Predicting the Degradability of Bioceramics through a DFT-based Descriptor

Bioceramics have attracted extensive attention for bone defect repair due to their excellent bioactivity and degradability.However,challenges remain in matching the rate between bioceramic degradation and new bone formation,necessitating a deeper understanding of their degradation properties.In this study,density functional theory(DFT)calculations was employed to explore the structural and electronic characteristics of silicate bioceramics.These findings reveal a linear correlation between the maximum isosurface value of the valence band maximum(VBM_(Fmax))and the degradability of silicate bioceramics.This correlation was subsequently validated through degradation experiments.Furthermore,the investigation on phosphate bioceramics demonstrates the potential of this descriptor in predicting the degradability of a broader range of bioceramics.This discovery offers valuable insights into the degradation mechanism of bioceramics and holds promise for accelerating the design and development of bioceramics with controllable degradation.

In silico optimization of actuation performance in dielectric elastomercomposites via integrated finite element modeling and deep learning

Dielectric elastomers(DEs)require balanced electric actuation performance and mechanical integrity under applied voltages.Incorporating high dielectric particles as fillers provides extensive design space to optimize concentration,morphology,and distribution for improved actuation performance and material modulus.This study presents an integrated framework combining finite element modeling(FEM)and deep learning to optimize the microstructure of DE composites.FEM first calculates actuation performance and the effective modulus across varied filler combinations,with these data used to train a convolutional neural network(CNN).Integrating the CNN into a multi-objective genetic algorithm generates designs with enhanced actuation performance and material modulus compared to the conventional optimization approach based on FEM approach within the same time.This framework harnesses artificial intelligence to navigate vast design possibilities,enabling optimized microstructures for high-performance DE composites.

Effect of Modulus Heterogeneity on the Equilibrium Shape and Stress Field ofαPrecipitate in Ti-6Al-4V

For media with inclusions(e.g.,precipitates,voids,reinforcements,and others),the difference in lattice parameter and the elastic modulus between the matrix and inclusions cause stress concentration at the interfaces.These stress fields depend on the inclusions’size,shape,and distribution and will respond instantly to the evolving microstructure.This study develops a phase-field model concerningmodulus heterogeneity.The effect of modulus heterogeneity on the growth process and equilibrium state of theαplate in Ti-6Al-4V during precipitation is evaluated.Theαprecipitate exhibits strong anisotropy in shape upon cooling due to the interplay of the elastic strain and interfacial energy.The calculated orientation of the habit plane using the homogeneous modulus ofαphase shows the smallest deviation fromthat of the habit plane observed in the experiment,compared to the case where the homogeneous modulus ofβphase is adopted.In addition,the equilibrium volume ofαphase within the systemusing homogeneousβmodulus exhibits the largest dependency on the applied stresses.The stress fields across theα/βinterface are further calculated under the assumption of modulus heterogeneity and compared to those using homogeneous modulus of eitherαorβphase.This study provides an essential theoretical basis for developing mechanics models concerning systems with heterogeneous structures.

MOFs‑Derived Strategy and Ternary Alloys Regulation in Flower‑Like Magnetic‑Carbon Microspheres with Broadband Electromagnetic Wave Absorption

Broadband electromagnetic(EM)wave absorption materials play an important role in military stealth and health protection.Herein,metal–organic frameworks(MOFs)-derived magnetic-carbon CoNiM@C(M=Cu,Zn,Fe,Mn)microspheres are fabricated,which exhibit flower-like nano–microstructure with tunable EM response capacity.Based on the MOFs-derived CoNi@C microsphere,the adjacent third element is introduced into magnetic CoNi alloy to enhance EM wave absorption performance.In term of broadband absorption,the order of efficient absorption bandwidth(EAB)value is Mn>Fe=Zn>Cu in the CoNiM@C microspheres.Therefore,MOFs-derived flower-like CoNiMn@C microspheres hold outstanding broadband absorption and the EAB can reach up to 5.8 GHz(covering 12.2–18 GHz at 2.0 mm thickness).Besides,off-axis electron holography and computational simulations are applied to elucidate the inherent dielectric dissipation and magnetic loss.Rich heterointerfaces in CoNiMn@C promote the aggregation of the negative/positive charges at the contacting region,forming interfacial polarization.The graphitized carbon layer catalyzed by the magnetic CoNiMn core offered the electron mobility path,boosting the conductive loss.Equally importantly,magnetic coupling is observed in the CoNiMn@C to strengthen the magnetic responding behaviors.This study provides a new guide to build broadband EM absorption by regulating the ternary magnetic alloy.

High-entropy alloys in thermoelectric application:A selective review

Since the superior mechanical,chemical and physical properties of high-entropy alloys(HEAs)were discovered,they have gradually become new emerging candidates for renewable energy applications.This review presents the novel applications of HEAs in thermoelectric energy conversion.Firstly,the basic concepts and structural properties of HEAs are introduced.Then,we discuss a number of promising thermoelectric materials based on HEAs.Finally,the conclusion and outlook are presented.This article presents an advanced understanding of the thermoelectric properties of HEAs,which provides new opportunities for promoting their applications in renewable energy.

Machine learning aided design of perovskite oxide materials for photocatalytic water splitting

Suffering from the inefficient traditional trial-and-error methods and the huge searching space filled by millions of candidates, discovering new perovskite visible photocatalysts with higher hydrogen production rate(RH_(2)) still remains a challenge in the field of photocatalytic water splitting(PWS). Herein, we established structural-property models targeted to RH_(2) and the proper bandgap(Eg) via machine learning(ML) technology to accelerate the discovery of efficient perovskite photocatalysts for PWS. The Pearson correlation coefficients(R) of leave-one-out cross validation(LOOCV) were adopted to compare the performances of different algorithms including gradient boosting regression(GBR), support vector regression(SVR), backpropagation artificial neural network(BPANN), and random forest(RF). It was found that the BPANN model showed the highest R values from LOOCV and testing data of 0.9897 and 0.9740 for RH_(2),while the GBR model had the best values of 0.9290 and 0.9207 for Eg. Furtherly, 14 potential PWS perovskite candidates were screened out from 30,000 ABO3-type perovskite structures under the criteria of structural stability, Eg, conduction band energy, valence band energy and RH_(2). The average RH_(2) of these14 perovskites is 6.4% higher than the highest value in the training data set. Moreover, the online web servers were developed to share our prediction models, which could be accessible in http://materialsdata-mining.com/ocpmdm/material_api/ahfga3d9puqlknig(E_g prediction) and http://materials-datamining.com/ocpmdm/material_api/i0 ucuyn3 wsd14940(RH_(2) prediction).

A bi-functional strategy involving surface coating and subsurface gradient co-doping for enhanced cycle stability of LiCoO_(2) at 4.6 V

Layered LiCoO_(2)(LCO)acts as a dominant cathode material for lithium-ion batteries(LIBs)in 3C products because of its high compacted density and volumetric energy density.Although improving the high cutoff voltage is an effective strategy to increase its capacity,such behavior would trigger rapid capacity decay due to the surface or/and structure degradation.Herein,we propose a bi-functional surface strategy involving constructing a robust spinel-like phase coating layer with great integrity and compatibility to LiCoO_(2) and modulating crystal lattice by anion and cation gradient co-doping at the subsurface.As a result,the modified LiCoO_(2)(AFM-LCO)shows a capacity retention of 80.9%after 500 cycles between 3.0and 4.6 V.The Al,F,Mg enriched spinel-like phase coating layer serves as a robust physical barrier to effectively inhibit the undesired side reactions between the electrolyte and the cathode.Meanwhile,the Al,F,Mg gradient co-doping significantly enhances the surficial structure stability,suppresses Co dissolution and oxygen release,providing a stable path for Li-ions mobility all through the long-term cycles.Thus,the surface bi-functional strategy is an effective method to synergistically improve the electrochemical performances of LCO at a high cut-off voltage of 4.6 V.

Layered manganese phosphorus trisulfides for high-performance lithium-ion batteries and the storage mechanism

Although advanced anode materials for the lithium-ion battery have been investigated for decades,a reliable,high-capacity,and durable material that can enable a fast charge remains elusive.Herein,we report that a metal phosphorous trichalcogenide of MnPS_(3)(manganese phosphorus trisulfide),endowed with a unique and layered van der Waals structure,is highly beneficial for the fast insertion/extraction of alkali metal ions and can facilitate changes in the buffer volume during cycles with robust structural stability.The few-layered MnPS_(3)anodes displayed the desirable specific capacity and excellent rate chargeability owing to their good electronic and ionic conductivities.When assembled as a half-cell lithium-ion battery,a high reversible capacity of 380 mA h g^(−1)was maintained by the MnPS_(3)after 3000 cycles at a high current density of 4 A g^(−1),with a capacity retention of close to or above 100%.In full-cell testing,a reversible capacity of 450 mA h g^(−1)after 200 cycles was maintained as well.The results of in-situ TEM revealed that MnPS_(3)nanoflakes maintained a high structural integrity without exhibiting any pulverization after undergoing large volumetric expansion for the insertion of a large number of lithium ions.Their kinetics of lithium-ion diffusion,stable structure,and high pseudocapacitance contributed to their comprehensive performance,for example,a high specific capacity,rapid charge-discharge,and long cyclability.MnPS_(3)is thus an efficient anode for the next generation of batteries with a fast charge/discharge capability.

Split-Ring Structured All-Inorganic Perovskite Photodetector Arrays for Masterly Internet of Things

Photodetectors with long detection distances and fast response are important media in constructing a non-contact human-machine interface for the Masterly Internet of Things(MIT).All-inorganic perovskites have excellent optoelectronic performance with high moisture and oxygen resistance,making them one of the promising candidates for high-performance photodetectors,but a simple,low-cost and reliable fabrication technology is urgently needed.Here,a dual-function laser etching method is developed to complete both the lyophilic split-ring structure and electrode patterning.This novel split-ring structure can capture the perovskite precursor droplet efficiently and achieve the uniform and compact deposition of CsPbBr3 films.Furthermore,our devices based on laterally conducting split-ring structured photodetectors possess outstanding performance,including the maximum responsivity of 1.44×105 mA W^(−1),a response time of 150μs in 1.5 kHz and one-unit area<4×10-2 mm2.Based on these split-ring photodetector arrays,we realized three-dimensional gesture detection with up to 100 mm distance detection and up to 600 mm s^(−1) speed detection,for low-cost,integrative,and non-contact human-machine interfaces.Finally,we applied this MIT to wearable and flexible digital gesture recognition watch panel,safe and comfortable central controller integrated on the car screen,and remote control of the robot,demonstrating the broad potential applications.

Lamellar-stacked cobalt-based nanopiles integrated with nitrogen/sulfur co-doped graphene as a bifunctional electrocatalyst for ultralong-term zinc-air batteries

Sluggish oxygen evolution reaction(OER)and oxygen reduction reaction(ORR)kinetics inevitably impede the practical performance of rechargeable zinc-air batteries.Thus,combing the structural designability of transition metal-based electrocatalysts with anionic regulation is highly desired.Herein,mesoporous lamellar-stacked cobalt-based nanopiles with surface-sulfurization modification are elaborately designed and integrated with N/S co-doped graphene to build a robust OER/ORR bifunctional electrocatalyst.The lamellar-stacking mode of mesoporous nanosheets with abundant channels accelerates gas-liquid mass transfer,and partial-sulfurization of cobalt-based matrix surface efficiently improves the intrinsic OER activity.Meanwhile,N/S co-doped graphene further reinforces the ORR active sites while providing a stable conductive skeleton.As expected,this composite electrocatalyst delivers considerable bifunctional activity and stability,with an OER overpotential of 323 m V at 10 m A cm^(-2)and high durability.When applied in zinc-air batteries,remarkable ultralong-term stability over 4000 cycles and a maximum power density of 150.1 m W cm^(-2)are achieved.This work provides new insight into structurecomposition synergistic design of rapid-kinetics OER/ORR bifunctional electrocatalyst for nextgeneration metal-air batteries.

Flux pinning evolution in multilayer Pb/Ge/Pb/Ge/Pb superconducting systems

Multicomponent superconductors exhibit nontrivial vortex behaviors due to the various vortex–vortex interactions,including the competing one in the recently proposed type-1.5 superconductor.However,potential candidate that can be used to study the multicomponent superconductivity is rare.Here,we prepared an artificial superconducting multilayer to act as an alternative approach to study multicomponent superconductivity.The additional repulsive length and the coupling strength among superconducting films were regulated by changing the thickness of the insulting layer.The magnetization measurements were performed to clarify the effect of the competition between the repulsive vortex interactions on the macroscopic superconductivity.The vortex phase diagram and the optimum critical current density have been determined.Furthermore,a second magnetization effect is observed,and is attributed to the upper layer,which provides the weak pinning sites to localize the flux lines.The pinning behaviors switches to the mixed type with the increase of the insulting layer thicknesses.Our results open a new perspective to the study and related applications of the multilayer superconducting systems.

材料、能源、机械工程中高效的电流变技术——从机理到应用

电流变(ER)技术是一种基于电流变效应的先进技术。电流变技术中最常见的材料是电流变液(ERF)。电流变液是一种软物质智能材料,其黏度可以通过施加电场来可逆地调节。电流变液的衍生物、一种新型的电响应软物质材料——电流变弹性体(ERE),由于其不沉降、易封装的优点也得到了越来越多的关注。电流变材料由于其可逆可调、快速响应、低能耗等特性在机械工程中有着广泛的应用。除了基础的电流变材料的合成和应用以外,电流变技术还应用在了能源材料制备、石油运输、储能等诸多领域。电流变技术在能源领域的应用为其在其他领域的潜在应用提供了一个很好的范例。本文结合最新的研究成果,从机理到应用,系统地综述了电流变技术在材料、能源和机械工程等领域的研究现状和未来发展前景。

Negative thermal expansion and phase transition of low-temperature Mg_(2)NiH_(4)

The negative thermal expansion(NTE) phenomenon is of great significance in fabricating zero thermal expansion(ZTE) materials to avoid thermal shock during heating and cooling. NTE is observed in limited groups of materials, e.g., metal cyanides, oxometallates, and metalorganic frameworks, but has not been reported in the family of metal hydrides. Herein, a colossal and continuous negative thermal expansion is firstly developed in the low-temperature phases of LT1-and LT2-Mg_(2)NiH_(4) between 488 K and 733 K from in-situ transmission electron microscope(TEM) video, with the volume contraction reaching 18.7% and 11.3%, respectively. The mechanisms for volume contraction of LT1 and LT2 phases are elucidated from the viewpoints of phase transformation, magnetic transition, and dehydrogenation, which is different from common NTE materials containing flexible polyhedra units in the structure. The linear volume shrinkage of LT2 in the temperature of 488-553 K corresponds to the phase transition of LT2→HT with a thermal expansion coefficient of -799.7 × 10^(-6) K^(-1) revealed by in-situ synchrotron powder X-ray diffraction. The sudden volume contraction in LT1 between 488 and 493 K may be caused by the rapid dehydrogenation of LT1 to Mg_(2)Ni. The revealed phenomenon in single composite material with different structures would be significant for preparing zero thermal expansion materials by tuning the fraction of LT1 and LT2 phases.

Unraveling the reaction reversibility and structure stability of nickel sulfide anodes for lithium ion batteries

The electrochemical performance of lithium-ion batteries,i.e.specific capacity and cyclability,is primarily determined by chemical reversibility and structural stability of the electrodes in cycling.Here we have investigated the fundamental reaction behaviors of nickel sulfide(NixSy)as lithium-ion battery anodes by in-situ TEM.We find that Ni_(3)S_(2)is the electrochemically stable phase,which appears in the first cycle of the NixSyanode.From the second cycle,conversion between Ni_(3)S_(2)and Li_(2)S/Ni is the dominant electrochemical reaction.In lithiation,the NixSynanoparticles evolve into a mixture of Ni nanocrystals embedded in Li_(2)S matrix,which form a porous structure upon full lithiation,and with the recrystallization of the Ni_(3)S_(2)phase in delithiation,a compact and interconnected network is built.Structural stability in cycles is susceptible to particle size and substrate restraint.Carbon substrate can certainly improve the tolerance for size-dependent pulverization of NixSynanoparticles.When NixSynanoparticle exceeds the critical size value,the morphology of the particle is no longer well maintained even under the constraints of the carbon substrate.This work deepens the understanding of electrochemical reaction behavior of conversiontype materials and helps to rational design of high-energy density battery anodes.

Multi-scale computation methods:Their applications in lithium-ion battery research and development

Based upon advances in theoretical algorithms, modeling and simulations, and computer technologies, the rational design of materials, cells, devices, and packs in the field of lithium-ion batteries is being realized incrementally and will at some point trigger a paradigm revolution by combining calculations and experiments linked by a big shared database, enabling accelerated development of the whole industrial chain. Theory and multi-scale modeling and simulation, as supplements to experimental efforts, can help greatly to close some of the current experimental and technological gaps, as well as predict path-independent properties and help to fundamentally understand path-independent performance in multiple spatial and temporal scales.

Catalytic effect of Ni@rGO on the hydrogen storage properties of MgH2

Uniform-uispersed Ni nanoparticics(NPs)anchored on reduced graphene oxide(Ni@rGO)catalyzed MgH2(MH-Ni@rGO)has been fabricated by mechanical milling.The effects of milling time and Ni loading amount on the hydrogen storage properties of MgH2 have been investigated.The initial hydrogen desorption temperature of MgH2 catalyzed by 10 wt.%Ni4@rGO6 for milling 5 h is significantly decreased from 251℃ to 190℃.The composite can absorb 5.0 wt.%hydrogen in 20 min at 100℃,while it can desorb 6.1 wt.%within 15 min at 300℃.Through the investigation of the phase transformation and dehydrogenation kinetics during hydrogen ab/desorption cycles,we found that the in-situ formed Mg2Ni/Mg2NiH4 exhibited better catalytic effect than Ni.When Ni loading amount is 45 wt.%,the rGO in Ni@rGO catalysts can prevent the reaction of Ni and Mg due to the strong interaction between rGO and Ni NPs.

Brief overview of electrochemical potential in lithium ion batteries

The physical fundamentals and influences upon electrode materials＇ open-circuit voltage （OCV） and the spatial distribution of electrochemical potential in the full cell are briefly reviewed. We hope to illustrate that a better understanding of these scientific problems can help to develop and design high voltage cathodes and interfaces with low Ohmic drop. OCV is one of the main indices to evaluate the performance of lithium ion batteries （LIBs）, and the enhancement of OCV shows promise as a way to increase the energy density. Besides, the severe potential drop at the interfaces indicates high resistance there, which is one of the key factors limiting power density.

Effects of hot top pulsed magneto-oscillation on solidification structure of steel ingot

Achieving a uniform structure with few defects in heavy steel ingot is of high commercial importance. In this present work, in order to verify the potential of pulsed magneto-oscillation(PMO) applied in the production of heavy ingot, an induction coil was located at the hot top of the steel ingot to develop a novel technique, named hot top pulsed magneto oscillation(HPMO). The influences of HPMO on the solidification structure, macro segregation and compactness of a cylindrical medium carbon steel ingot with the weight of 160 kg were systematically investigated by optical microscope(OM) and laser induced breakdown spectroscopy original position metal analyzer(LIBSOPA-100). The results show that HPMO not only causes significant grain refinement and promotes the occurrence of columnar to equiaxed transition(CET) but also can homogenize the carbon distribution and enhance the compactness of the steel ingot. Therefore, HPMO technique has the potential to be applied in the production of heavy steel ingots on an industrial scale.

Remarks on the recent progress of Materials Genome Initiative

The Materials Genome Initiative(MGI)has attracted great attention globally since June 2011,when the US President Obama announced Advanced Manufacturing Partnership(AMP),in which MGI is a key component.In June 2014,the US National Science and Technology Council published‘‘Materials Genome Initiative Strategic Plan’’,describing in detail the strategy that guides and coordinates US Federal activities and provides a clear technical path

Lithium-ion transport in inorganic solid state electrolyte

An overview of ion transport in lithium-ion inorganic solid state electrolytes is presented, aimed at exploring and de signing better electrolyte materials. Ionic conductivity is one of the most important indices of the performance of inorganic solid state electrolytes. The general definition of solid state electrolytes is presented in terms of their role in a working cell （to convey ions while isolate electrons）, and the history of solid electrolyte development is briefly summarized. Ways of using the available theoretical models and experimental methods to characterize lithium-ion transport in solid state elec- trolytes are systematically introduced. Then the various factors that affect ionic conductivity are itemized, including mainly structural disorder, composite materials and interface effects between a solid electrolyte and an electrode. Finally, strategies for future material systems, for synthesis and characterization methods, and for theory and calculation are proposed, aiming to help accelerate the design and development of new solid electrolytes.