activity
20212024
most citedPhysical origin of enhanced electrical conduction in aluminum-graphene composites

10 citations · 10 across the 5 of their papers we have counts for

collaborators

5 papers

cond-mat.mtrl-sci202410 cited

Physical origin of enhanced electrical conduction in aluminum-graphene composites

K. Nepal, C. Ugwumadu, K. N. Subedi +2

The electronic and transport properties of aluminum-graphene composite materials were investigated using ab initio plane wave density functional theory. The interfacial structure i…

cond-mat.mtrl-sci2023

Automated Grain Boundary (GB) Segmentation and Microstructural Analysis in 347H Stainless Steel Using Deep Learning and Multimodal Microscopy

Shoieb Ahmed Chowdhury, M. F. N. Taufique, Jing Wang +5

Austenitic 347H stainless steel offers superior mechanical properties and corrosion resistance required for extreme operating conditions such as high temperature. The change in mic…

cs.LG2023

Neural Lumped Parameter Differential Equations with Application in Friction-Stir Processing

James Koch, WoongJo Choi, Ethan King +5

Lumped parameter methods aim to simplify the evolution of spatially-extended or continuous physical systems to that of a "lumped" element representative of the physical scales of t…

cs.CV2023

Parameters, Properties, and Process: Conditional Neural Generation of Realistic SEM Imagery Towards ML-assisted Advanced Manufacturing

Scott Howland, Lara Kassab, Keerti Kappagantula +2

The research and development cycle of advanced manufacturing processes traditionally requires a large investment of time and resources. Experiments can be expensive and are hence c…

cs.LG2021

Differential Property Prediction: A Machine Learning Approach to Experimental Design in Advanced Manufacturing

Loc Truong, WoongJo Choi, Colby Wight +4

Advanced manufacturing techniques have enabled the production of materials with state-of-the-art properties. In many cases however, the development of physics-based models of these…