8 citations · 9 across the 7 of their papers we have counts for
7 papers
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…
Substrate-Mediated Evaporation and Stochastic Evolution of Supported Au Nanoparticles
Dmitri N. Zakharov, Xiaohui Qu, Hong Wang +6
We use in situ transmission electron microscopy with automated tracking to study supported gold nanoparticles (NPs) during high-temperature vacuum annealing. \rev{The average mass…
Ultra-fast Vacancy Migration: A Novel Approach for Synthesizing Sub-10 nm Crystalline Transition Metal Dichalcogenide Nanocrystals
Pawan Kumar, Jiazheng Chen, Andrew C. Meng +9
Two-dimensional materials, such as transition metal dichalcogenides (TMDCs), have the potential to revolutionize the field of electronics and photonics due to their unique physical…
Elucidation of Relaxation Dynamics Beyond Equilibrium Through AI-informed X-ray Photon Correlation Spectroscopy
James P. Horwath, Xiao-Min Lin, Hongrui He +7
Understanding and interpreting dynamics of functional materials \textit{in situ} is a grand challenge in physics and materials science due to the difficulty of experimentally probi…
Surface Rearrangement and Evaporation Kinetics of Supported Gold Nanoparticle Catalysts
James P. Horwath, Colin Lehman-Chong, Aleksandra Vojvodic +1
Heterogeneous catalysts consisting of supported metallic nanoparticles typically derive exceptional catalytic activity from their large proportion of under-coordinated surface site…
Direct Visualisation of Out-of-Equilibrium Structural Transformations in Atomically-Thin Chalcogenides
Pawan Kumar, James P. Horwath, Alexandre C. Foucher +5
Two-dimensional (2D) transition metal dichalcogenides (TMDCs) have been the subject of sustained research interest due to their extraordinary electronic and optical properties. The…
Understanding Important Features of Deep Learning Models for Transmission Electron Microscopy Image Segmentation
James P. Horwath, Dmitri N. Zakharov, Remi Megret +1
Cutting edge deep learning techniques allow for image segmentation with great speed and accuracy. However, application to problems in materials science is often difficult since the…