Nanoparticles in Noisy Chemical Environments: Insights from a Million Electronic Excitation Calculations
Ari Chakraborty, Syracuse University
The relationship between structure and property is central to chemistry and enables the understanding of chemical phenomena and processes. Need for an efficient conformational sampling of chemical systems arise from the presence of solvents and the existence of non-zero temperatures. However, conformational sampling of structures to compute molecular quantum mechanical properties is computationally expensive because a large number of electronic structure calculations are required. In this work, the development and implementation of the effective stochastic potential (ESP) method is presented to perform efficient conformational sampling of molecules. The overarching goal of this work is to alleviate the computational bottleneck associated with performing a large number of electronic structure calculations required for conformational sampling. We introduce the concept of a deformation potential and demonstrate its existence by the proof-by-construction approach. A statistical description of the fluctuations in the deformation potential due to non-zero temperature was obtained using infinite-order moment expansion of the distribution. The formal mathematical definition of the ESP was derived using functional minimization approach to match the infinite-order moment expansion for the deformation potential. Practical implementation of the ESP was obtained using the random-matrix theory method. The developed method was applied to calculate quasiparticle gap, exciton binding energies, and excitation energies of solvated CdSe and PbSe nanoparticles at 300K. The need for large sample size to obtain statistically meaningful results was demonstrated by calculating ensemble-averaged electronic excitation energies from a sample size of ESP-CIS calculations. The results from these calculations demonstrated the efficacy of the ESP method for performing efficient conformational sampling. We envision that the fundamental nature of this work will not only extend our knowledge of chemical systems at non-zero temperatures but will also generate new insights for innovative technological applications.
Reference:
[1] Jeremy A. Scher, Michael G. Bayne, Amogh Srihari, Shikha Nangia, and Arindam Chakraborty. "Development of effective stochastic potential method using random matrix theory for efficient conformational sampling of semiconductor nanoparticles at non-zero temperatures." The Journal of chemical physics (2018) 149, 014103. https://doi.org/10.1063/1.5026027
[2] Jeremy A. Scher, Niranjan Govind, and Arindam Chakraborty. "Evidence of Skewness and Sub-Gaussian Character in Temperature Dependent Distributions of One Million Electronic Excitation Energies in PbS Quantum Dots." Journal of Physical Chemistry Letters (ASAP) https://dx.doi.org/10.1021/acs.jpclett.9b03103
[3] Peter F. McLaughlin and Arindam Chakraborty “Compact Real-Space Representation of Excited States Using Frequency-Dependent Explicitly Correlated Electron–Hole Interaction Kernel”. JCTC (2020), 16, 5762-5770 https://doi.org/10.1021/acs.jctc.9b01238