Postdoctoral Fellow
Research group| Computational Catalysis Group
Main supervisor|?Ainara Nova Flores
Affiliation |?Department of Chemistry UiO
Contact | m.p.franco@kjemi.uio.no
Short bio
I earned my Ph.D. at the Universidade de S?o Paulo (Prof. Ataualpa A. C. Braga), studying palladium-catalyzed Buchwald–Hartwig aminations via DFT and spending a year at the University of Oxford (Prof. John E. McGrady) on theoretical studies of open-shell complexes. I then completed postdoctoral research at the Instituto Tecnológico de Aeronáutica (Prof. René F. K. Spada) on spin-crossover phenomena and at UNICAMP (Prof. André L. B. Formiga) on ligand design for CO? conversion. I am currently a DS Train postdoctoral researcher at the University of Oslo (UiO), developing the #HETCO2 project on ligand design and mechanistic strategies for CO? reduction.
Research interests and hobbies
My research interests lie at the interface of catalysis and the understanding of structure–property and structure–reactivity relationships in coordination compounds. I focus on how ligand design and electronic structure influence catalytic activity, selectivity, and reaction mechanisms, with particular emphasis on transition-metal-mediated transformations, including CO? conversion and cross-coupling reactions. By combining data-science and computational chemistry approaches, such as density functional theory, with experimental insights, I aim to uncover the fundamental principles that govern reactivity and to guide the rational design of more efficient and sustainable catalysts.
In my DS Train project, I am focusing on the data-driven design of heterogenized electrocatalysts for the reduction of CO? to C? products. The goal is to combine computational modeling and machine learning approaches to understand how catalyst structure-reactivity relationships influence activity and selectivity, guiding the rational design of efficient and selective electrocatalysts for sustainable CO? conversion.
In my free time, I enjoy gaming, exploring comic book stories, and playing board games, activities that combine creativity, strategy, and storytelling.
DSTrain project
Data-driven design of heterogenized electrocatalysts for the reduction of CO2 to C2 products
The electrocatalytic reduction of CO? into high-value C? products, such as ethanol and acetic acid, offers a promising approach to carbon capture and utilization, aligning with global sustainability goals. However, achieving high selectivity and efficiency remains challenging due to the stability of CO? and the complexity of C–C bond formation.
This project aims to design and optimize molecular electrocatalysts for CO? reduction to C? products, integrating computational chemistry, data-driven methodologies, and experimental data. Density Functional Theory (DFT) and microkinetic modeling (MKM) will be employed to elucidate reaction mechanisms, identifying key intermediates and rate-limiting steps, and benchmark results with experimental data. Data analysis techniques will analyze large datasets to predict catalyst performance and guide structural modifications, to enhance activity and selectivity.
Building on studies showing improved C? production with immobilized molecular catalysts, we will model electrocatalysts immobilized onto Metal-Organic Frameworks (MOFs) to evaluate their potential for enhanced reactivity and selectivity towards C2 products. This hybrid approach combines the precision of molecular catalysts with the robustness of heterogeneous systems, optimizing pathways for C? formation.
The project is structured into four work packages: (1) computational characterization of catalytic cycles, (2) data-driven optimization of catalysts, (3) modelling catalyst onto MOFs, and (4) workflow integration for catalyst validation. By leveraging computational insights and experimental feedback, the project will establish a predictive platform for designing efficient CO? reduction catalysts. HETCO2's interdisciplinary approach aligns with global efforts to mitigate climate change by advancing CO? conversion technologies. In addition, it will benefit from ongoing activities on the development of electrochemical setups for testing and monitoring CO2 reduction reactions with MOF based catalysts.
Publications
DSTrain publications
ORCID https://orcid.org/0000-0002-0193-8397
Previous publications
?
?