Research
Our Research Tools
In nexSAS, we have developed a platform - AiNU - for extraction of fundamental materials parameters using physics-based machine learning. It has been used in a study of thermal degradation of perovskite, and it serves as one of the cornerstones of the studies in nexSAS.
We anticipate intensive use of AiNU in future across a diverse array of projects and we are excited about collaboration. If you think AiNU or any of our works might be useful for your research, please do not hesitate contacting us at hualin.zhan@anu.edu.au.
Research Projects
Mechanistic analysis of perovskite degradation for stable photovoltaics
Physics-based AI for mechanistic analysis of perovskite degradation
Physics-based AI for Robots
Empowering the robotic high-throughput platform to think like a scientist.
Atomic origin of instability at the perovskite interfaces
AI-enhanced atomistic study of interface physics.
Transport phenomenon at the tri-phase interface in hydrogen energy systems
This research investigates the transport of electrons, ions, and molecules at the tri-phase interface in hydrogen energy systems.
Development of a low-cost and quantitative materials analysis platform by physics-based machine learning
ACAP Postdoctoral Fellowship (R4, 2023).
Development of user friendly machine learning toolkit for perovskite solar cell analysis
An Honours project for Bachelor of Computer Science