by Judy Marouf and Anastasia Duenas

Summary of Topic

For our podcast project, we chose to explore the topic of computational chemistry and its role in modern chemistry. Computational chemistry is a field that uses computer algorithms and simulations to study chemical systems and processes. As the complexity of chemical systems has grown beyond the capabilities of traditional experimental methods over the decades, computational methods and tools in chemistry have become increasingly important.

In the first episode of the podcast, we shared some background information on how we reached the topic of our podcast before jumping into an overview of the role of computational chemistry in modern chemistry and the importance of computer science in the field. We discussed how computational chemistry has become an essential tool for understanding chemical reactions and predicting the properties of molecules and materials. We also highlighted some of the key advantages of using computational methods. In our second episode, we introduced the discussion by covering the history of computational chemistry. Specifically, we shared the work of John Pople, a British theoretical chemist who laid the foundation for many of the methods still used today in computational chemistry. We demonstrated how Pople's groundbreaking work revolutionized the field of computational chemistry and made it possible to accurately model the electronic structures and properties of molecules. In the final part of the episode, we detailed some of the latest computational tools being developed by researchers to predict the properties of molecules and materials. We outlined the growing use of Machine Learning and Artificial Intelligence in computational chemistry and how these technologies are changing the way chemists approach problems in the field. Finally, we presented some of the key benefits and limitations of using these tools.

Read the full report here.