Computational materials scientist with a special interest in using machine learning to design new materials.
Research at Argonne is focused on combining first principles modeling and machine learning to drive the accelerated prediction and design of semiconductors with tailored optical and electronic properties.
- B. Tech., Metallurgical and Materials Engineering, Indian Institute of Technology Roorkee, India.
- PhD, Materials Science and Engineering, University of Connecticut, USA.
- A. Mannodi-Kanakkithodi, J. S. Park, N. Jeon, D. H. Cao, D. J. Gosztola, A. B. F. Martinson, M. K. Y. Chan, “Comprehensive Computational Study of Partial Lead Substitution in Methylammonium Lead Bromide”, Chemistry of Materials 31 (10), 3599–3612 (2019).
- A. Mannodi-Kanakkithodi, M. Toriyama, F. G. Sen, M. Davis, R. F. Klie, M. K. Y. Chan, “Machine learned impurity level prediction in semiconductors: the example of Cd-based chalcogenides”, under review, preprint: https://arxiv.org/abs/1906.02244 (2019).
- P. Guo, A. Mannodi-Kanakkithodi, J. Gong, Y. Xia, C. C. Stoumpos, D. H. Cao, B. T. Diroll, J. B. Ketterson, G. P. Wiederrecht, T. Xu, M. K. Y. Chan, M. G. Kanatzidis, R. D. Schaller “Infrared-pump electronic-probe of methylammonium lead iodide reveals electronically decoupled organic and inorganic sublattices”, Nature Communications 10, 482 (2019).
- D. H. Cao, P. Guo, A. Mannodi-Kanakkithodi G. P. Wiederrecht, D. J. Gosztola, N. Jeon, R. D. Schaller, M. K. Y. Chan, A. B. F. Martinson, “Charge Transfer Dynamics of Phase Segregated Halide Perovskites”, ACS Appl. Mater. Interfaces 11, 9583–9593 (2019).
- BOOK CHAPTER: A. Mannodi-Kanakkithodi, R. Ramprasad, “Rational Design of Polymer Dielectrics: An Application of Density Functional Theory and Machine Learning”, Computational Materials Discovery, The Royal Society of Chemistry (2018).
- INVITED REVIEW: A. Mannodi-Kanakkithodi, A. Chandrasekaran, C. Kim, T. D. Huan, G. Pilania, V. Botu, R. Ramprasad, “Scoping the Polymer Genome: A Roadmap for Rational Polymer Dielectrics Design and Beyond”, Materials Today, 21, 785-796 (2018).
- INVITED REVIEW: R. Ramprasad, R. Batra, G. Pilania, A. Mannodi-Kanakkithodi, C. Kim, “Machine Learning and Materials Informatics: Recent Applications and Prospects”, npj Computational Materials 3, 54 (2017).