Публикации

Сотрудничество с ИОХ РАН:

Miniaturization of NMR Systems: Desktop Spectrometers, Microcoil Spectroscopy, and “NMR on a Chip” for Chemistry, Biochemistry, and Industry

Sergey S. Zalesskiy,1 Ernesto Danieli,2 Bernhard Blümich,2,* Valentine P. Ananikov1,2,*

1 Zelinsky Institute of Organic Chemistry, Russian Academy of Sciences, Moscow, 119991, Russia.

2 Institut für Technische Chemie und Makromolekulare Chemie, RWTH Aachen University, Worringerweg 1, D-52074 Aachen, Germany.

3 Department of Chemistry, Saint Petersburg State University, Stary Petergof, 198504, Russia.

Chem. Rev., 2014, asap. DOI: 10.1021/cr400063g | PDF


Table of Contents:


  • 1. Introduction
  • 2. Development of Equipment for NMR Miniaturization
    • 2.1. Magnet Development and Design
    • 2.2. Electronics and Radiofrequency Transmission Part
    • 2.3. Probes and Microcoil Systems Development
    • 2.4. New Designs and Alternative Detection Methods
    • 2.5. Perspectives of Hardware Miniaturization
  • 3. Properties and Applications of Miniaturized NMR
    • 3.1. Flow Systems and LC–NMR
    • 3.2. NMR on a Chip and Total Analysis Systems (TAS)
    • 3.3. In Vivo Studies
    • 3.4. Industrial Applications
      • 3.4.1. Rubber and Polymer Materials
      • 3.4.2. Concrete and Building Materials
      • 3.4.3. Cultural Heritage
      • 3.4.4. Plant Phenotyping
      • 3.4.5. Pharmaceutical Industry
      • 3.4.6. Food Industry
      • 3.4.7. Process Analysis and Control
  • 4. Conclusions

Catalytic C–C and C–Heteroatom Bond Formation Reactions: In Situ Generated or Preformed Catalysts? Complicated Mechanistic Picture Behind Well-Known Experimental Procedures

Alexey S. Kashin,1 and Valentine P. Ananikov,1,2,*

1 Zelinsky Institute of Organic Chemistry, Russian Academy of Sciences, Leninsky Prospect 47, Moscow, 119991, Russia.
2 Department of Chemistry, Saint Petersburg State University, Stary Petergof, 198504, Russia.

J. Org. Chem., 2013, 78,11117 - 11125. DOI: 10.1021/jo402038p | PDF


Abstract: In situ generated catalysts and preformed catalysts are two practical strategies widely used in cross-coupling methodology that have long been considered to involve the same active species in the catalytic cycle. Recent mechanistic studies have revealed two fundamentally different pictures of catalytic reactions in solution. Preformed catalysts with strongly bound ligands initiate transformations mainly involving single type of metal species. In contrast, in situ generated catalysts give rise to cocktail-type systems with different metal species presented in solution. The role of catalyst precursor, inter­conversions of catalytic species during reaction, stability and recycling of catalyst, catalysis by autocatalyst exhaust and plausible sources of metal-containing contaminants are the key points discussed in this review.

Self-Assembled Selenium Monolayers: From Nanotechnology to Materials Science and Adaptive Catalysis

Leonid V. Romashov,1 Valentine P. Ananikov,1,2,*

1 Zelinsky Institute of Organic Chemistry, Russian Academy of Sciences, Leninsky Prospect 47, Moscow, 119991, Russia.
2 Department of Chemistry, Saint Petersburg State University, Stary Petergof, 198504, Russia.

Chem. Eur. J., 2013, 19,17640 - 17660. DOI: 10.1002/chem.201302115 | PDF


Self-assembled monolayers (SAMs) of selenium have emerged into a rapidly developing field of nano­tech­nology with several promising opportunities in materials chemistry and catalysis. Comparison between sulfur-based self-assembled monolayers and newly developed sele­ni­um-based monolayers reveal outstanding complimentary features on surface chemistry and highlighted the key role of the headgroup element. Diverse structural properties and reactivity of organosulfur and organoselenium groups on the surface provide flexible frameworks to create new gene­ra­ti­ons of materials and adaptive catalysts with unprecedented selectivity. Important practical utility of adaptive catalytic systems deals with development of sustainable tech­no­lo­gies and industrial processes based on natural resources. Independent development of nanotechnology, materials science and catalysis has led to the discovery of common fundamental principles of the surface chemistry of chalco­gen compounds.

Recent Advances in Computational Predictions of NMR Parameters for The Structure Elucidation of Carbohydrates: Methods and Limitations

Filip V. Toukach,1 Valentine P. Ananikov,1,2,*

1 Zelinsky Institute of Organic Chemistry, Russian Academy of Sciences, Leninsky Prospect 47, Moscow, 119991, Russia.
2 Department of Chemistry, Saint Petersburg State University, Stary Petergof, 198504, Russia.

Chem. Soc. Rev.2013, 42, 8376 - 8415. DOI: 10.1039/C3CS60073D | PDF


All living systems are comprised of four fundamental classes of macromolecules – nucleic acids, proteins, lipids, and carbohydrates (glycans). Glycans play a unique role of joining three principal hierarchical levels of the living world: (1) the molecular level (pathogenic agents and vaccine recognition by the immune system, metabolic pathways involving saccha­rides that provide cells with energy, and energy accumulation via photosynthesis); (2) the nanoscale level (cell membrane me­cha­nics, structural support of biomolecules, and the glyco­sylation of macromolecules); (3) the microscale and macro­scale levels (polymeric materials, such as cellulose, starch, glycogen, and biomass). NMR spectroscopy is the most powerful research approach for getting insight into the solution structure and function of carbohydrates at all hierarchical levels, from monosaccharides to oligo- and polysaccharides. Recent progress in computational procedures has opened up novel opportunities to reveal the structural information available in the NMR spectra of saccharides and to advance our understanding of the corresponding biochemical processes. The ability to predict the molecular geometry and NMR parameters is crucial for the elucidation of carbohydrate structures. In the present paper, we review the major NMR spectrum simulation techniques with regard to chemical shifts, coupling constants, relaxation rates and nuclear Overhauser effect prediction applied to the three levels of glycomics. Outstanding development in the related fields of genomics and proteomics has clearly shown that it is the advancement of research tools (automated spectrum analysis, structure elucidation, synthesis, sequencing and amplification) that drives the large challenges in modern science. Combining NMR spectroscopy and the computational analysis of structural information encoded in the NMR spectra reveals a way to the automated elucidation of the structure of carbohydrates.

Fast and Accurate Computational Modeling of Adsorption on Graphene: A Dispersion Interaction Challenge

Evgeniy G. Gordeev,1 Mikhail V. Polynski,1 Valentine P. Ananikov,1,2,*

1 Zelinsky Institute of Organic Chemistry, Russian Academy of Sciences, Leninsky Prospect 47, Moscow, 119991, Russia.
2 Department of Chemistry, Saint Petersburg State University, Stary Petergof, 198504, Russia.

Phys. Chem. Chem. Phys.2013, 15, 18815 - 18821. DOI: 10.1039/C3CP53189A | PDF


Understanding molecular interactions of graphene is a question of key importance to design new materials and catalytic systems for practical usage. Although for small models good accuracy was demonstrated in theoretical analysis with ab initio and density functional methods, the application to real-size systems with thousands of atoms is currently hardly possible on routine bases due to the high computational cost. In the present study we report that incorporation of dispersion cor­rection led to the principal improvement in the description of graphene systems at a semi-empirical level. The accuracy and the scope of the calculations were explored for a wide range of molecules adsorbed on graphene surfaces (H2, N2, CO, CO2, NH3, CH4, H2O, benzene, naphthalene, coronene, ovalene and cyclohexane). As a challenging parameter, the calculated adsorption energy of aromatic hydrocarbons on graphene Eads = −1.8 ± 0.1 kcal mol−1 (per one carbon atom) at the PM6-DH2 level was in excellent agreement with the experimentally de­termined value of Eads = −1.7 ± 0.3 kcal mol−1. The dispersion corrected semi-empirical method was found to be a remarkable computational tool suitable for everyday laboratory studies of real-size graphene systems. Significant performance improvement (ca. 103 times faster) and excellent accuracy were found as compared to the ωB97X-D density functional calculations.