Abstract
The production of chemicals is a complex task due to the highly nonlinear behaviour of chemical processes; therefore, traditional approaches may not be very effective in developing or predicting such processes and their outcomes at optimal level. Consequently, it has always been challenging to find ways to improve efficiency and productivity while reducing the time and cost. Artificial Intelligence (AI) techniques are becoming valuable in chemistry due to several reasons such as easy to learn and use, simple implementation, easy designing, effectiveness, generality, robustness, and flexibility. AI is comprised of several techniques within it, such as artificial neural networks, evolutionary algorithms and fuzzy logic. AI techniques have been widely used in various areas of chemistry including molecule design, molecular property prediction, retrosynthesis, reaction outcome prediction and reaction conditions prediction. Therefore, this paper investigates AI applications in the aforementioned areas, wherein it explains about each aforementioned area with a suitable example, limitations of traditional techniques, and types of AI techniques which are utilised within those areas.
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Naik, I., Naik, D., Naik, N. (2024). Artificial Intelligence (AI) Applications in Chemistry. In: Naik, N., Jenkins, P., Grace, P., Yang, L., Prajapat, S. (eds) Advances in Computational Intelligence Systems. UKCI 2023. Advances in Intelligent Systems and Computing, vol 1453. Springer, Cham. https://doi.org/10.1007/978-3-031-47508-5_42
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DOI: https://doi.org/10.1007/978-3-031-47508-5_42
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