[HTML][HTML] Accelerated discovery of nanostructured high-entropy and multicomponent alloys via high-throughput strategies
Nanostructured materials (NsMs) exhibit many interesting and useful properties; yet they are
generally unstable at elevated temperatures limiting their process methods and applications …
generally unstable at elevated temperatures limiting their process methods and applications …
High energy absorption design of porous metals using deep learning
M Tang, L Wang, Z Xin, Z Luo - International Journal of Mechanical …, 2024 - Elsevier
Due to its remarkable energy absorption properties, porous metals have widespread
applications in engineering. However, the high randomness of pore morphology greatly …
applications in engineering. However, the high randomness of pore morphology greatly …
Efficient structure-informed featurization and property prediction of ordered, dilute, and random atomic structures
Abstract Structure-informed materials informatics is a rapidly evolving discipline of materials
science relying on the featurization of atomic structures or configurations to construct vector …
science relying on the featurization of atomic structures or configurations to construct vector …
Application of machine learning in polyimide structure design and property regulation
W Huo, H Wang, L Guo, R Zheng… - High Performance …, 2025 - journals.sagepub.com
Polyimide (PI) is widely used in modern industry due to its excellent properties. Its synthesis
methods and property research have significantly progressed. However, the design and …
methods and property research have significantly progressed. However, the design and …
Efficient Generation of Grids and Traversal Graphs in Compositional Spaces towards Exploration and Path Planning Exemplified in Materials
Many disciplines of science and engineering deal with problems related to compositions,
ranging from chemical compositions in materials science to portfolio compositions in …
ranging from chemical compositions in materials science to portfolio compositions in …
High-entropy oxides as energy materials: from complexity to rational design
Z Yang, X Xiang, J Yang, ZY Zhao - Materials Futures, 2024 - iopscience.iop.org
Abstract High-entropy oxides (HEOs), with their multi-principal-element compositional
diversity, have emerged as promising candidates in the realm of energy materials. This …
diversity, have emerged as promising candidates in the realm of energy materials. This …
Denoising diffusion probabilistic models for generative alloy design
Inverse material design is an extremely challenging optimization task made difficult by, in
part, the highly nonlinear relationship linking performance with composition. Quantitative …
part, the highly nonlinear relationship linking performance with composition. Quantitative …
Data-driven inverse design of MoNbTiVWZr refractory multicomponent alloys: Microstructure and mechanical properties
Multicomponent refractory alloys have the potential to operate in high-temperature
environments. Alloys with heterogeneous/composite microstructure exhibit an optimal …
environments. Alloys with heterogeneous/composite microstructure exhibit an optimal …
Efficient generation of grids and traversal graphs in compositional spaces towards exploration and path planning
Diverse disciplines across science and engineering deal with problems related to
compositions, which exist in non-Euclidean simplex spaces, rendering many standard tools …
compositions, which exist in non-Euclidean simplex spaces, rendering many standard tools …
Supervised machine learning for multi-principal element alloy structural design
J Berry, KA Christofidou - Materials Science and Technology, 2024 - journals.sagepub.com
The application of supervised Machine Learning (ML) in material science, especially
towards the design of structural Multi-Principal Element Alloys (MPEAs) has rapidly …
towards the design of structural Multi-Principal Element Alloys (MPEAs) has rapidly …