I was born on 5th December 1995 in Kogalym, Western Siberia. When I was four, my family and I moved to Moscow, which gave me the opportunity to study at some of the best schools in Russia. Currently, I am an undergraduate student of the Higher Chemical College of the Russian Academy of Sciences.
I have been doing scientific research since I was in the 10th grade of school. My research interests are:
In the present paper, samples of pure and doped lithium iron phosphate composite with the following composition: LiFePO4/С, Li0.99Fe0.98(CrNi)0.01PO4/С were synthesized. The samples were synthesized using the sol-gel method. According to the acquired data, all the obtained samples of lithium iron phosphate are crystallized in the orthorhombic modification of lithium iron phosphate with the structure of olivine. The average particle size of the obtained materials varies in the range of 50-100 nm. The carbon content was 4 wt%. The doping of lithium iron phosphate with trivalent cations of chromium and nickel results in the increase of the discharge capacity at high discharge rates with the simultaneous stability augmentation during the cycling.
Lithium iron phosphate samples doped with chromium and nickel were successfully synthesized by sol-gel method. Their electrochemical behavior has been investigated with the use of charge/discharge tests. These studies showed that doped lithium iron phosphate has lower discharge capacity compared with undoped sample. However, the dependence of discharge capacity versus current density for all of the doped samples is less pronounced.
Lithium iron phosphates with olivine structure doped by trivalent cations and co-doped by divalent and trivalent cations of the compositions Li1-xFe1-xMIIIxPO4 (MIII=Al, Cr, Ga, Y, In) and Li1-xFe1-2x(NiMIII)xPO4 (MIII=Al, In) were prepared by the sol-gel method. Structure, morphology, and conductivity of the prepared materials were studied by the X-ray diffraction analysis, scanning electron microscopy, and impedance spectroscopy. The solubility of M3+ cations in LiFePO4 with olivine structure was estimated. Single-phase samples were shown to be preserved at x ≤ 0.05 for Cr3+ and Al3+ cations, at x ≤ 0.02 for In3+, and at x ≤ 0.005 for Ga3+ and Y3+ cations. The materials doped with M3+ and co-doped with both M2+ and M3+ cations were characterized by a higher ionic conductivity and by a lower activation energy of ionic conductivity. Carbon-coated materials Li0.995Fe0.99(NiM)0.005PO4/C (MIII=Al, In) were prepared, and their electrochemical behavior was studied using the charge/discharge tests. Due to LiFePO4 co-doping with M2+ and M3+ cations, capacity slightly decreases but the charge/discharge rate increases.
Glycan Optimized Dual Empirical Spectrum Simulation (GODESS) is a web service, which has been recently shown to be one of the most accurate tools for simulation of 1H and 13C 1D NMR spectra of natural carbohydrates and their derivatives. The new version of GODESS supports visualization of the simulated 1H and 13C chemical shifts in the form of most 2D spin correlation spectra commonly used in carbohydrate research, such as 1H–1H TOCSY, COSY/COSY-DQF/COSY-RCT, and 1H–13C edHSQC, HSQC–COSY, HSQC–TOCSY, and HMBC. Peaks in the simulated 2D spectra are color-coded and labeled according to the signal assignment and can be exported in JCAMP-DX format. Peak widths are estimated empirically from the structural features. GODESS is available free of charge via the Internet at the platform of the Carbohydrate Structure Database project (http://csdb.glycoscience.ru).
Carbohydrates play an immense role in different aspects of life. NMR spectroscopy is the most powerful tool for investigation of these compounds. Nowadays, progress in computational procedures has opened up novel opportunities giving an impulse to the development of new instruments intended to make the research simpler and more efficient. In this paper, we present a new approach for simulating 13C NMR chemical shifts of carbohydrates. The approach is suitable for any atomic observables, which could be stored in a database. The method is based on sequential generalization of the chemical surroundings of the atom under prediction and heuristic averaging of database data. Unlike existing applications, the generalization scheme is tuned for carbohydrates, including those containing phosphates, amino acids, alditols, and other non-carbohydrate constituents. It was implemented in the Glycan-Optimized Dual Empirical Spectrum Simulation (GODESS) software, which is freely available on the Internet. In the field of carbohydrates, our approach was shown to outperform all other existing methods of NMR spectrum prediction (including quantum-mechanical calculations) in accuracy. Only this approach supports NMR spectrum simulation for a number of structural features in polymeric structures.
The improved Carbohydrate Structure Generalization Scheme has been developed for the simulation of 13C and 1H NMR spectra of oligo- and polysaccharides and their derivatives, including those containing noncarbohydrate constituents found in natural glycans. Besides adding the 1H NMR calculations, we improved the accuracy and performance of prediction and optimized the mathematical model of the precision estimation. This new approach outperformed other methods of chemical shift simulation, including database-driven, neural net-based, and purely empirical methods and quantum-mechanical calculations at high theory levels. It can process structures with rarely occurring and noncarbohydrate constituents unsupported by the other methods. The algorithm is transparent to users and allows tracking used reference NMR data to original publications. It was implemented in the Glycan-Optimized Dual Empirical Spectrum Simulation (GODESS) web service, which is freely available at the platform of the Carbohydrate Structure Database (CSDB) project (http://csdb.glycoscience.ru).