Research Highlight

Accelerated Material Design Framework using Uncertainty-Quantified Hybrid Machine Learning/Density Functional Theory Approach

Prof. Yousung Jung’s group has developed a new accelerated high throughput screening (HTS) method using uncertainty-quantified machine learning (ML) and density functional theory (DFT) that was applied to explore the Mg-Mn-O chemical space for photoanode application. Notably, the proposed HTS scheme required only 1.5% of the target chemical space for further DFT calculations, accelerating the entire process by > 50 times for the same discovery compared to the brute-force DFT-HTS done previously. This means an improvement of the screening performance (discoverability) by more than a factor of 2 compared to the conventional ML-based HTS approach....read more