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The Journal of Physical Chemistry. A|February 16, 2022
Enabling Rapid and Accurate Construction of CCSD(T)-Level Potential Energy Surface of Large Molecules Using Molecular Tailoring ApproachSubodh S Khire, Nalini D Gurav, Apurba Nandi, et al.
The Journal of Chemical Physics|April 24, 2017
A combined theoretical and experimental study of phenol-(acetylene)<sub>n</sub> (n ≤ 7) clustersGurmeet Singh, Apurba Nandi, Shridhar R Gadre, et al.
Cognitive Neurodynamics|July 3, 2025
A multilayer deep neural network framework for hemodynamic assessment of cognitive load management during problem-solving tasksPriyanka Paul, Shaoni Banerjee, Apurba Nandi, et al.
The Journal of Physical Chemistry Letters|May 19, 2021
Breaking the Coupled Cluster Barrier for Machine-Learned Potentials of Large Molecules: The Case of 15-Atom AcetylacetoneChen Qu, Paul L Houston, Riccardo Conte, et al.
The Journal of Chemical Physics|February 9, 2021
Δ-machine learning for potential energy surfaces: A PIP approach to bring a DFT-based PES to CCSD(T) level of theoryApurba Nandi, Chen Qu, Paul L Houston, et al.
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