Hyperparameter on-line learning of stochastic resonance based threshold networks

Aiming at training the feed-forward threshold neural network consisting of nondifferentiable activation functions, the approach of noise injection forms a stochastic resonance based threshold network that can be optimized by various gradient-based optimizers. The introduction of injected noise extends the noise level into the parameter space of the designed threshold network, but leads to a highly non-convex optimization landscape of the loss function. Thus, the hyperparameter on-line learning procedure with respective to network weights and noise levels becomes of challenge. It is shown that the Adam optimizer, as an adaptive variant of stochastic gradient descent, manifests its superior learning ability in training the stochastic resonance based threshold network effectively. Experimental results demonstrate the significant improvement of performance of the designed threshold network trained by the Adam optimizer for function approximation and image classification.     

Self-oscillating gels based on novel catalyst for the Belousov–Zhabotinsky reaction

We report on the synthesis of new Ru(bpy)₂(phen) catalyst for the oscillatory Belousov–Zhabotinsky chemical reaction and on the preparation of novel Ru(bpy)₂(phen)-based self-oscillating gels. The synthesized gels exhibit high-amplitude autonomous mechanical oscillations when the Belousov–Zhabotinsky reaction proceeds inside these gels     

2.3–21 GHz broadband and high linearity distributed low noise amplifier

This paper focuses on the design of a 2.3–21 GHz Distributed Low Noise Amplifier (LNA) with low noise figure (NF), high gain (S₂₁), and high linearity (IIP3) for broadband applications. This distributed amplifier (DA) includes S/C/X/Ku/K-band, which makes it very suitable for heterodyne receivers. The proposed DA uses a 0.18 μm GaAs pHEMT process (OMMIC ED02AH) in cascade architecture with lines adaptation and equalization of phase velocity techniques, to absorb their parasitic capacitances into the gate and drain transmission lines in order to achieve wide bandwidth and to enhance gain and linearity. The proposed broadband DA achieved an excellent gain in the flatness of 13.5 ± 0.2 dB, a low noise figure of 3.44 ± 1.12 dB, and a small group delay variation of ±19.721 ps over the range of 2.3–21 GHz. The input and output reflection coefficients S₁₁ and S₂₂ are less than −10 dB. The input compression point (P_1dB) and input third-order intercept point (IIP3) are −1.5 dBm and 11.5 dBm, respectively at 13 GHz. The dissipated power is 282 mW and the core layout size is 2.2 × 0.8 mm².     

A posteriori error analysis of a quadratic finite volume method for nonlinear elliptic problems

In this article, we construct and analyze a residual-based a posteriori error estimator for a quadratic finite volume method (FVM) for solving nonlinear elliptic partial differential equations with homogeneous Dirichlet boundary conditions. We shall prove that the a posteriori error estimator yields the global upper and local lower bounds for the norm error of the FVM. So that the a posteriori error estimator is equivalent to the true error in a certain sense. Numerical experiments are performed to illustrate the theoretical results.     

Full counting statistics of transport electrons through a two-level quantum dot with spin–orbit coupling

We study the full counting statistics of transport electrons through a semiconductor two-level quantum dot with Rashba spin–orbit (SO) coupling, which acts as a nonabelian gauge field and thus induces the electron transition between two levels along with the spin flip. By means of the quantum master equation approach, shot noise and skewness are obtained at finite temperature with two-body Coulomb interaction. We particularly demonstrate the crucial effect of SO coupling on the super-Poissonian fluctuation of transport electrons, in terms of which the SO coupling can be probed by the zero-frequency cumulants. While the charge currents are not sensitive to the SO coupling.     

Macroscopic and Microscopic Structures of Cesium Lead Iodide Perovskite from Atomistic Simulations

A first‐principles‐based effective Hamiltonian is developed and employed to investigate finite‐temperature structural properties of a prototype of perovskite halides, that is CsPbI₃. Such simulations, when using first‐principles‐extracted coefficients, successfully reproduce the existence of an orthorhombic Pnma state and its iodine octahedral tilting angles around room temperature. However, they also yield a direct transformation from Pnma to cubic $Pm\overline{3}m$ upon heating, unlike measurements that reported the occurrence of an intermediate long‐range‐tilted tetragonal P4/mbm phase in‐between the orthorhombic and cubic phases. Such disagreement, which may cast some doubts about the extent to which first‐principle methods can be trusted to mimic hybrid perovskites, can be resolved by “only” changing one short‐range tilting parameter in the whole set of effective Hamiltonian coefficients. In such a case, some reasonable values of this specific parameter result in the predictions that i) the intermediate P4/mbm state originates from fluctuations over many different tilted states; and ii) the cubic $Pm\overline{3}m$ phase is highly locally distorted and develops strong transverse antiphase correlation between first‐nearest neighbor iodine octahedral tiltings, before undergoing a phase transition to P4/mbm under cooling.     

3D‐morphology reconstruction of nanoscale phase‐separation in polymer memory blends

In many organic electronic devices functionality is achieved by blending two or more materials, typically polymers or molecules, with distinctly different optical or electrical properties in a single film. The local scale morphology of such blends is vital for the device performance. Here, a simple approach to study the full 3D morphology of phase‐separated blends, taking advantage of the possibility to selectively dissolve the different components is introduced. This method is applied in combination with AFM to investigate a blend of a semiconducting and ferroelectric polymer typically used as active layer in organic ferroelectric resistive switches. It is found that the blend consists of a ferroelectric matrix with three types of embedded semiconductor domains and a thin wetting layer at the bottom electrode. Statistical analysis of the obtained images excludes the presence of a fourth type of domains. The criteria for the applicability of the presented technique are discussed. © 2015 Wiley Periodicals, Inc. J. Polym. Sci., Part B: Polym. Phys. 2015 , 53, 1231–1237     

Morphology and microphase separation of star copolymers

Star copolymers have attracted significant interest due to their different characteristics compared with diblock copolymers, including higher critical micelle concentration, lower viscosity, unique spatial shape, or morphologies. Development of synthetic skills such as anionic polymerization and controlled radical polymerization have made it possible to make diverse architectures of polymers. Depending on the molecular architecture of the copolymer, numerous morphologies are possible, for instance, Archimedean tiling patterns and cylindrical microdomains at symmetric volume fraction for miktoarm star copolymers as well as asymmetric lamellar microdomains for star‐shaped copolymers, which have not been reported for linear block copolymers. In this review, we focus on morphologies and microphase separations of miktoarm (A_mB_n and ABC miktoarm) star copolymers and star‐shaped [(A‐b‐B)_n] copolymers with nonlinear architecture. © 2014 Wiley Periodicals, Inc. J. Polym. Sci., Part B: Polym. Phys. 2015 , 53, 1–21