Critical Assessment of the DFT + U Approach for the Prediction of Vanadium Dioxide Properties

In a previous study (Stahl and Bredow, Chem. Phys. Lett. 2018, 695, 28–33), we have studied structural, energetic, and electronic properties of two vanadium dioxide VO₂ polymorphs with modified global and range-separated hybrid functionals. Since hybrid methods are computationally demanding, we evaluate the computationally more efficient DFT + U method in the present study. We assessed the widely used Dudarev PBE + U approach with a literature value of the effective Hubbard parameter U_eff = 3.4 eV. We compared the PBE + U results for the two VO₂ polymorphs with our previous results, a self-consistent hybrid functional sc-PBE0, and the meta-GGA functional SCAN. It was found that the PBE + U method yields a strongly distorted monoclinic phase and does not reproduce the metal-to-insulator transition of VO₂ correctly, even with modified values of U_eff. On the other hand, sc-PBE0 and SCAN describe the relative stability and the electronic structure of both polymorphs correctly and also provide reasonable lattice parameters. The functional SCAN yields the optimal balance between computational efficiency and accuracy. © 2019 The Authors. Journal of Computational Chemistry published by Wiley Periodicals, Inc.     

Homogenization of Periodically Heterogeneous Thin Beams

Consider an elastic thin three-dimensional body made of a periodic distribution of elastic inclusions. When both the thickness of the beam and the size of the heterogeneities tend simultaneously to zero the authors obtain three different one-dimensional models of beam depending upon the limit of the ratio of these two small parameters.     

Carbon nanotube dielectrophoresis: Theory and applications

Carbon nanotubes (CNTs) are one of the most extensively studied nanomaterials in the 21st century. Since their discovery in 1991, many studies have been reported advancing our knowledge in terms of their structure, properties, synthesis, and applications. CNTs exhibit unique electrothermal and conductive properties which, combined with their mechanical strength, have led to tremendous attention of CNTs as a nanoscale material in the past two decades. To introduce the various types of CNTs, we first provide basic information on their structure followed by some intriguing properties and a brief overview of synthesis methods. Although impressive advances have been demonstrated with CNTs, critical applications require purification, positioning, and separation to yield desired properties and functional elements. Here, we review a versatile technique to manipulate CNTs based on their dielectric properties, namely dielectrophoresis (DEP). A detailed discussion on the DEP aspects of CNTs including the theory and various technical microfluidic realizations is provided. Various advancements in DEP-based manipulations of single-walled and multiwalled CNTs are also discussed with special emphasis on applications involving separation, purification, sensing, and nanofabrication.     

Study on the mechanism of catalytic synthesis of dimethyldichlorosilane by AlCl3/MIL‐53(Al)@γ‐Al2O3

Dimethyldichlorosilane, one of the most consumed organosilicon monomers in the industry, can be prepared in a highly efficient and environmentally friendly synthesis method of disproportionating methylchlorosilanes. However, the internal mechanism of the reaction remains unclear. In this paper, the mechanism catalyzed by AlCl₃/MIL‐53(Al) and AlCl₃/MIL‐53(Al)@γ‐Al₂O₃ catalysts was calculated at B3LYP/6‐311++G(3df, 2pd) level by using the density functional theory (DFT). The results showed that although the two catalysts had similar active structures, the catalytic effects were significantly different. The Lewis acid center on the surface of γ‐Al₂O₃ in the core‐shell catalyst is complementary to the classic Lewis acid AlCl₃ through the spatial superposition effect, which greatly improves the Lewis acid catalytic activity of AlCl₃/MIL‐53(Al)@γ‐Al₂O₃.     

多元统计分析中一类矩阵迹函数最小化问题的有效算法

研究来源于多元统计分析中的一类矩阵迹函数最小化问题$\min c+ tr(AX)+\sum\limits_{j=1}^{m}tr(B_j X C_jX^{T}),\ \ {\rm s. t.} \ X^TX=I_p,$其中$c$为常数, $A\in R^{p\times n}\ (n\geq p)$, $B_j\in R^{n\times n}, C_j\in R^{p\times p}$为给定系数矩阵. 数值实验表明已有的Majorization算法虽可行, 但收敛速度缓慢且精度不高. 本文从黎曼流形的角度重新研究该问题, 基于Stiefel流形的几何性质, 构造一类黎曼非单调共轭梯度迭代求解算法, 并给出算法收敛性分析.数值实验和数值比较验证所提出的算法对于问题模型是高效可行的.     

Order-Stability in Complex Biological,Social, and AI-Systems from Quantum Information Theory

This paper is our attempt, on the basis of physical theory, to bring more clarification on the question “What is life?” formulated in the well-known book of Schrödinger in 1944. According to Schrödinger, the main distinguishing feature of a biosystem’s functioning is the ability to preserve its order structure or, in mathematical terms, to prevent increasing of entropy. However, Schrödinger’s analysis shows that the classical theory is not able to adequately describe the order-stability in a biosystem. Schrödinger also appealed to the ambiguous notion of negative entropy. We apply quantum theory. As is well-known, behaviour of the quantum von Neumann entropy crucially differs from behaviour of classical entropy. We consider a complex biosystem S composed of many subsystems, say proteins, cells, or neural networks in the brain, that is, S=(Si). We study the following problem: whether the compound system S can maintain “global order” in the situation of an increase of local disorder and if S can preserve the low entropy while other Si increase their entropies (may be essentially). We show that the entropy of a system as a whole can be constant, while the entropies of its parts rising. For classical systems, this is impossible, because the entropy of S cannot be less than the entropy of its subsystem Si. And if a subsystems’s entropy increases, then a system’s entropy should also increase, by at least the same amount. However, within the quantum information theory, the answer is positive. The significant role is played by the entanglement of a subsystems’ states. In the absence of entanglement, the increasing of local disorder implies an increasing disorder in the compound system S (as in the classical regime). In this note, we proceed within a quantum-like approach to mathematical modeling of information processing by biosystems—respecting the quantum laws need not be based on genuine quantum physical processes in biosystems. Recently, such modeling found numerous applications in molecular biology, genetics, evolution theory, cognition, psychology and decision making. The quantum-like model of order stability can be applied not only in biology, but also in social science and artificial intelligence.     

基于Ni-SnO2纳米颗粒的GS-PUF设计

气敏传感器具有气体识别、探测和监测等功能, 广泛应用于工业生产等领域, 但在泄漏预警时缺乏迅速识别和定位等功能. 本文基于传感器制备工艺偏差分析, 通过对传感器气敏机制的研究, 提出一种基于Ni-SnO2纳米颗粒的气敏传感器物理不可克隆函数(Gas Sensor-Physical Unclonable Function, GS-PUF)设计方案. 该方案利用掺杂Ni元素的方法, 结合静电喷雾沉积技术制备Ni-SnO2气敏传感器, 以获取更加稳定可靠的物理特征值, 然后采集气敏传感器对不同浓度下气体的响应数据, 最后利用随机阻值多位平衡算法比较不同组气敏传感器响应电信号值, 实现PUF数据输出. 制备每组样本可产生128位二进制数据的多组PUF样本, 进行对比实验. 结果表明, 所设计的GS-PUF具有气体泄漏源头识别定位的功能, 且随机性提升至99%, 唯一性达49.80%.