Material Design Approach Research Articles

(Re) active materials for sensitive, adaptive and interactive design. Practices for a (re) generation of sense for well-being and comfort

The article aims to read the transition of material design approaches identifying an evolutive models with major principles and contribution into the health improvement through material innovations. The analysis follows a bottom-up approach, using a case-based reasoning methodology to study well-being concept evolution and identify new material experimentations frontiers within three approaches: Imitative, Augmentative, and Mutational. The contribution of the article reflects and suggests the introduction of new material design approaches to manage the design of advanced materials’ behaviuors in their future development, highlighting their potential impact on user satisfaction and acceptance, collective welfare improvement, performance optimization, and environmental concerns.

The Effect of Carbon Structure of DLC Coatings on Friction Characteristics of MoDTC-Derived Tribofilm by Using an In Situ Reflectance Spectroscopy

In this study, six types of DLC coatings were prepared, featuring different carbon structures (including amorphous ta-C coatings and GNC coatings with nanocrystallites) and different doped Ta amounts, to investigate friction characteristics. The results of friction tests with MoDTC-added lubricant revealed a consistent trend: DLC coatings with a higher ID/IG ratio exhibited lower friction coefficients. In addition, in situ observations using reflectance spectroscopy highlighted that the tribofilm formed on DLC coatings with a higher ID/IG ratio maintained a higher MoS2/(MoS2+MoO3)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${{\ ext{MoS}}}_{2}/({{\ ext{MoS}}}_{2}+{{\ ext{MoO}}}_{3})$$\\end{document} ratio, which exhibited a strong correlation with the friction coefficient. Measurements of a work function of each DLC coating indicated that those with a higher ID/IG ratio had a higher work function, suggesting the inclusion of a larger amount of graphite structure defects. These active defects in the graphite structure were deemed responsible for enhancing the friction reduction effect of MoDTC. The outcomes of this study propose a material design approach for DLC coatings that amplifies the effectiveness of lubricant additives in friction reduction.Graphical abstract

Enhancing ablation resistance of CuCr contact materials through metallic element doping: First-principles calculations

In this paper, a first-principles design approach for ablation-resistant contact materials was developed. Take Cu16Cr16 for example, the melting point was used as the criterion to screen the improved doped alloys, and mechanical properties were computed to guarantee that the designed doped alloys satisfy the contacts' operational requirements. This technique revealed that Cu16Cr15W1, Cu16Cr15Os1, and Cu16Cr13Co3 have stronger properties than Cu16Cr16 in terms of melting point and resistance to deformation, which can be utilized to enhance the ablation resistance and mechanical strength of the contacts. Simultaneously, the doped alloys' brittleness guarantees the welding resistance of the contacts. As a result, strengthening contact materials can be made from these doped alloys.

A physics informed bayesian optimization approach for material design: application to NiTi shape memory alloys

The design of materials and identification of optimal processing parameters constitute a complex and challenging task, necessitating efficient utilization of available data. Bayesian Optimization (BO) has gained popularity in materials design due to its ability to work with minimal data. However, many BO-based frameworks predominantly rely on statistical information, in the form of input-output data, and assume black-box objective functions. In practice, designers often possess knowledge of the underlying physical laws governing a material system, rendering the objective function not entirely black-box, as some information is partially observable. In this study, we propose a physics-informed BO approach that integrates physics-infused kernels to effectively leverage both statistical and physical information in the decision-making process. We demonstrate that this method significantly improves decision-making efficiency and enables more data-efficient BO. The applicability of this approach is showcased through the design of NiTi shape memory alloys, where the optimal processing parameters are identified to maximize the transformation temperature.

Luminescence covalent organic frameworks for metal ions detection via turntable sites

In recent years, environmental issues have been caused by heavy metals, which have not been effectively resolved. Fluorescent materials are being used as promising detectors. Covalent organic frameworks (COFs) possess excellent porosity that provides extensive space for guest molecule. The turntable skeleton is also a crucial factor in designing the target site for capturing them. In this study, the hydrazone-based crystalline H–COF-1 and H–COF-2 were successfully synthesized through a solvothermal process. Their luminescence activities are controlled from blue to green for H–COF-1 and H–COF-2 due to the turntable conjugated sites on the walls. More specifically, the intramolecular hydrogen between the ortho-hydroxyl group and imine bond constructs the conjugations binding site of H–COF-2. H–COF-2 possesses more interacted sites for metal ions and demonstrates efficient fluorescence quenching for Cu2+ at 85 % in water, surpassing the performance of H–COF-1. The selectivity and detection limits were also significantly improved as a result. The turntable sites present a novel design approach for luminescent materials as chemical sensors.

Hierarchically Porous Ceramic and Metal‐Ceramic Hybrid Materials Structured by Vat Photopolymerization‐Induced Phase Separation

Additive manufacturing techniques such as vat photopolymerization have laid the foundation for impressive advances in the 3D structuring of ceramic materials. However, simultaneous structuring of these complex‐shaped ceramic objects on the sub‐µm scale, an essential feature for a wide range of applications in separation, energy conversion and storage, adsorption or sensing, has remained a tremendous challenge. This study demonstrates how complex‐shaped polymer‐derived SiOC ceramics exhibiting hierarchical porosity ranging from the sub‐µm‐ to the millimeter‐range can be generated by combining vat photopolymerization with photopolymerization‐induced phase separation using preceramic polymer‐based phase‐separating resins. In addition to allowing single‐step, multi‐level structural control, this new processing concept allows for the chemical modification of the 3D‐printable, phase‐separating preceramic polymer resins using organometallic compounds, including the possibility to generate functional metal nanoparticles in situ during the polymer‐to‐ceramic conversion. In this manner, a chemical toolbox is provided, facilitating the introduction of Ni, Co, Mo, or La into the hierarchically structured SiOC matrix. The versatile applicability of this new materials design approach is demonstrated by employing complex‐shaped, hierarchically porous monoliths containing in situ generated Ni nanoparticles as heterogeneous catalysts for CO2 methanation, with a profound increase in catalyst performance attained by oxidative post‐treatment of the metal‐ceramic hybrid material.

Non-trivial topological phases in transition metal rich half-Heusler oxides

Topological insulators with gapless surface states and insulating bulk in non-centrosymmetric cubic systems have been extensively explored following the discovery of two-dimensional quantum spin hall effect in zincblende HgTe. In such systems the negative band inversion strength E (= E E 0) governs the robustness of the non-trivial topological states at ambient conditions. Hence, realizing large negative values of E has been a guiding motivation of several investigations reported in literature. Here, we present a material design approach which can be employed to realize large negative values of E in cubic materials such as half-Heusler (HH) oxides with 18 valence electron configurations. We explore 27 HH oxides of the form ABO (A = Li, K, Rb; B = Cu, Ag, Au) in α-, β-, and γ-phase (by placing transition metal atom at different Wyckoff positions) for their non-trivial topological phase. Off these three phases, we found that, the α-phase of nine HH oxides (wherein the transition metal atoms occupy 4a Wyckoff positions in the crystal structure) is the most promising with non-trivial topological phase which is governed by the mass-Darwin fully-relativistic effects enhancing E. Whereas the other phases were found to be either trivial semiconductors or semimetals or metals and most of them being dynamically unstable. We focus on RbAuO in α-phase with E of −1.29 eV and the effect of strain fields on the topological surface states of this compound. We conclude that the α-phase of HH oxide presented here can be synthesized experimentally for diverse room temperature applications in spintronics and nanoelectronics.

Controlled Crystallographic Texture Orientation in Structural Materials Using the Laser Powder Bed Fusion Process—A Review

Advantages of the laser powder bed fusion (LPBF) process over conventional processing methods include microstructural control capability and complex geometry parts fabrication. For most alloys, the microstructure–property relationship typically guides the LPBF process toward achieving application‐specific properties. Nonetheless, the LPBF process produces a high degree of anisotropy, primarily from the epitaxial preferred grain growth mechanisms during solidification and the consequent highly textured microstructures produced. The crystallographic texture‐controlled build concept through the LPBF process is a material design and processing approach gaining a lot of interest because of the promising unique and superior properties offered by the anisotropy accompanying the LPBF process. The numerous attempts at intentional texture‐controlled building or parts fabrication from structural materials using the LPBF process warrant an up‐to‐date review. Thus, this review presents solidification mechanisms that influence texture evolution during the LPBF process such as the melting mode, melt pool shape, influence of thermal gradient, and solidification rate. Furthermore, this review delves into the influence of LPBF process parameters on texture, accompanying microstructural evolution, and the intentional control of texture effects on properties such as mechanical, corrosion, and oxidation resistance.

Investigation on high performance and stabilized surface of AlF3-coated V2O5 micro-flower for zinc energy storage

Vanadium oxide (V2O5) cathode material, possessing abundant reserves and high theoretical capacity, has been extensively researched in aqueous zinc ion batteries (ZIBs). However, its electrochemical performance is significantly hindered by insufficient electronic conductivity, vanadium dissolution into electrolyte, and slow diffusion kinetics. In this study, the V2O5 micro-flower was first synthesized by a solvothermal method, and then modified by coating with AlF3 passivation layer, forming AlF3@V2O5 hybrid material. Impressively, AlF3@V2O5 exhibits excellent electrochemical and kinetic properties due to the special structure of V2O5 and the interfacial protection of AlF3. An exceptional rate property (325 mAh g−1 at 0.1 A g−1, 188 mAh g−1 at 15 A g−1) as well as extraordinary cycling stability with 89.3% capacity retention after 6000 cycles at 10 A g−1 can be attained with 2 wt% AlF3 addition (that is AF-2@V2O5). The computation based on density functional theory (DFT) suggests that AlF3 coating can reduce the interlayer electrostatic interaction and adsorption energy barrier between the intercalated Zn2+ and V2O5 host, thereby enabling fast redox kinetics. This study showcases the efficacy of interfacial modification of passivated coatings and presents an influential approach for material design in ZIBs.

Coexistence of quantum spin Hall and magnetic states in zigzag bismuth nanoribbons

Chemical modifications and/or simple vertical stacking of disparate van der Waals layered crystals can be used as a materials design approach for creating novel phases of matter. Here, using ab initio computations, we demonstrate the realization of an unusual state in a bismuth nanoribbon decorated with nitrogen atoms along one of the edges. In this phase, the quantum spin Hall state on one edge of the nanoribbon coexists with the ferromagnetism on the other edge. Such a coexistence is made possible by the short-range nature of the exchange interactions on the magnetic edge. As a result, the quantum spin Hall state on the opposite edge of the nanoribbon does not feel the local breaking of time-reversal symmetry on the magnetic edge. While the edge with quantum spin Hall state exhibits the typical spin-helical texture associated with the state, the magnetic edge displays ±k-asymmetry due to the interplay of Rashba and exchange effects. The latter is also a half-metal and can generate a fully spin-polarized current. We demonstrate that this coexistence of states is robust and that it is exhibited even when the nitrogen-decorated nanoribbon is placed on a substrate. In addition, with a proof-of-principle heterostructure, composed of an undecorated bismuth nanoribbon on hexagonal boron nitride, we show that this mixture of states can potentially exist even without passivation with nitrogen-atoms. In the heterostructure, an unequal relaxation along the two edges of the nanoribbon is found to be responsible for the coexistence of two states.

Characterization and analysis of filled knitted fabric formworks for advanced manufacturing of composite structures

An alternative construction methodology has been raising interest, consisting of employing fabrics as formworks. The implementation of flexible formworks allows the production of highly optimized organic structures, avoiding the use of unnecessary materials and consequently reducing construction loads, costs and waste. This study aims to integrate the experimental characterization of the mechanical behaviour of the knitted textiles used as formworks, the mechanical and deformational behaviour of the formworks while being filled with fresh mortar, and the numerical simulation of the multi-step process leading to the final structure. The integration of these different processes is essential for a sound design of this composite system as a construction strategy. To this end, this investigation identified several aspects, related to either experimental or computational mechanics that are relevant to the topic and should be further investigated, with the aim of a future integrated material and structural design approach.

Super Adhesive Fluorescent Materials for Encrypted Messages, Underwater Leak Repair and Their Potential Application in Fluorescent Tattoos.

Achieving high-performance luminescence for underwater bonding remains a significant challenge in materials science. This study addressed this issue by synthesizing a luminescent material based on an aggregation-induced emission (AIE) monomer and copolymerizing it with lipoic acid (LA) to create an AIE supramolecular polymer. The resulting copolymer exhibited strong fluorescence under ultraviolet (UV) irradiation at 365nm due to the AIE of TPEE and enabled underwater adhesion. The P(LA-TPEE) polymer demonstrated potential for digital encryption and decryption of quick response (QR) codes underwater. Furthermore, it could dissolve well in anhydrous ethanol, producing an environment-friendly and super waterproof adhesive. Most notably, the P(LA-TPEE) solution could be sprayed on human skin, creating an invisible tattoo that only became visible under UV light due to the hydrogen bond (H-bond) and π-π structures. This smart tattoo could be quickly wiped away with alcohol, avoiding the painful and harmful process of tattoo removal. It could also be repeatedly applied to draw the preferred tattoo pattern. This AIE supramolecular polymer showed great potential in underwater adhesion and repair, underwater message encryption, and non-toxic and painless invisible tattooing. Overall, this study provides a valuable approach for material design in the future. This article is protected by copyright. All rights reserved.

Simultaneous improvement on strength and conductivity of CrB2/Cu composites by inhomogeneous design

Inhomogeneous CrB2/Cu composites with 5 vol% CrB2, namely CrB2 concentrated in special areas rather than uniformly dispersed in the whole materials were prepared by powder metallurgy combined with hot extrusion process. Results show that obvious submillimeter-sized CrB2 rich-irregular regions or band structures can be observed on the vertical and parallel to extrusion directions, respectively. The inhomogeneous degree can be adjusted by using the ball milled CrB2-Cu composite powder with different sizes, and has big influence on the strength and electrical conductivity of the composites. When the size of composite powder is 425–850 μm, the best combination properties of strength (436 MPa) and electrical conductivity (82.84%) can be obtained. Compared with the conventional homogeneous with the same chemical composition, the strength increases by 89%, but the electrical conductivity only decreases by 6%. This work provides a new approach for material design, which can coordinate between strength-conductivity of Cu matrix composites, effectively.

Potential of Integrated Component-Driven Material Design to Improve Crash Box Performance

The crushing of crash boxes is a complex phenomenon characterized by a strong interaction of structural and material properties. Many attempts to improve their energy absorption by adopting one aspect resulted in unacceptable unprogressive bucking. Thus, special considerations are required for crash box optimization including both material and structural effects. In this study, the structural behavior of the crash box is analyzed and a new design approach is introduced to fulfill these requirements. Currently, components, processes, and materials are mainly developed independently. However, to exploit the full potential of modern materials in component design, integrative development work is necessary. Component performance-based requirements and corresponding local material properties must be taken into account concurrently. In this work, a component-driven material design approach is presented, in which local-material-property requirements are derived from component simulations. This new approach is demonstrated by the use case of a quasistatically deformed crash box produced out of steel DP600 for the optimization target “energy absorption”. The finite element simulations were carried out on the crash box, and required material properties for improving the crash box performance were derived based on the simulations. Heat treatment strategies were developed afterwards and experimentally validated to fulfill these requirements. The finite element (FE) simulations based on the experimentally extracted material properties reveal the potential of the component-driven material design approach to improve the crash box performance. The introduced approach enables exploiting the full energy-absorption capacity of the material while ensuring the desired service behavior of the component.

Machine learning for shock compression of solids using scarce data

Data-driven machine learning techniques can be useful for the rapid evaluation of material properties in extreme environments, particularly in cases where direct access to the materials is not possible. Such problems occur in high-throughput material screening and material design approaches where many candidates may not be amenable to direct experimental examination. In this paper, we perform an exhaustive examination of the applicability of machine learning for the estimation of isothermal shock compression properties, specifically the shock Hugoniot, for diverse material systems. A comprehensive analysis is conducted where effects of scarce data, variances in source data, feature choices, and model choices are systematically explored. New modeling strategies are introduced based on feature engineering, including a feature augmentation approach, to mitigate the effects of scarce data. The findings show significant promise of machine learning techniques for design and discovery of materials suited for shock compression applications.

Optically selective SiC-based nanocomposite objects derived from titanium and boron-modified polycarbosilanes

Herein, we introduce a bottom-up material design approach of optically selective SiC-based nanocomposite objects. Precursors have been firstly synthesized by reaction of allylhydridopolycarbosilane with titanium and boron complexes before a pyrolysis at 1000 °C in flowing argon to deliver single-phase amorphous Si–Ti–C–N(B,H) ceramics. The later was then heat-treated up to 1800 °C under argon. Relatively dense nanocomposites made of TiCxN1-x (0 ≤ x ≤ 1) nanocrystals homogeneously formed in situ in a SiCxN4-x-type phases (0 ≤ x ≤ 4) have been isolated after heat-treatment at 1400 °C. Above 1400 °C, our experimental data showed a continuous evolution of carbon and nitrogen contents up to 1800 °C due to carbothermal reduction reactions forming carbide phases while releasing nitrogen-containing species. Thus, heat-treatment at 1800 °C led to porous and fully crystallized TiC(N)/SiC(B) nanocomposites that displayed a maximal optical selectivity of 1.67 measured at room temperature; a value significantly increased compared to the SiC(B) counterpart.

Material research in the design field: a gender gap analysis

Within the framework of technology, design and material production are profoundly influenced by the class relations of production. Artifacts and objects are no longer seen as separate from society, but as part of the social matter that regulates and holds the society together. The development and use of materials are also closely connected to the social systems in which they operate. To date we have few empirical observations in this regard, especially on the investigation of the female presence in the discourse of material design. The connection between material research and gender has recently become an issue of social and technological relevance, as there is a lack of data on women activity. In addition, the communicative aspect of the material design approach will be analysed through forms of social constructivism, which foresees people working together constructing artifacts, and their potential to enhance the perception of matter in its forthcoming dimension. This contribution aims to investigate the approaches of women designers to the innovation of materials. It will start from an historical perspective via figures such as the Italian architect Anna Castelli Ferrieri up to the new generations of women designers and researchers who consider specific factors for each study and observation, applying what is called the “clinical approach”. We will encompass selected examples of good practices of social sustainability through the inclusion of women in the field of material research and production. In addition, we consider the profound impact of contemporary good design practices, questioning what impact they have on social life and the environment, due to the relationships with our artifacts and habitat under the climate crisis. Overall, we propose that gender issues are finally embedded in the design discourse and some results are emerging.

Accurate property prediction with interpretable machine learning model for small datasets via transformed atom vector

Machine learning techniques can greatly accelerate material discovery while high-dimensional representation often causes overfitting problems and leads to poor model performance. Building a structure-property relationship with low-dimensional representation is always an open challenge, especially for diverse structures within small datasets. To address this issue, a low-dimensional representation named the transformed atom vector (TAV) is proposed, which is a crystal-graph-based descriptor. As an example, we apply it in two-dimensional materials and predict the band gap at the Heyd-Scuseria-Ernzerhof level with only 500 samples at acceptable accuracy. Moreover, TAV representation retains interpretability, based on which a property-oriented search method through element substitution is developed. This work provides a universal low-dimensional representation containing rich material information, as well as an intuitive interpretation approach for material design, which improves the feasibility and interpretability of machine learning models for small datasets and helps realize accurate yet meaningful property prediction at a lower cost.

Cetyltrimethylammonium bromide assisted intercalation and exfoliation for titanium carbide with enlarged interlayer spacing for high-performance supercapacitor

It is well known that the interlayer spacing of two-dimensional (2D) materials is crucial in enhancing their electrochemical performance. However, the interlayer spacing of titanium carbide (Ti3C2Tx) nanosheets prepared by current synthetic methods is either limited or the experimental methods are too complicated. Based on this, we propose a new synthesis method using the mixture of hydrogen fluoride (HF) and cetyltrimethylammonium bromide (CATB) as the etching agent, and the interlayer spacing of the Ti3C2Tx nanosheets obtained by exfoliation is as high as 37.8 Å. The enlarged interlayer spacing not only exposes more active sites but is sufficient to accommodate more insertion and deinsertion of cations, which achieves a significantly improved capacitance value of 322 F/g with scan rate of 5 mV/s in acidic electrolyte and excellent rate performance. In particular, the advantages of the enlarged interlayer spacing in energy storage are more reflected both in neutral electrolyte and alkaline electrolyte. The density functional theory (DFT) analysis indicates that the optimal energy storage performance is achieved only with the optimal interlayer spacing. This work provides a guiding design approach for MXene materials and high-performance supercapacitors.

Sensitivity of structural and electronic properties of Li-ion battery cathode materials to Hubbard U correction: an efficient first-principle approach

A new material design approach using first-principles density functional theory (DFT) calculations with acceptable precision can elucidate many critical features in emerging high-performance lithium-ion battery fields. However, the dominant impact of transition metals (TM) as the major component and/or modification dopant element with localized d-electrons in this material system, which needs so-called Hubbard correction U, limits DFT to many extents. As the U correction is not completely transferable, one may need to recalculate it for the same input structure with structural or elemental changes. While the accurate calculation of U is costly, it is worth investigating its sensitivity to input system parameters, such as cell size, structure, and chemical composition, to dismiss unessential recalculations, especially in high-throughput schemes. Furthermore, implementing DFT + U to get the expected properties is computationally expensive too. The necessity of including the U correction for expected properties or its small variation should be investigated. In this study, Hubbard correction for TM using a density functional perturbation theory (DFPT) approach was considered to investigate the electronic structure and structural stability of LiNiO2, LiCoO2, and LiNi0.75Co0.167Al0.083O2. The effect of system parameters (cell size, structure, and chemical composition) on U values was considered for different systems. The dependency of calculated electronic densities of states, lattice parameters, preferred doping sites, and vacancy formation energy, as well as charge voltage, was investigated, and low and high sensitivities were discussed. Furthermore, the effect of different doping scenarios with Co and Al on structural stability was studied with the efficient DFT + U approach. The results showed that the structural variation due to doping and vacancy site formation has a negligible effect on calculated U values. Significant correlation of predicted electronic properties with U for all systems was observed, while calculated lattice parameters, as well as preferred doping sites, reflected very low dependency on U variations.