APL Machine Learning
About APL Machine Learning
APL Machine Learning features vibrant and timely research for two communities: researchers who use machine learning (ML) and data-driven approaches for physical sciences and related disciplines, and researchers from these disciplines who work on novel concepts, including materials, devices, systems, and algorithms relevant for the development of better ML and AI technologies.
- Website: https://pubs.aip.org/aip/aml
- Current Issue: https://pubs.aip.org/aip/aml/issue
News
27 Aug 2025
Tohoku University
Researchers at Tohoku University have unified experimental and computational data into one valuable resource: a map that instantly guides scientists to suitable materials out of countless candidates.
06 Aug 2024
Singapore University of Technology and Design
In a multi-institutional collaboration, one SUTD researcher finds a way to optimise the design of perovskite tandem solar cells using machine learning.
28 Jun 2024
Tohoku University
To form qubit states in semiconductor materials, it requires tuning for numerous parameters. But as the number of qubits increases, the amount of parameters also increases, thereby complicating this process. Now, Tohoku University researchers have automated this process, overcoming a significant barrier to realizing quantum computers.