Electrospun tin-carbon nanocomposite as anode material for all solid state lithium-ion batteries

Journal of Solid State Electrochemistry - All-solid-state batteries represent the next generation of electrochemical energy storage systems. A tin-carbon nanocomposite material is prepared by the...     

Experimental study of heat and mass transfer from a horizontal cylinder in downward air-water mist flow with blockage effect

An experimental study was made on convective heat and mass transfer from a horizontal heated cylinder in a downward flow of air-water mist at a blockage ratio of 0.4. The measured local heat transfer coefficients agree fairly well with the authors' numerical solutions obtained previously for the front surface of a cylinder over the ranges mass flow ratio 0–4.5×10⁻², a temperature difference between the cylinder and air 10–43 K, gas Reynolds number (7.9–23)×10³, Rosin-Rammler size parameter 105–168 μm, and dispersion parameter 3.4–3.7. Heat transfer augmentation, two-pahse to single-phase of greater than 19 was attained at the forward stagnation point. For heat transfer in the rear part of the cylinder, an empirical formula is derived by taking into account the dimensionless governing variables, that is, coolant-feed and evaporation parameters.     

Probabilistic evaluation of interconnectable capacity for wind power generation

We propose a novel framework for probabilistic evaluation of interconnectable capacity for wind power generation. This is based on mathematical modeling of load frequency control systems, which captures their nonlinear (saturation and rate limiting) dynamical characteristics, and stochastic uncertainty of wind power output deviation. The method called stochastic linearization is used to analyze resulting power quality. The effectiveness of the proposed method is examined by numerical simulation.     

Analog computation through high-dimensional physical chaotic neuro-dynamics

Conventional von Neumann computers have difficulty in solving complex and ill-posed real-world problems. However, living organisms often face such problems in real life, and must quickly obtain suitable solutions through physical, dynamical, and collective computations involving vast assemblies of neurons. These highly parallel computations through high-dimensional dynamics (computation through dynamics) are completely different from the numerical computations on von Neumann computers (computation through algorithms). In this paper, we explore a novel computational mechanism with high-dimensional physical chaotic neuro-dynamics. We physically constructed two hardware prototypes using analog chaotic-neuron integrated circuits. These systems combine analog computations with chaotic neuro-dynamics and digital computation through algorithms. We used quadratic assignment problems (QAPs) as benchmarks. The first prototype utilizes an analog chaotic neural network with 800-dimensional dynamics. An external algorithm constructs a solution for a QAP using the internal dynamics of the network. In the second system, 300-dimensional analog chaotic neuro-dynamics drive a tabu-search algorithm. We demonstrate experimentally that both systems efficiently solve QAPs through physical chaotic dynamics. We also qualitatively analyze the underlying mechanism of the highly parallel and collective analog computations by observing global and local dynamics. Furthermore, we introduce spatial and temporal mutual information to quantitatively evaluate the system dynamics. The experimental results confirm the validity and efficiency of the proposed computational paradigm with the physical analog chaotic neuro-dynamics.     

Reproduction of distance matrices and original time series from recurrence plots and their applications

We propose a method to reproduce distance matrices and original time series from recurrence plots. The procedure is to (i)convert a recurrence plot to a weighted graph and (ii)calculate a distance between each pair of nodes on this weighted graph. We demonstrate this method by reproducing the topological shape of original time series. We also propose two applications. The first application is to obtain the maximal Lyapunov exponent from a recurrence plot without reproducing the shapes of original time series. The second application is to reconstruct a common deterministic driving force from observations of forced systems. Thus, the method opens new fields in data analysis.     

Interdisciplinary challenges in the study of power grid resilience and stability and their relation to extreme weather events

This topical issue collects contributions to the interdisciplinary study of power grid stability in face of increasing volatility of energy production and consumption due to increasing renewable energy infeed and changing climatic conditions. The individual papers focus on different aspects of this field and bring together modern achievements from various disciplines, in particular complex systems science, nonlinear data analysis, control theory, electrical engineering, and climatology. Main topics considered here are prediction and volatility of renewable infeed, modelling and theoretical analysis of power grid topology, dynamics and stability, relationships between stability and complex network topology, and improvements via topological changes or control. Impacts for the design of smart power grids are discussed in detail.     

Aromaticity and Diatropicity of Polyacenequinododimethides

Typical polyacenequinododimethides exist only in a single classical structure. These hydrocarbons are moderately aromatic and diatropic, although they have no aromatic conjugated circuits. This apparent dichotomy was resolved with our graph theory of aromaticity and magnetotropicity. Many nonconjugated circuits were found to contribute collectively to aromaticity and diatropicity. For individual molecules, local aromaticity increases with distance from the exo‐methylene groups. This fact indicates that the conjugated‐circuit model is not always applicable to semibenzenoid hydrocarbons such as polyacenequinododimethides.     

Photon-echo profile in the ultrashort time region for pentacene molecules in crystals

Photon-echo behavior in the ultrashort time region is studied for pentacene molecules in p-terphenyl crystals at 1.7 K by means of the accumulated three-pulse echo. We show highly resolved echo spectra with a parameter of time separation and also time behavior of echo intensity as a function of pulse separation measured at various frequencies near the peak position of the absorption line of the S₀–S₁ transition. We demonstrate various features of echo profile in both time and frequency domains, which are dependent on the time region of observation.     

Parameter identification for stochastic diffusion equations with unknown boundary conditions

Stochastic diffusion equations with unknown boundary conditions are encountered in practice whenever the boundary is observed only through measurement errors. Parameter identification for such systems is studied in the present paper. The boundary condition is treated as an unknown parameter in a function space as an intermediate step in solving the identification problem.