Principal Investigator
Oleksandr I. Malyi
Computational materials theorist leading the Inverse Materials Design group. His work connects first-principles calculations, atomistic modeling, and machine-learning workflows to turn mechanisms into design rules for energy-storage materials, defects, gapped metals, and realistic interfaces.
Research Program
Mechanism-first inverse materials design
The group starts from a target function, builds atomistic models that include the relevant disorder and constraints, identifies the controlling mechanism, and converts the result into a design rule that can be tested experimentally.
The current program is centered on sodium-ion battery materials, especially hard-carbon anodes, where interlayer spacing, local carbon order, pores, oxygen chemistry, and ion pathways determine whether a proposed design rule is useful.
The same logic is used for polymer and liquid electrolytes, defect compensation in semiconductors, gapped metals and transparent conductors, polymorphous materials, and optical response at realistic interfaces.
Methods are selected by the physical question: DFT, defect thermodynamics, molecular dynamics, machine-learned potentials, optical-response calculations, and post-analysis are combined only when they improve the mechanism or the design rule.
- Hard-carbon sodium-ion anodes Interlayer spacing, pore filling, oxygen chemistry, plateau capacity, fast charging, and local disorder.
- Electrolyte materials Ion pathways, solvent coordination, polymer-chain bottlenecks, Lewis-acid fluorides, and stability mechanisms.
- Defects and gapped metals Defect compensation, antidoping, off-stoichiometry, dielectric response, and intrinsic carriers.
- Realism in predicted materials Phase stability, local symmetry breaking, polymorphous solids, and the burden of proof for exotic phases.
- Optical response and interfaces First-principles optical properties connected to Casimir-Lifshitz forces at heterogeneous interfaces.
Current project anchors
Impact and Funding
Research impact, independence, and funded responsibility
The profile is strongest where publication impact, corresponding-author responsibility, and funded research roles align around a coherent materials-design program.
Bibliometric values are rounded public-profile indicators.
Funding and project roles
Background
Academic path
Appointments
- 2024-present ENSEMBLE3 Centre of Excellence, PolandPart-time leader of the Inverse Materials Design group.
- 2022-2024 ENSEMBLE3 Centre of Excellence, PolandFull-time leader of the Inverse Materials Design group.
- 2019-2022 University of Colorado Boulder, USAResearch associate in Prof. Alex Zunger's group.
- 2014-2019 University of Oslo, NorwayResearcher and postdoctoral fellow in Prof. Clas Persson's group.
- 2016-2017 Nanyang Technological University, SingaporePostdoctoral fellow in Prof. Xiaodong Chen's group.
- 2012-2014 National University of SingaporeResearch assistant and fellow with Prof. Sergei Manzhos.
Education & research visits
- PhD Nanyang Technological UniversityPhD, 2013 · Supervised by Prof. Zhong Chen; scientific interaction with Assoc. Prof. Ping Wu.
- Physics Cherkasy National University, UkraineBachelor’s and master’s training in solid-state physics.
- Visits Research visitsUniversity of Colorado Boulder, Nanyang Technological University, and the Institute of Physics at Humboldt-Universitaet zu Berlin.
Group Leadership
Training researchers to connect computation with experimental decisions
The group is organized around independent ownership of a mechanism, a reproducible calculation record, and a clear route from prediction to experimentally useful guidance.
Group record
- Current team Postdoctoral researchers work on hard-carbon sodium-ion anodes, first-principles analysis, and transferability of machine-learning potentials.
- Alumni and visitors Former researchers contributed to batteries, functional defects, gapped metals, and Casimir-Lifshitz response.
Mentoring focus
- Physics before automation Every project needs a mechanism, a falsifiable calculation, and a connection to measurable behavior.
- Reproducible computational practice Models, structures, descriptors, and interpretation are kept traceable from calculation to paper.
- Collaboration with experiments The group prioritizes design rules that can guide synthesis, characterization, or electrochemical testing.