
معرفی
Jesus Jover Modrego is an Associate Professor in the Department of Inorganic and Organic Chemistry at the Faculty of Chemistry, University of Barcelona. He serves as Department Secretary and leads the Computational Inorganic Chemistry group established in 2024, with affiliations to the Electronic Structure Group (GEE) and Institute of Theoretical and Computational Chemistry (IQTC).
His academic credentials include:
- B.Sc. in Chemistry (2002, University of Barcelona)
- MSc in Chemistry (2004, University of Barcelona)
- PhD in Chemistry (2008, University of Barcelona)
His research spans Computational Inorganic Chemistry with expertise in catalytic reaction mechanisms, molecular magnetism of lanthanides/transition metals, and electronic structure analysis. He pioneers Machine Learning applications for chemical property prediction and develops QSAR/QSPR methodologies. Current work focuses on homogeneous/heterogeneous catalysis, metal-organic frameworks, and solar cell sensitizers through computational modeling.
Recent publications (2019-2024) demonstrate consistent innovation in catalytic coupling reactions (Suzuki-Miyaura), NMR prediction via transfer learning, and molecular magnetism. His work bridges statistical modeling with experimental chemistry, emphasizing industrial applications in sealant development and sustainable chemistry.
Key recognition includes:
- Juan de la Cierva fellowship (2012)
He has supervised six undergraduate theses, six Master's theses, and one PhD student across Chemistry, Chemical Engineering, Pharmacy, and Geology programs. His research portfolio exceeds 70 publications and 10 funded projects including AstraZeneca/Henkel collaborations, EU H2020 initiatives (A-LEAF), and Spanish Ministry grants (PGC2018-093863-B-C21). Current projects address computational catalysis (BigData4Cat), high-performance computing transfer (X4HPC), and immersive virtual reality for chemistry education.
As principal investigator of the Computational Inorganic Chemistry group, he directs research in transition metal catalysis and electronic structure while advancing computational methodologies for industrial chemistry applications.
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