PROJECT NAME
SPIROPYRAN-FUNCTIONALIZED MOFs AS STIMULI-RESPONSIVE "SMART" MATERIALS: LIGHT-CONTROLLED MOLECULAR CAPTURE, AI-ASSISTED DESIGN, AND SYNCHROTRON CHARACTERIZATION OF STRUCTURAL TRANSFORMATIONS
The goal
Development of a new class of stimuli-responsive metal-organic frameworks (MOFs) functionalized with spiropyran photochromic groups, capable of reversible light-controlled capture and release of target molecules through light-induced spiropyran–merocyanine isomerization.
The project aims to create a comprehensive approach combining the rational design of hybrid photochromic MOFs, accelerated optimization of their composition and synthesis conditions using artificial intelligence and machine learning methods, and precision diagnostics of structural transformations of the framework and the photoswitchable center by synchrotron radiation methods (in situ/operando XANES, EXAFS, XRD) in real time during photoswitching.
The project aims to create a comprehensive approach combining the rational design of hybrid photochromic MOFs, accelerated optimization of their composition and synthesis conditions using artificial intelligence and machine learning methods, and precision diagnostics of structural transformations of the framework and the photoswitchable center by synchrotron radiation methods (in situ/operando XANES, EXAFS, XRD) in real time during photoswitching.
Field of sciences
Chemistry and Materials Sciences
Topics of Ongoing Projects at The Smart Materials Research Institute
- Theoretical and experimental study of the photoswitching dynamics of molecular magnets: preparation for femtosecond X-ray experiments at XFEL;
- Study of materials for energy conversion using synchrotron radiation and supercomputer modeling;
- Development of methods for constructing hybrid materials based on three-dimensional metal-organic coordination polymers and photochromic compounds of various structures;
- Picometer-scale diagnostics of 3D local atomic structure parameters of nanomaterials based on XANES spectroscopy;
- Palladium nanocatalysts in key oxidation reactions: studies using in situ, operando, and modulated-excitation methods with synchrotron radiation;
- Rational design of palladium-based catalysts for C–H bond activation and ruthenium-based catalysts for C–O bond hydrogenation: from operando X-ray absorption spectroscopy to multispectral diagnostics using machine learning;
- New efficient nanocatalysts for photostimulated "green" hydrogen production reactions: computational design, laboratory and synchrotron studies using machine learning technologies;
- Nanocomposites for X-ray photodynamic therapy of deep-seated tumors in oncology;
- AI-controlled robotic station at a synchrotron radiation source for accelerated development of new advanced materials and their real-time diagnostics;
- Full-cycle technologies for the rapid development of functional materials for the low-carbon economy under AI control;
- New functional nanomaterials for applications in catalytic processes and in energy storage and conversion technologies;
- Theoretical and experimental study of the photoswitching dynamics of molecular magnets: preparation for femtosecond X-ray experiments at XFEL;
- Understanding the kinetics of photoelectrocatalytic reactions based on in situ diagnostics using synchrotron radiation and artificial intelligence;
- Frontier Laboratory of X-ray Spectral Nanometrology.
Methods
- Synthesis of metal-organic frameworks with embedded or post-synthetically grafted spiropyran ligands, including microfluidic synthesis methods for controlling particle morphology and uniformity;
- Advanced experimental methods for materials characterization (XANES, EXAFS, XRD, including studies at synchrotron radiation sources in in situ and operando modes);
- Machine learning algorithms and design of experiments (DoE) for predicting and optimizing synthesis parameters and photophysical characteristics;
- Spectroscopic methods for monitoring photoswitching (UV-Vis, FTIR spectroscopy) and adsorption measurements of target-molecule capture/release.
Equipment
- Microfluidic synthesis setups;
- Laboratory and synchrotron X-ray sources (XAFS/XANES/EXAFS beamlines);
- A complex of analytical equipment for polymer and composite materials (GPC/SEC, HPLC, TGA/DSC, FTIR, SEM);
- A supercomputer cluster, including specialized nodes for AI-based computations;
- Synchrotron radiation centers;
- The only laboratory R-XAS spectrometer (Rigaku) in Europe.
Leadership:
1. «Fundamentals and novel technologies for accelerated development of advanced functional materials based on supercomputer modeling, flow synthesis and diagnostics under the control of artificial intelligence»;
2. «Understanding the kinetics of photoelectrocatalytic reactions based on in-situ charaсterisation using synchrotron radiation and artificial intelligence»;
3. «An artificial intelligence-controlled robotic station at a synchrotron radiation infrastructure for accelerated development of advanced novel materials and their on-the-fly characterization»;
4. «Frontier laboratory for X-ray spectral nanometrology»;
5. «Development of a novel generation of nanoporous material to ensure efficient storage and
rational logistics of food products».
1. «Fundamentals and novel technologies for accelerated development of advanced functional materials based on supercomputer modeling, flow synthesis and diagnostics under the control of artificial intelligence»;
2. «Understanding the kinetics of photoelectrocatalytic reactions based on in-situ charaсterisation using synchrotron radiation and artificial intelligence»;
3. «An artificial intelligence-controlled robotic station at a synchrotron radiation infrastructure for accelerated development of advanced novel materials and their on-the-fly characterization»;
4. «Frontier laboratory for X-ray spectral nanometrology»;
5. «Development of a novel generation of nanoporous material to ensure efficient storage and
rational logistics of food products».
1. J. Vercammen, M. Bocus, S. Neale, Aram Bugaev, S, Van Minnebruggen, J. Hajek, P. Tomkins, Alexander Soldatov, A. Krajnc, G. Mali, V. Van Speybroeck, D. E. De Vos. Shape-Selective C-H Activation of Aromatics to Biarylic Compounds Using Molecular Palladium in Zeolites // Nature Catalysis.- 2020.- V. 3. P. 1002–1009. Impact-factor: 41.813. DOI: 10.1038/s41929-020-00533-6 https://dx.doi.org/10.1038/s41929-020-00533-6
2. N. Van Velthoven, M. Henrion, J. Dallenes, A. Krajnc, A.L. Bugaev, P. Liu, S. Bals, A.V. Soldatov, G. Mali, D.E. De Vos. S,O-Functionalized Metal-Organic Frameworks as Heterogeneous Single-Site Catalysts for the Oxidative Alkenylation of Arenes via C-H activation // ACS Catalysis.- 2020.- V. 10 (9). P. 5077-5085.Impact-factor: 13.084. DOI: 10.1021/acscatal.0c00801 https://dx.doi.org/10.1021/acscatal.0c00801
3. M. Stalpaert, K. Janssens, C. Marquez, M. Henrion, A.L. Bugaev, A.V. Soldatov, and D.E. De Vos. Olefins from Biobased Sugar Alcohols via Selective, Ru-mediated reaction in Catalytic Phosphonium Ionic Liquids // ACS Catalysis.- 2020.- V. 10 (16). P. 9401–9409. Impact-factor: 13.084. DOI: 10.1021/acscatal.0c02188 https://dx.doi.org/10.1021/acscatal.0c02188
4. O. A. Usoltsev, A. A. Skorynina, B. O. Protsenko, V. Martin-Diaconescu, R. Pellegrini, A. V. Soldatov, J. van Bokhoven, A. L. Bugaev. Evolution of surface and bulk structure of supported palladium nanoparticles by in situ X-ray absorption and infrared spectroscopies: Effect of temperature, CO and CH4 gas // Applied Surface Science.- 2023. - V. 614. 156171. Impact-factor: 7.392. DOI: 10.1016/j.apsusc.2022.156171 https://dx.doi.org/10.1016/j.apsusc.2022.156171
5. K. Janssens, A. L. Bugaev, E. G. Kozyr, V. Lemmens, A. A. Guda, O. A. Usoltsev, S. Smolders, A. V Soldatov, D. E. De Vos. Evolution of the active species of homogeneous Ru hydrodeoxygenation catalysts in ionic liquids // Chemical Science.- 2022.- V. 13. P. 10251-10259. Impact-factor: 9.969. DOI: 10.1039/D2SC02150A https://dx.doi.org/10.1039/D2SC02150A
6. David Trummer, Keith Searles, Alexander Algasov, Sergey A. Guda, Alexander V. Soldatov, Harry Ramanantoanina, Olga V. Safonova, Alexander A. Guda, and Christophe Copéret. Deciphering the Phillips Catalyst by Orbital Analysis and Supervised Machine Learning from Cr Pre-edge XANES of Molecular Libraries // Journal of the American Chemical Society.- 2021.- V. 143 (19). P. 7326–7341. Impact-factor: 14.612. DOI: 10.1021/jacs.0c10791 https://dx.doi.org/10.1021/jacs.0c10791
7. A. A. Guda, S. A. Guda, A. Martini, A. N. Kravtsova, A. Algasov, A. Bugaev, S. P. Kubrin, L. V. Guda, P. Šot, J. A. van Bokhoven, C. Copéret and A. V. Soldatov. Understanding X-ray absorption spectra by means of descriptors and machine learning algorithms // Nature partner journal: Computational Materials.- 2021.- V. 7. 203. Impact-factor: 12.241. DOI: 10.1038/s41524-021-00664-9 https://dx.doi.org/10.1038/s41524-021-00664-9
8. Gorbunov D. N., Nenasheva M. V., Terenina M. V., Kardasheva Y. S., Naranov E. R., Bugaev A. L., Soldatov A. V., Maximov A. L., Tilloy S., Monflier E., Karakhanov E. A. Phosphorus-free nitrogencontaining catalytic systems for hydroformylation and tandem hydroformylation-based
reactions // Applied Catalysis A: General.- 2022.- V. 647. 118891. Impact-factor: 5.723. DOI: 10.1016/j.apcata.2022.118891 https://dx.doi.org/10.1016/j.apcata.2022.118891
9. E. V. Lengert, D.B. Trushina, M. Soldatov, A.V. Ermakov. Microfluidic Synthesis and Analysis of Bioinspired Structures Based on CaCO3 for Potential Applications as Drug Delivery Carriers // Pharmaceutics.- 2022.- V. 14 (1). 139. Impact-factor: 6.321. DOI: 10.3390/pharmaceutics14010139 https://dx.doi.org/10.3390/pharmaceutics14010139
10. Aslam Hossain, M. S. Meera, E. A. Mukhanova, A. V. Soldatov, A. M. A. Henaish, Jahangeer Ahmed, Yuanbing Mao, S. M. A. Shibli. Influences of Partial Destruction of Ti-MOFs on Photo(electro)catalytic H2 Evolution by Dominating Role of Charge Carrier Trapping over Surface Area, Small 2023 (2300492) (Impact-factor: 15.153 ) DOI: 10.1002/smll.202300492
2. N. Van Velthoven, M. Henrion, J. Dallenes, A. Krajnc, A.L. Bugaev, P. Liu, S. Bals, A.V. Soldatov, G. Mali, D.E. De Vos. S,O-Functionalized Metal-Organic Frameworks as Heterogeneous Single-Site Catalysts for the Oxidative Alkenylation of Arenes via C-H activation // ACS Catalysis.- 2020.- V. 10 (9). P. 5077-5085.Impact-factor: 13.084. DOI: 10.1021/acscatal.0c00801 https://dx.doi.org/10.1021/acscatal.0c00801
3. M. Stalpaert, K. Janssens, C. Marquez, M. Henrion, A.L. Bugaev, A.V. Soldatov, and D.E. De Vos. Olefins from Biobased Sugar Alcohols via Selective, Ru-mediated reaction in Catalytic Phosphonium Ionic Liquids // ACS Catalysis.- 2020.- V. 10 (16). P. 9401–9409. Impact-factor: 13.084. DOI: 10.1021/acscatal.0c02188 https://dx.doi.org/10.1021/acscatal.0c02188
4. O. A. Usoltsev, A. A. Skorynina, B. O. Protsenko, V. Martin-Diaconescu, R. Pellegrini, A. V. Soldatov, J. van Bokhoven, A. L. Bugaev. Evolution of surface and bulk structure of supported palladium nanoparticles by in situ X-ray absorption and infrared spectroscopies: Effect of temperature, CO and CH4 gas // Applied Surface Science.- 2023. - V. 614. 156171. Impact-factor: 7.392. DOI: 10.1016/j.apsusc.2022.156171 https://dx.doi.org/10.1016/j.apsusc.2022.156171
5. K. Janssens, A. L. Bugaev, E. G. Kozyr, V. Lemmens, A. A. Guda, O. A. Usoltsev, S. Smolders, A. V Soldatov, D. E. De Vos. Evolution of the active species of homogeneous Ru hydrodeoxygenation catalysts in ionic liquids // Chemical Science.- 2022.- V. 13. P. 10251-10259. Impact-factor: 9.969. DOI: 10.1039/D2SC02150A https://dx.doi.org/10.1039/D2SC02150A
6. David Trummer, Keith Searles, Alexander Algasov, Sergey A. Guda, Alexander V. Soldatov, Harry Ramanantoanina, Olga V. Safonova, Alexander A. Guda, and Christophe Copéret. Deciphering the Phillips Catalyst by Orbital Analysis and Supervised Machine Learning from Cr Pre-edge XANES of Molecular Libraries // Journal of the American Chemical Society.- 2021.- V. 143 (19). P. 7326–7341. Impact-factor: 14.612. DOI: 10.1021/jacs.0c10791 https://dx.doi.org/10.1021/jacs.0c10791
7. A. A. Guda, S. A. Guda, A. Martini, A. N. Kravtsova, A. Algasov, A. Bugaev, S. P. Kubrin, L. V. Guda, P. Šot, J. A. van Bokhoven, C. Copéret and A. V. Soldatov. Understanding X-ray absorption spectra by means of descriptors and machine learning algorithms // Nature partner journal: Computational Materials.- 2021.- V. 7. 203. Impact-factor: 12.241. DOI: 10.1038/s41524-021-00664-9 https://dx.doi.org/10.1038/s41524-021-00664-9
8. Gorbunov D. N., Nenasheva M. V., Terenina M. V., Kardasheva Y. S., Naranov E. R., Bugaev A. L., Soldatov A. V., Maximov A. L., Tilloy S., Monflier E., Karakhanov E. A. Phosphorus-free nitrogencontaining catalytic systems for hydroformylation and tandem hydroformylation-based
reactions // Applied Catalysis A: General.- 2022.- V. 647. 118891. Impact-factor: 5.723. DOI: 10.1016/j.apcata.2022.118891 https://dx.doi.org/10.1016/j.apcata.2022.118891
9. E. V. Lengert, D.B. Trushina, M. Soldatov, A.V. Ermakov. Microfluidic Synthesis and Analysis of Bioinspired Structures Based on CaCO3 for Potential Applications as Drug Delivery Carriers // Pharmaceutics.- 2022.- V. 14 (1). 139. Impact-factor: 6.321. DOI: 10.3390/pharmaceutics14010139 https://dx.doi.org/10.3390/pharmaceutics14010139
10. Aslam Hossain, M. S. Meera, E. A. Mukhanova, A. V. Soldatov, A. M. A. Henaish, Jahangeer Ahmed, Yuanbing Mao, S. M. A. Shibli. Influences of Partial Destruction of Ti-MOFs on Photo(electro)catalytic H2 Evolution by Dominating Role of Charge Carrier Trapping over Surface Area, Small 2023 (2300492) (Impact-factor: 15.153 ) DOI: 10.1002/smll.202300492
1. Soldatov A.V., Pnevskaya A.Y., Protsenko B.O.
Computer program: «Virtual tour of synchrotron radiation sources»
Number 2023668223 dated 08/24/2023;
2. Polyanichenko D.S., Chernov A.V., Kartashov O.O., Aleksandrov A.A., Butakova M.A., Soldatov A. V.
Computer program: «Program for automated computer modeling and labeling of flow synthesis images using a microdisperse droplet generator»
Number 2022684679 dated 12/16/2022;
3. Polozencev O.E., Pankin I.A., Rud P.A., Mukhanova E.A., Soldatov A.V.
Database: «Summary table of synthesis parameters, particle sizes and morphology and luminescence intensity for a series of X-ray phosphors based on gadolinium fluoride doped with terbium ions»
Number 2022623633 dated 12/23/2022;
4. Soldatov A.V., Bagliy A.P., Guda S.A.
Computer program: «Software package for optimizing the parameters of chemical reactions in a microfluidic reactor based on absorption spectra data»
Number 2023611518 dated 01/20/2023;
5. Medvedev P.V., Soldatov A.V., Sivokon D.N., Bagliy A.P.
Computer program: «Software package for controlling a microfluidic synthesis unit with a graphical interface»
Number 2022667654 dated 09/23/2022;
6. Guda S.A., Guda A.A., Soldatov A.V.
Computer program: «Program for analyzing spectral data, forecasting and optimizing experimental parameters in real time based on machine learning methods»
Number 2022610807 dated 17.01.2022;
7. Pankin I.A., Guda S.A., Guda A.A., Soldatov A.V.
Database: «Theoretical XANES X-ray absorption spectra obtained by the finite difference method in the full potential for various structural models of active copper centers of the Cu-SSZ-13 catalyst»
Number 2020621698 dated 17.09.2020;
8. Guda A.A., Guda S.A., Soldatov A.V.
Computer program: «Descriptor»
Number 2020660701 dated 10.09.2020;
9. Tereshchenko A.A., Guda A.A., Rusalev Y.V., Bugaev A.L., Soldatov A.V.
Patent: «Method for determining the oxygen storage capacity in oxide materials»
Number 2708899 dated 12/12/2019;
10. Skorynina A.A., Rusalev Y.V., Guda A.A., Soldatov A.V., Bugaev A.L., Tereshchenko A. A.
Patent: «Cell for spectral diagnostics»
Number 190702 2020;
11. Patent: «Synthesis system with online spectral control»
Number 2021139660;
12. Grigory Smolentsev, Alexander V. Soldatov. FitIt // International Tables for
Crystallography.2024. Vol. I
Computer program: «Virtual tour of synchrotron radiation sources»
Number 2023668223 dated 08/24/2023;
2. Polyanichenko D.S., Chernov A.V., Kartashov O.O., Aleksandrov A.A., Butakova M.A., Soldatov A. V.
Computer program: «Program for automated computer modeling and labeling of flow synthesis images using a microdisperse droplet generator»
Number 2022684679 dated 12/16/2022;
3. Polozencev O.E., Pankin I.A., Rud P.A., Mukhanova E.A., Soldatov A.V.
Database: «Summary table of synthesis parameters, particle sizes and morphology and luminescence intensity for a series of X-ray phosphors based on gadolinium fluoride doped with terbium ions»
Number 2022623633 dated 12/23/2022;
4. Soldatov A.V., Bagliy A.P., Guda S.A.
Computer program: «Software package for optimizing the parameters of chemical reactions in a microfluidic reactor based on absorption spectra data»
Number 2023611518 dated 01/20/2023;
5. Medvedev P.V., Soldatov A.V., Sivokon D.N., Bagliy A.P.
Computer program: «Software package for controlling a microfluidic synthesis unit with a graphical interface»
Number 2022667654 dated 09/23/2022;
6. Guda S.A., Guda A.A., Soldatov A.V.
Computer program: «Program for analyzing spectral data, forecasting and optimizing experimental parameters in real time based on machine learning methods»
Number 2022610807 dated 17.01.2022;
7. Pankin I.A., Guda S.A., Guda A.A., Soldatov A.V.
Database: «Theoretical XANES X-ray absorption spectra obtained by the finite difference method in the full potential for various structural models of active copper centers of the Cu-SSZ-13 catalyst»
Number 2020621698 dated 17.09.2020;
8. Guda A.A., Guda S.A., Soldatov A.V.
Computer program: «Descriptor»
Number 2020660701 dated 10.09.2020;
9. Tereshchenko A.A., Guda A.A., Rusalev Y.V., Bugaev A.L., Soldatov A.V.
Patent: «Method for determining the oxygen storage capacity in oxide materials»
Number 2708899 dated 12/12/2019;
10. Skorynina A.A., Rusalev Y.V., Guda A.A., Soldatov A.V., Bugaev A.L., Tereshchenko A. A.
Patent: «Cell for spectral diagnostics»
Number 190702 2020;
11. Patent: «Synthesis system with online spectral control»
Number 2021139660;
12. Grigory Smolentsev, Alexander V. Soldatov. FitIt // International Tables for
Crystallography.2024. Vol. I
Principal Researcher
- Soldatov Alexander VladimirovichSoldatov Alexander Vladimirovich, Doctor of Physical and Mathematical Sciences, Professor, Scientific Director of the "Materials Science and Synchrotron-Neutron Research" direction at SFedU, Acting Director of the International Research Institute of Intelligent Materials of SFedU, Head of the scientific laboratory "Frontier Laboratory of X-ray Spectral Nanometrology."
The field of science and scientific directions:
Nanotechnology, Materials, Physics
Soldatov A.V. was repeatedly a member and chairman of the program committees of international scientific conferences.
Soldatov A.V. was repeatedly a member and chairman of the program committees of international scientific conferences.
The results of his research have received international recognition, and he has repeatedly worked as a visiting professor at leading foreign educational centers (University of Rome (Italy), University of Western Ontario (Canada), University of Antwerp (Belgium), University of Nijmegen (Netherlands), at the Free University of Berlin (Germany). Member of the editorial boards of a number of scientific journals, including the Journal of Chemical Physics of the Russian Academy of Sciences, Surface: Synchrotron and Neutron Research of the Russian Academy of Sciences, and Russian Nanotechnology.
He has successfully supervised the implementation of over 80 research grants and projects, including over 30 international projects.
Soldatov A.V. is one of the highly cited scientists in Russia ("Active Russian Scientist -2023". He has over 1,000 scientific publications (including over 450 articles in highly rated international peer-reviewed scientific journals).
He has trained 29 candidates and 5 Doctors of Sciences. Currently, he directs the training of 6 graduate students and 3 doctoral students.
Actively conducts pedagogical work. He has prepared more than 60 teaching aids and three electronic multimedia textbooks.
He developed and implemented the training courses "Solid State Physics", "X-ray spectroscopy", "Nanoscale structure of matter", "Electronic structure of matter", "Physics of nanoclusters", "Multiscale computer modeling"
The results of his research have received international recognition, and he has repeatedly worked as a visiting professor at leading foreign educational centers (University of Rome (Italy), University of Western Ontario (Canada), University of Antwerp (Belgium), University of Nijmegen (Netherlands), at the Free University of Berlin (Germany). Member of the editorial boards of a number of scientific journals, including the Journal of Chemical Physics of the Russian Academy of Sciences, Surface: Synchrotron and Neutron Research of the Russian Academy of Sciences, and Russian Nanotechnology.
He has successfully supervised the implementation of over 80 research grants and projects, including over 30 international projects.
Soldatov A.V. is one of the highly cited scientists in Russia ("Active Russian Scientist -2023". He has over 1,000 scientific publications (including over 450 articles in highly rated international peer-reviewed scientific journals).
He has trained 29 candidates and 5 Doctors of Sciences. Currently, he directs the training of 6 graduate students and 3 doctoral students.
Actively conducts pedagogical work. He has prepared more than 60 teaching aids and three electronic multimedia textbooks.
He developed and implemented the training courses "Solid State Physics", "X-ray spectroscopy", "Nanoscale structure of matter", "Electronic structure of matter", "Physics of nanoclusters", "Multiscale computer modeling"
Postdocs
- Role of the Postdoctoral FellowThe postdoc will be involved in cooperation with a team of specialists in the field of chemistry, physics and computer modeling. The postdoc must form a team around him/herself that will be able to solve diagnostic problems in the process of synthesizing new materials using machine learning methods.
- Candidate Requirements
- age up to 39;
- PhD degree (or equivalent) in materials science, applied mathematics, chemistry, physics;
- fluent English (at least upper intermediate level - B2);
- at least 3 publications (Scopus and Web of Science) on the topic of the project;
- experience in data analysis and machine learning, with a focus on applications in spectroscopy, cheminformatics and materials science;
- general programming skills related to machine learning (preferably Python with the ability to use tools: Pandas, numpy, sklearn, scipy, statmodels, pytorch\jax\tensorflow);
- experience in writing scientific articles and literature reviews.
Nanotechnology, Materials, Physics
Expected results:
publication preparation, RIA preparation, student supervision, training of scientific personnel, participation in scientific conferences
Expected results:
publication preparation, RIA preparation, student supervision, training of scientific personnel, participation in scientific conferences
The Smart Materials Research Institute, Southern Federal University
- Terms and ConditionsSalary – 120,000 rubles.
Additional support –support in obtaining a visa, official housing, assistance in employment and education of family members, internships, trips, visits to medical institutions, Russian language courses, etc.
The estimated duration of work is 2-3 years
Working languages