activity
20172026
most citedOn-the-fly Closed-loop Autonomous Materials Discovery via Bayesian Active Learning

549 citations · 1.7k across the 44 of their papers we have counts for

collaborators
Showing 2026Show all

7 papers · 1 filter

eess.IV2026

AutoRASOR: Autonomous Rapid Scanning Electron Microscope Operator

Kevin Zhang, Mohammad Taha, Rafael Espinosa Castañeda +7

Scanning Electron Microscopy (SEM) is a foundational technique for characterizing material microstructure, which dictates many fundamental physical and chemical properties. With th…

physics.data-an2026

Accelerating Electrochemical Impedance Spectroscopy Measurements by Reducing Reliance on Noisy Low-Frequency Data

Qiuyu Shi, Naohiro Fujinuma, Yonatan Kurniawan +4

Electrochemical impedance spectroscopy (EIS) is a powerful tool for probing kinetic and transport processes in electrochemical systems, but its practical use is often limited by th…

cond-mat.mtrl-sci2026

Physics-informed time-series forecasting of perovskite photoluminescence stability

Alexander Wieczorek, Manuel Kober-Czerny, Fábio Lopes +5

Accelerated ageing using elevated temperatures and illumination is one of the most common methods to rapidly study the stability of novel semiconductor materials. However, as the p…

cond-mat.mtrl-sci2026

Building a physics-aware AI ecosystem for solid-state hydrogen storage materials

Seong-Hoon Jang, Yiwen Yao, Chuanyu Liu +66

Hydrogen storage remains a central bottleneck for scalable hydrogen energy systems due to the multiscale and coupled nature of the thermodynamics, kinetics, and microstructural evo…

cond-mat.mtrl-sci2026

Diversity-Aware Active Learning Builds Materials Datasets for Current and Future Objectives

Rafael Espinosa Castañeda, Ashley Dale, Hongchen Wang +6

Materials science data collection can be expensive, making dataset reuse and long-term utility important for future discovery. In practice, data collection often prioritizes proper…

cond-mat.mtrl-sci2026

Materials Acceleration Platform for Electrochemistry: a Platform for Autonomous Electrochemistry

Daniel Persaud, Mike Werezak, Mark Xu +9

Corrosion testing is slow, labor-intensive, and sensitive to operator technique, limiting the generation of large, high-quality datasets for data-driven materials discovery. The Ma…

physics.plasm-ph2026

Autonomous Sampling and SHAP Interpretation of Deposition-Rates in Bipolar HiPIMS

Alexander Wieczorek, Nathan Rodkey, Jan Sommerhäuser +2

High-power impulse magnetron sputtering (HiPIMS) offers considerable control over ion energy and flux, making it invaluable for tailoring the microstructure and properties of advan…