5 papers
AEcroscopyWave: Towards Self-Driving Characterization Platforms for Agentic AI
Yongtao Liu, Jawad Chowdhury, Ganesh Narasimha +8
The characterization of electronic materials has traditionally been stratified into two distinct regimens: industry-scale automated systems to inspect materials for defects and ens…
Attention-Based Explainability for Structure-Property Relationships
Boris N. Slautin, Utkarsh Pratiush, Yongtao Liu +4
Machine learning methods are emerging as a universal paradigm for constructing correlative structure-property relationships in materials science based on multimodal characterizatio…
Materials Discovery in Combinatorial and High-throughput Synthesis and Processing: A New Frontier for SPM
Boris N. Slautin, Yongtao Liu, Kamyar Barakati +13
For over three decades, scanning probe microscopy (SPM) has been a key method for exploring material structures and functionalities at nanometer and often atomic scales in ambient,…
Building Workflows for Interactive Human in the Loop Automated Experiment (hAE) in STEM-EELS
Utkarsh Pratiush, Kevin M. Roccapriore, Yongtao Liu +3
Exploring the structural, chemical, and physical properties of matter on the nano- and atomic scales has become possible with the recent advances in aberration-corrected electron e…
Autonomous scanning probe microscopy with hypothesis learning: Exploring the physics of domain switching in ferroelectric materials
Yongtao Liu, Anna Morozovska, Eugene Eliseev +4
We report the development and implementation of a hypothesis learning based automated experiment, in which the microscope operating in the autonomous mode identifies the physical l…