6 citations · 11 across the 4 of their papers we have counts for
6 papers
Audacity of huge: overcoming challenges of data scarcity and data quality for machine learning in computational materials discovery
Aditya Nandy, Chenru Duan, Heather J. Kulik
Machine learning (ML)-accelerated discovery requires large amounts of high-fidelity data to reveal predictive structure-property relationships. For many properties of interest in m…
MOFSimplify: Machine Learning Models with Extracted Stability Data of Three Thousand Metal-Organic Frameworks
A. Nandy, G. Terrones, N. Arunachalam +3
We report a workflow and the output of a natural language processing (NLP)-based procedure to mine the extant metal-organic framework (MOF) literature describing structurally chara…
Using Machine Learning and Data Mining to Leverage Community Knowledge for the Engineering of Stable Metal-Organic Frameworks
Aditya Nandy, Chenru Duan, Heather J. Kulik
Although the tailored metal active sites and porous architectures of MOFs hold great promise for engineering challenges ranging from gas separations to catalysis, a lack of underst…
Machine learning to tame divergent density functional approximations: a new path to consensus materials design principles
Chenru Duan, Shuxin Chen, Michael G. Taylor +2
Computational virtual high-throughput screening (VHTS) with density functional theory (DFT) and machine-learning (ML)-acceleration is essential in rapid materials discovery. By nec…
Unusual Transport Properties with Non-Commutative System-Bath Coupling Operators
Chenru Duan, Chang-Yu Hsieh, Junjie Liu +1
Understanding non-equilibrium heat transport is crucial for controling heat flow in nano-scale systems. We study thermal energy transfer in a generalized non-equilibrium spin-boson…
A Nonequilibrium Variational Polaron Theory to Study Quantum Heat Transport
ChangYu Hsieh, Junjie Liu, Chenru Duan +1
We propose a nonequilibrium variational polaron transformation, based on an ansatz for nonequilibrium steady state (NESS) with an effective temperature, to study quantum heat trans…