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Pokuri Balaji

Title(s):

Publications

1. Ryno, S. M., R. Noruzi, C. Karunasena, B. S. S. Pokuri, S. Li, B. Ganapathysubramanian, and C. Risko
(2022). Following the crystal growth of anthradithiophenes through atomistic molecular dynamics sim-
ulations and graph characterization. Molecular Systems Design & Engineering.
2. Li, S., B. S. S. Pokuri, S. M. Ryno, A. Nkansah, C. De’Vine, B. Ganapathysubramanian, and C. Risko
(2020). Determination of the Free Energies of Mixing of Organic Solutions through a Combined Molec-
ular Dynamics and Bayesian Statistics Approach. Journal of chemical information and modeling 60(3), 1424–
1431.
3. Pokuri, B. S. S., S. Ghosal, A. Kokate, S. Sarkar, and B. Ganapathysubramanian (2019). Interpretable deep
learning for guided microstructure-property explorations in photovoltaics. npj Computational Materials
5(1), 1–11.
4. Pokuri, B. S. S., J. Stimes, K. O’Hara, M. L. Chabinyc, and B. Ganapathysubramanian (2019). GRATE: A
framework and software for GRaph based Analysis of Transmission Electron Microscopy images of poly-
mer films. Comput. Mater. Sci. 163, 1–10.
5. Shah, V., A. Joshi, S. Ghosal, B. Pokuri, S. Sarkar, B. Ganapathysubramanian, and C. Hegde (2019). Encod-
ing invariances in deep generative models. arXiv: 1906.01626.
6. Pfeifer, S., B. S. S. Pokuri, P. Du, and B. Ganapathysubramanian (Mar. 2018). Process optimization for
microstructure-dependent properties in thin film organic electronics. Mater. Discov. 11, 6–13.
7. Pokuri, B. S. S., A. Lofquist, C. M. Risko, and B. Ganapathysubramanian (Sept. 2018). PARyOpt: A soft-
ware for Parallel Asynchronous Remote Bayesian Optimization. arXiv Prepr. arXiv: 1809.04668.
8. Pokuri, B. S. S., J. Sit, O. Wodo, D. Baran, T. Ameri, C. J. Brabec, A. J. Moule, and B. Ganapathysubra-
manian (Aug. 2017). Nanoscale Morphology of Doctor Bladed versus Spin-Coated Organic Photovoltaic
Films. Adv. Energy Mater. 7(22), 1701269.
9. Pokuri, B. S. S. and B. Ganapathysubramanian (2016). Morphology control in polymer blend fibers—a
high throughput computing approach. Modelling and Simulation in Materials Science and Engineering 24(6),
065012.
10. Wodo, O., J. Zola, B. S. S. Pokuri, P. Du, and B. Ganapathysubramanian (Jan. 2015). Automated, high
throughput exploration of process–structure–property relationships using the MapReduce paradigm.
Mater. Discov. 1, 21–28.

11. Pfeifer, S., B. S. S. Pokuri, O. Wodo, and B. Ganapathysubramanian (2020). “Quantifying the effects of
noise on early states of spinodal decomposition:: Cahn–Hilliard–Cook equation and energy-based met-
rics”. In: Uncertainty Quantification in Multiscale Materials Modeling. Elsevier, pp.301–327

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