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Mirsaidov U.,National University of Singapore | Mirsaidov U.,USPolyResearch | Timashev S.F.,Karpov Institute of Physical Chemistry | Polyakov Y.S.,USPolyResearch | And 4 more authors.
Analyst | Year: 2011

The functional properties of many technological surfaces in biotechnology, electronics, and mechanical engineering depend to a large degree on the individual features of their nanoscale surface texture, which in turn is a function of the surface manufacturing process. Among these features, the surface irregularities and self-similarity structures at different spatial scales, especially in the range of 1 to 100 nm, are of high importance because they greatly affect the surface interaction forces acting at a nanoscale distance. An analytical method for parameterizing the surface irregularities and their correlations in nanosurfaces imaged by atomic force microscopy (AFM) is proposed. In this method, flicker noise spectroscopy - a statistical physics approach - is used to develop six nanometrological parameters characterizing the high-frequency contributions of jump- and spike-like irregularities into the surface texture. These contributions reflect the stochastic processes of anomalous diffusion and inertial effects, respectively, in the process of surface manufacturing. The AFM images of the texture of corrosion-resistant magnetite coatings formed on low-carbon steel in hot nitrate solutions with coating growth promoters at different temperatures are analyzed. It is shown that the parameters characterizing surface spikiness are able to quantify the effect of process temperature on the corrosion resistance of the coatings. It is suggested that these parameters can be used for predicting and characterizing the corrosion-resistant properties of magnetite coatings. © 2011 The Royal Society of Chemistry.

Polyakov Y.S.,USPolyResearch | Neilsen J.,Massachusetts Institute of Technology | Neilsen J.,Harvard - Smithsonian Center for Astrophysics | Timashev S.F.,Karpov Institute of Physical Chemistry
Astronomical Journal | Year: 2012

We examine stochastic variability in the dynamics of X-ray emission from the black hole system GRS 1915+105, a strongly variable microquasar commonly used for studying relativistic jets and the physics of black hole accretion. The analysis of sample observations for 13 different states in both soft (low) and hard (high) energy bands is performed by flicker-noise spectroscopy (FNS), a phenomenological time series analysis method operating on structure functions and power spectrum estimates. We find the values of FNS parameters, including the Hurst exponent, flicker-noise parameter, and characteristic timescales, for each observation based on multiple 2500 s continuous data segments. We identify four modes of stochastic variability driven by dissipative processes that may be related to viscosity fluctuations in the accretion disk around the black hole: random (RN), power-law (1F), one-scale (1S), and two-scale (2S). The variability modes are generally the same in soft and hard energy bands of the same observation. We discuss the potential for future FNS studies of accreting black holes. © 2012 The American Astronomical Society. All rights reserved.

Timashev S.F.,Karpov Institute of Physical Chemistry | Polyakov Yu.S.,USPolyResearch | Lakeev S.G.,Karpov Institute of Physical Chemistry | Misurkin P.I.,RAS Semenov Institute of Chemical Physics | Danilov A.I.,RAS Frumkin Institute of Physical Chemistry and Electrochemistry
Russian Journal of Physical Chemistry A | Year: 2010

The possibility in principle of extending metrological concepts to the characteristics of complex objects, the primary information about the state or structure of which is presented in the form of complex chaotic dependences and cannot be expressed using standard metrological images such as directly measured time and length and other dimensional values, is shown. To correctly characterize the dynamic state of such complex objects, including states of objects during nonstationary evolution, or the special features of structures formed under the conditions of external actions of various intensities, it is necessary, first, to introduce autocorrelation dependences averaged over time or spatial intervals on the basis of measured dynamic variables and, next, to use these dependences to find sets of information parameters, which can be presented as metrological characteristics of the dynamic state under study or spatial image to be analyzed. The phenomenological basis of the corresponding analysis is provided by flicker-noise spectroscopy with its possibilities of developing procedures and algorithms that can be used to obtain metrological characteristics over various frequency (time and spatial) ranges of the signals analyzed. This is the basis on which unity of metrological characteristic measurements with a determined uncertainty (error) in measurements can be achieved, standards and reference samples of fluctuation metrology can be created, and methods for the transfer of standard parameters from standards to reference samples and then to working measurement instruments can be developed. This opens up the possibility for solving many practical problems of microelectronics, energetics, nanoindustry, chemical technology, which include standardization of the state of complex systems and articles of various functional purposes, and the quality of products created. © 2010 Pleiades Publishing, Ltd.

Ryabinin G.V.,Russian Academy of Sciences | Polyakov Yu.S.,USPolyResearch | Gavrilov V.A.,Institute of Volcanology and Seismology | Timashev S.F.,Karpov Institute of Physical Chemistry
Natural Hazards and Earth System Science | Year: 2011

A phenomenological systems approach for identifying potential precursors in multiple signals of different types for the same local seismically active region is proposed based on the assumption that a large earthquake may be preceded by a system reconfiguration (preparation) on different time and space scales. A nonstationarity factor introduced within the framework of flicker-noise spectroscopy, a statistical physics approach to the analysis of time series, is used as the dimensionless criterion for detecting qualitative (precursory) changes within relatively short time intervals in arbitrary signals. Nonstationarity factors for chlorine-ion concentration variations in the underground water of two boreholes on the Kamchatka peninsula and geacoustic emissions in a deep borehole within the same seismic zone are studied together in the time frame around a large earthquake on 8 October 2001. It is shown that nonstationarity factor spikes (potential precursors) take place in the interval from 70 to 50 days before the earthquake for the hydrogeochemical data and at 29 and 6 days in advance for the geoacoustic data. © Author(s) 2011.

Litak G.,Lublin University of Technology | Polyakov Y.S.,USPolyResearch | Polyakov Y.S.,New Jersey Institute of Technology | Timashev S.F.,Karpov Institute of Physical Chemistry | Rusinek R.,Lublin University of Technology
Physica A: Statistical Mechanics and its Applications | Year: 2013

We use flicker-noise spectroscopy (FNS), a phenomenological method for the analysis of time and spatial series operating on structure functions and power spectrum estimates, to identify and study harmful chatter vibrations in a regenerative turning process. The 3D cutting force components experimentally measured during stainless steel turning are analyzed, and the parameters of their stochastic dynamics are estimated. Our analysis shows that the system initially exhibiting regular vibrations associated with spindle rotation becomes unstable to high-frequency noisy oscillations (chatter) at larger cutting depths. We suggest that the chatter may be attributed to frictional stick-and-slip interactions between the contact surfaces of cutting tool and workpiece. We compare our findings with previously reported results obtained by statistical, recurrence, multifractal, and wavelet methods. We discuss the potential of FNS in monitoring the turning process in manufacturing practice. © 2013 Elsevier B.V. All rights reserved.

Polyakov Y.S.,USPolyResearch | Zydney A.L.,Pennsylvania State University
Journal of Membrane Science | Year: 2013

Several recent studies have quantified the performance characteristics of ultrafiltration membranes in terms of the inherent trade-off between the membrane selectivity and permeability. However, none of these studies have accounted for the effects of membrane fouling on the evolution of the selectivity and permeability during typical ultrafiltration processes. This review paper examines a range of available fouling models, including the classical pore blockage/pore constriction models as well as newer models based on depth filtration and solute adsorption, with a particular focus on understanding the effects of these fouling phenomena on the permeability-selectivity tradeoff. Although fouling always causes a reduction in permeability, the selectivity can actually increase, e.g., if the larger (less selective) pores are preferentially blocked during ultrafiltration or if the pores are constricted by the foulants. The evolution of the permeability-selectivity tradeoff can be quite complex, depending on both the underlying fouling mechanism as well as the distribution of pore and solute sizes. These results provide new insights into the behavior of ultrafiltration processes. © 2013 Elsevier B.V.

Polyakov Yu.S.,New Jersey Institute of Technology | Polyakov Yu.S.,USPolyResearch
Theoretical Foundations of Chemical Engineering | Year: 2014

A discrete multilayer model for the deposition of solutes inside membrane pores during ultrafiltration is proposed. The model takes into account the time-dependent steric exclusion of solutes at the pore inlet and the difference between the deposition coefficients for the first and higher layers caused by the action of the double-layer electrostatic repulsion forces between suspended and deposited solutes. The governing differential equations are solved numerically for 2- and 3-layer deposition on the pore wall. Also, a much simpler approximate solution with an error less than 10% is obtained for the main practical scenario by the generalized variable-parameter averaging method. Permeability, rejection, and selectivity-permeability tradeoff curves are calculated and compared for the monolayer coverage (Langmuir adsorption), 2-layer, and 3- layer cases at different values of higher-to-first layer deposition coefficient and initial pore radius. It is shown that the value of the deposition coefficient for the higher deposited layers of solutes can dramatically affect the performance of the membrane. For the monolayer coverage case, simple algebraic equations for finding the rejection coefficient and its minimum are derived. They imply that the rejection coefficient can follow three scenarios: monotonically decreasing, monotonically increasing, or having a minimum. A set of derived equations for determining the initial, minimum, and steady-state values of the rejection coefficient and permeate flux is suggested to use along with an experimental selectivity-permeability tradeoff curve to find the unknown physicochemical and geometrical parameters needed to describe the ultrafiltration process of interest, optimize its process parameters, and change the process of membrane manufacturing in order to obtain a more efficient membrane. © 2014 Pleiades Publishing, Ltd.

Ryabinin G.V.,Russian Academy of Sciences | Gavrilov V.A.,Institute of Volcanology and Seismology | Polyakov Y.S.,USPolyResearch | Timashev S.F.,Karpov Institute of Physical Chemistry
Acta Geophysica | Year: 2012

We propose a new type of earthquake precursor based on the analysis of correlation dynamics between geophysical signals of different nature. The precursor is found using a two-parameter cross-correlation function introduced within the framework of flicker-noise spectroscopy, a general statistical physics approach to the analysis of time series. We consider an example of cross-correlation analysis for water salinity time series, an integral characteristic of the chemical composition of groundwater, and geoacoustic emissions recorded at the G-1 borehole on the Kamchatka peninsula in the time frame from 2001 to 2003, which is characterized by a sequence of three groups of significant seismic events. We found that cross-correlation precursors took place 27, 31, and 35 days ahead of the strongest earthquakes for each group of seismic events, respectively. At the same time, precursory anomalies in the signals themselves were observed only in the geoacoustic emissions for one group of earthquakes. © 2012 Versita Warsaw and Springer-Verlag Wien.

Timashev S.F.,Karpov Institute of Physical Chemistry | Panischev O.Y.,Kazan Federal University | Polyakov Y.S.,USPolyResearch | Demin S.A.,Kazan Federal University | Kaplan A.Y.,Moscow State University
Physica A: Statistical Mechanics and its Applications | Year: 2012

We apply flicker-noise spectroscopy (FNS), a time series analysis method operating on structure functions and power spectrum estimates, to study the clinical electroencephalogram (EEG) signals recorded in children/adolescents (11 to 14 years of age) with diagnosed schizophrenia-spectrum symptoms at the National Center for Psychiatric Health (NCPH) of the Russian Academy of Medical Sciences. The EEG signals for these subjects were compared with the signals for a control sample of chronically depressed children/adolescents. The purpose of the study is to look for diagnostic signs of subjects' susceptibility to schizophrenia in the FNS parameters for specific electrodes and cross-correlations between the signals simultaneously measured at different points on the scalp. Our analysis of EEG signals from scalp-mounted electrodes at locations F3 and F4, which are symmetrically positioned in the left and right frontal areas of cerebral cortex, respectively, demonstrates an essential role of frequencyphase synchronization, a phenomenon representing specific correlations between the characteristic frequencies and phases of excitations in the brain. We introduce quantitative measures of frequencyphase synchronization and systematize the values of FNS parameters for the EEG data. The comparison of our results with the medical diagnoses for 84 subjects performed at NCPH makes it possible to group the EEG signals into 4 categories corresponding to different risk levels of subjects' susceptibility to schizophrenia. We suggest that the introduced quantitative characteristics and classification of cross-correlations may be used for the diagnosis of schizophrenia at the early stages of its development. © 2011 Elsevier B.V. All rights reserved.

Timashev S.F.,Karpov Institute of Physical Chemistry | Polyakov Y.S.,USPolyResearch | Misurkin P.I.,RAS Semenov Institute of Chemical Physics | Lakeev S.G.,Karpov Institute of Physical Chemistry
Physical Review E - Statistical, Nonlinear, and Soft Matter Physics | Year: 2010

We propose an interpolation expression using the difference moment (Kolmogorov transient structural function) of the second order as the average characteristic of displacements for identifying the anomalous diffusion in complex processes when the stochastic (the term "stochastic" in this paper refers to random variability in the signals of complex systems characterized by nonlinear interactions, dissipation, and inertia) dynamics of the system under study reaches a steady state (large time intervals). Our procedure based on this expression for identifying anomalous diffusion and calculating its parameters in complex processes is applied to the analysis of the dynamics of blinking fluorescence of quantum dots, x-ray emission from accreting objects, fluid velocity in Rayleigh-Bénard convection, and geoelectrical signal for a seismic area. For all four examples, the proposed interpolation is able to adequately describe the stochastic part of the experimental difference moment, which implies that anomalous diffusion manifests itself in these complex processes. The results of this study make it possible to broaden the range of complex natural processes in which anomalous diffusion can be identified. © 2010 The American Physical Society.

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