.64 forε_(s)=3 at t=10 nm.This work indicates that choosing a substrate with a smaller permittivity helps to achieve a better modulation effect,and provides guidance for the application of natural hyperbolic materials in the near-field radiative modulator.