12 papers
Physics-Informed Neural Networks for Sparse Strain-Field Reconstruction in 4D-STEM
Roberto dos Reis, Gabriel T. dos Santos, Yukun Liu +2
Quantitative strain mapping using four-dimensional scanning transmission electron microscopy (4D-STEM) typically requires densely sampled scans that can damage beam-sensitive speci…
Schema-Bound LLM Control of Scientific Instrumentation through Model Context Protocol Skills
Roberto dos Reis, Vinayak P. Dravid
Large language models (LLMs) can plan tool-mediated scientific work, but scientific instruments remain difficult to connect to such agents: vendor APIs may load only inside acquisi…
Physics-Constrained Learning of Dose-Dependent Spectral Degradation in Metal--Organic Frameworks from In Situ Low-Loss EELS
Gabriel T. dos Santos, Roberto dos Reis, Vinayak P. Dravid
Electron-beam irradiation limits atomic-resolution characterization of beam-sensitive hybrid materials, yet quantitative models that connect \textit{in situ} spectroscopy to dose-d…
Born-Qualified: An Autonomous Framework for Deploying Advanced Energy and Electronic Materials
Steven R. Spurgeon, Milad Abolhasani, Frederick Baddour +28
Autonomous science is transforming how we discover materials and chemical systems for advanced energy technologies. However, many initially promising systems never reach deployment…
Microstructural Topology as a Prescriptor for Quantum Coherence: Towards A Unified Framework for Decoherence in Superconducting Qubits
Vinayak P. Dravid, Akshay A. Murthy, Peter Lim +5
In superconducting quantum circuits, decoherence improvements are frequently obtained through process interventions that simultaneously modify surface chemistry, microstructural to…
Oxide-nitride heteroepitaxy for low-loss dielectrics in superconducting quantum circuits
David A. Garcia-Wetten, Mitchell J. Walker, Peter G. Lim +9
Superconducting qubits show great promise for the realization of fault-tolerant quantum computing, but lossy, amorphous dielectrics limit current technology. Identifying highly cry…