Active Learning‐Guided Accelerated Discovery of Ultra‐Efficient High‐Entropy Thermoelectrics (Adv. Mater. 10/2026)
Abstract
Active Learning In their Research Article (DOI: 10.1002/adma.202515054), Min-Wook Oh, Yeon Sik Jung, YongJoo Kim, and co-workers accelerate the discovery of high-entropy chalcogenides with zT > 2 via active learning. The framework pinpoints top materials in only 80 experiments out of 16 206 candidates (< 0.5% of the design space).
Fields of Study & Subjects
Machine Learning in Materials Science
Advanced Thermoelectric Materials and Devices
High Entropy Alloys Studies
Publication details
- Journal / source
- Advanced Materials
- Volume
- 38
- Issue
- 10
- Publication date
- 1 February 2026
- Language
- EN