Research
Research interests, recent projects, selected publications, and invited talks.
Research interests
- Materials informatics and artificial intelligence for materials discovery and design
- Computational materials science and physics
- Polymers, functional materials, and quantum materials
- Bridging fundamental research, materials innovation, and industrial applications
Recent projects
- Ongoing projects with industrial partners; selected results have been published with colleagues from Bosch in Polym. Chem. 16, 3459 (2025) and with colleagues from Shell in Chem. Mater. 38, 8125 (2026).
- NSF SBIR Phase I: “A Physics-Informed/Encoded Polymer Informatics Platform for Accelerated Development of Advanced Polymers and Formulations”, 2023–2024.
- ONR SBIR Phase I: “Machine-Learning Approach for Accelerated Design of Low-Flammability Polymer Matrix Composites”, 2023–2024 (press release).
Selected publications
Full list on Google Scholar; selected preprints on arXiv.
- “Superconductor discovery in the emerging paradigm of materials informatics,” Review Article, Chem. Mater. 36, 10939 (2024) [PDF].
- “Design of functional and sustainable polymers assisted by artificial intelligence,” Review Article, Nat. Rev. Mater. 9, 866 (2024) [PDF].
- “Machine-learning approach for discovery of conventional superconductors,” Phys. Rev. Materials 7, 054805 (2023) [PDF, raw data, model training].
- “Informatics-driven selection of polymers for fuel-cell applications,” J. Phys. Chem. C 127, 977 (2023) [PDF].
- “Toward recyclable polymers: ring-opening polymerization enthalpy from first principles,” J. Phys. Chem. Lett. 13, 4778 (2022) [PDF].
- “Probabilistic deep learning approach for targeted hybrid organic-inorganic perovskites,” Phys. Rev. Materials 5, 125402 (2021) [PDF, model training].
- “Machine-learning predictions of polymer properties with Polymer Genome,” Tutorial Article, J. Appl. Phys. 128, 171104 (2020) [PDF].
- “Polymer structure prediction from first principles,” J. Phys. Chem. Lett. 11, 5823 (2020) [PDF].
- “Advanced polymeric dielectrics for high energy density applications,” Review Article, Prog. Mater. Sci. 83, 236 (2016) [PDF].
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“Pathways towards ferroelectricity in hafnia,”
Phys. Rev. B 90, 064111 (2014)
[PDF].
A first-principles computational discovery of the ferroelectric phases of hafnia (HfO2). In 2011, ferroelectricity was unexpectedly observed in hafnia thin films, a puzzling result given that all known phases of this material are centrosymmetric. I predicted two metastable ferroelectric phases, Pca21 and Pmn21. The former was quickly confirmed and is now widely recognized; the latter has been harder to realize, but supporting evidence has continued to emerge over the past decade. Most recently, in May 2026, a team at Samsung reported that in ultra-thin films (1.5 nm and below) the conventional Pca21 phase degrades and collapses, leaving the Pmn21 phase.
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“Low-energy polymeric phases of alanates,”
Phys. Rev. Lett. 110, 135502 (2013)
[PDF].
A first-principles computational discovery of novel polymeric structural motifs in alanates MAlH4, characterized by networks of corner-sharing AlH6 octahedra that form wires and/or planes throughout the materials. In 2015, such motifs were observed experimentally.
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“Valence bond entanglement and fluctuations in random singlet phases,”
Phys. Rev. B 84, 144420 (2011)
[PDF].
A computational method for quantifying quantum entanglement in a family of models of non-Abelian anyons, exotic quasiparticles of particular interest for the eventual realization of topological quantum computing.
Selected invited talks
- “Polymer Genome approach for functional polymer design,” Machine Learning in Autonomous Science: Synthesis, Characterization, and Theory, ORNL, Knoxville, TN, USA (Aug. 7, 2023).
- “Accelerating materials science with artificial intelligence,” 6th International Symposium on Frontiers in Materials Science, Phu Quoc, Vietnam (Nov. 21–23, 2022).
- “Polymer informatics: current status and critical next steps,” 2021 International Symposium in Materials Informatics, Japan Advanced Institute of Science and Technology, Ishikawa, Japan (Feb. 26, 2021).
- “Computational materials science: from physics- to data-driven approaches,” Colloquium, Department of Physics and Materials Science, University of Memphis, Memphis, TN, USA (Oct. 11, 2019).