most citedDeep learning with reflection high-energy electron diffraction images to predict cation ratio in SrTiO thin films

9 citations · 11 across the 3 of their papers we have counts for

collaborators

5 papers

cond-mat.mtrl-sci2026

An Open-Source Hardware and Software Toolkit to Enable Agentic RHEED-Guided Thin-Film Synthesis

Asraful Haque, Christopher M. Rouleau, Rama K. Vasudevan +1

Reflection high-energy electron diffraction (RHEED) provides rich information about evolving surfaces during thin-film growth, but non-automated, operator-dependent alignment and f…

physics.optics2026★ 2 cited

Direct observation of ultrafast defect-bound and free exciton dynamics in defect-engineered WS monolayers

Tae Gwan Park, Xufan Li, Kyungnam Kang +7

Defects in two-dimensional transition metal dichalcogenides (TMDCs) broadly affect their optical and electronic properties. Directly capturing the ultrafast processes of exciton tr…

cond-mat.mtrl-sci2026

Active Learning for Tractable and Reproducible Pulsed Laser Deposition

Jackson S. Bentley, Christopher Rouleau, Ilia N. Ivanov +8

This paper shows how data-driven machine learning approaches can improve growth control, reproducibility, and physical insight in the pulsed laser deposition (PLD) growth of correl…

cond-mat.mtrl-sci2025

Human-AI collaborative autonomous synthesis with pulsed laser deposition for remote epitaxy

Asraful Haque, Daniel T. Yimam, Jawad Chowdhury +10

Autonomous laboratories typically rely on data-driven decision-making, occasionally with human-in-the-loop oversight to inject domain expertise. Fully leveraging AI agents, however…

cond-mat.mtrl-sci2025★ 9 cited

Deep learning with reflection high-energy electron diffraction images to predict cation ratio in SrTiO thin films

Sumner B. Harris, Patrick T. Gemperline, Christopher M. Rouleau +2

Machine learning (ML) with in situ diagnostics offers a transformative approach to accelerate, understand, and control thin film synthesis by uncovering relationships between synth…