Reactor Engineering

Digital design, additive manufacturing and practical validation of chemical reactors for modern organic synthesis.

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Mechanisms of catalytic reactions

Catalysis has fundamentally changed chemistry of the 21st century and became the basis of the modern industrial processes.

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AI in Chemistry

The project developed and improved unique competences in the application of artificial intelligence (AI) to solve complex chemistry problems.

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Biofilms and Biofouling

Biofilms shape environmental processes, industrial performance, and many clinically important infections. They are structurally complex, dynamic, and often resistant to conventional treatment.

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News

05 May 2026

Reactive gas modulation alters metal nanostructures nuclearity and boosts catalytic activity

The article «Reactive gas modulation alters metal nanostructures nuclearity and boosts catalytic activity» by Galushko A.S., Chepkasov I.V., Shaydullin R.R., Boiko D.A., Kvashnin A.G., Abakumov A.M., Ananikov V.P. was published in Chinese Journal of Catalysis (Elsevier B.V.)

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03 April 2026

Deep learning-based high-information-content graph representation of early stage bacterial biofilms

The article «Deep learning-based high-information-content graph representation of early stage bacterial biofilms» by Nersesyan L.E., Boiko D.A., Kurbanalieva S., Dzhemileva L.U., Kozlov K.S., Ananikov V.P. was published in npj Biofilms and Microbiomes (Springer Nature)

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30 March 2026

Unforeseen Light-Emitting Diode Aging: Impact on Scientific Equipment, Research Precision, and Reproducibility

The article «Unforeseen Light-Emitting Diode Aging: Impact on Scientific Equipment, Research Precision, and Reproducibility» by Kozlov K.S., Kobelev A.D., Surzhikova I.I., Shlapakov N.S., Ananikov V.P. was published in ChemPhotoChem (Wiley)

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19 March 2026

When ligands promote, inhibit, or disappear: reaction-dependent roles in Au and Cu catalysis

The article «When ligands promote, inhibit, or disappear: reaction-dependent roles in Au and Cu catalysis» by Grudova M.V., Galushko A.S., Skuratovich V.A., Nakhatova A.O., Ilyushenkova V.V., Chernyshev V.M., Ananikov V.P. was published in Inorg. Chem. Front. (Royal Society of Chemistry)

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02 March 2026

Image-to-molecule benchmarking dataset with fractal pattern and hierarchical morphology recognition

The article «Image-to-molecule benchmarking dataset with fractal pattern and hierarchical morphology recognition» by Arkhipova D.M., Boiko D.A., Oganov A.A., Kashin A.S., Gordeev E.G., Ananikov V.P. was published in Sci. Data. (Wiley)

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Welcome to Ananikov Lab

Understanding how molecules and catalysts transform

Ananikov Lab studies the life cycle of molecules, catalysts and reactive intermediates under real chemical conditions. Our central research theme – Molecular Complexity and Transformations – connects organic synthesis, catalysis, nanoscale chemistry, photochemistry, molecular modeling and machine learning into a unified approach to modern reaction science.

Led by Prof. Valentine P. Ananikov at the Zelinsky Institute of Organic Chemistry, Russian Academy of Sciences, the laboratory develops experimental, theoretical and data-driven methods to understand how chemical systems form, operate, adapt and degrade. We investigate catalytic transformations across multiple scales — from molecular complexes and reactive intermediates to clusters, nanoparticles, carbon materials and single-atom catalytic centers.

Our goal is to reveal the mechanisms of chemical transformations and use this knowledge to design more selective, efficient and sustainable transformations for organic synthesis, materials chemistry and chemical technologies. The laboratory combines advanced spectroscopy, microscopy, computational chemistry, molecular modeling and artificial intelligence to build a predictive picture of catalytic and molecular behavior.

Building on the strong tradition of Russian organic chemistry and working within the international research landscape, Ananikov Lab aims to create chemistry that is mechanistically understandable, reproducible, data-rich and useful for solving contemporary scientific and technological challenges.