The Berry connection rendered as a tangent vector field on the Brillouin-zone torus, winding once around a central pink vortex core — a depiction of Chern number 1.

Condensed Matter & Materials Physics

Casey Clark

Computing the hidden topology of disordered quantum materials.

I am a PhD candidate at the University of Utah working in condensed matter and materials physics, in the Liu and Sparks groups. My research focuses on topology in disordered quantum materials — specifically, amorphous topological insulators, in which nontrivial band topology persists despite the loss of crystalline order. Using first-principles electronic-structure theory, tight-binding models, real-space topological markers, and machine-learning approaches, I study how disorder reshapes the quantum and electronic properties of crystalline materials — with an eye toward robust, device-relevant materials.

Research interests

Topology in disordered systems

Can topological protection persist once crystalline symmetry is broken? I look for the measurable signatures of nontrivial topology — Berry curvature, topological markers, topological phase transitions — that survive in disordered solids.

First-principles structure–property design

How do composition, strain, local environments, and disorder reshape a material's electronic structure? I connect the real-space atomic structure to quantum behavior with DFT, tight-binding and Wannier models, and machine-learning approaches.

Geometric-engineered altermagnetism

Can altermagnetic order be designed into a non-magnetic crystal through geometry alone? I probe whether an antidot superlattice patterned into monolayer graphene hosts intrinsic altermagnetism.

Education & research

PhD · Materials Science

2025 – present · expected 2028

University of Utah

Disordered topological quantum materials — discovering 3D amorphous topological insulators with first-principles methods, tight-binding models, real-space invariants, and machine-learned interatomic potentials.

Advised in the Liu Group · Sparks Group

Methods & tools

Tight-binding models Density functional theory Real-space invariants VASPWannier90WannierToolsMachine-learned interatomic potentials Agentic workflowsLLMsAIPython High-performance computing

Publications

2026

KnowMat: An Agentic Approach to Transforming Unstructured Materials Science Literature into Structured Data

H. M. Sayeed, C. Clark, T. Mohanty, T. D. Sparks

Integrating Materials and Manufacturing Innovation (2026)

DOI ↗

2025

MOF-encapsulation of metal nanoparticles alters the d-band center

B. Diamond, C. Clark, C. Hendon

In review

2022

Evaluating the accuracy of the AMBER protein force fields in modeling dihydrofolate reductase structures

O. D. Love, M. C. P. Lima, C. H. Clark, S. Cornillie, S. M. Roalstad, T. E. Cheatham III

Journal of Biomolecular Structure and Dynamics (2022)

DOI ↗