School of Science Department of Chemistry 4 Deep Learning in Synthesis Planning Supervisor: SU Haibin / CHEM Student: WANG Yizhou / CHEM Course: UROP2100, Fall Most of organic reactions require catalysts in order to occur and end efficiently, in which metal catalysts attract a lot of interest of researchers to study. Unlike heavy metals, which are rare and toxic, some light metals, such as nickel, can also perform wonderfully in catalyzing various kinds of organic reactions, like reductive coupling, C-O activation, etc. Besides, nickel is also capable of catalyzing the conversion of carbon dioxide into acetic acid in order to absorb the greenhouse gas. This report is an overview of reactions and conditions using nickel catalysts with bidentate nitrogen ligands, and will analyze the conditions including ligand types, base and so on. Virtual Reality in Chemistry Supervisor: SU Haibin / CHEM Student: KONG Yui Hin / CHEM Course: UROP1100, Fall Molecular dynamics (MD) refers to using computer simulations to study and predict physical movement of atoms and molecules over time. MD spans across multiple fields of science as a easy and efficient tool to predict or verify experiments. MD as a field of computational chemistry is becoming more popular as computing power becomes more cheaper and easily available. Here, a brief review of history and principles of molecular dynamics is given. Then, multiple MD scenarios are simulated on a consumer level computer to compare efficiency. Futures and limitations of MD are discussed. The Impact of Spike Mutations on SARS-CoV-2 Neutralization Supervisor: SU Haibin / CHEM Student: ANGELA Donna / SENG Course: UROP1000, Summer The COVID-19 pandemic has been a global challenge people are facing. One of the main issues is the development of new variants, making it more dangerous for us. Despite many efforts given by various parties, the team and I involve in finding a novel way to track mutations of the spike protein, mainly RBD and NTD discussed here. One of the methods in fulfilling our goals is through variant decomposition, which gives access to specific mutation information of the unique sequences we have and discovers the significant mutation trend related to relevant amino acid types for variants of concern or interest targeted.