6 papers
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…
The Power of the Pareto Front: Balancing Uncertain Rewards for Adaptive Experimentation in scanning probe microscopy
Yu Liu, Sergei V. Kalinin
Automated experimentation has the potential to revolutionize scientific discovery, but its effectiveness depends on well-defined optimization targets, which are often uncertain or…
Rewards-based image analysis in microscopy
Kamyar Barakati, Yu Liu, Utkarsh Pratiush +2
Imaging and hyperspectral data analysis is central to progress across biology, medicine, chemistry, and physics. The core challenge lies in converting high-resolution or high-dimen…
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…
Reward based optimization of resonance-enhanced piezoresponse spectroscopy
Yu Liu, Boris Slautin, Jason Bemis +6
Dynamic spectroscopies in Scanning Probe Microscopy (SPM) are critical for probing material properties, such as force interactions, mechanical properties, polarization switching, a…