Materials design for new superconductors
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phonons, thermal conductivity, energy storage (inc↗
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Developing an oxidation materials ontology for data-driven materials design
Materials data is complex, and managing and storing materials data for use and reuse is a common challenge. An ontology-based data management framework can address these challenges through encoding data attributes and relationships in a flexible way. This presentation discusses the creation of an ontology for alloy oxidation test data and reviews the logic, structure and interoperability of the ontology.
advanced alloy development↗
Materials Design via Optimized Intramolecular Noncovalent Interactions for High-Performance Organic Semiconductors
Abstract not provided
Guo, Xiaojie↗
Artificial intelligence-driven approaches for materials design and discovery
Materials design is an important component of modern science and technology, yet traditional approaches rely heavily on trial and error and can be inefficient. Computational techniques, enhanced by modern artificial intelligence, have reshaped the landscape of designing new materials. Among these approaches, inverse design has shown great promise in designing materials that meet specific property requirements. Here, in this Review, we present key computational advances in materials design over the past few decades. We follow the evolution of relevant materials design techniques, from high-throughput forward machine learning methods and evolutionary algorithms, to advanced artificial intelligence strategies such as reinforcement learning and deep generative models. We highlight the paradigm shift from conventional screening approaches to inverse generation driven by deep generative models. Finally, we discuss current challenges and future perspectives of materials inverse design. This Review may serve as a brief guide to the approaches, progress and outlook of designing future functional materials with technological relevance.
computational methods↗
Computational material design for Q&P steels with plastic instability theory
In this paper, the deformation limits of Quenching and Partitioning (Q&P) steels are examined with the plastic instability theory. For this purpose, the constituent phase properties of various Q&P steels were first experimentally obtained, and used to estimate the overall tensile stress-strain curves based on the simple rule of mixture (ROM) with the iso-strain and iso-stress assumptions. Plastic instability theory was then applied to the obtained overall stress-strain curves in order to estimate the deformation limits of the Q&P steels. A parametric study was also performed to examine the effects of various material parameters on the deformation limits of Q&P steels. Computational material design was subsequently carried out based on the information obtained from the parametric study. The results show that the plastic instability theory with iso-stress-based stress-strain curve may be used to provide the lower bound estimate of the uniform elongation (UE) for the various Q&P steels considered. The results also indicate that higher austenite stability/volume fractions, less strength difference between the primary phases, higher hardening exponents of the constituent phases are generally beneficial for the performance improvement of Q&P steels, and that various material parameters may be concurrently adjusted in a cohesive way in order to improve the performance of Q&P steel. The information from this study may be used to devise new heat treatment parameters and alloying elements to produce Q&P steels with the improved performance.
Cheng, G.↗
Novel phase diagram behavior and materials design in heterostructural semiconductor alloys
Structure and composition control the behavior of materials. Isostructural alloying is historically an extremely successful approach for tuning materials properties, but it is often limited by binodal and spinodal decomposition, which correspond to the thermodynamic solubility limit and the stability against composition fluctuations, respectively. We show that heterostructural alloys can exhibit a markedly increased range of metastable alloy compositions between the binodal and spinodal lines, thereby opening up a vast phase space for novel homogeneous single-phase alloys. We distinguish two types of heterostructural alloys, that is, those between commensurate and incommensurate phases. Because of the structural transition around the critical composition, the properties change in a highly nonlinear or even discontinuous fashion, providing a mechanism for materials design that does not exist in conventional isostructural alloys. The novel phase diagram behavior follows from standard alloy models using mixing enthalpies from first-principles calculations. Furthermore, thin-film deposition demonstrates the viability of the synthesis of these metastable single-phase domains and validates the computationally predicted phase separation mechanism above the upper temperature bound of the nonequilibrium single-phase region.
14 SOLAR ENERGY↗
Critical review and future prospects for desiccant coated heat exchangers: Materials, design, and manufacturing
Solid desiccant dehumidification is a promising alternative to vapor compression-based air-dehumidification to reduce energy consumption and improve air quality. Desiccant coated heat exchanger (DCHE), as one type of solid desiccant dehumidification system, can improve system performance and efficiency. The thermal performance and moisture removal capability of the DCHE greatly influence its dehumidification performance.The present work aims to critically analyze the designs, materials, and manufacturing methods of heat exchangers used for solid desiccant coating and look into recent developments in regular heat exchangers, potentially deployed as a substrate for DCHE applications. A comprehensive literature review of publications regarding solid desiccant materials, heat exchangers, manufacturing and coating methods, binder materials, and the performance of heat exchangers has been developed. Alternative heat exchangers are described as better options than fin and tube heat exchangers that have been considered thus far for DCHE applications. Additionally, the heat exchanger's manufacturing process and materials over their thermal and mass exchange performance have been analyzed. Despite the widespread use of fin and tube heat exchangers for solid desiccant coating, recent developments in heat exchanger design, and related fields such as manufacturing methods and materials, open the possibilities for their application in solid desiccant dehumidification systems. Lastly, the authors provide their outlook on possible developments of DCHE technology, aiming to increase systems' energy and dehumidification performance.
36 MATERIALS SCIENCE↗
MDTri: robust and efficient global mixed integer search of spaces of multiple ternary alloys: A DIRECT-inspired optimization algorithm for experimentally accessible computational material design
Computational materials design has suffered from a lack of algorithms formulated in terms of experimentally accessible variables. Here we formulate the problem of (ternary) alloy optimization at the level of choice of atoms and their composition that is normal for synthesists. Mathematically, this is a mixed integer problem where a candidate solution consists of a choice of three elements, and how much of each of them to use. This space has the natural structure of a set of equilateral triangles. We solve this problem by introducing a novel version of the DIRECT algorithm that (1) operates on equilateral triangles instead of rectangles and (2) works across multiple triangles. We demonstrate on a test case that the algorithm is both robust and efficient. Lastly, we offer an explanation of the efficacy of DIRECT -- specifically, its balance of global and local search -- by showing that 'potentially optimal rectangles' of the original algorithm are akin to the Pareto front of the 'multi-component optimization' of global and local search.
97 MATHEMATICS AND COMPUTING↗
Revealing Electronic Signatures of Lattice Oxygen Redox in Lithium Ruthenates and Implications for High-Energy Li-Ion Battery Material Designs
Anion redox in lithium transition-metal oxides such as Li 2 RuO 3 and Li 2 MnO 3 has catalyzed intensive research efforts to find transition-metal oxides with anion redox that may boost the energy density of lithium-ion batteries. The physical origin of the observed anion redox remains debatable, and more direct experimental evidence is needed. In this work, we have shown electronic signatures of oxygen–oxygen coupling, direct evidence central to lattice oxygen redox (O 2- /(O 2 ) n- ), in charged Li 2– $_x$RuO 3 after Ru oxidation (Ru 4+ /Ru 5+ ) upon first electron removal with lithium deintercalation. Experimental Ru L 3 -edge high-energy-resolution fluorescence-detected X-ray absorption spectra (HERFD-XAS), supported by ab initio simulations, revealed that the increased intensity in the high-energy shoulder upon lithium deintercalation resulted from increased O–O coupling, inducing (O–O) σ*-like states with π overlap with Ru d-manifolds, in agreement with O K-edge XAS spectra. Experimental and simulated O K-edge X-ray emission spectra further supported this observation with the broadening of the oxygen nonbonding feature upon charging, also originated from (O–O) σ* states. This lattice oxygen redox of Li 2–x RuO 3 was accompanied by a small amount of O 2 evolution in the first charge from differential electrochemistry mass spectrometry but diminished in the subsequent cycles, in agreement with the more reduced states of Ru in later cycles from Ru L 3 -edge HERFD-XAS. These observations indicated that Ru redox contributed more to discharge capacities after the first cycle. This study has pinpointed the key spectral fingerprints related to lattice oxygen redox from a molecular level and constructed a transferrable framework to rationally interpret the spectroscopic features by combining advanced experiments and theoretical calculations to design materials for Li-ion batteries and electrocatalysis applications.
25 ENERGY STORAGE↗
Computational materials design of a corrosion resistant high entropy alloy for harsh environments
Not provided.
Materials Science↗
All-optical materials design of chiral edge modes in transition-metal dichalcogenides
Monolayer transition-metal dichalcogenides are novel materials which at low energies constitute a condensed-matter realization of massive relativistic fermions in two dimensions. Here, we show that this picture breaks for optical pumping—instead, the added complexity of a realistic materials description leads to a new mechanism to optically induce topologically protected chiral edge modes, facilitating optically switchable conduction channels that are insensitive to disorder. In contrast to graphene and previously discussed toy models, the underlying mechanism relies on the intrinsic three-band nature of transition-metal dichalcogenide monolayers near the band edges. Photo-induced band inversions scale linearly in applied pump field and exhibit transitions from one to two chiral edge modes on sweeping from red to blue detuning. As a result, we develop an ab initio strategy to understand non-equilibrium Floquet–Bloch bands and topological transitions, and illustrate for WS 2 that control of chiral edge modes can be dictated solely from symmetry principles and is not qualitatively sensitive to microscopic materials details.
36 MATERIALS SCIENCE↗
Study for material analogs of FeSb 2 : Material design for thermoelectric materials
Using the ab initio evolutionary algorithm (implemented in uspex) and electronic structure calculations we investigate the properties of a new thermoelectric material FeSbAs, which is a material analog of the enigmatic thermoelectric FeSb 2 . We utilize the density functional theory and the Gutzwiller method to check the energetics. We find that FeSbAs can be made thermodynamically stable above ~ 30 GPa. We investigate the electronic structure and thermoelectric properties of FeSbAs based on the density functional theory and compare with those of FeSb 2 . Above 50 K, FeSbAs has higher Seebeck coefficients than FeSb 2 . Upon doping, the figure of merit becomes larger for FeSbAs than for FeSb 2 . Another material analog FeSbP, was also investigated, and found thermodynamically unstable even at very high pressure. Regarding FeSb 2 as a member of a family of compounds (FeSb 2 , FeSbAs, and FeSbP) we elucidate what are the chemical handles that control the gaps in this series. Here, we also investigate solubility (As or P for Sb in FeSb 2 ) we found As to be more soluble. Finally, we study a two-band model for thermoelectric properties and find that the temperature dependent chemical potential and the presence of the ionized impurities are important to explain the extremum in the Seebeck coefficient exhibited in experiments for FeSb 2 .
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Correlated materials design: prospects and challenges
The design of correlated materials challenges researchers to combine the maturing, high throughput framework of DFT-based materials design with the rapidly-developing first-principles theory for correlated electron systems. We review the field of correlated materials, distinguishing two broad classes of correlation effects, static and dynamics, and describe methodologies to take them into account. We introduce a material design workflow, and illustrate it via examples in several materials classes, including superconductors, charge ordering materials and systems near an electronically driven metal to insulator transition, highlighting the interplay between theory and experiment with a view towards finding new materials. We review the statistical formulation of the errors of currently available methods to estimate formation energies. We formulate an approach for estimating a lower-bound for the probability of a new compound to form. Correlation effects have to be considered in all the material design steps. Furthermore, these include bridging between structure and property, obtaining the correct structure and predicting material stability. We introduce a post-processing strategy to take them into account.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Charging toward improved lithium-ion polymer electrolytes: exploiting synergistic experimental and computational approaches to facilitate materials design
Ion-conducting polymer electrolytes are attractive materials for all-solid-state lithium-ion batteries (LiBs) as a result of their potential to improve performance, mitigate safety concerns, and facilitate efficient device processing. Understanding how lithium-ionic transport is influenced by the macromolecular features, such as dielectric strength, solvation site connectivity, monomer segment relaxation timescales, segregation strength, and mesophase composition, is crucial for advancing ion-conducting materials. The integration of experimental and computational efforts can provide comprehensive links between chemical and structural characteristics (e.g., ion solvation, chain mobility, morphology) and macroscopic performance properties, accelerating the adoption of next-generation polymer electrolytes. Furthermore, this perspective highlights several synergistic experimental–computational approaches that have provided unique insights into local ion and polymer interactions, chain dynamics, and thermodynamics to promote the rational design of new ion-conducting polymers. Additionally, this work concludes with several suggested areas in which methodologies can be augmented, novel properties can be realized, and polymer electrolytes can be integrated to generate more robust LiB systems.
25 ENERGY STORAGE↗
Quantified uncertainty in thermodynamic modeling for materials design
Phase fractions, compositions and energies of the stable phases as a function of macroscopic composition, temperature, and pressure (X-T-P) are the principle correlations needed for the design of new materials and improvement of existing materials. They are the outcomes of thermodynamic modeling based on the CALculation of PHAse Diagrams (CALPHAD) approach. Here, the accuracy of CALPHAD predictions vary widely in X-T-P space due to experimental error, model inadequacy and unequal data coverage. In response, researchers have developed frameworks to quantify the uncertainty of thermodynamic property model parameters and propagate it to phase diagram predictions. In most previous studies, uncertainty was represented as intervals on phase boundaries (with respect to composition or temperature) and was unable to represent the uncertainty in invariant reactions or in the stability of phase regions. In this work, we propose a suite of tools that leverages samples from the multivariate model parameter distribution to represent uncertainty in forms that surpass previous limitations and are well suited to materials design. These representations include the distribution of phase diagrams and their features, as well as the dependence of phase stability and the distributions of phase fraction, composition, activity and Gibbs energy on X-T-P location - irrespective of the total number of components. Most critically, the new methodology allows the material designer to interrogate a certain composition and temperature domain and get in return the probability of different phases to be stable, which can positively impact materials design.
36 MATERIALS SCIENCE↗
Featureless adaptive optimization accelerates functional electronic materials design
Electronic materials that exhibit phase transitions between metastable states (e.g., metal-insulator transition materials with abrupt electrical resistivity transformations) are challenging to decode. For these materials, conventional machine learning methods display limited predictive capability due to data scarcity and the absence of features that impede model training. In this article, we demonstrate a discovery strategy based on multi-objective Bayesian optimization to directly circumvent these bottlenecks by utilizing latent variable Gaussian processes combined with high-fidelity electronic structure calculations for validation in the chalcogenide lacunar spinel family. We directly and simultaneously learn phase stability and bandgap tunability from chemical composition alone to efficiently discover all superior compositions on the design Pareto front. Previously unidentified electronic transitions also emerge from our featureless adaptive optimization engine. Our methodology readily generalizes to optimization of multiple properties, enabling co-design of complex multifunctional materials, especially where prior data is sparse.
36 MATERIALS SCIENCE↗
A physics informed bayesian optimization approach for material design: application to NiTi shape memory alloys
Abstract 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.
Chemistry↗