Jeremie Zaffran | Theoretical Chemistry | Best Researcher Award

Published on by Analytical Chemistry

Prof. Dr. Jeremie Zaffran | Theoretical Chemistry | Best Researcher Award

Professor at CNRS- (Centre National de la Recherche Scientifique),  France

Profile

🌟 Early Academic Pursuits

Jeremie Zaffran’s academic journey began with distinction, marked by a Bachelor’s degree in Chemistry from Université Paris Diderot-Paris 7, where he graduated cum laude and ranked among the top of his class. He continued his studies with a Master of Science in Materials Science, specializing in Nanosciences, where his exceptional performance earned him a summa cum laude distinction. His doctoral studies at the Ecole Normale Supérieure de Lyon solidified his expertise, culminating in a PhD in Chemistry awarded with the highest distinction. His thesis laid the groundwork for fast predictions of catalytic reactivity in biomass valorization, merging quantum calculations with statistical analysis.

🧑‍🔬 Professional Endeavors

Jeremie’s professional path reflects a global and multidisciplinary perspective. Starting with his postdoctoral fellowship at the Technion in Israel, he delved into computational design for solar water-splitting catalysts, forging collaborations with experimentalists worldwide. As a Research Assistant Professor at ShanghaiTech University, he expanded his expertise in computational catalysis, designing electrocatalysts for renewable energy applications. Currently, as a tenured research fellow at CNRS and part of the E2P2L lab in Shanghai, he focuses on integrating machine learning with computational chemistry to accelerate catalyst design for sustainable industrial processes.

🏗️ Contributions and Research Focus

Jeremie’s contributions span heterogeneous catalysis modeling, renewable energy applications, and advanced computational techniques like DFT and microkinetic simulations. His projects address critical challenges in biomass transformation, solar water splitting, and CO₂ valorization. He has developed machine learning models to predict catalytic activity and mechanisms, reducing the need for exhaustive computational resources. Jeremie’s interdisciplinary approach bridges theoretical insights and practical applications, resulting in innovative solutions for green chemistry.

🏆 Accolades and Recognition

Jeremie’s work has been recognized through numerous awards and honors, such as the prestigious Lady Davis Fellowship and the Grand Technion Energy Program Fellowship. His academic excellence is underscored by distinctions at every level of his education. Furthermore, his leadership in securing competitive grants has brought substantial funding to projects focused on sustainable chemistry, totaling millions in financial support.

🌍 Impact and Influence

Through collaborations with experimental and theoretical groups, Jeremie has shaped the landscape of computational catalysis. His research has influenced industrial partners, such as Solvay, and academic communities alike. With a robust portfolio of high-impact publications, he has contributed to fields ranging from photocatalytic hydrogen production to CO₂ utilization. His leadership in combining artificial intelligence with chemical research positions him as a pioneer in the digital transformation of catalysis.

🔮 Legacy and Future Contributions

Jeremie’s work continues to inspire innovation in green chemistry. By mentoring the next generation of scientists and fostering interdisciplinary collaborations, he is laying the groundwork for a sustainable future. His legacy includes not only his scientific advancements but also his commitment to bridging academic and industrial research, ensuring that his contributions endure for decades to come.

Publication Top Notes

  • “Unveiling the phenol direct carboxylation reaction mechanism at ZrO2 surface”

    • Authors: Kaihua Zhang, Changru Ma, Sebastien Paul, Jeremie Zaffran*
    • Journal: Molecular Catalysis
    • Year: 2024

  • “Photocatalytic dihydroxylation of light olefins to glycols by water”

    • Authors: Chunyang Dong, Yinghao Wang, Ziqi Deng, et al., Jeremie Zaffran, Andrei Y. Khodakov*, Vitaly V. Ordomsky*
    • Journal: Nature Communications
    • Year: 2024

  • “Upgrading the density functional theory with machine learning for the fast prediction of polyaromatic reactivity at bimetallic catalysts”

    • Authors: Jérémie Zaffran*, Minyang Jiao, Raphaël Wischert, Stéphane Streiff, Sébastien Paul
    • Journal: The Journal of Physical Chemistry C
    • Year: 2024

  • “Deoxydehydration of glycerol to allyl alcohol catalyzed by ceria-supported rhenium oxide”

    • Authors: Karen Silva Vargas, Marcia Araque, Jeremie Zaffran, Benjamin Katryniok*, Masahiro Sadakane*
    • Journal: Molecular Catalysis
    • Year: 2023

  • “Direct Photocatalytic Synthesis of Acetic Acid from Methane and CO at Ambient Temperature using Water as Oxidant”

    • Authors: Chunyang Dong, Maya Marinova, Karima Ben Tayeb, et al., Jeremie Zaffran, Andrei Y. Khodakov*, Vitaly V. Ordomsky*
    • Journal: The Journal of the American Chemical Society
    • Year: 2023

  • “Identifying Metal-Halogen bonding for Hydrogen Induced Acid Generation in Bifunctional Catalysis”

    • Authors: Yong Zhou, Martine Trentesaux, Jean-Charles Morin, et al., Jérémie Zaffran*, Vitaly Ordomsky*
    • Journal: ACS Catalysis
    • Year: 2023

  • “Catalytic selective oxidation of isobutane in a decoupled redox-process”

    • Authors: Li Zhang, Jeremie Zaffran, Franck Dumeignil, Sébastien Paul*, Axel Lofberg, Benjamin Katryniok*
    • Journal: Applied Catalysis A: General
    • Year: 2022

  • “Theoretical Insights into the Formation Mechanism of Methane, Ethylene, and Methanol in Fischer-Tropsch Synthesis at Co2C Surfaces”

    • Authors: Jeremie Zaffran*, Bo Yang*
    • Journal: ChemCatChem
    • Year: 2021

  • “First-Principles-Based Microkinetic Simulations of CO2 Hydrogenation to Methanol over Intermetallic GaPd2”

    • Authors: Panpan Wu, Jeremie Zaffran, Bo Yang*
    • Journal: The Journal of Physical Chemistry C
    • Year: 2020

  • “Fast Prediction of Oxygen Reduction Reaction Activity on Carbon Nanotubes with a Localized Geometric Descriptor”

    • Authors: Kunran Yang†, Jeremie Zaffran†, Bo Yang*
    • Journal: Physical Chemistry Chemical Physics
    • Year: 2020

Sicong Ma | Theoretical and Computational Chemistry | Best Researcher Award

Published on by Analytical Chemistry

Assoc. Prof. Dr. Sicong Ma | Theoretical and Computational Chemistry | Best Researcher Award

Shanghai Institute of Organic Chemistry, China

👨‍🎓Profiles

🎓 Early Academic Pursuits

Dr. Sicong Ma, born in March 1992, began his academic journey with a strong foundation in applied chemistry at the China University of Petroleum (Beijing), where he completed his Bachelor of Science in 2013. He continued at the same institution for a Master's degree in Chemistry, working under the guidance of Professor Zhen Zhao until 2016. His academic path led him to Fudan University, where he earned his Ph.D. in Physical Chemistry in 2019 under Professor Zhi-Pan Liu. Here, he developed his expertise in theoretical and computational chemistry, laying the groundwork for his future contributions to catalysis and machine learning.

🏢 Professional Endeavors

After completing his Ph.D., He joined Fudan University as a postdoctoral researcher, continuing his work with Professor Zhi-Pan Liu until 2021. In August 2021, he joined the Shanghai Institute of Organic Chemistry as an Assistant Researcher. Recently promoted to Associate Professor, He has led several projects funded by prestigious institutions, including the National Natural Science Excellent Youth Fund, Shanghai Municipal Science and Technology Commission, and the China Postdoctoral Fund.

🔍 Contributions and Research Focus

His research interests span a unique blend of machine learning and catalysis. His expertise extends across both homogeneous and heterogeneous catalysis, with a particular focus on: Machine Learning and Heterogeneous Catalysis: He has conducted research on syngas-to-olefins conversions on OX-ZEO catalysts, propane hydrogenation, and similar transformations, Machine Learning and Homogeneous Catalysis: His work includes studies on the carbonylation of olefins and the development of a metal-phosphine ligand catalyst database, Zeolite Chemistry: He is also active in studying the mechanisms of zeolite formation and their applications in catalysis, contributing significantly to zeolite-related database construction.

📈 Impact and Influence

He has made substantial contributions to the field, publishing more than 20 papers in renowned journals such as Nature Catalysis, Nature Communications, and ACS Catalysis. Notably, he has served as first or corresponding author on 15 of these publications, solidifying his role as a leader in his field. His work has garnered attention and citations, reflecting his influence within theoretical and computational chemistry.

📚 Academic Achievements and Honors

Recognized for his academic excellence, He has received numerous awards and honors. He was honored with the Excellent Doctoral Dissertation Award from Fudan University in 2019, recognized as an Academic Star of Fudan University the same year, and awarded a Shanghai Super Postdoctoral Fellowship. Recently, he was inducted as a member of the Youth Innovation Promotion Association by the Chinese Academy of Sciences in 2023.

🛠️ Technical Skills

His technical expertise includes advanced machine learning algorithms for catalysis, computational modeling in chemistry, and extensive knowledge of catalysis mechanisms in both homogeneous and heterogeneous systems. His computational skills and programming knowledge enable him to create and manage large databases, crucial for his projects on zeolite and catalyst-related data.

📖 Teaching and Mentoring Experience

While focused primarily on research, He has also contributed to the academic community by mentoring postdocs and junior researchers in his lab. His guidance fosters a collaborative environment, ensuring that emerging researchers develop the skills necessary to advance in computational chemistry and catalysis.

🌐 Legacy and Future Contributions

His ongoing work promises to deepen the integration of machine learning in catalysis, with potential implications for sustainable energy solutions and efficient industrial chemical processes. As a young innovator and leader in his field, he is set to make lasting contributions, furthering both academic knowledge and practical applications in computational chemistry.

📖Notable Publications