1 citations · 1 across the 3 of their papers we have counts for
7 papers
Feature engineering for microstructure-property mapping in organic photovoltaics
Sepideh Hashemi, Baskar Ganapathysubramanian, Stephen Casey +2
Linking the highly complex morphology of organic photovoltaic (OPV) thin films to their charge transport properties is critical for achieving high performance material system that…
Machine learning approaches for feature engineering of the crystal structure: Application to the prediction of the formation energy of cubic compounds
Prathik R. Kaundinya, Kamal Choudhary, Surya R. Kalidindi
In this study, we present a novel approach along with the needed computational strategies for efficient and scalable feature engineering of the crystal structure in compounds of di…
Signal Processing Challenges and Examples for {\it in-situ} Transmission Electron Microscopy
Josh Kacher, Yao Xie, Sven P. Voigt +4
Transmission Electron Microscopy (TEM) is a powerful tool for imaging material structure and characterizing material chemistry. Recent advances in data collection technology for TE…
Recurrent Localization Networks applied to the Lippmann-Schwinger Equation
Conlain Kelly, Surya R. Kalidindi
The bulk of computational approaches for modeling physical systems in materials science derive from either analytical (i.e. physics based) or data-driven (i.e. machine-learning bas…
Digital representation and quantification of discrete dislocation networks
Andreas E. Robertson, Surya R. Kalidindi
Dislocation networks and their evolution are known to control the mechanical properties of metal samples. However, the lack of computationally efficient and statistically rigorous…
A Bayesian Framework for the Estimation of the Single Crystal Elastic Parameters from Spherical Indentation Stress-Strain Measurements
Andrew Castillo, Surya R. Kalidindi
This paper presents a two-step Bayesian framework for the estimation of the intrinsic single crystal elastic stiffness parameters from the measurements of spherical indentation str…