57 citations · 314 across the 23 of their papers we have counts for
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Can Machine Learning Potentials Be More Accurate Than the Methods They Are Trained On?
Pavlo O. Dral, Yi-Fan Hou, Yuxinxin Chen +4
Although machine learning potentials (MLPs) generalize across configurational and chemical compound spaces, their accuracy is commonly believed to be limited by their training meth…
Adaptive Expansions of the Optimized Effective Potential in Physically Motivated Response Spaces
Gabriel Chirchir, Aditi Singh, Yan Lukashevich +4
The optimized effective potential (OEP) method provides an exact framework for incorporating orbital-dependent exchange within Kohn-Sham (KS) density-functional theory (DFT). Its p…
A Unified Dielectric-Dependent Hybrid Functional for Accurate Band Gaps across Dimensions
Subrata Jana, Manoar Hossain, Arghya Ghosh +3
Predicting fundamental band gaps across material classes and dimensionalities remains a central challenge in electronic-structure theory. Here, we show that intrinsic dielectric sc…
Nonlocal Orbital-Free Kinetic Energy Functional from the Jellium-with-Gap Model for Finite Systems
Abhishek Bhattacharjee, Subrata Jana, Szymon Smiga +1
The quasi-linear scaling of orbital-free density functional theory (OF-DFT) with system size makes it a computationally efficient alternative to conventional Kohn--Sham density fun…
Accurate starting points for one-shot and Bethe-Salpeter Equation calculations via effective tuning of range-separated hybrid functionals
Aditi Singh, Subrata Jana, Szymon Śmiga
The accuracy of one-shot and Bethe-Salpeter equation (BSE) calculations depends strongly on the underlying starting-point eigensystem, which is commonly obtained from a me…
Frontier Orbital Engineering in Heteroatom-Doped Prototypical Organic Dyes for Dye-Sensitized Solar Cells
Aditi Singh, Ram Dhari Pandey, Subrata Jana +3
The computational design of heteroatom-doped organic dyes for dye-sensitized solar cells (DSSCs) remains challenging, as predictive methods must accurately describe long-range char…