6 papers · 1 filter
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…
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…
Octupole-driven spin-transfer torque switching of all-antiferromagnetic tunnel junctions
Jaimin Kang, Mohammad Hamdi, Shun Kong Cheung +23
Magnetic tunnel junctions (MTJs) based on ferromagnets are canonical devices in spintronics, with wide-ranging applications in data storage, computing, and sensing. They simultaneo…
Towards Space Group Determination from EBSD Patterns: The Role of Deep Learning and High-throughput Dynamical Simulations
Alfred Yan, Muhammad Nur Talha Kilic, Gert Nolze +4
The design of novel materials hinges on the understanding of structure-property relationships. However, in recent times, our capability to synthesize a large number of materials ha…
Electron-Induced Radiation Chemistry in Environmental Transmission Electron Microscopy
Kunmo Koo, Nikhil S. Chellam, Sangyoon Shim +4
Environmental transmission electron microscopy (E-TEM) enables direct observation of nanoscale chemical processes crucial for catalysis and materials design. However, the high-ener…