36 citations · 83 across the 20 of their papers we have counts for
11 papers · 1 filter
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…
Scientific Exploration with Expert Knowledge (SEEK) in Autonomous Scanning Probe Microscopy with Active Learning
Utkarsh Pratiush, Hiroshi Funakubo, Rama Vasudevan +2
Microscopy techniques have played vital roles in materials science, biology, and nanotechnology, offering high-resolution imaging and detailed insights into properties at nanoscale…
Invariant Discovery of Features Across Multiple Length Scales: Applications in Microscopy and Autonomous Materials Characterization
Aditya Raghavan, Utkarsh Pratiush, Mani Valleti +6
Physical imaging is a foundational characterization method in areas from condensed matter physics and chemistry to astronomy and spans length scales from atomic to universe. Images…
Integration of Scanning Probe Microscope with High-Performance Computing: fixed-policy and reward-driven workflows implementation
Yu Liu, Utkarsh Pratiush, Jason Bemis +8
The rapid development of computation power and machine learning algorithms has paved the way for automating scientific discovery with a scanning probe microscope (SPM). The key ele…
Evolution of ferroelectric properties in SmxBi1-xFeO3 via automated Piezoresponse Force Microscopy across combinatorial spread libraries
Aditya Raghavan, Rohit Pant, Ichiro Takeuchi +6
Combinatorial spread libraries offer a unique approach to explore evolution of materials properties over the broad concentration, temperature, and growth parameter spaces. However,…
Bayesian Co-navigation: Dynamic Designing of the Materials Digital Twins via Active Learning
Boris N. Slautin, Yongtao Liu, Hiroshi Funakubo +3
Scientific advancement is universally based on the dynamic interplay between theoretical insights, modelling, and experimental discoveries. However, this feedback loop is often slo…
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…
Co-orchestration of Multiple Instruments to Uncover Structure-Property Relationships in Combinatorial Libraries
Boris N. Slautin, Utkarsh Pratiush, Ilia N. Ivanov +6
The rapid growth of automated and autonomous instrumentations brings forth an opportunity for the co-orchestration of multimodal tools, equipped with multiple sequential detection…
Coexistence and interplay of two ferroelectric mechanisms in Zn1-xMgxO
Jonghee Yang, Anton V. Ievlev, Anna N. Morozovska +7
Ferroelectric materials promise exceptional attributes including low power dissipation, fast operational speeds, enhanced endurance, and superior retention to revolutionize informa…
Unraveling the Impact of Initial Choices and In-Loop Interventions on Learning Dynamics in Autonomous Scanning Probe Microscopy
Boris N. Slautin, Yongtao Liu, Hiroshi Funakubo +1
The current focus in Autonomous Experimentation (AE) is on developing robust workflows to conduct the AE effectively. This entails the need for well-defined approaches to guide the…