Yang Lab

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Research

The Yang Lab at Georgia Institute of Technology in the School of Chemical and Biomolecular Engineering works on sustainability challenges in energy storage by leveraging first-principles calculations, machine learning, and molecular dynamics, all grounded by electrochemical experiments. While we are primarily a computational group, we work closely with experimental data. In doing so, we test and advance state-of-the-art methods to solve a variety of experimental challenges.

Areas of interest

Electrodes
  • Activated internetwork pathways in partially-disordered spinel cathode materials with ultrahigh rate performance. Advanced Energy Materials, 13(4):2202955, 2022.
  •  Insights into layered oxide cathodes for rechargeable batteries, Molecules, 26(11):3173, 2021.
  • Direct observation of alternating and prismatic sodium layers in O3-type transition metal oxides, Advanced Energy Materials, 10(31):2001151, 2020.
Sustainable solvents and electrolytes
  • Room-temperature decomposition of the ethaline deep eutectic solvent, The Journal of Physical Chemistry Letters, 16, 12, 3039–3046, 2025.
  • Transferability and accuracy of ionic liquid simulations and equivariant machine learning interatomic potentials. The Journal of Physical Chemistry Letters, 15(30):7539-7547, 2024.
Interfacial degradation
  • Buried No Longer: Recent Computational Advances in Explicit Interfacial Modeling of Lithium-Based All-Solid-State Battery Materials, Frontiers in Energy Research, 13:1621807, 2025.

Primary Tools

Density Functional Theory

Machine learned interatomic potentials

Cluster expansions

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