High-pressure study of the basal-plane anisotropy of the upper critical field of the topological superconductor SrxBi2Se3

We report a high-pressure transport study of the upper-critical field, $B_{c2}(T)$, of the topological superconductor Sr$_{0.15}$Bi$_2$Se$_3$ ($T_c = 3.0$ K). $B_{c2}(T)$ was measured for magnetic fields directed along two orthogonal directions, $a$ and $a^*$, in the trigonal basal plane. While superconductivity is rapidly suppressed at the critical pressure $p_c \sim 3.5$ GPa, the pronounced two-fold basal-plane anisotropy $B_{c2}^a/B_{c2}^{a^*} = 3.2$ at $T=0.3$ K, recently reported at ambient pressure (Pan et al., 2016), is reinforced and attains a value of $\sim 5$ at the highest pressure (2.2 GPa). The data reveal that the unconventional superconducting state with broken rotational symmetry is robust under pressure

Robust H∞ feedback control for uncertain stochastic delayed genetic regulatory networks with additive and multiplicative noise

The official published version can found at the link below.Noises are ubiquitous in genetic regulatory networks (GRNs). Gene regulation is inherently a stochastic process because of intrinsic and extrinsic noises that cause kinetic parameter variations and basal rate disturbance. Time delays are usually inevitable due to different biochemical reactions in such GRNs. In this paper, a delayed stochastic model with additive and multiplicative noises is utilized to describe stochastic GRNs. A feedback gene controller design scheme is proposed to guarantee that the GRN is mean-square asymptotically stable with noise attenuation, where the structure of the controllers can be specified according to engineering requirements. By applying control theory and mathematical tools, the analytical solution to the control design problem is given, which helps to provide some insight into synthetic biology and systems biology. The control scheme is employed in a three-gene network to illustrate the applicability and usefulness of the design.This work was funded by Royal Society of the U.K.; Foundation for the Author of National Excellent Doctoral Dissertation of China. Grant Number: 2007E4; Heilongjiang Outstanding Youth Science Fund of China. Grant Number: JC200809; Fok Ying Tung Education Foundation. Grant Number: 111064; International Science and Technology Cooperation Project of China. Grant Number: 2009DFA32050; University of Science and Technology of China Graduate Innovative Foundation

Independence Test for High Dimensional Random Vectors

This paper proposes a new mutual independence test for a large number of high dimensional random vectors. The test statistic is based on the characteristic function of the empirical spectral distribution of the sample covariance matrix. The asymptotic distributions of the test statistic under the null and local alternative hypotheses are established as dimensionality and the sample size of the data are comparable. We apply this test to examine multiple MA(1) and AR(1) models, panel data models with some spatial cross-sectional structures. In addition, in a flexible applied fashion, the proposed test can capture some dependent but uncorrelated structures, for example, nonlinear MA(1) models, multiple ARCH(1) models and vandermonde matrices. Simulation results are provided for detecting these dependent structures. An empirical study of dependence between closed stock prices of several companies from New York Stock Exchange (NYSE) demonstrates that the feature of cross-sectional dependence is popular in stock marketsIndependence test, cross-sectional dependence, empirical spectral distribution, characteristic function, Marcenko-Pastur Law

Highly Stable Luminous "snakes" from CsPbX3 Perovskite Nanocrystals Anchored on Amine-Coated Silica Nanowires

CsPbX3 (X = Cl, Br, and I) perovskite nanocrystals (NCs) are known for their exceptional optoelectronic properties, yet the material's instability toward polar solvents, heat, or UV irradiation greatly limits its further applications. Herein, an efficient in situ growing strategy has been developed to give highly stable perovskite NC composites (abbreviated CsPbX3@CA-SiO2) by anchoring CsPbX3 NCs onto silica nanowires (NWs), which effectively depresses the optical degradation of their photoluminescence (PL) and enhances stability. The preparation of surface-functionalized serpentine silica NWs is realized by a sol-gel process involving hydrolysis of a mixture of tetraethyl orthosilicate (TEOS), 3-aminopropyltriethoxysilane (APTES), and trimethoxy(octadecyl)silane (TMODS) in a water/oil emulsion. The serpentine NWs are formed via an anisotropic growth with lengths up to 8 μm. The free amino groups are employed as surface ligands for growing perovskite NCs, yielding distributed monodisperse NCs (∼8 nm) around the NW matrix. The emission wavelength is tunable by simple variation of the halide compositions (CsPbX3, X = Cl, Br, or I), and the composites demonstrate a high photoluminescence quantum yield (PLQY 32-69%). Additionally, we have demonstrated the composites CsPbX3@CA-SiO2 can be self-woven to form a porous 3D hierarchical NWs membrane, giving rise to a superhydrophobic surface with hierarchical micro/nano structural features. The resulting composites exhibit high stability toward water, heat, and UV irradiation. This work elucidates an effective strategy to incorporate perovskite nanocrystals onto functional matrices as multifunctional stable light sources

Nanoladder cantilevers made from diamond and silicon

We present a "nanoladder" geometry that minimizes the mechanical dissipation of ultrasensitive cantilevers. A nanoladder cantilever consists of a lithographically patterned scaffold of rails and rungs with feature size $\sim$ 100 nm. Compared to a rectangular beam of the same dimensions, the mass and spring constant of a nanoladder are each reduced by roughly two orders of magnitude. We demonstrate a low force noise of $158 (+62)(-42)\,$zN and $190 (+42)(-33)\,$zN in a one-Hz bandwidth for devices made from silicon and diamond, respectively, measured at temperatures between 100--150 mK. As opposed to bottom-up mechanical resonators like nanowires or nanotubes, nanoladder cantilevers can be batch-fabricated using standard lithography, which is a critical factor for applications in scanning force microscopy

Microphase transitions of block copolymer/homopolymer under shear flow

Cell dynamics simulation is used to investigate the phase behavior of block copolymer/homopolymer mixture subjected to a steady shear flow. Phase transitions occur from transverse to parallel and then to perpendicular lamellar structure with an increase of shear rate and this is the result of interaction between the shear flow and the concentration fluctuation. Rheological properties, such as normal stress differences and shear viscosity, are all closely related with the direction of the lamellae. Furthermore, we specifically explore the phase behavior and the order parameter under weak and strong shear of two different initial states, and realize the importance of the thermal history. It is necessary to apply the shear field at the appropriate time if we want to get what we want. These results provide an easy method to create ordered, defect-free materials in experiment and engineering technology through imposing shear flow.Comment: 14 pages, 9 figure

Pseudospectral Model Predictive Control under Partially Learned Dynamics

Trajectory optimization of a controlled dynamical system is an essential part of autonomy, however many trajectory optimization techniques are limited by the fidelity of the underlying parametric model. In the field of robotics, a lack of model knowledge can be overcome with machine learning techniques, utilizing measurements to build a dynamical model from the data. This paper aims to take the middle ground between these two approaches by introducing a semi-parametric representation of the underlying system dynamics. Our goal is to leverage the considerable information contained in a traditional physics based model and combine it with a data-driven, non-parametric regression technique known as a Gaussian Process. Integrating this semi-parametric model with model predictive pseudospectral control, we demonstrate this technique on both a cart pole and quadrotor simulation with unmodeled damping and parametric error. In order to manage parametric uncertainty, we introduce an algorithm that utilizes Sparse Spectrum Gaussian Processes (SSGP) for online learning after each rollout. We implement this online learning technique on a cart pole and quadrator, then demonstrate the use of online learning and obstacle avoidance for the dubin vehicle dynamics.Comment: Accepted but withdrawn from AIAA Scitech 201