Challenges in Mathematics Arising from Theoretical and Computational Chemistry
Echegu Darlington Arinze,1 and Alum Benedict Nnachi2
1School of Mathematics and Computing, Kampala International University, Uganda
2Research and Publication extension, Kampala International University, Uganda
Email: darlington.echegu@kiu.ac.ug nzeechegu@gmail.com
ORCID: 0009-0002-6644-1709
ABSTRACT
The combination of theoretical chemistry and mathematics represents a significant advancement in science since it has yielded insights into the enigmas surrounding atoms and molecules. The advancement of technology has greatly benefited drug development, leading to significant advancements in both medicine and materials research. This summary discusses innovative methodologies and computational challenges in the expansive domain of theoretical and computational chemistry. Despite the computational challenges associated with the Schrodinger equation and Density Functional Theory (DFT), quantum mechanics offers a basic understanding of the behaviour of molecules and atoms. While MD simulations may not handle long-range interactions and complex configuration spaces, they nonetheless excel at capturing various time scales of molecular behaviour. Nevertheless, the process of transforming abstract notions into computer models for the purpose of solving MD simulations continues to be difficult; statistical mechanics offers a theoretical framework for understanding MD simulations. Data-driven methodologies and machine learning have significantly transformed the perspective of computational chemistry by enabling the observation and comprehension of very complex chemical interactions. We must also address concerns about interpretability, reliability in limited data streams, and system transferability. These challenges expedite the advancement of novel materials, product designs, and pharmaceuticals by leveraging machine learning and integrating it with specialised domain expertise. We used available data from many reputable databases, spanning the time period from 2010 to 2024. It is imperative to prioritise the advancement of multiscale modelling techniques and hybrid quantum-classical tools in order to achieve sufficient mastery over chemical phenomena. Another potential benefit is the use of novel mathematical models to uncover previously unknown patterns and connections in genetic data. The most effective way to tackle mathematical problems is by employing a straightforward approach and engaging in collaboration with experts from other fields. By adopting this approach, we can effectively address significant societal issues and propel advancements in chemistry.
Keywords: mathematics, computational, chemistry, theoretical, challenges, quantum mechanics
CITE AS: Echegu Darlington Arinze and Alum Benedict Nnachi (2024). Challenges in Mathematics Arising from Theoretical and Computational Chemistry. IDOSR JOURNAL OF SCIENCE AND TECHNOLOGY 10(2):31-37. https://doi.org/10.59298/IDOSR/JST/24/102.313700