6 citations · 8 across the 22 of their papers we have counts for
23 papers
Strategies for Deploying AI Agents in Production at Scientific User Facilities
Ming Du, Xiangyu Yin, Michael Prince +40
Agentic artificial intelligence (AI) is moving beyond research demonstrations toward production use at scientific user facilities, including light sources, neutron sources, nanosci…
APEXA: Execution-Integrity Enforcement for Multi-Agent LLM Automation of Synchrotron Data Reduction
Pawan K. Tripathi, Hemant Sharma, Andrew Chuang +1
LLM agents can make expert scientific workflows accessible through natural language, but a plausible response does not establish that the requested computation ran. This matters at…
On-chip Bragg peak extraction from MHz frame rate X-ray detectors using a cellular automaton architecture
S. Fowler, S. Strempfer, D. Beniwal +13
High-frame rate pixel detectors can produce data volumes that exceed available off-chip bandwidth, yet in many applications only a sparse subset of each frame carries relevant info…
Artifact-centered Claim-aware Observability for Autonomous Scientific Agents
Xiangyu Yin, Ming Du, Michael H. Prince +1
Autonomous scientific agents now increasingly propose ideas, write code, run experiments, analyze results, and even draft papers. Observe and audit those agents are necessary but l…
XRF-to-Optical Field-of-View Localization with Vision Language Models
Xiangyu Yin, Tatjana Paunesku, Letonia Copeland-Hardin +7
Registering images acquired with different microscopy modalities is essential for relating complementary measurements of the same specimen. In correlative X-ray fluorescence (XRF)…
Acquisition Geometry-Assisted Whole-Group Localization of X-ray Fluorescence Maps in Optical Microscopy Images
Xiangyu Yin, Tatjana Paunesku, Letonia Copeland-Hardin +7
X-ray fluorescence (XRF) microscopy maps elemental distributions, while optical microscopy can provide complementary morphological context. Localizing XRF fields of view (FOVs) in…
An End-to-End Differentiable Forward Model for High-Energy Diffraction Microscopy
Hemant Sharma, Nina Andrejevic, Simon Zhang +1
High-Energy Diffraction Microscopy (HEDM) recovers crystallographic orientation, strain, and grain position from rotating-crystal X-ray diffraction patterns. Existing forward model…
A corrective agentic hybrid RAG and an operations-grounded evaluation for a scientific facility
Rajat Sainju, Dariusz Jarosz, Hairong Shang +5
Scientific user facilities accumulate decades of operational knowledge that no single search index covers: electronic logbooks, technical documents, internal wikis, operations chat…
CVEvolve: Autonomous Algorithm Discovery for Unstructured Scientific Data Processing
Ming Du, Xiangyu Yin, Yanqi Luo +4
Scientific data processing often requires task-specific algorithms or AI models, creating a barrier for domain scientists who need to analyze their data but may not have extensive…
AlphaDiffract: Automated Crystallographic Analysis of Powder X-ray Diffraction Data
Nina Andrejevic, Ming Du, Hemant Sharma +6
Materials identification and structural understanding from powder X-ray diffraction (PXRD) data is a long-standing challenge in materials science, fundamental to discovering and ch…
EAA: Automating materials characterization with vision language model agents
Ming Du, Yanqi Luo, Srutarshi Banerjee +3
We present Experiment Automation Agents (EAA), a vision-language-model-driven agentic system designed to automate complex experimental microscopy workflows. EAA integrates multimod…
Pty-Chi: A PyTorch-based modern ptychographic data analysis package
Ming Du, Hanna Ruth, Steven Henke +11
Ptychography has become an indispensable tool for high-resolution, non-destructive imaging using coherent light sources. The processing of ptychographic data critically depends on…
Fidelity-preserving enhancement of ptychography with foundational text-to-image models
Ming Du, Volker Rose, Junjing Deng +3
Ptychographic phase retrieval enables high-resolution imaging of complex samples but often suffers from artifacts such as grid pathology and multislice crosstalk, which degrade rec…
Operating advanced scientific instruments with AI agents that learn on the job
Aikaterini Vriza, Michael H. Prince, Tao Zhou +2
Advanced scientific user facilities, such as next generation X-ray light sources and self-driving laboratories, are revolutionizing scientific discovery by automating routine tasks…
DONUT: Physics-aware Machine Learning for Real-time X-ray Nanodiffraction Analysis
Aileen Luo, Tao Zhou, Ming Du +3
Coherent X-ray scattering techniques are critical for investigating the fundamental structural properties of materials at the nanoscale. While advancements have made these experime…
Demonstration of an AI-driven workflow for dynamic x-ray spectroscopy
Ming Du, Mark Wolfman, Chengjun Sun +2
X-ray absorption near edge structure (XANES) spectroscopy is a powerful technique for characterizing the chemical state and symmetry of individual elements within materials, but re…
Ptychographic Image Reconstruction from Limited Data via Score-Based Diffusion Models with Physics-Guidance
Refik Mert Cam, Junjing Deng, Rajkumar Kettimuthu +2
Ptychography is a data-intensive computational imaging technique that achieves high spatial resolution over large fields of view. The technique involves scanning a coherent beam ac…
Homomorphic data compression for real time photon correlation analysis
Sebastian Strempfer, Zichao Wendy Di, Kazutomo Yoshii +8
The construction of highly coherent x-ray sources has enabled new research opportunities across the scientific landscape. The maximum raw data rate per beamline now exceeds 40 GB/s…
Optical Control of Adaptive Nanoscale Domain Networks
Marc Zajac, Tao Zhou, Tiannan Yang +13
Adaptive networks can sense and adjust to dynamic environments to optimize their performance. Understanding their nanoscale responses to external stimuli is essential for applicati…
Deep Learning of Structural Morphology Imaged by Scanning X-ray Diffraction Microscopy
Aileen Luo, Tao Zhou, Martin V. Holt +2
Scanning X-ray nanodiffraction microscopy is a powerful technique for spatially resolving nanoscale structural morphologies by diffraction contrast. One of the critical challenges…
Predicting ptychography probe positions using single-shot phase retrieval neural network
Ming Du, Tao Zhou, Junjing Deng +3
Ptychography is a powerful imaging technique that is used in a variety of fields, including materials science, biology, and nanotechnology. However, the accuracy of the reconstruct…
Three-dimensional Hard X-ray Ptychographic Reflectometry Imaging on Extended Mesoscopic Surface Structures
Peco Myint, Ashish Tripathi, Michael J. Wojcik +7
Many nano and quantum devices, with their sizes often spanning from millimeters down to sub-nanometer, have intricate low-dimensional, non-uniform, or hierarchical structures on su…
Spontaneous supercrystal formation during a strain-engineered metal-insulator transition
O. Yu. Gorobtsov, L. Miao, Z. Shao +13
Mott metal-insulator transitions possess electronic, magnetic, and structural degrees of freedom promising next generation energy-efficient electronics. We report a previously unkn…