Mikhail Konstantinovich

Mr. Mikhail Konstantinovich


Research Focus & Metrics

Academic Career Length

5Years (2022-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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16 October 2024 in Nanomaterials
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Journal Article
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MRMaxim Rabchinskii
Maxim Rabchinskii
KSKseniya Shiyanova
Kseniya Shiyanova
Maria BrzhezinskayaMaria Brzhezinskaya
Maria Brzhezinskaya
MGMaksim Vladimirovich Gudkov
Maksim Vladimirovich Gudkov
SSSviatoslav D. Saveliev
Sviatoslav D. Saveliev
VMValery Melnikov
Valery Melnikov
Conductive polymer composites (CPCs) with nanocarbon fillers are at the high end of modern materials science, advancing current electronic applications. Herein, we establish the interplay between the chemistry and electrophysical properties of reduced graphene oxide (rGO), separately and as a filler for CPCs with the segregated structure conferred by the chemical composition of the initial graphene oxide (GO). A set of experimental methods, namely X-ray photoelectron spectroscopy (XPS), ultraviolet-visible spectroscopy, van der Paw and temperature-dependent sheet resistance measurements, along with dielectric spectroscopy, are employed to thoroughly examine the derived materials. The alterations in the composition of oxygen groups along with their beneficial effect on nitrogen doping upon GO reduction by hydrazine are tracked with the help of XPS. The slight defectiveness of the graphene network is found to boost the conductivity of the material due to facilitating the impact of the nitrogen lone-pair electrons in charge transport. In turn, a sharp drop in material conductivity is indicated upon further disruption of the π-conjugated network, predominantly governing the charge transport. Particularly, the transition from the Mott variable hopping transport mechanism to the Efros–Shklovsky one is signified. Finally, the impact of rGO chemistry and physics on the electrophysical properties of CPCs with the segregated structure is evaluated. Taken together, our results give a hint at how GO chemistry manifests the properties of rGO and the CPC derived from it, offering compelling opportunities for their practical applications.

30 September 2022 in Polymers
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Journal Article
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KSKseniya Shiyanova
Kseniya Shiyanova
MGMaksim Vladimirovich Gudkov
Maksim Vladimirovich Gudkov
MKMikhail Konstantinovich
Mikhail Konstantinovich
NRNatalia Ryvkina
Natalia Ryvkina
ICIgor Chmutin
Igor Chmutin
VMValery Melnikov
Valery Melnikov
This work is devoted to the formation and study of polymer composites with a segregated structure filled with single-walled carbon nanotubes (SWCNTs), reduced graphene oxide (rGO), and their mixtures. For the first time, polymer composites with a segregated structure filled with rGO/SWCNTs mixtures were obtained. A copolymer of vinylidene fluoride and tetrafluoroethylene (P(VDF-TFE)) was used as a polymer matrix. At a fixed value of the total mass fraction of carbon nanofillers (0.5, 1, and 1.5 wt%), the rGO/SWCNTs ratio was varied. The composites were examined using scanning electron microscopy, wide-range dielectric spectroscopy, and tested for the compression. The effect of the rGO/SWCNTs ratio on the electrical conductivity and mechanical properties of the composites was evaluated. It was shown that, with a decrease in the rGO/SWCNTs ratio, the electrical conductivity increased and reached the maximum at the 1 wt% filling, regardless of the samples’ composition. The maximum value of electrical conductivity from the entire data set was 12.2 S/m. The maximum of elastic modulus was 378.7 ± 3.5 MPa for the sample with 1 wt% SWCNTs, which is 14% higher than the P(VDF-TFE) elastic modulus. The composite filled with a mixture of 0.5 wt% rGO and 0.5 wt% SWCNTs reflected 70% of the electromagnetic wave energy from the front boundary, which is 14% and 50% more than for composites with 1 wt% SWCNTs and with 1 wt% rGO, respectively. The lowest transmission coefficient of ultra-high frequencies waves was obtained for a composite sample with a mixture of 0.5 wt% rGO and 0.5 wt% SWCNTs and amounted to less than 1% for a 2 mm thickness sample.

11 May 2026 in Nanomaterials
Verified
Journal Article
Open access
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KSKseniya Shiyanova
Kseniya Shiyanova
MKMikhail Konstantinovich
Mikhail Konstantinovich
EIEgor A. Inshakov
Egor A. Inshakov
SRSergei A. Ryzhkov
Sergei A. Ryzhkov
Maria BrzhezinskayaMaria Brzhezinskaya
Maria Brzhezinskaya
MRMaxim Rabchinskii
Maxim Rabchinskii
Conductive polymer composites with a segregated structure are a promising route to obtaining electrically active materials at low filler loadings. In this work, aminated graphene (AmG) was used as a functional conductive filler for the fabrication of composites with a segregated structure based on polyvinyl chloride (PVC) and poly(vinylidene fluoride-co-tetrafluoroethylene) (P(VDF-TFE)). AmG was comprehensively characterized by electron microscopy, core-level and near-edge spectroscopy, optical spectroscopy, and electrical measurements. The synthesized AmG contained 14.34 at.% nitrogen, with amines accounting for 81.44% of the nitrogen-related spectral intensity, corresponding to an amine concentration of 11.78 at.%. AmG also exhibited a restored π-conjugated network, intrinsic conductivity of 20–33 S/cm, and a crumpled-flake morphology favorable for interfacial contact with polymer particles. At a filler loading of only 1 wt.%, the segregated composites reached electrical conductivity up to 1.3–1.4 × 10−4 S/cm, exceeding those of the unfilled polymers by seven orders of magnitude. At 11 GHz, the AmG-filled P(VDF-TFE) composite showed 15.1 dB attenuation for a theoretical thickness of 30 mm, transmitting no more than 3% of the incident radiation. These results identify AmG as a functional conductive filler for segregated electrically conductive polymer composites and demonstrate that the combination of amine-containing surface chemistry, restored electrical conductivity, and crumpled morphology enables conductive interparticle network formation in PVC- and P(VDF-TFE)-based composites at only 1 wt.% filler loading.