20 citations · 119 across the 77 of their papers we have counts for
4 papers · 1 filter
InSpecLearn4SDL: Interpretable Spectral Features Predict Conductivity in Self-Driving Doped Conjugated Polymer Labs
Ankush Kumar Mishra, Jacob P. Mauthe, Nicholas Luke +2
To accelerate materials discovery using self-driving labs (SDLs), we present a machine learning pipeline that predicts the electrical conductivity of doped conjugated polymers usin…
3D Multiphase Heterogeneous Microstructure Generation Using Conditional Latent Diffusion Models
Nirmal Baishnab, Ethan Herron, Aditya Balu +3
The ability to generate 3D multiphase microstructures on-demand with targeted attributes can greatly accelerate the design of advanced materials. Here, we present a conditional lat…
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…
Physics-aware Deep Generative Models for Creating Synthetic Microstructures
Rahul Singh, Viraj Shah, Balaji Pokuri +3
A key problem in computational material science deals with understanding the effect of material distribution (i.e., microstructure) on material performance. The challenge is to syn…