7 citations · 9 across the 11 of their papers we have counts for
11 papers
Synthesis and Characterization of Compositionally Complex (Gd/Ho/Er/Dy)2Zr2O7 Thin Film Combinatorial Library
Dalton A. Pearl, Jade Holliman, Reece Emory +13
High-throughput synthesis and characterization of novel ceramic materials with improved thermomechanical properties and phase stability are needed to accelerate the discovery of ne…
SPEAR: Structure Property Explainability with Attention Regularization
Aditya Raghavan, Utkarsh Pratiush, Dalton A. Pearl +4
Machine learning is increasingly used to learn structure property relationships from spectroscopic and diffraction data, yet its adoption in materials discovery is often limited by…
Autonomous Probe Microscopy with Robust Bag-of-Features Multi-Objective Bayesian Optimization: Pareto-Front Mapping of Nanoscale Structure-Property Trade-Offs
Kamyar Barakati, Haochen Zhu, C Charlotte Buchanan +3
Combinatorial materials libraries are an efficient route to generate large families of candidate compositions, but their impact is often limited by the speed and depth of character…
Bayesian Co-Navigation of a Computational Physical Model and AFM Experiment to Autonomously Survey a Combinatorial Materials Library
Boris N. Slautin, Kamyar Barakati, Yu Liu +3
Building autonomous experiment workflows requires transcending beyond the data-driven surrogate models to incorporate and dynamically refine physical theory during exploration. Her…
Accelerated Materials Discovery through Cost-Aware Bayesian Optimization of Real-World Indentation Workflows
Vivek Chawla, Stephen Puplampu, Haochen Zhu +3
Accelerating the discovery of mechanical properties in combinatorial materials requires autonomous experimentation that accounts for both instrument behavior and experimental cost.…
Morphotropic Phase Boundary (MPB) Induced Enhancement of Ferroelectric and Piezoelectric Properties in Li and Ta modified K0.5Na0.5NbO3
Satyaranjan Sahoo, Dhiren K. Pradhan, Shalini Kumari +9
Lead-free (K0.48Na0.48Li0.04)(Nb1-xTax)O3 (KNLNT-x) ceramics were synthesized to study the effects of Li and Ta substitution on phase transition behavior, microstructure, and ferro…
SAM: Task-Adaptive SAM with Physics-Guided Rewards
Kamyar Barakati, Utkarsh Pratiush, Sheryl L. Sanchez +5
Image segmentation is a critical task in microscopy, essential for accurately analyzing and interpreting complex visual data. This task can be performed using custom models trained…
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,…
Machine Learning-Based Reward-Driven Tuning of Scanning Probe Microscopy: Towards Fully Automated Microscopy
Yu Liu, Roger Proksch, Jason Bemis +8
Since the dawn of scanning probe microscopy (SPM), tapping or intermittent contact mode has been one of the most widely used imaging modes. Manual optimization of tapping mode not…
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…