8 papers · 1 filter
Closed-loop discovery of out-of-distribution processing protocols by evolutionary search and uncertainty-aware learning
Yu Liu, Stanislav Udovenko, Ching-Che Lin +4
Many materials and chemical systems exhibit history-dependent responses, where functional outcomes are governed not only by final-state variables but by the time-dependent sequence…
LLM-Guided Open Hypothesis Learning from Autonomous Scanning Probe Microscopy Experiments
Boris Slautin, Utkarsh Pratiush, Yu Liu +2
Autonomous experimentation has transformed microscopy and materials discovery by enabling closed-loop optimization including imaging and spectroscopy tuning, strucutre property rel…
Mechanism-Resolved PFM of Ferroionic and Ferroelectric Responses in Thickness-Gradient Hf0.5Zr0.5O2 Libraries
Yu Liu, Yi-Xiu Chen, Haotong Liang +2
Resolving growth mechanisms and thickness evolution of functional properties is one of the key tasks in materials discovery and optimization involving thin-film materials, traditio…
Domain Switching on the Pareto Front: Multi-Objective Deep Kernel Learning in Automated Piezoresponse Force Microscopy
Yu Liu, Utkarsh Pratiush, Kamyar Barakati +5
Ferroelectric polarization switching underpins the functional performance of a wide range of materials and devices, yet its dependence on complex local microstructural features ren…
Exploring Domain Wall Pinning in Ferroelectrics via Automated High Throughput AFM
Kamyar Barakati, Yu Liu, Hiroshi Funakubo +1
Domain-wall dynamics in ferroelectric materials are strongly position-dependent since each polar interface is locked into a unique local microstructure. This necessitates spatially…
Reward driven workflows for unsupervised explainable analysis of phases and ferroic variants from atomically resolved imaging data
Kamyar Barakati, Yu Liu, Chris Nelson +4
Rapid progress in aberration corrected electron microscopy necessitates development of robust methods for the identification of phases, ferroic variants, and other pertinent aspect…