20 citations · 28 across the 10 of their papers we have counts for
10 papers
Achieving 5-angstrom-resolution diffraction contrast with an uncorrected electron probe and nanosized defect characterizations
Yao Li, Austin C. Houston, Ziang Yu +8
Atomic-resolution micrographs remain limited in application due to small field of view and low numbers of recorded defects. Defect imaging with reliable statistics in transmission…
Hierarchical automation of scanning probe microscopy through agentic orchestration and algorithmic control
Boris N. Slautin, Sheryl L. Sanchez, Aidan Swanger +5
Rapid advances in agentic artificial intelligence enable scientific systems to interpret open-ended objectives, combine heterogeneous information, invoke specialized tools, and rev…
From Photons to Electrons: Accelerated Materials Discovery via Random Libraries and Automated Scanning Transmission Electron Microscopy
Boris Slautin, Kamyar Barakati, Utkarsh Pratiush +10
The real-world implementation of materials prediction algorithms remains limited by persistent characterization bottlenecks in materials discovery, where photon-based probe techniq…
Towards Self-Optimizing Electron Microscope: Robust Tuning of Aberration Coefficients via Physics-Aware Multi-Objective Bayesian Optimization
Utkarsh Pratiush, Austin Houston, Richard Liu +2
Realizing high-throughput aberration-corrected Scanning Transmission Electron Microscopy (STEM) exploration of atomic structures requires rapid tuning of multipole probe correctors…
Mic-hackathon 2024: Hackathon on Machine Learning for Electron and Scanning Probe Microscopy
Utkarsh Pratiush, Austin Houston, Kamyar Barakati +70
Microscopy is a primary source of information on materials structure and functionality at nanometer and atomic scales. The data generated is often well-structured, enriched with me…
Roadmap on Atomic-scale Semiconductor Devices
Steven R. Schofield, Andrew J. Fisher, Eran Ginossar +47
Spin states in semiconductors provide exceptionally stable and noise-resistant environments for qubits, positioning them as optimal candidates for reliable quantum computing techno…
Unsupervised Reward-Driven Image Segmentation in Automated Scanning Transmission Electron Microscopy Experiments
Kamyar Barakati, Utkarsh Pratiush, Austin C. Houston +2
Automated experiments in scanning transmission electron microscopy (STEM) require rapid image segmentation to optimize data representation for human interpretation, decision-making…
Implementing dynamic high-performance computing supported workflows on Scanning Transmission Electron Microscope
Utkarsh Pratiush, Austin Houston, Sergei V Kalinin +1
Scanning Transmission Electron Microscopy (STEM) coupled with Electron Energy Loss Spectroscopy (EELS) presents a powerful platform for detailed material characterization via rich…
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…
Human-in-the-loop: The future of Machine Learning in Automated Electron Microscopy
Sergei V. Kalinin, Yongtao Liu, Arpan Biswas +5
Machine learning methods are progressively gaining acceptance in the electron microscopy community for de-noising, semantic segmentation, and dimensionality reduction of data post-…