低维螺旋磁体纳米条带中磁场驱动的磁结构演变规律

利用蒙特卡洛方法研究了低维螺旋磁体纳米条带中磁场驱动的磁结构演变规律，以及偶极相互作用对螺旋磁体纳米条带中磁结构的影响。研究表明，螺旋磁体纳米条带中的自旋结构由自旋的面内取向平行或垂直于边界的边缘态和中间聚集态两部分构成。在一定范围内增加外磁场，条带边缘平行于边界的自旋排列将增多，最终将在条带外围形成大的磁涡旋环，该涡旋环十分稳定，即使在很强的外磁场下仍然存在。处于条带中间的聚集态随着外磁场的增大，从磁螺旋态逐步过渡到Skyrmions态，最终形成铁磁态。Skyrmions的排列状况与条带尺寸密切相关。此外，偶极相互作用对磁矩平行于边界且首尾顺次连接的排列起积极作用，在无外磁场作用下，随着偶极相互作用的增大，体系终将形成涡旋态。     

近红外光谱LASSO特征选择方法及其聚类分析应用研究

近红外光谱技术是一种通过分析样本的特征光谱数据，实现定性或定量分析的无损检测方法，特征数据的完整性和代表性决定了所建模型的性能，而现有分析方法只能实现光谱子区间特征筛选，导致分析模型稳定性差、且难以再优化。为实现近红外光谱区间高维数特征提取，有效提高近红外光谱定性分析模型的精度和稳定性，提出一种基于最小绝对收缩和选择算法(LASSO)的光谱特征筛选方法，并以我国特色高值外贸产品云南松茸为分析对象进行聚类应用研究，讨论了该方法对于高维光谱特征筛选的有效性、分析对比了LASSO筛选特征变量及主元分析(PCA)降维算法所建松茸真伪甄别及食用菌分类模型的预测精度及稳定性。通过调研发现，云南产鲜松茸因其独特外形易于分辨，而片状的干松茸失去其独有的外形特征，导致国内干松茸掺假事件屡禁不止。选取云南产松茸、杏鲍菇、老人头、姬松茸四种干样共166样本数据进行分析，采用光谱范围为900～1 700 nm的NIRQuest512型近红外光谱仪获得166×512维原始光谱数据，剔除异常数据后采用标准正态变换对光谱数据进行预处理。在此基础上，利用LASSO筛选出全光谱区间的特征变量，再使用Kennard-Stone法并结合典型线性(KNN)和非线性建模(BP)算法，构建松茸真伪甄别模型和食用菌分类模型，对两种模型进行盲样测试，并分析了LASSO与PCA算法的不同点，最后使用蒙特卡罗方法检测两种模型的稳定性。实验结果表明基于LASSO光谱特征选择的松茸真伪甄别模型和食用菌分类模型预测精度和稳定性均高于PCA方法，其中基于原始光谱数据所建真伪甄别模型的预测准确率为69.57% (BP)和60.87% (KNN)，食用菌分类模型准确率为67.39% (BP)和65.22% (KNN)，基于LASSO特征筛选的真伪甄别模型预测准确率分别达到100% (BP)和78.26% (KNN)，食用菌分类模型预测准确率分别达到89.13% (BP)和80.43% (KNN)，对两种模型进行10次蒙特卡罗实验，其结果平均值分别为99.93%和97.22%，由此可知，与PCA等数据降维算法相比，LASSO可实现全光谱区间的光谱特征选择和数据降维，有效地提高了近红外定性分析模型的预测性能，为近红外分析提供了一种新的特征筛选方法。     

80.5 MeV/u碳离子诱发铜靶的放射性剩余产物测量

高能重带电粒子能直接穿透靶原子核外电子层,与原子核发生直接碰撞,发生散裂反应,产生一系列具有放射性的剩余产物核.重带电粒子诱发靶材放射性剩余核与辐射防护和人员安全有着密切联系,当前,大部分剩余核产额主要依靠蒙特卡罗粒子输运程序进行模拟计算,其准确程度亟需通过实验测量进行准确评估.本文利用能量为80.5 MeV/u的(12)^C⁶⁺粒子对薄铜靶开展了辐照实验与伽玛射线测量,结合伽玛谱学分析方法,得出了辐照产生的18种放射性剩余产物的初始活度和产生截面值,并与PHITS模拟结果进行对比.结果表明,PHITS模拟程序对放射性剩余核种类的估计具有较高可靠性,在其绝对产额方面,与实验测量仍具有较大偏差.     

Controlling ionic current through a nanopore by tuning pH: a local equilibrium Monte Carlo study

ABSTRACT

The purpose of this work is to create a model of a nanofluidic transistor which is able to mimic the effects of pH on nanopore conductance. The pH of the electrolyte is an experimentally controllable parameter through which the charge pattern can be tuned: pH affects the ratio of the protonated/deprotonated forms of the functional groups anchored to the surface of the nanopore (for example, amino and carboxyl groups). Thus, the behaviour of the bipolar transistor changes as it becomes ion selective in acidic/basic environments. We relate the surface charge to pH and perform particle simulations (Local Equilibrium Monte Carlo) with different nanopore geometries (cylindrical and double conical). The simulations form a self consistent system with the Nernst–Planck equation with which we compute ionic flux. We discuss the mechanism behind pH-control of ionic current: formation of depletion zones.     

Ab initio and Monte Carlo studies of phase transitions and magnetic properties of YCrO3: Heisenberg model

By using the density functional theory (DFT) and Monte Carlo simulations (MCS) with the Heisenberg model, we have studied magnetic properties of the bulk perovskite YCrO₃. The exchange couplings of the Heisenberg model and the magnetic anisotropy are investigated. The 110 direction in the crystalline structure of the compound has shown the minimum energy, it is the easy magnetic direction. Using Monte Carlo simulations, the magnetizations behavior, the effects of system parameters and the critical exponents of the compound YCrO₃ are implemented. It is shown that the bulk perovskite YCrO₃ belongs to the 3D Heisenberg universality class.     

A Theoretical study on the charge and discharge states of Na-ion battery cathode material,Na1+xFePO4F

Na₂FePO₄F is a promising cathode material for a Na-ion battery because of its high electronic capacity and good cycle performance. In this work, first principle calculations combined with cluster expansion and the Monte Carlo method have been applied to analyze the charge and discharge processes of Na₂FePO₄F by examining the voltage curve and the phase diagram. As a result of the density functional theory calculation and experimental verification with structural analysis, we found that the most stable structure of Na_1.5FePO₄F has the P2₁/b11 space group, which has not been reported to date. The estimated voltage curve has two clear plateaus caused by the two-phase structure composed of P2₁/b11 Na_1.5FePO₄F and Pbcn Na₂FePO₄F or Na₁FePO₄F and separated along the c-axis direction. The phase diagram shows the stability of the phase-separated structure. Considering that Na₂FePO₄F has diffusion paths in the a- and c-axis directions, Na₂FePO₄F has both innerphase and interphase diffusion paths. We suggest that the stable two-phase structure and the diffusion paths to both the innerphase and interphases are a key for the very clear plateau. We challenge to simulate a nonequilibrium state at high rate discharge with high temperature by introducing a coordinate-dependent chemical potential. The simulation shows agreement with the experimental discharge curve on the disappearance of the two plateaus. © 2018 Wiley Periodicals, Inc.     

The effective geometry Monte Carlo algorithm: Applications to molecular communication

In this work, we address the systematic biases and random errors stemming from finite step sizes encountered in diffusion simulations. We introduce the Effective Geometry Monte Carlo (EG-MC) simulation algorithm which modifies the geometry of the receiver. We motivate our approach in a 1D toy model and then apply our findings to a spherical absorbing receiver in a 3D unbounded environment. We show that with minimal computational cost the impulse response of this receiver can be precisely simulated using EG-MC. Afterwards, we demonstrate the accuracy of our simulations and give tight constraints on the single free parameter in EG-MC. Finally, we comment on the range of applicability of our results. While we present the EG-MC algorithm for the specific case of molecular diffusion, we believe that analogous methods with effective geometry manipulations can be utilized to approach a variety of problems in other branches of physics such as condensed matter physics and cosmological large scale structure simulations.     

A new Monte Carlo model for predicting the mechanical properties of fiber yarns

Understanding the complicated failure mechanisms of hierarchical composites such as fiber yarns is essential for advanced materials design. In this study, we developed a new Monte Carlo model for predicting the mechanical properties of fiber yarns that includes statistical variation in fiber strength. Furthermore, a statistical shear load transfer law based on the shear lag analysis was derived and implemented to simulate the interactions between adjacent fibers and provide a more accurate tensile stress distribution along the overlap distance. Simulations on two types of yarns, made from different raw materials and based on distinct processing approaches, predict yarn strength values that compare favorably with experimental measurements. Furthermore, the model identified very distinct dominant failure mechanisms for the two materials, providing important insights into design features that can improve yarn strength.     

Highly Selective Zeolite Topologies for Flue Gas Separation

The separation of carbon dioxide from flue gas is essential for the reduction of greenhouse gas emissions. In adsorptive methods, the challenge lies in the choice of suitable porous materials. Among all zeolite topologies, a number of adsorbents with pore dimensions in the range of the guest molecules were identified to allow an excellent separation by diffusion, and MRE and AFO zeolite topologies appear to be the best candidates based on equilibrium adsorption. Also, it was found that the behavior of this gas mixture in DFT and APD zeolites differed from the normal behavior.     

Molecular structure and properties of click hydrogels with controlled dangling end defect

In this study, controlled amount of dangling ends is introduced to the two series of poly(ethylene glycol)‐based hydrogel networks with three and four crosslinking functionality by using click chemistry. The structure of the gels with regulated defect percentage is confirmed by comparing the results of low‐field NMR characterization and Monte Carlo simulation. The mechanical properties of these gels were characterized by tensile stress–strain behaviors of the gels, and the results are analyzed by Gent model and Mooney–Rivlin model. The shear modulus of the swollen gels is found to be dependent on the functionality of the network, and decreases with the defect percentage. Furthermore, the value of shear modulus well obeys the Phantom model for all the gels with varied percentage of the defects. The maximum extension ratio, obtained from the fitting of Gent model, is also found to be dependent on the functionality of the network, and does not change with the defect percentage, except at very high defect percentage. The value of the maximum extension ratio is between that predicted from Phantom model and the Affine model. This indicates that at the large deformation, the fluctuation of the crosslinking points is suppressed for some extend but still exists. Polymer volume fractions at various defect percentages obtained from prediction of Flory–Rehner model are found to be in well agreement with the swelling experiment. All these results indicate that click chemistry is a powerful method to regulate the network structure and mechanical properties of the gels. © 2016 Wiley Periodicals, Inc. J. Polym. Sci., Part B: Polym. Phys. 2016 , 54, 1227–1236