Ergodicity breaking of an inorganic glass in aging near Tg{T_g} probed by elasticity relaxation

We performed a series of aging experiments of an inorganic glass (As${_2}$Se${_3}$) at a temperature ${T_2}$ near the glass transition point ${T_g}$ by first relaxing it at ${T_1}$. The relaxation of Young's modulus was monitored, which was(almost if not ideally) exponential with a ${T_1}$-dependent relaxation time ${\tau(T_1)}$. We demostrate the Kovacs' paradox for the first time in an inorganic glasses. Associated with the divergence of ${\tau}$, the quasi-equilibrated Young's modulus ${E_\infty}$ does not converge either. An elastic model of relaxation time and a Mori-Tanaka analysis of ${E_\infty}$ lead to a similar estimate of the persistent memory of the history, ergodicity breaking within the accessible experimental time. Experiments with different ${T_2}$ exhibits a critical temperature ${T_p \sim T_g}$, i.e., when ${T_2 > T_p}$, both ${\tau}$ and ${E_\infty}$ converge.Comment: 7 pages, 5 figure

Semi-sparsity Priors for Image Structure Analysis and Extraction

Image structure-texture decomposition is a long-standing and fundamental problem in both image processing and computer vision fields. In this paper, we propose a generalized semi-sparse regularization framework for image structural analysis and extraction, which allows us to decouple the underlying image structures from complicated textural backgrounds. Combining with different textural analysis models, such a regularization receives favorable properties differing from many traditional methods. We demonstrate that it is not only capable of preserving image structures without introducing notorious staircase artifacts in polynomial-smoothing surfaces but is also applicable for decomposing image textures with strong oscillatory patterns. Moreover, we also introduce an efficient numerical solution based on an alternating direction method of multipliers (ADMM) algorithm, which gives rise to a simple and maneuverable way for image structure-texture decomposition. The versatility of the proposed method is finally verified by a series of experimental results with the capability of producing comparable or superior image decomposition results against cutting-edge methods.Comment: 18 page

Semi-Sparsity for Smoothing Filters

In this paper, we propose an interesting semi-sparsity smoothing algorithm based on a novel sparsity-inducing optimization framework. This method is derived from the multiple observations, that is, semi-sparsity prior knowledge is more universally applicable, especially in areas where sparsity is not fully admitted, such as polynomial-smoothing surfaces. We illustrate that this semi-sparsity can be identified into a generalized $L_0$-norm minimization in higher-order gradient domains, thereby giving rise to a new "feature-aware" filtering method with a powerful simultaneous-fitting ability in both sparse features (singularities and sharpening edges) and non-sparse regions (polynomial-smoothing surfaces). Notice that a direct solver is always unavailable due to the non-convexity and combinatorial nature of $L_0$-norm minimization. Instead, we solve the model based on an efficient half-quadratic splitting minimization with fast Fourier transforms (FFTs) for acceleration. We finally demonstrate its versatility and many benefits to a series of signal/image processing and computer vision applications

Intrinsic Image Transfer for Illumination Manipulation

This paper presents a novel intrinsic image transfer (IIT) algorithm for illumination manipulation, which creates a local image translation between two illumination surfaces. This model is built on an optimization-based framework consisting of three photo-realistic losses defined on the sub-layers factorized by an intrinsic image decomposition. We illustrate that all losses can be reduced without the necessity of taking an intrinsic image decomposition under the well-known spatial-varying illumination illumination-invariant reflectance prior knowledge. Moreover, with a series of relaxations, all of them can be directly defined on images, giving a closed-form solution for image illumination manipulation. This new paradigm differs from the prevailing Retinex-based algorithms, as it provides an implicit way to deal with the per-pixel image illumination. We finally demonstrate its versatility and benefits to the illumination-related tasks such as illumination compensation, image enhancement, and high dynamic range (HDR) image compression, and show the high-quality results on natural image datasets

MXene-based Membranes for Drinking Water Production

The soaring development of industry exacerbates the shortage of fresh water, making drinking water production an urgent demand. Membrane techniques feature the merits of high efficiency, low energy consumption, and easy operation, deemed as the most potential technology to purify water. Recently, a new type of two-dimensional materials, MXenes as the transition metal carbides or nitrides in the shape of nanosheets, have attracted enormous interest in water purification due to their extraordinary properties such as adjustable hydrophilicity, easy processibility, antifouling resistance, mechanical strength, and light-to-heat transformation capability. In pioneering studies, MXene-based membranes have been evaluated in the past decade for drinking water production including the separation of bacteria, dyes, salts, and heavy metals. This review focuses on the recent advancement of MXene-based membranes for drinking water production. A brief introduction of MXenes is given first, followed by descriptions of their unique properties. Then, the preparation methods of MXene membranes are summarized. The various applications of MXene membranes in water treatment and the corresponding separation mechanisms are discussed in detail. Finally, the challenges and prospects of MXene membranes are presented with the hope to provide insightful guidance on the future design and fabrication of high-performance MXene membranes

Enhanced stability of Zr-doped Ba(CeTb)O3−δ-Ni cermet membrane for hydrogen separation

A mixed protonic and electronic conductor material BaCe0.85Tb0.05Zr0.1O3−δ (BCTZ) is prepared and a Ni-BCTZ cermet membrane is synthesized for hydrogen separation. Stable hydrogen permeation fluxes can be obtained for over 100 h through the Ni-BCTZ membrane in both dry and humid conditions, which exhibits an excellent stability compared with Ni-BaCe0.95Tb0.05O3−δ membrane due to the Zr doping.Sino-German center for Science Promotion/GZ 911National Science Foundation of China/21225625National Science Foundation of China/2117608

A CO2-stable reduction-tolerant Nd-containing dual phase membrane for oxyfuel CO2 capture

We report a novel CO2-stable reduction-tolerant dual-phase oxygen transport membrane 40 wt% Nd0.6Sr0.4FeO3-delta-60 wt% Ce0.9Nd0.1O2-delta (40NSFO-60CNO), which was successfully developed by a facile one-pot EDTA-citric sol-gel method. The microstructure of the crystalline 40NSFO-60CNO phase was investigated by combined in situ X-ray diffraction (XRD), scanning electron microscopy (SEM), back scattered SEM (BSEM), and energy dispersive X-ray spectroscopy (EDXS) analyses. Oxygen permeation and long-time stability under CO2 and CH4 atmospheres were investigated. A stable oxygen flux of 0.21 cm(3) min(-1) cm(-2) at 950 degrees C with undiluted CO2 as sweep gas is found which is increased to 0.48 cm(3) min(-1) cm(-2) if the air side is coated with a porous La0.6Sr0.4CoO3-delta (LSC) layer. All the experimental results demonstrate that the 40NSFO-60CNO not only shows good reversibility of the oxygen permeation fluxes upon temperature cycling, but also good phase stability in a CO2 atmosphere and under the harsh conditions of partial oxidation of methane to synthesis gas up to 950 degrees C.Sino-German Centre for Science Promotion/GZ 676, GZ911National Science Fund for Distinguished Young Scholars of China/2122562

Feature extraction for license plate location based on L0-norm smoothing

We propose a simple feature extraction algorithm for license plate location, which can reduce the occurrence of pseudo-licenses significantly. Our scheme arises from a novel L-0 -norm image smoothing, in which the multiple local textures in the complex backgrounds can be suppressed remarkably without changing the structures and edges of the license objects. Due to this "edgeaware" property, we then combine a feature filtering with an efficient binarized image, a simple multi-scale image analysis algorithm, to remove the potential false license plates. Finally, we extract license plates with a projection method. Experimental results show the proposed method provides a flexible and powerful way to the license plate location in complex backgrounds