Synchrotron radiation facilities are powerful X-ray sources that can be employed for numerous experimental techniques, including X-ray spectroscopic, scattering and imaging methods. The features of synchrotron radiation - high intensity and broad energy spectrum - make these sources ideally suited for in-situ and operando investigations of advanced materials.
In the focus of our group's research is the application and development of complementary synchrotron radiation techniques (X-ray absorption spectroscopy, high-energy X-ray diffraction coupled with pair distribution function analysis, small-angle X-ray scattering) that provide information about the transformations of catalyst structure on different length and time scales under catalytically relevant conditions.
By combining unique synthesis methods, state-of-the art tools for experimental characterization and advanced approaches to data analysis, atomistic details of chemical and electrochemical reactions at gas/solid and liquid/solid interfaces are revealed, and structure-property relationship in these materials are established.
C. Li, W. Ju, S. Vijay, J. Timoshenko, K. Mou, D.A. Cullen, J. Yang, X. Wang, P. Pachfule, S. Brückner, H. Jeon, F. Haase, S.-C. Tsang, C. Rettenmaier, K. Chan, B. Roldan Cuenya, A. Thomas and P. Strasser: Covalent Organic Framework (COF) derived Ni-N-C Catalysts for Electrochemical CO2 Reduction: Unraveling Fundamental Kinetic and Structural Parameters of the Active Sites. Angewandte Chemie International Edition61 (15), e202114707 (2022).
H. Liu, X. Lang, C. Zhu, J. Timoshenko, M. Rüscher, L. Bai, N. Guijarro, H. Yin, Y. Peng, J. Li, Z. Liu, W. Wang, B. Roldan Cuenya and J. Luo: Efficient Electrochemical Nitrate Reduction to Ammonia with Copper supported Rhodium Cluster and Single-Atom Catalysts. Angewandte Chemie International Edition61 (23), e202202556 (2022).
E. Zschech, E. Topal, K. Kutukova, J. Gluch, M. Löffler, S. Werner, P. Guttmann, G. Schneider, Z. Liao and J. Timoshenko: Multi-scale microscopy study of 3D morphology and structure of MoNi4/MoO2@Ni electrocatalytic systems for fast water dissociation. Micron158, 103262 (2022).
X. Feng, H. Jena, C. Krishnaraj, D. Arenas-Esteban, K. Leus, G. Wang, J. Sun, M. Rüscher, J. Timoshenko, B. Roldan Cuenya, S. Bals and P. Van Der Voort: Creation of Exclusive Artificial Cluster Defects by Selective Metal Removal in the (Zn, Zr) Mixed-metal UiO-66. Journal of the American Chemical Society143 (51), 21511–21518 (2021).
S. Kunze, P. Grosse, M.B. Lopez, I. Sinev, I. Zegkinoglou, H. Mistry, J. Timoshenko, M.Y. Hu, J. Zhao, E.E. Alp, S.W. Chee and B. Roldan Cuenya: Operando NRIXS and XAFS Investigation of Segregation Phenomena in Fe‐Cu and Fe‐Ag Nanoparticle Catalysts during CO2 Electroreduction. Angewandte Chemie International Edition59 (50), 22667–22674 (2020).
T. Möller, F. Scholten, T.N. Thanh, I. Sinev, J. Timoshenko, X. Wang, Z. Jovanov, M. Gliech, B. Roldan Cuenya, A.S. Varela and P. Strasser: Electrocatalytic CO2 Reduction on CuOx Nanocubes: Tracking the Evolution of Chemical State, Geometric Structure, and Catalytic Selectivity using Operando Spectroscopy. Angewandte Chemie International Edition59 (41), 17974–17983 (2020).
M. Ahmadi, J. Timoshenko, F. Behafarid and B. Roldan Cuenya: Tuning the Structure of Pt Nanoparticles through Support Interactions: An In Situ Polarized X-ray Absorption Study Coupled with Atomistic Simulations. The Journal of Physical Chemistry C123 (16), 10666–10676 (2019).
Timoshenko, J.: Tracking Dynamics and Heterogeneity in Working Nanocatalysts Using Time Resolved Synchrotron Studies and Machine Learning. FHI-Workshop on Current Research at the Interface of Physics and Chemistry, Potsdam, Germany (2022)
Timoshenko, J.: Probing Kinetics of Catalyst Transformations Using Synchrotron-Based Operando Techniques and Machine Learning. 6th International School-Conference on Catalysis for Young Scientists, Catalyst Design: From Molecular to Industrial Level, Online Event (2021)
Timoshenko, J.: Electrochemical Reduction and Brass Formation in Copper-Zinc Nanocatalysts: Deciphering In-Situ EXAFS Data Using Artificial Neural-Network. E-MRS Fall Meeting and Exhibit 2019, Warsaw, Poland (2019)