Selected Honors & Awards

MIT Chemical Engineering Rising Stars, MIT (2021)

Dr. James M. Coull Memorial Award, University of Pittsburgh (2020)

        The top outstanding PhD student in the department.

CoMSEF Division Graduate Student Award, AIChE (2019)

Fulbright Scholarship, The Fulbright Student Program (2015)

Stanford International Honors Award, Stanford University (2014)

Courses

ChE244: Heat and Mass Transfer

Selected Publications:

Basdogan, Y.; Pollard, D.R.; Shastry, T.; Carbone, M.R.; Kumar, S.K.; Wang, Z.G., "Machine Learning-Guided Discovery of Polymer Membranes for CO2 Separation," ChemRxiv, 2023. DOI: 10.26434/chemrxiv-2023-5h4s7.

Basdogan, Y.; Wang, Z.G., "Tuning Ether Motifs in Polymer Membranes for CO2 Separation," ChemRxiv, 2022. DOI: 10.26424/chemrxiv-2022-4ml8d.

Basdogan, Y.; Maldonado, A.M.; Keith, J.A., "Advances and challenges in modeling solvated reaction mechanisms for renewable fuels and chemicals," Wires, 2019. DOI: 10.1002/wcms.1446

Basdogan, Y.; Groenenboom, M.C.; Henderson, E.; De, S.; Rempe, S.B.; Keith, J.A., "Machine Learning-Guided Approach for Studying Solvation Environments," ACS Publications, 2020. DOI: 10.1021/acs.jctc.9b00605.

Basdogan, Y.; Keith, J.A., "A paramedic treatment for modeling explicitly solvated chemical reaction mechanisms," Royal Society of Chemistry, 2018. DOI: 10.1039/C8SC01424H.

Research Overview:

In the Basdogan Lab, we combine molecular simulations (MD) and quantum chemistry (QC) calculations to generate smart, reliable, and efficient computational data that will inform molecular design and leverage artificial intelligence (AI) to design new materials for sustainability and energy applications. We use this multifaceted approach to address problems related to climate change: (1) Developing artificial membranes to separate CO₂ from other gasses, (2) Engineering solvents to capture and transfer CO₂, and (3) Designing new catalysts that will convert CO₂ to other chemicals.

Research Overview

Research Interests

• Artificial Intelligence; Machine Learning; Molecular Dynamics Simulations; Quantum Chemistry; Computational Materials Design; Energy and Sustainability; Polymers, Solutions, Catalysis