9 citations · 14 across the 10 of their papers we have counts for
10 papers
Composition-Driven Phase Evolution in Sm-Doped BiFeO3 via Latent-Field Reconstruction of Atomically Resolved STEM Data
Newsha Javanmardi, Christopher T. Nelson, Anna N. Morozovska +3
Functionalities of ferroelectric materials are governed by the spatial organization and coupling of polarization, strain, lattice rotation, and structural order accessible via atom…
Causal Discovery from Data Assisted by Large Language Models
Kamyar Barakati, Alexander Molak, Chris Nelson +3
Knowledge driven discovery of novel materials necessitates the development of the causal models for the property emergence. While in classical physical paradigm the causal relation…
Automated Materials Discovery Platform Realized: Scanning Probe Microscopy of Combinatorial Libraries
Yu Liu, Aditya Raghavan, Utkarsh Pratiush +13
Combinatorial materials libraries provide a powerful platform for mapping how physical properties evolve across binary and ternary cross-sections of multicomponent phase diagrams.…
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…
Real-time experiment-theory closed-loop interaction for autonomous materials science
Haotong Liang, Chuangye Wang, Heshan Yu +6
Iterative cycles of theoretical prediction and experimental validation are the cornerstone of the modern scientific method. However, the proverbial "closing of the loop" in experim…
SANE: Strategic Autonomous Non-Smooth Exploration for Multiple Optima Discovery in Multi-modal and Non-differentiable Black-box Functions
Arpan Biswas, Rama Vasudevan, Rohit Pant +3
Both computational and experimental material discovery bring forth the challenge of exploring multidimensional and multimodal parameter spaces, such as phase diagrams of Hamiltonia…
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,…
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…
A case study of multi-modal, multi-institutional data management for the combinatorial materials science community
Sarah I. Allec, Eric S. Muckley, Nathan S. Johnson +9
Although the convergence of high-performance computing, automation, and machine learning has significantly altered the materials design timeline, transformative advances in functio…