Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Toward the design of ultrahigh-entropy alloys via mining six million texts.

ABSTRACT: It has long been a norm that researchers extract knowledge from literature to design materials. However, the avalanche of publications makes the norm challenging to follow. Text mining (TM) is efficient in extracting information from corpora. Still, it cannot discover materials not present in the corpora, hindering its broader applications in exploring novel materials, such as high-entropy alloys (HEAs). Here we introduce a concept of "context similarity" for selecting chemical elements for HEAs, based on TM models that analyze the abstracts of 6.4 million papers. The method captures the similarity of chemical elements in the context used by scientists. It overcomes the limitations of TM and identifies the Cantor and Senkov HEAs. We demonstrate its screening capability for six- and seven-component lightweight HEAs by finding nearly 500 promising alloys out of 2.6 million candidates. The method thus brings an approach to the development of ultrahigh-entropy alloys and multicomponent materials.

SUBMITTER: Pei Z

PROVIDER: S-EPMC9813346 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Toward the design of ultrahigh-entropy alloys via mining six million texts.

Pei Zongrui Z Yin Junqi J Liaw Peter K PK Raabe Dierk D

Nature communications 20230104 1

It has long been a norm that researchers extract knowledge from literature to design materials. However, the avalanche of publications makes the norm challenging to follow. Text mining (TM) is efficient in extracting information from corpora. Still, it cannot discover materials not present in the corpora, hindering its broader applications in exploring novel materials, such as high-entropy alloys (HEAs). Here we introduce a concept of "context similarity" for selecting chemical elements for HEAs ...[more]

PMID: 36599862

Similar Datasets

Author Correction: Toward the design of ultrahigh-entropy alloys via mining six million texts.

Project description: Not available

| S-EPMC10275856 | biostudies-literature

Design of antiferroelectric polarization configuration for ultrahigh capacitive energy storage via increasing entropy.

Project description:Electric field induced antiferroelectric-ferroelectric phase transition is a double-edged sword for energy storage properties, which not only offers a congenital superiority with substantial energy storage density but also poses significant challenges such as large polarization hysteresis and poor efficiency, deteriorating the operation and service life of capacitors. Here, entropy increase effect is utilized to simultaneously break the long-range antiferroelectric order and locally adjust the fourfold commensurate modulated polarization configuration, leading to a breakthrough in the trade-off between recoverable energy storge density (14.8 J cm-3) and efficiency (90.2%) in medium-entropy antiferroelectrics. The embedding of non-polar phase regions in the incommensurate antiferroelectric matrices, revealing as a mixture of commensurate, incommensurate, and relaxor antiferroelectric polarization configurations, contributes to the diffuse antiferroelectric-ferroelectric phase transition, enhanced phase transition electric field, delayed polarization saturation, and efficient recovery of polarization. This work demonstrates that controlling local diverse antiferroelectric polarization configurations by increasing entropy is an effective avenue to develop high-performance energy storage antiferroelectrics, with implications that can be extended to other materials and functionalities.

| S-EPMC11748700 | biostudies-literature

First principles-based design of lightweight high entropy alloys.

Project description:Recently, the design of lightweight high entropy alloys (HEAs) with a mass density lower than 5 g/cm3 has attracted much research interest in structural materials. We applied a first principles-based high-throughput method to design lightweight HEAs in single solid-solution phase. Three lightweight quinary HEA families were studied: AlBeMgTiLi, AlBeMgTiSi and AlBeMgTiCu. By comprehensively exploring their entire compositional spaces, we identified the most promising compositions according to the following design criteria: the highest stability, lowest mass density, largest elastic modulus and specific stiffness, along with highest Pugh's ratio. We found that HEAs with the topmost compositions exhibit a negative formation energy, a low density and high specific Young's modulus, but a low Pugh's ratio. Importantly, we show that the most stable composition, Al0.31Be0.15Mg0.14Ti0.05Si0.35 is energetically more stable than its metallic compounds and it significantly outperforms the current lightweight engineering alloys such as the 7075 Al alloy. These results suggest that the designed lightweight HEAs can be energetically more stable, lighter, and stiffer but slightly less ductile compared to existing Al alloys. Similar conclusions can be also drawn for the AlBeMgTiLi and AlBeMgTiCu. Our design methodology and findings serve as a valuable tool and guidance for the experimental development of lightweight HEAs.

| S-EPMC10728166 | biostudies-literature

Giant energy-storage density with ultrahigh efficiency in lead-free relaxors via high-entropy design.

Project description:Next-generation advanced high/pulsed power capacitors rely heavily on dielectric ceramics with high energy storage performance. However, thus far, the huge challenge of realizing ultrahigh recoverable energy storage density (Wrec) accompanied by ultrahigh efficiency (η) still existed and has become a key bottleneck restricting the development of dielectric materials in cutting-edge energy storage applications. Here, we propose a high-entropy strategy to design "local polymorphic distortion" including rhombohedral-orthorhombic-tetragonal-cubic multiphase nanoclusters and random oxygen octahedral tilt, resulting in ultrasmall polar nanoregions, an enhanced breakdown electric field, and delayed polarization saturation. A giant Wrec ~10.06 J cm-3 is realized in lead-free relaxor ferroelectrics, especially with an ultrahigh η ~90.8%, showing breakthrough progress in the comprehensive energy storage performance for lead-free bulk ceramics. This work opens up an effective avenue to design dielectric materials with ultrahigh comprehensive energy storage performance to meet the demanding requirements of advanced energy storage applications.

| S-EPMC9163056 | biostudies-literature

High-throughput design of high-performance lightweight high-entropy alloys.

Project description:Developing affordable and light high-temperature materials alternative to Ni-base superalloys has significantly increased the efforts in designing advanced ferritic superalloys. However, currently developed ferritic superalloys still exhibit low high-temperature strengths, which limits their usage. Here we use a CALPHAD-based high-throughput computational method to design light, strong, and low-cost high-entropy alloys for elevated-temperature applications. Through the high-throughput screening, precipitation-strengthened lightweight high-entropy alloys are discovered from thousands of initial compositions, which exhibit enhanced strengths compared to other counterparts at room and elevated temperatures. The experimental and theoretical understanding of both successful and failed cases in their strengthening mechanisms and order-disorder transitions further improves the accuracy of the thermodynamic database of the discovered alloy system. This study shows that integrating high-throughput screening, multiscale modeling, and experimental validation proves to be efficient and useful in accelerating the discovery of advanced precipitation-strengthened structural materials tuned by the high-entropy alloy concept.

| S-EPMC8282813 | biostudies-literature

Design of high bulk moduli high entropy alloys using machine learning.

Project description:In this work, the authors have demonstrated the use of machine learning (ML) models in the prediction of bulk modulus for High Entropy Alloys (HEA). For the first time, ML has been used for optimizing the composition of HEA to achieve enhanced bulk modulus values. A total of 12 ML algorithms were trained to classify the elemental composition as HEA or non-HEA. Among these models, Gradient Boosting Classifier (GBC) was found to be the most accurate, with a test accuracy of 78%. Further, six regression models were trained to predict the bulk modulus of HEAs, and the best results were obtained by LASSO Regression model with an R-square value of 0.98 and an adjusted R-Square value of 0.97 for the test data set. This work effectively bridges the gap in the discovery and property analysis of HEAs. By accelerating material discovery via providing alternate means for designing virtual alloy compositions having favourable bulk modulus for respective applications, this work opens new avenues of applications of HEAs.

| S-EPMC10665368 | biostudies-literature

Design metastability in high-entropy alloys by tailoring unstable fault energies.

Project description:Metastable alloys with transformation-/twinning-induced plasticity (TRIP/TWIP) can overcome the strength-ductility trade-off in structural materials. Originated from the development of traditional alloys, the intrinsic stacking fault energy (ISFE) has been applied to tailor TRIP/TWIP in high-entropy alloys (HEAs) but with limited quantitative success. Here, we demonstrate a strategy for designing metastable HEAs and validate its effectiveness by discovering seven alloys with experimentally observed metastability for TRIP/TWIP. We propose unstable fault energies as the more effective design metric and attribute the deformation mechanism of metastable face-centered cubic alloys to unstable martensite fault energy (UMFE)/unstable twin fault energy (UTFE) rather than ISFE. Among the studied HEAs and steels, the traditional ISFE criterion fails in more than half of the cases, while the UMFE/UTFE criterion accurately predicts the deformation mechanisms in all cases. The UMFE/UTFE criterion provides an effective paradigm for developing metastable alloys with TRIP/TWIP for an enhanced strength-ductility synergy.

| S-EPMC9462695 | biostudies-literature

Design of Hierarchical Porosity Via Manipulating Chemical and Microstructural Complexities in High-Entropy Alloys for Efficient Water Electrolysis.

Project description:Achieving a porous architecture with multiple-length scales and utilizing the synergetic effects of multicomponent chemicals bring up new opportunities for further improving the electrocatalytic performance of nanocatalysts. Herein, the synthesis of a self-supported hierarchical porous electrocatalyst based on a high-entropy alloy (HEA) containing multiple transitional metals via physical metallurgy and dealloying strategies is reported. Microscale phase separation and nanoscale spinodal decomposition are modulated in a highly concentrated FeCoNiCu HEA, which makes it possible to obtain a porous structure with different length scales, i.e., relatively large porous channels formed by removing one separated phase and ultrafine mesopores obtained from leaching out one decomposition phase. The resultant hierarchical porous HEA exhibits superior water splitting performance, which takes full advantage of the enlarged surface area offered by the bi-continuous mesoporous structure with the exceptional intrinsic reactivity originating from the synergetic electronic effects of the different components in alloying. Moreover, the microscale porous structure plays an important role in the significantly improved mass transportation, as well as the durability during electrocatalysis. This effective strategy that simultaneously utilizes the chemical and microstructural advantages of HEAs opens up a new avenue for developing HEA-based, high-performance porous electrocatalysts for various energy conversion/store applications.

| S-EPMC9036019 | biostudies-literature

Theory-guided design of high-entropy alloys with enhanced strength-ductility synergy.

Project description:Metallic alloys have played essential roles in human civilization due to their balanced strength and ductility. Metastable phases and twins have been introduced to overcome the strength-ductility tradeoff in face-centered cubic (FCC) high-entropy alloys (HEAs). However, there is still a lack of quantifiable mechanisms to predict good combinations of the two mechanical properties. Here we propose a possible mechanism based on the parameter κ, the ratio of short-ranged interactions between closed-pack planes. It promotes the formation of various nanoscale stacking sequences and enhances the work-hardening ability of the alloys. Guided by the theory, we successfully designed HEAs with enhanced strength and ductility compared with other extensively studied CoCrNi-based systems. Our results not only offer a physical picture of the strengthening effects but can also be used as a practical design principle to enhance the strength-ductility synergy in HEAs.

| S-EPMC10154317 | biostudies-literature

Mining human periodic behaviors via tensor factorization and entropy

Project description: Not available

| S-EPMC10909198 | biostudies-literature