Scientist at UKZN Advances Computational Chemistry
Scientist at UKZN Advances Computational Chemistry
Dr Thishana Singh, a distinguished computational chemist and senior lecturer at the University of KwaZulu-Natal’s School of Chemistry and Physics, has been awarded two prestigious grants to support her innovative research in the field of computational chemistry.
The Deutscher Akademischer Austauschdienst (DAAD) grant and the Royal Society of Chemistry (RSC) Researcher Collaboration grant will fund her innovative project aimed at developing a density functional theory (DFT) model for the accurate prediction of high-resolution nuclear magnetic resonance (NMR) chemical shifts of flavonols.
Singh’s innovative research brings about an intersection of DFT and machine learning (ML) as this aims to revolutionise the way scientists predict NMR chemical shifts, crucial for the structural interpretation of organic compounds. The core of her project involves creating an ML augmented DFT approach. This hybrid model is designed to enhance the accuracy of 13C and 1H NMR chemical shift predictions for flavonols, a class of bioactive compounds with significant medicinal properties.
The methodology of Singh’s innovative project is multifaceted and meticulous as it combines computational chemistry and machine learning to synergise DFT-calculated features with structural descriptors. This method will ensure more accuracy than traditional methods.
Singh’s research is supported by international collaborations with esteemed experts in the field of computational chemistry. The DAAD grant facilitates her partnership with Professor Christoph Jacob at the Institute for Theoretical and Physical Chemistry, Technical University of Braunschweig in Germany. Jacob’s expertise in theoretical and physical chemistry will provide valuable insights and support for the DFT components of the project.
The RSC grant supports Singh’s collaboration with Professor Grant Hill at the School of Mathematical and Physical Sciences, University of Sheffield in England whose extensive knowledge in mathematical and physical sciences will be instrumental in integrating advanced machine learning techniques with DFT calculations.
The project underscores the importance of collaboration and international partnerships in advancing scientific research. Singh’s work not only strengthens the reputation of UKZN’s School of Chemistry and Physics but also contributes to the global scientific community’s efforts to harness computational techniques for solving complex chemical problems.
Being awarded the DAAD and RSC grants is a testament to her innovative project that has led to this collaboration with experts from Germany and the United Kingdom.
Words: Siphesihle Shezi
Photograph: Supplied
