School of Science Department of Chemistry 3 Prediction of Inorganic Solar Cell Materials with Double Perovskite Structure Using Machine Learning Approach Supervisor: SU Haibin / CHEM Student: CHEUNG Ka Key / CHEM Course: UROP1100, Fall Solving the covalency and ionicity partition in solid states has many useful applications. For example, ionicity affects grain boundary which Jahn-Teller distortion can happen and directly determines the strength of the solid. In this work, we investigate CsPbI3, solid state material with cubic perovskite structure. Vienna Ab initio Simulation Package (VASP) is used for the simulation which gives useful parameters such as potential and electron density in different locations of the lattice. We can break down the energy into ionic and polarization energy partition to understand the ionicity. Deep Learning in Synthesis Planning Supervisor: SU Haibin / CHEM Student: CHUI Sin Yu / CHEM Course: UROP3100, Fall UROP4100, Spring Nickel-catalyzed reactions raised more attention in the development of organic synthesis. The benefits of using nickel compound as the homogeneous transition metal catalyst for cross-coupling reactions have been recognized by different researchers. Cross-coupling reactions involving C-O bond activation, C-N bond activation and C-H bond activation have also been developed to form organic compounds. This report will be focused on using computational methods to collect research papers on homo-nickel-catalyzed crosscoupling reactions. Further analysis of photochemistry will also be mentioned. Deep Learning in Synthesis Planning Supervisor: SU Haibin / CHEM Student: DOO Kwan Lam / CHEM Course: UROP1000, Summer Synthesis planning is essential for many reactions. Using this technique, it is possible to discover many new reactions to make different molecules in a faster and cheaper way. It would have many applications in drug discovery, medicinal chemistry, etc. This summer I learned about the synthesis planning of homogeneous nickel catalysis. This report is an overview of my data extraction progress in 2022 June, July, and August. The task includes data extraction of homogeneous nickel catalysis and some copper catalysis reactions. I will analyze the data I collected from the three aspects of leaving group, reactant group, and ligands with figures.