Joseph Frimpong

NST, Argonne National Laboratory

I am postdoctoral researcher at Argonne National Laboratory, where I study the electronic structure and optical properties of materials to advance applications in catalysis, energy, and optoelectronics. My research focuses on computational methods, including density functional theory (DFT), many-body perturbation theory (GW/BSE), and machine learning, to explore structure-property relationships in heterogeneous interfaces, quantum dots, and other nanoscale materials. I am also passionate about leveraging computational chemistry and machine learning to accelerate materials discovery and improve the efficiency of next-generation materials.

In addition to my academic pursuits, I aspire to share my knowledge and experiences through blogging, shedding light on complex topics in a simplified manner.

I am currently working on a blog to share insights and insights on academic life and computational materials science.

Research Interests

  • Many-body electronic-structure (GW/BSE) and dielectric embedding for complex interfaces.
  • Machine learning models that accelerate excited-state calculations and screening workflows.
  • Quantum dots, nanoscale interfaces, and catalysis-directed materials design.

Latest Posts

News

  • Nov 04, 2024 – Joined Argonne National Laboratory as Postdoctoral Researcher — Started a postdoctoral appointment in the NST division to develop AI/ML-assisted GW/BSE workflows for heterogeneous materials.
  • Aug 30, 2024 – Defended Ph.D. in Chemistry at Wayne State University — Successfully defended my dissertation on many-body approaches for quantum dots and covalent interfaces.
  • Jul 01, 2023 – Led Chemistry Meets Computers Summer Bootcamp — taught a week intensive introducing Python and ML to high school students, mentoring on computational chemistry and machine learning.

See the full list on the news page.

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