2 citations · 5 across the 7 of their papers we have counts for
7 papers
Physics-informed Bayesian Optimization for Quantitative High-Resolution Transmission Electron Microscopy
Xiankang Tang, Yixuan Zhang, Juri Barthel +4
Quantitative high-resolution transmission electron microscopy (HRTEM) provides an indispensable means to understand the structure-property relationships of a material in atomic dim…
Information-Theoretic Multi-Model Fusion for Target-Oriented Adaptive Sampling in Materials Design
Yixuan Zhang, Zhiyuan Li, Weijia He +4
Target-oriented discovery under limited evaluation budgets requires making reliable progress in high-dimensional, heterogeneous design spaces where each new measurement is costly,…
Accelerated Design of Mechanically Hard Magnetically Soft High-entropy Alloys via Multi-objective Bayesian Optimization
Mian Dai, Yixuan Zhang, Weijia He +7
Designing high-entropy alloys (HEAs) that are both mechanically hard and possess soft magnetic properties is inherently challenging, as a trade-off is needed for mechanical and mag…
SuperSalt: Equivariant Neural Network Force Fields for Multicomponent Molten Salts System
Chen Shen, Siamak Attarian, Yixuan Zhang +4
Molten salts are crucial for clean energy applications, yet exploring their thermophysical properties across diverse chemical space remains challenging. We present the development…
Stable diffusion for the inverse design of microstructures
Yixuan Zhang, Teng Long, Hongbin Zhang
In materials science, microstructures and their associated extrinsic properties are critical for engineering advanced structural and functional materials, yet their robust reconstr…
Generative deep learning for the inverse design of materials
Teng Long, Yixuan Zhang, Hongbin Zhang
In addition to the forward inference of materials properties using machine learning, generative deep learning techniques applied on materials science allow the inverse design of ma…
Kalman filter enhanced Adversarial Bayesian optimization for active sampling in inelastic neutron scattering
Nihad Abuawwad, Yixuan Zhang, Samir Lounis +1
Spin waves, or magnons, are fundamental excitations in magnetic materials that provide insights into their dynamic properties and interactions. Magnons are the building blocks of m…