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The worldwide usage of large quantities of cement leads to increase in the CO2 emission; which is one of the major causes for global warming. Therefore, it is essential to replace cement with some novel material, with equal strength and zero CO2 emissions. In this study, an eco-friendly mix, which is formed using a new approach considering energy, CO2 emission, cost and strength for design and construction, has been proposed. This study reveals the addition of waste materials like fly ash, which can be used for material design and also can be effective by consuming less energy and emits less CO2. At the same time, it attains the required strength and workability.

Recent technical progress in the industry has led to an urgent requirement on new materials with enhanced multi-properties. To meet this multi-property requirement, the materials consisting of three and more elements have attracted increasing attention. However, facing to the nearly unknown huge multi-component materials system, the traditional trial and error method cannot provide sufficient data efficiently. Therefore, an efficient material innovation strategy is significant. The first-principles calculation based on the density functional theory is a powerful tool for both the accurate prediction of material properties and the identification of its underlying thermodynamics and dynamics. At the same time, the advances of computational methods and computer calculation abilities that are orders of magnitude faster than before make the high throughput first-principles calculations popular. At present, the simulation-assisted material design has become a main branch in the material research field and a great many successes have been made. In this article, the advances of the high throughput first-principles calculations are reviewed to show the achievements of the first-principles calculations and guide the future directions of its applications in ceramics.

Designing biointegrated electronics for resilience starts at the molecular level, whereby “molecular architecture” dictates function. The ability to predict how variations in molecular level features translate to bulk polymer properties is critical for realizing large-scale bulk applications and opening avenues for niche applications. Inspired by architectural resilient design principles, this article reviews analogous principles for materials used in biointegrated electronics, including strategies to address mechanical mismatch, fouling, improper adhesion, and degradation within biological systems. Moreover, innovations in artificial intelligence and automation that will play an important role in elucidating new material design principles and their practical large-scale construction are discussed. Finally, alternative avenues for simplifying the production of future biointegrated electronics are proposed, such as using self-assembly processes that draw inspiration from biology to construct devices in vivo.

Geometric structures of carbon networks are key in designing their material properties. In particular, optimization of curved structures through the introduction of topological defects and doping of heteroatoms in the lattice is crucial to the design of carbon-based, non-noble-metal-free catalysts. A simple and practical mathematical model based on discrete geometric analysis is proposed to describe the geometric features of carbon networks and their relationships to their material properties. This model can pre-screen candidates for novel material design, and these candidates can be further examined by the density functional theory (DFT). Inspired by observations regarding the preferential doping of heteroatoms at local curved sites, the important characteristics of the candidate material were experimentally realized, and its enhanced catalytic activity facilitated by chemical dopants was confirmed in the designed carbon network.

The world’s increasing population requires the process industry to produce food, fuels, chemicals, and consumer products in a more efficient and sustainable way. Functional process materials lie at the heart of this challenge. Traditionally, new advanced materials are found empirically or through trial-and-error approaches. As theoretical methods and associated tools are being continuously improved and computer power has reached a high level, it is now efficient and popular to use computational methods to guide material selection and design. Due to the strong interaction between material selection and the operation of the process in which the material is used, it is essential to perform material and process design simultaneously. Despite this significant connection, the solution of the integrated material and process design problem is not easy because multiple models at different scales are usually required. Hybrid modeling provides a promising option to tackle such complex design problems. In hybrid modeling, the material properties, which are computationally expensive to obtain, are described by data-driven models, while the well-known process-related principles are represented by mechanistic models. This article highlights the significance of hybrid modeling in multiscale material and process design. The generic design methodology is first introduced. Six important application areas are then selected: four from the chemical engineering field and two from the energy systems engineering domain. For each selected area, state-of-the-art work using hybrid modeling for multiscale material and process design is discussed. Concluding remarks are provided at the end, and current limitations and future opportunities are pointed out.

Rechargeable tellurium (Te)-based batteries are emerging as energy storage devices with high volumetric energy density due to tellurium's superior electronic conductivity and high specific volumetric capacity. However, Te-based batteries are quite new, raising fundamental questions regarding the electrochemistry of Te-based cathodes and holistic aspects of full-cell performance. This review begins with a critical discussion on Li-Te electrochemistry in carbonate and ether electrolytes, followed by a comprehensive review on material design, cell architectures, and the working mechanism of Te-based cathodes in Li-Te-based batteries. The primary focus is to develop a fundamental understanding of the Te structure's role, carbon host chemistry and porosity, and the use of electrolytes to address Te pulverization and parasitic polytellurides shuttle effects and to establish reversible Te and Li2Te phase transitions. In addition, liquid and solid-state electrolytes for Li-Te batteries showing promise of enabling a stable solid electrolyte interphase (SEI) and reversible Te cathode reactions are presented. The following section exemplifies other novel metal-Te based batteries, including Na-Te, K-Te, Mg-Te, Zn-Te, and Al-Te systems, highlighting their respective cathode and electrolyte selection. Then, the comparison of quantitative performance data of various metal-Te-based batteries across Li-ion and Li-S batteries is revealed to provide a landscape of current research. In closing, this work identifies unanswered scientific and technological questions, discusses promising research directions, and highlights the experimental and simulation-based studies needed to discover the unknown of rechargeable Te-based batteries.

Purpose This paper aims to develop a Mini-Tribometer for in-situ observation of subsurface. Design/methodology/approach To observe the change of the microstructure during wear in real time, an in-situ observation mini-tribometer was developed according to the requirements of the basic frictional experiments and carried out the verification experiments. Findings The subsurface images and the tribological data obtained from the mini-tribometer clearly show that the graphite in the matrix moves to the surface and takes part in lubrication mainly in the form of extrusion and peeling off, and the migration of graphite in the copper-based composite to the frictional interface to act as lubricant and to result in the decrease of the friction coefficient. The experimental results of the developed tribometer are accurate, which can provide important references for further research on the wear mechanism of materials. Originality/value The developed in-situ observation mini-tribometer can be used to observe the dynamic wear mechanism of the frictional pairs, which is very important for optimization of material design and tribological performances.

Photocatalysis utilizes solar energy to produce clean fuels such as hydrogen or generate highly reactive species to subsequently break the organic pollutants into clean end products. Direct Z-scheme heterostructured photocatalysts can overcome the fundamental shortcomings in conventional photocatalysts and thus enable this green technology in tackling the energy crisis and environmental problems at the same time. Various approaches and numerous materials have been attempted in the hope of achieving high efficiency and broad effectiveness for practical applications. This work intends to provide a comprehensive and timely review on direct Z-scheme photocatalysts from the material’s point of view. The formation mechanisms based on the driving forces of the charge transfer are firstly discussed to guide the material design. Three mechanisms, namely internal electric field, interfacial defect-induced charge transfer, and facet-induced charge transfer, are identified and summarized. Various material systems are then extensively discussed and compared according to their applications, followed by the emerging material modification strategies for performance improvement. Lastly, the review provides the perspectives for future development. It is expected that the insights of this up-to-date review could guide the material design and performance improvement of the direct Z-scheme systems to achieve their maximum potentials.

The rapid development of electric vehicles and mobile electronic devices is the main driving force to improve advanced high-performance lithium ion batteries (LIBs). The capacity, rate performance and cycle stability of LIBs rely directly on the electrode materials. As far as the development of the advanced LIBs electrode is concerned, the improvement of anode materials is more urgent than the cathode materials. Industrial production of anode materials superior to commercial graphite still faces some challenges. This review sets out the most basic LIBs anode material design. The reaction principles and structural design of carbon materials, various transition metal oxides, silicon and germanium are summarized, and then the progress of other anode materials are analyzed. Due to the rapid development of metal organic frameworks (MOFs) in energy storage and conversion in recent years, the synthesis process and energy storage mechanism of nanostructures derived from MOF precursors are also discussed. From the perspective of novel structural design, the progress of various MOFs-derived materials for alleviating the volume expansion of anode materials is discussed. Finally, challenges for the future development of advanced anode materials for LIBs will be considered.

Particulate materials possessing dual functionalities have received tremendous investigations in many fields, owing to their superiority over mono-functional counterparts and their potential for process integration and intensification. This review focuses on bi-functional catalytic particles which also serve as sorbents/adsorbents or heat suppliers in the scheme of various thermo-chemical processes, enabling inherent separation or energy conservation within single-step operation. Bi-functional particles applied for integration of reaction and separation including sorption-enhanced hydrogen production and integrated capture and catalytic conversion processes are reviewed in detail, providing insights into material design and key performance indicators. On the other hand, bi-functional particles applied for integration of reaction and non-thermal radiation heating, including electrothermal and photothermal assisted heterogeneously catalyzed reactions, are also reviewed, with emphasis on the material property and energy efficiency improvement. These bi-functional particles show broad adaptability and feasibility in various reactions operated in integrated and intensified schemes, affording huge potentials for further improving productivity and efficiency in thermo-chemical processes.

The utilization of chemical sequence control in polymeric materials is key to enabling material design on par with biomacromolecular systems. One important avenue for scalable sequence-controlled polymers leverages the random copolymerization of distinct monomers, with the statistical distribution of the monomeric sequence arising from reaction kinetics following a first-order Markov process. Here we utilize the framework of the random phase approximation (RPA) to develop a theory for the phase behavior of symmetric polyelectrolyte coacervates whose chemical sequences are dictated by simple statistical distributions. We find that a high charge "blockiness" within the random sequences favors the formation of denser and more salt-resistant coacervates while simultaneously increasing the width of the two-phase region. We trace these physical effects to the increased cooperativity of Coulomb interactions that results from increased charge blockiness in oppositely charged polyelectrolytes.

Lead (Pb) halide perovskites have achieved great success in recent years due to their excellent optoelectronic properties, which is largely attributed to the lone-pair s orbital-derived antibonding states at the valence band edge. Guided by the key band-edge orbital character, a series of ns2-containing (i.e., Sn2+, Sb3+, Bi3+) Pb-free perovskite alternatives have been explored as potential photovoltaic candidates. On the other hand, based on the band-edge orbital components (i.e., M2+ s and p/X- p orbitals), a series of strategies have been proposed to optimize their optoelectronic properties by modifying the atomic orbitals and orbital interactions. Therefore, understanding the band-edge electronic features from the recently reported halide perovskites is essential for future material design and device optimization. Here, this Perspective first attempts to establish the band-edge orbital-property relationship using a chemically intuitive approach, and then rationalizes their superior properties and understands the trends in electronic properties. We hope that this Perspective will provide atomic-level guidance and insights toward the rational design of perovskite semiconductors with outstanding optoelectronic properties.

The Ni-rich layered material LiNixCoyMzO2 (M=Mn or Al, x+y+z=1) plays a crucial role in LIBs and attracts much attention owing to its comprehensive advantages in terms of energy density, production cost, and environmental friendliness, leading to the development of LIBs and related energy-storage devices. However, Ni-rich layered materials are limited in certain aspects such as safety, life cycle, and application range, which fail to meet the requirements for application in the market entirely. Starting from the factors including cation mixing, phase transition, crackle, and so on, which cause the performance degradation of nickel-rich cathode materials, this paper analyzes the mechanism of their action, and summarizes the mutual transformation relationship between the factors. Cutting off this transition process may, like inhibiting these factors, help improve the performance of materials. At the same time, the research progress on the strategies and mechanisms to deal with these failure factors is summarized, and the role of simulation calculation in material design and mechanism demonstration is discussed. The purpose of this paper is to give an introduction to the related research results of nickel-rich layered cathodes in recent years and to help researchers understand the development status of this field in a timely and rapid manner.

The requirement for increased resolution has created the concept of displays with nanoscale pixels; that is, each subpixel consists of multiple or even a single nanolight source, which is considered the ultimate light source for light field, near-eye, and implantable displays. However, related research is still at an early stage, and further insights into this future display concept should be provided. In this Perspective, we provide our proposed term for this future display, namely, nanopixel light-emitting display (NLED). We present an overview of nanolight-emitting diodes, which are considered the core component of NLEDs. Then, a roadmap to realize NLEDs from the view of material design is provided. Finally, we introduce our proposed operation mode (nonelectrical contact and noncarrier injection mode) for NLEDs and recommend possible nanopixel-level drive approaches. We hope that this Perspective will be helpful in designing innovative display technologies.

The emerging class of heptazine-based polymeric materials has shown potential candidature as photocatalyst materials for hydrogen evolution. At the same time, they have shown promising application as solid base materials to catalyse various organic transformations. Thus, the material design rationale needs to be developed around the heptazine-based polymeric frameworks in order to specifically design task specific materials. Herein, we utilised controlled reaction conditions to synthesize the desired polymeric networks with trichloroheptazine as precursor. Material design strategy employed nitrogen rich [tris(2-aminoethylamine) and hydrazine] as soft linkers to understand the effect on band structure of developed heptazine-based polymeric networks. The developed polymeric networks were explored as platform to study systematically the effect on their respective photophysical properties and understand their surface basicity. The framework having aminoalkyl linker showed superior activity in photocatalysis as well as heterogeneous base catalysis. Further, model catalysts revealed the importance of N-atoms as active basic sites in these systems.

Important progresses in the study of laser additive manufacturing on metal matrix composites (MMCs) have been made. Recent efforts and advances in additive manufacturing on 5 types of MMCs are presented and reviewed. The main focus is on the material design, the combination of reinforcement and the metal matrix, the synthesis principle during the manufacturing process, and the resulted microstructures as well as properties. Thereafter, the trend of development in future is forecasted, including: Formation mechanism and reinforcement principle of strengthening phase; Material and process design to actively achieve expected performance; Innovative structure design based on the special properties of laser AM MMCs; Simulation, monitoring and optimization in the process of laser AM MMCs.

This paper aims to provide an overview of the current state of the art in molecule and material design and a perspective on open questions. First, we discuss the interplay between process design and the design of molecules and materials and then present the basic trade-offs and interdependencies that need to be considered in this integrated design problem. Second, we introduce methods and open questions in the area of processing materials, with special emphasis placed on heterogeneous catalysts due to their importance in the chemical industry. Finally, we discuss materials for photovoltaic cells as one example of a chemical product that is likely to help supply sustainable energy and address climate change concerns. What is presented here is based on presentations and discussions during the FIPSE-4 meeting in June 2018 (https://www.fi-in-pse.org/fipse-4-2018).

Searching thermoelectric materials with high performance and low cost is now receiving special attention and great challenges in the field of material design. In this work, we perform first-princip...

This work explores the possibilities for the processing of Ni- and Ti3C2Tx (T = OH, O) MXene-containing composite electrodes, by co-pressing and plastic deformation or by etching of the electrodes prepared directly by self-propagation high-temperature synthesis (SHS). Various material design approaches were also explored. In order to tune the Ti3C2 interlayer distance in Ti3C2Al MAX phase, an introduction of additional Al to form Ti3C2Alz materials with z > 1 was attempted. Self-propagation high-temperature synthesis of powder mixtures with extra Ni and Al content (e.g. Ni:Ti:Al:C = 1:2:3:1) resulted in SHS products containing Ti3C2Alz z > 1 material and Ni–Al alloys. Further etching of these products in 10M NaOH allowed the direct formation of electrodes with active surface containing Ti3C2Tx (T = OH, O) MXene- and Raney nickel-containing composites. The electrochemical studies were focused on hydrogen evolution and showed the potential for boosting the electrochemical reaction in Ni and MXene-containing composite electrodes, especially at high current densities. The guidelines for the processing of such electrodes under fluorine-free conditions are proposed and discussed.

Combinatorial and high-throughput experimentation (HTE) is achieving more relevance in material design, representing a turning point in the process of accelerated discovery, development, and optimization of materials based on data-driven approaches. The versatility of drop-on-demand inkjet printing (IJP) allows performing combinatorial studies through fabrication of compositionally graded materials with high spatial precision, here by mixing superconducting REBCO precursor solutions with different rare earth (RE) elements. The homogeneity of combinatorial Y1−xGdxBa2Cu3O7 samples was designed with computational methods and confirmed by energy-dispersive Xray spectroscopy (EDX) and high-resolution X-ray diffraction (XRD). We reveal the advantages of this strategy in the optimization of the epitaxial growth of high-temperature REBCO superconducting films using the novel transient liquid-assisted growth method (TLAG). Advanced characterization methods, such as in situ synchrotron growth experiments, are tailored to suit the combinatorial approach and demonstrated to be essential for HTE schemes. The experimental strategy presented is key for the attainment of large datasets for the implementation of machine learning backed material design frameworks., The authors acknowledge the European Research Council for the ULTRASUPERTAPE project (ERC-2014-ADG-669504) and EU COST action for CA16218 (NANOCOHYBRI). We also acknowledge financial support from the Spanish Ministry of Economy and Competitiveness, and Spanish Ministry of Science, Innovation and Universities through the “Severo Ochoa” Program for Centers of Excellence in R&D (SEV-2015-0496 and CEX2019-000917-S), SUMATE project (RTI2018-095853-B-C21, co-financed by the European Regional Development Fund). Synchrotron SOLEIL is acknowledged for granting the beamtime (under project no. 20190274) and P. Joly for setup assistance at the DiffAbs beamline. We also acknowledge support from the Catalan Government with 2017-SGR-1519 and the energy Catalan network E4S. A.Q. thanks the Spanish Ministry of Science, Innovation and Universities for his “Juan de la Cierva” postdoctoral fellowship (Grant no. IJC2018-035034-I). We acknowledge support of the publication fee by the CSIC Open Access Publication Support Initiative through its Unit of Information Resources for Research (URICI).

Solid-state batteries are generally considered to be safer than their liquid-state counterparts due to their decreased potential for fire or short circuiting. The fabrication of solid-state batteries relies on the application of stack crimping pressure that increases the interfacial surface contacts between electrolytes and the electrodes. However, excessive compressive crimping stresses (that occur in cell assembly) can give rise to cracking phenomena that can degrade battery performance and lead to thermal runaway or failure. It is, therefore, important to develop an understanding of failure mechanisms in solid-state Li-ion electrolytes. In this paper, we use a combination of in-situ optical microscopy and Digital Imaging Correlation (strain mapping) techniques to study compressive deformation and cracking phenomena in a novel solid-state Li-ion electrolyte. The stress states associated with the different stages of compressive deformation are also presented along with those due to charge–discharge cycles. The implications of the results are discussed for the material design of robust solid-state Li ion batteries.

Concrete compressive strength prediction is an essential process for material design and sustainability. This study investigates several novel hybrid adaptive neuro-fuzzy inference system (ANFIS) evolutionary models, i.e., ANFIS-particle swarm optimization (PSO), ANFIS-ant colony, ANFIS-differential evolution (DE), and ANFIS-genetic algorithm to predict the foamed concrete compressive strength. Several concrete properties, including cement content (C), oven dry density (O), water-to-binder ratio (W), and foamed volume (F) are used as input variables. A relevant data set is obtained from open-access published experimental investigations and used to build predictive models. The performance of the proposed predictive models is evaluated based on the mean performance (MP), which is the mean value of several statistical error indices. To optimize each predictive model and its input variables, univariate (C, O, W, and F), bivariate (C-O, C-W, C-F, O-W, O-F, and W-F), trivariate (C-O-W, C-W-F, O-W-F), and four-variate (C-O-W-F) combinations of input variables are constructed for each model. The results indicate that the best predictions obtained using the univariate, bivariate, trivariate, and four-variate models are ANFIS-DE- (O) (MP = 0.96), ANFIS-PSO- (C-O) (MP = 0.88), ANFIS-DE- (O-W-F) (MP = 0.94), and ANFIS-PSO- (C-O-W-F) (MP = 0.89), respectively. ANFIS-PSO- (C-O) yielded the best accurate prediction of compressive strength with an MP value of 0.96.

Proton exchange membrane (PEM) fuel cells are a promising candidate as the next-generation power sources for portable, transportation, and stationary applications. Gas diffusion layers (GDL) coated with microporous layers (MPL) are a vital component of PEM fuel cells, providing multiple functions of mechanical support, reactant transport, liquid water removal, waste heat removal, and electron conductance. In this review, we explain several most important aspects in the research and development (R&D) of this fuel cell component, including material characterization, liquid water detection/quantitation, structure reconstruction, fundamental modeling, transport properties, and durability. Specially, the commonly used microstructure reconstruction methods for GDLs are presented and discussed. Visualization techniques for liquid water detection in the GDL and MPL microstructures are described. Major modeling approaches, such as the multiphase mixture (M2) formulation, pore networks model (PNM), lattice Boltzmann method (LBM) and volume of fluid (VOF) approach, are reviewed and explained. Important material properties and parameters that greatly influence two-phase flow and fuel cell performance, and GDL-related material degradation issues are discussed and summarized to further advance on the GDL material design and development.

Vertically stacked van der Waals heterostructures made of two-dimensional compounds are almost an infinite playground for the fabrication of nano-engineered materials for the most diverse applications. Unfortunately, high-throughput electronic structure theory, which often serves as a guidance for material design, is not practical in this case. In fact, the compositional and structural complexity of van der Waals heterostructures make the number of prototypes to calculate combinatorially large. In this work a method is developed to compute the bandstructure of van der Waals heterostructures with an arbitrary composition and geometry using minimal computational resources. Such scheme is applied to the systematic study of a library of two-dimensional hexagonal XY2 compounds. The method is based on the density functional theory and on the assumption that the inter-layer electronic interaction is limited to classical electrostatic screening. Our analysis enables us to identify and categorize a large range of van der Waals bilayer heterostructures with electronic band gaps of different nature ranging from 0.1 to 5.5 eV and various types of band line-up.

The widespread adoption of high-energy-density solid-state batteries (SSBs) requires cost-effective processing and the integration of solid electrolytes of about the same thickness as the polymer-membrane separators found in conventional lithium-ion batteries. In this Review, we critically discuss the current status of research on SSB processing as well as recent cost calculations, and compare SSB oxide electrolyte material and processing options in terms of performance parameters for thick versus thin ceramics. We identify as critical for future SSB design the need to capture the thermal processing budget and the stability of the phase of interest for oxide solid electrolytes, namely lithium phosphorus oxynitride, sodium superionic conductors, perovskites and garnets, in addition to the classic plots of Arrhenius lithium transport and the electrochemical stability window. Transitioning to SSB oxide electrolyte films with thicknesses close to the range for lithium-ion battery separators could provide ample opportunities for low-temperature ceramic manufacture and potential cost reduction. High-performance solid-state electrolytes are key to enabling solid-state batteries that hold great promise for future energy storage. The authors survey the fabrication process of thin-film versus thick oxide-based solid-state electrolytes and discuss their material design and processing options.

A key bottleneck for material discovery is synthesis. While significant advances have been made in computational material design, synthesis pathways are still often determined through trial and err...

The shortage of fossil fuel has triggered global concern due to environmental issues. Consequently, fuel cells have been designed to efficiently generate electricity from clean and renewable fuels and have gained increasing attention. In recent years, the development of earth-abundant and cost-effective materials for application in fuel cells has become a key objective worldwide to push the commercialization of this technology. Anion exchange membrane fuel cells (AEMFCs) have become one of the most popular research topics because their alkaline environment allows a wider range of cost-effective materials to be employed as membranes and electrodes. Unitized regenerative AEMFCs (UR-AEMFCs) have also attracted great research interest because of their additional energy storage capability. The electrode performance plays critical role in the practical application of (UR-)AEMFCs. Oxide-based precious metal (PM)-free electrocatalysts have been developed as one class of promising candidates for application in (UR-)AEMFCs due to their many advantages, such as low cost, earth-abundant resources, intrinsic tunable electronic structures and surface properties, and structural flexibility, which can be utilized to lower the kinetic and thermodynamic barriers of oxygen electrocatalysis in an alkaline environment. Herein, we provide a comprehensive review of recent advances in oxide-based PM-free electrocatalysts used for (UR-)AEMFCs considering their synthetic strategies, such as morphology and structure control, electronic and surface properties. In addition, their design principles and corresponding catalytic performances are summarized. The current challenges with their wide application are also discussed to provide some guidelines for the design of next-generation oxide-based electrocatalysts for (UR-)AEMFCs.

The shuttle effect seriously impedes the development and practical application of lithium sulfur (Li-S) batteries. It is still a long-term challenge to find effective anchoring materials to hinder the shuttle effect of Li-S batteries. Using carbon allotrope as anchoring materials is an effective strategy to alleviate the shuttling effect. However, the influence factors of carbon allotrope on the adsorption performance of LIPSS at the atomic level are not clear, which limits the application of carbon allotrope in Li-S batteries. Herein, using first – principles simulations, a systematical calculation of carbon allotropes with various ring size (6 ≤ S ≤ 16) and shape is conducted to understand the adsorption mechanism. The results show that the T-G monolayers with suitable ring structure and high charge transfer can significantly enhance the interaction between the monolayer and LiPSs, allowing them to have high capacity and high coulombic efficiency. Further diffusion studies show that LiPSs on the T-G monolayer have the low diffusion barriers, which ensures the charging and discharging rate of batteries. Our studies could provide material design principles of carbon allotrope monolayers used as anchoring materials of the high performance Li-S batteries.

Organic electrochemical transistors (OECTs) are highly versatile in terms of their form factor, fabrication approach that can be applied, and freedom in the choice of substrate material. Their ability to transduce ionic into electric signals and the use of bio-compatible organic materials makes them ideally suited for a wide range of applications, in particular in areas where electronic circuits are interfaced with biologic matter. OECT technology has attracted widespread interest in recent years, which has been accompanied by a steady increase in its performance. However, this progress was mainly driven by device optimization and less by targeting the design of new device geometries and OECT materials. To narrow this gap, this review provides an overview on the different device models that are used to explain the underlying physics governing the steady and transient behavior of OECTs. We show how the models can be used to identify synthetic targets to produce higher performing OECT materials and summarize recently reported materials classes. Overall, a road-map of future research in new device models and material design is presented summarizing the most pressing open questions in the understanding of OECTs.

Chemical looping is a class of emerging process intensification technologies that enable emission reduction of a wide range of chemical processes. The performance of oxygen carrier materials is critical to the effectiveness of the chemical looping processes. Over the past two decades, understanding of how oxygen carriers behave over chemical looping cycles continued to improve, leading to encouraging advancements in recent years, including several newly developed chemical looping applications showing promise to achieve lower CO2 footprints compared to conventional reactor technologies. Amongst the key material design considerations, having appropriate lattice oxygen activity is critical for maximising the product yield and selectivity of chemical looping processes. In this minireview, material design approaches enabling the development of oxygen carriers with well-defined and well-regulated lattice oxygen activity are overviewed and critically assessed. Besides the significant progress made, there remain key knowledge gaps in the area of lattice oxygen engineering. Lastly, the potential roles which computational tools could play in designing oxygen carriers with targeted lattice oxygen activities are discussed.

Artificial intelligence, especially machine learning (ML) and deep learning (DL) algorithms, is becoming an important tool in the fields of materials and mechanical engineering, attributed to its power to predict materials properties, design de novo materials and discover new mechanisms beyond intuitions. As the structural complexity of novel materials soars, the material design problem to optimize mechanical behaviors can involve massive design spaces that are intractable for conventional methods. Addressing this challenge, ML models trained from large material datasets that relate structure, properties and function at multiple hierarchical levels have offered new avenues for fast exploration of the design spaces. The performance of a ML-based materials design approach relies on the collection or generation of a large dataset that is properly preprocessed using the domain knowledge of materials science underlying chemical and physical concepts, and a suitable selection of the applied ML model. Recent breakthroughs in ML techniques have created vast opportunities for not only overcoming long-standing mechanics problems but also for developing unprecedented materials design strategies. In this review, we first present a brief introduction of state-of-the-art ML models, algorithms and structures. Then, we discuss the importance of data collection, generation and preprocessing. The applications in mechanical property prediction, materials design and computational methods using ML-based approaches are summarized, followed by perspectives on opportunities and open challenges in this emerging and exciting field.

The heat conduction of thermal interface materials (TIMs) is derived from the transport of electrons and phonons in the materials. Investigation on the thermal transport of electrons and phonons in TIMs will aid in promoting the advancement of TIMs with high performance. In this review, we summarize the current strategies for regulating the thermal transport of electrons and phonons during the preparation of TIMs. The interplay between the polymer matrix and fillers and the thermally conductive network formed by fillers is discussed. In addition, we present some new thermal measurement techniques to measure the interfacial thermal resistance. The reduction of interfacial thermal resistance is helpful for obtaining TIMs with larger thermal conductivity. Finally, we provide possible future research directions for the material design and measurement of interfacial thermal resistance.

The bulk photovoltaic (BPV) effect of conventional ferroelectric (FE) materials has sparked a great deal of interest due to anomalous above-bandgap photovoltage. However, large bandgaps and weak photocurrents remain longstanding challenges for FE PV materials in practical applications. To address these issues, we propose a new defect-engineering strategy and demonstrate it on a narrow bandgap centrosymmetric material, BiNbO4 (BNO): the BPV effect is introduced into BNO by tuning the defect amounts, then a defect-modified homojunction structure is constructed to enhance the BPV effect. This defect engineering strategy enables synergetic effects, e.g., enhanced light absorption, FE-like depolarization field and interfacial polarization. This homojunction structure results in two-fold promotion of photovoltage and ten-fold promotion of photocurrent, compared to the defect-modified BNO sample. We believe this new strategy will break through limitations in traditional material design and pave a novel route to future multifunctional materials, especially high performance BPV materials.

Understanding the effect of nonstoichiometry on material properties is of critical importance for the Thermal Barrier Coatings (TBCs) application. In this work, the effect of nonstoichiometry was systematically investigated in Y3NbO7, a recently identified promising TBCs material for next-generation gas turbine engines. The results show that the nonstoichiometry effect mediates the microstructure, mechanical properties, thermophysical properties, oxygen ionic conductivity and optical transmittance. The results suggest that the oxygen ionic conductivity is correlated to the mass diffusion in the oxygen-deficient fluorite oxides Y1-xNbxO1.5+x. The stoichiometric composition Y3NbO7, with the lowest thermal conductivity and slowest mass diffusion in Y1-xNbxO1.5+x series, is optimal for the TBCs application, which can be of relevance for TBCs material design and coating fabrication.

Force Spectroscopy (FS), which is one of the operating modes of Atomic Force Microscope (AFM) technique proven to be useful in many biological and medical applications, such as cancer cells recognition. Currently, many scientific institutions carry on research on the Young’s modulus of individual cancer cells in order to detect the disease at an early stage of its development. As a result of the growing interest in the use of force spectroscopy to study cells’ mechanic, this review summarizes new applications of this method to study changes in the physical and chemical properties of cells under the influence of external stimuli of different origins. The work is divided into four research areas, in which the use of AFM force spectroscopy was used to explain phenomena occurring at the early stages of intracellular organization changes. Research areas presented in this manuscript focuses on detailed description of the effect of manifold external stimuli on cells, such as: (i) cell aging, (ii) active ingredients used in the cosmetics industry to improve skin condition, (iii) nanoparticles used in biomedicine, and (iv) micro- and nano-structures of topography on the surface of substrates used for cell cultures. This review is based on a critical analysis of the latest literature reports (seven of which were created with Author’s contribution) describing the use of force spectroscopy as an effective tool to study the mechanical properties of living cells.

This article deals with initial material selection and design method of long fibre-reinforced thermoplastic (LFT) based on impact resistance requirements. In this study, effects of material propert...

The challenges in the field of chromatographic separation mainly fast and efficient separation for variety of samples has led to the changes in particle size, improvement in packing material design, development of synthetic method has provided the possibility of fabricating silica nanoparticle with different sizes in nanometer ranges. In present review, we have tried to show the journey of silica particle over the years and changes in the size, surface, internal pore size and packings. Their applications especially the mesoporous nanoparticles have also been mentioned. Keywords: Silica, Amorphous, Crystalline, Cores shell, Hybrid, Monoliths.

The success of approximate computational methods, such as molecular mechanics, or dispersion-corrected density functional theory, in the description of non-covalent interactions relies on accurate parameterizations. Benchmark data sets are thus required. This area is well developed for organic molecules and biomolecules but practically non-existent for boron clusters, which have been gaining in importance in modern drug as well as material design. To fill this gap, we have introduced two data sets featuring the most common non-covalent interaction of boron clusters, the dihydrogen bond, and calculated reference interaction energies at the "golden standard" CCSD(T)/CBS level. The boron clusters studied interact with formamide, methanol, water and methane at various distances and in two geometrical arrangements. The performance of the tested approximate methods is variable and recommendations for further use are given.

Many shape memory alloys can support large recoverable strains of a few percent by reversible stress-induced martensite transformation, yet they behave non-linear within a narrow operating temperature range. Developing the bulk metallic materials with ultra-large linear elasticity over a wide temperature range has proven to be difficult. In this work, a material design concept was proposed, that is true elastic deformation and reversible twinning-detwinning deformation run in parallel to overcome this challenge. By engineering the residual internal stress to realize the concurrency of true elastic deformation and twinning-detwinning deformation, a bulk nanocrystalline NiTi that possesses an ultra-large linear elastic strain up to 5.1 % and a high yield stress of 2.16 GPa over a wide temperature range of 270 °C was developed. This study offers a new avenue for developing the metallic materials with ultra-large linear elasticity over a wide temperature range of 270 °C (from 70 °C to −197 °C).

Hydrogen gas is rapidly approaching a global breakthrough as a carbon-free energy vector. In such a hydrogen economy, safety sensors for hydrogen leak detection will be an indispensable element along the entire value chain, from the site of hydrogen production to the point of consumption, due to the high flammability of hydrogen-air mixtures. To stimulate and guide the development of such sensors, industrial and governmental stakeholders have defined sets of strict performance targets, which are yet to be entirely fulfilled. In this Perspective, we summarize recent efforts and discuss research strategies for the development of hydrogen sensors that aim at meeting the set performance goals. In the first part, we describe the state-of-the-art for fast and selective hydrogen sensors at the research level, and we identify nanostructured Pd transducer materials as the common denominator in the best performing solutions. As a consequence, in the second part, we introduce the fundamentals of the Pd-hydrogen interaction to lay the foundation for a detailed discussion of key strategies and Pd-based material design rules necessary for the development of next generation high-performance nanostructured Pd-based hydrogen sensors that are on par with even the most stringent and challenging performance targets.

Despite the recent breakthroughs of polymer solar cells (PSCs) exhibiting a power conversion efficiency of over 17%, toxic and hazardous organic solvents such as chloroform and chlorobenzene are still commonly used in their fabrication, which impedes the practical application of PSCs. Thus, the development of eco-friendly processing methods suitable for industrial-scale production is now considered an imperative research focus. This Review provides a roadmap for the design of efficient photoactive materials that are compatible with non-halogenated green solvents (e.g., xylenes, toluene, and tetrahydrofuran). We summarize the recent development of green processing solvents and the processing methods to match with the efficient photoactive materials used in non-fullerene solar cells. We further review progress in the use of more eco-friendly solvents (i.e., water or alcohol) for achieving truly sustainable and eco-friendly PSC fabrication. For example, the concept of water- or alcohol-dispersed nanoparticles made of conjugated materials is introduced. Also, recent important progress and strategies to develop water/alcohol-soluble photoactive materials that completely eliminate the use of conventional toxic solvents are discussed. Finally, we provide our perspectives on the challenges facing the current green processing methods and materials, such as large-area coating techniques and long-term stability. We believe this Review will inform the development of PSCs that are truly clean and renewable energy sources.

In this contribution, we aim at supporting theoretical transistor material design using a combination of electronic structure theory, transport simulations, and local current analysis. Our effort f...

Abstract Quantitative modelling of precipitation kinetics can play an important role in a computational material design framework where, for example, optimization of alloying can become more efficient if it is computationally driven. Precipitation hardening (PH) stainless steels is one example where precipitation strengthening is vital to achieve optimum properties. The Langer–Schwartz–Kampmann–Wagner (LSKW) approach for modelling of precipitation has shown good results for different alloy systems, but the specific models and assumptions applied are critical. In the present work, we thus apply two state-of-the-art LSKW tools to evaluate the different treatments of nucleation and growth. The precipitation modelling is assessed with respect to experimental results for Cu precipitation in PH stainless steels. The LSKW modelling is able to predict the precipitation during ageing in good quantitative agreement with experimental results if the nucleation model allows for nucleation of precipitates with a composition far from the equilibrium and if a composition-dependent interfacial energy is considered. The modelling can also accurately predict trends with respect to alloy composition and ageing temperature found in the experimental data. For materials design purposes, it is though proposed that the modelling is calibrated by measurements of precipitate composition and fraction in key experiments prior to application. Graphic abstract

In this work, combined experimental and fractal nature analysis procedures are proposed in order to both model and design mechanical properties of porous ceramics. Several porous ceramics samples have been considered both from an in-situ experimental campaign and from the literature. Microstructural information concerning pore size distribution has been approximated by the Intermingled Fractal units (IFU) approach and effective mechanical properties are derived by a simple discrete model. The capability of the proposed methodology to reproduce high-scattered mechanical properties is fully shown and a comparison with classical bounds and estimates is also reported. Finally, the combined experimental, fractal nature analysis and homogenisation scheme is implemented as a design procedure for the technological production of advanced porous ceramics.

The use of cobalt-free LiNi0.5Mn1.5O4 (LNMO) would provide a great leap forward towards the realization of sustainable lithium-ion batteries. However, the high operating voltage remains to be a great challenge for the cathode/electrolyte stability. Herein, we report a rational material design to address these challenges by carefully tuning the synthesis parameters in order to engineer LNMO crystals with tailored surface facets, providing an exceptional rate capability and improved interfacial stability. The additional introduction of protective TMPOx coatings further enhances the long-term cycling stability, in particular, at elevated cut-off potentials up to 4.95 V, increased temperature of 40 °C, and high dis-/charge rates. As a result of the careful design of the LNMO active material particles, lithium-ion cells employing this material together with Li4Ti5O12 anodes provide an excellent rate capability with 80% of the low-rate capacity at fast dis-/charge rates of 10C combined with highly stable cycling at such high rate, as highlighted by a capacity fading of less than 5% after 1000 cycles.

Purpose. The aim of this work is to analyze the latest literature data on current state of the issue in the development of the chemical composition and heat treatment modes of steels that implement the TRIP effect under loading. Due to the deformation martensitic transformation of retained austenite, these steels have increased mechanical and operational properties with cost-saving alloying. Methodology. The information published over a long period of time in scientific literature, including domestic sources and high-rating foreign publications are used in this work. The information is systematized by the main TRIP-steels’ types and relates to their chemical composition and heat treatment technology. Findings. The article presents a retrospective of the research progress on the development of structural TRIP effect added steels namely: high-alloy single-phase metastable austenitic steels, as well as low-alloy multiphase TRIP-assisted steels, in which the TRIP effect plays an supporting role, as an additional strengthening and providing increased plasticity mechanism. The latter group of steels includes low alloy TRIP-assisted steels, δ-TRIP steels and maraging TRIP steels. The typical alloying schemes and applied heat treatment modes that make it possible to achieve the optimal phase-structural components ratio, the volume fraction and stability of retained austenite to deformation martensitic transformation in steels and, as a result, to provide an increased mechanical and operational properties were described. The key role of the carbide-free structure formation is noted, which is achieved by alloying with silicon and/or aluminum in providing high properties of steel. The prospects of using modern structural TRIP steels in the automotive and in the machine-building industry are shown. Recommendations for further research directions in this area are made. Originality. The article provides an analysis and systematization of relevant literature data on the development of technologies for the production of multiphase structural steels with retained metastable austenite, realizing the TRIP effect. Practical value. The results of the research can be used as reference materials in solving material design problems, as well as for educational purposes in the preparation of specialized professionals in engineering specialties.

Spiders, silks, and webs are marvels of nature that have inspired high-performance material design, resilient structural design, and innovative manufacturing in the materials science and engineering fields. In this article, we review the roles and mechanisms of self-assembly and spinning processes for making hierarchical structures of synthetic and natural fibers with multifunctionality. We discuss the ability of spider webs to maintain their functionality under construction while withstanding predator, human, and environmental threats, which comes from their self-assembled structures from nanoscales to macroscales. We conclude by exploring the future of novel mobile, autonomous, time- and cost-effective spider-inspired three-dimensional printing technology for making resilient biomaterials, structures, and synthetic silk materials.

Integrating artificial intelligence (AI) and computer science together with current approaches in material synthesis and optimization will act as an effective approach for speeding up the discovery of high-performance photoactive materials in organic solar cells (OSCs). Yet, like model selection in statistics, the choice of appropriate machine learning (ML) algorithms plays a vital role in the process of new material discovery in databases. In this study, we constructed five common algorithms, and introduced 565 donor/acceptor (D/A) combinations as training data sets to evaluate the practicalities of these ML algorithms and their application potential when guiding material design and D/A pairs screening. Thus, the best predictive capabilities are provided by using the random forest (RF) and boosted regression trees (BRT) approaches beyond other ML algorithms in the data set. Furthermore, >32 million D/A pairs were screened and calculated by RF and BRT models, respectively. Among them, six photovoltaic D/A pairs are selected and synthesized to compare their predicted and experimental power conversion efficiencies. The outcome of ML and experiment verification demonstrates that the RF approach can be effectively applied to high-throughput virtual screening for opening new perspectives to design of materials and D/A pairs, thereby accelerating the development of OSCs.

Computational approaches have been used effectively in material design for solid oxide fuel cells (SOFCs). As a way to improve the performance and stability of anode materials in SOFCs, the exsolution phenomenon has been extensively taken advantage of. In the exsolution process, highly active and stable nanoparticles (NPs) are formed uniformly over the surface of the host oxide due to the anchoring effects of exsolved NPs in the host’s structure. In this review, we particularly focus on how computational approaches such as density functional theory calculation, phase field modeling, and analytic methods can be used to understand the exsolution phenomenon; this knowledge can then be exploited to design enhanced anode materials for SOFCs. We first review the nature of exsolution and then look into catalytic applications of exsolved NPs. From this point, we investigate how to engineer exsolved nanoparticles to maximize their catalytic activity with a view that any enhanced performance will aid future applications.

In this paper, we use finite element analysis (FEA) to study the linear viscoelastic response of polyurea, a type of hard–soft block copolymer. A Niblack’s algorithm-based technique employed on atomic force microscopy images provides geometry inputs for the FEA model, while the viscoelastic master curves of the soft matrix are obtained via a combination of dynamic mechanical analysis data and molecular dynamic (MD) estimations. In this microstructural image-based FEA framework, we introduce an interphase area of altered properties between the hard and soft domains. Both spatial and property distributions of this interphase area affect the viscoelastic response of the copolymer system. To quantitatively investigate the impact of structural and property features of the interphase on the energy storage and dissipation of a system during linear perturbation, we develop a statistical descriptor representation of the interphase region related to physical parameters. Utilizing decision-tree and random forest concepts from machine learning, we apply a ranking algorithm to identify the most significant features for four different mechanical response descriptors. Results show that the total interphase volume fraction and shifting factor distributions in the interphase area dominate the magnitude of the tan δ peak, whereas the magnitudes of the shifting factors primarily affect the tan δ peak location in frequency space. This method allows us to readily identify the dominant features impacting individual properties and paves the way for material design of hard–soft block copolymer systems.