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Computational Modelling of Functional Materials for Driving Sustainable Innovation

Coordinator: Prof. Catharine Esterhuysen (Stellenbosch University), Deputy coordinator: Dr Edwin Mapasha (University of Pretoria)

Scientific question and goal

Utilise advanced computational methods and machine learning techniques to accelerate the discovery and design of functional materials with a specific focus on energy, space and gas-sensing materials.

Measurable success: new functional materials and/or protocols to develop these.

Institutions

  • Stellenbosch University
  • University of Pretoria
  • University of Venda
  • North-West University
  • University of South Africa
  • University of KwaZulu-Natal
  • Council for Scientific and Industrial Research

Some recent publications

  • Tshwane, D.M., Dima, R.S., Maleka, P.M. & Maphanga, R.R. Investigation of the Structural, Electronic, and Mechanical Stability of XVSe2 (X = Li, K, Cs, and Rb) Using Density Functional Theory. In: Okamoto, Y. (eds) Proceedings of the 34th IUPAP Conference on Computational Physics. CCP2023 2023. Springer Proceedings in Physics, vol 356. Springer, Singapore. https://doi.org/10.1007/978-981-92-0844-9_41
  • Getachew Denbela Loko, G.D., Mohammed, A.M., Mekonnen, Y.S. & Obodo, K.O. Exploring Ti2MoC2O2 MXene as a promising anode material for Lithium-ion batteries: a density functional theory study. Computational Materials Science 276, 115115 (2026). https://doi.org/10.1016/j.commatsci.2026.115115

Members

Catharine Esterhuysen, Edwin Mapasha, Regina Maphanga, Tjaart Krüger, Eric Maluta, Kingsley Obodo, Abdulrafiu Tunde Raji, Lynndle Square, David Tshwane, Aniekan Ukpong

Focus Area