Aharonov–Bohm effect for bound states on spin-0 massive charged particles in a Gödel-type space–time with Coulomb potential

In this paper, we investigate the relativistic quantum dynamics of spin-0 massive charged particles in a Gödel-type space–time with electromagnetic interactions. We derive the radial wave equation of the Klein–Gordon equation with an internal magnetic flux field and Coulomb-type potential in the Som–Raychaudhuri space–time with cosmic string. We solve this equation and analyze the analog effect in relation to the Aharonov–Bohm effect for bound states.     

Implementation of a separate fluid-neutral energy equation in SOLPS-ITER and its impact on the validity range of advanced fluid-neutral models

In plasma edge transport codes for nuclear fusion devices, fluid-neutral models offer an interesting alternative to the currently used kinetic Monte Carlo simulations, especially for cases of high ion-neutral collisionality. In this paper, we elaborate a separate neutral energy equation in the state-of-the-art SOLPS-ITER code suite, which previously assumed perfect ion-neutral temperature equilibration. Furthermore, we study the coupled plasma-neutral solutions for a range of divertor operating regimes, proving the validity of these fluid-neutral models for high-recycling and detached regimes.     

Gas-Sensing Activity of Amorphous Copper Oxide Porous Nanosheets

In this paper, the gas-sensing properties of copper oxide porous nanosheets in amorphous and highly crystalline states were comparatively investigated on the premise of almost the same specific surface area, morphology and size. Unexpectedly, the results show that amorphous copper oxide porous nanosheets have much better gas sensing properties than highly crystalline copper oxide to a serious of volatile organic compounds, and the lowest detection limit (LOD) of the amorphous copper oxide porous nanosheets to methanal is even up to 10 ppb. By contrast, the LOD of the highly crystalline copper oxide porous nanosheets to methanal is 95 ppb. Experiments prove that the oxygen vacancies contained in the amorphous copper oxide porous nanosheets play a key role in improving gas sensitivity, which greatly improve the chemical activity of the materials, especially for the adsorption of molecules containing oxygen-groups such as methanal and oxygen.     

超强频率梳激光场驱动下多光子共振谐波辐射的相位突变研究

本文从理论上研究了在双色频率梳激光场驱动下多光子谐波辐射光谱中的相位突变现象。我们利用Floquet理论非微扰地模拟了频率梳激光场与原子分子等量子系统的相互作用过程。谐波辐射信号是多光子偶极跃迁相干叠加的结果,通过调节频率梳激光场间的相对相位,可以相干地控制谐波辐射信号的强度。通过对谐波信号进行傅里叶变换,可以提取不同跃迁路径的相对相位信息。我们通过改变频率梳组激光场的强度和频率组分实现多光子跃迁频率,让其跨越共振跃迁频率时,谐波相位会发生突变。从而可以观测超强激光场驱动下量子系统共振跃迁频率的斯塔克能移。     

基于改进云推理算法的塔架结构损伤识别

为了解决塔架结构的损伤识别问题,提出了基于应变能和改进云推理算法的损伤识别方法。首先描述了云模型的基本理论和数字特征,并给出了模态应变能的基本公式;然后分析了X条件云发生器和Y条件云发生器的基本算法和运行步骤,借助灰云模型建立相应的前件云和后件云规则,考虑了测量噪声的影响,利用云发生器生成多组云滴,并利用多模式下云滴的确定度和生成值构建了基本云推理算法及其损伤识别指标。基本云推理算法中常会产生不均匀发散的云滴,从而使计算结果产生一定的偏差,为了降低云滴发散产生的偏差影响,提出了基于损伤模式数量加权的云推理改进策略。计算结果表明:云推理算法可以较好地应用于塔架结构的损伤识别,其识别结果明显优于传统的应变能耗散率指标方法;而改进云推理算法进一步提高了识别的精度,优于基本云推理算法。     

Calculus of variations as a basic tool for modelling of reaction paths and localisation of stationary points on potential energy surfaces

ABSTRACT

The theory of calculus of variations is a mathematical tool which is widely used in different scientific areas in particular in physics and chemistry. This theory is strongly related with optimisation. In fact the former seeks to optimise an integral related with some physical magnitude over some space to an extremum by varying a function of the coordinates. On the other hand, reaction paths and potential energy surfaces, in particular their stationary points, are the basis of many chemical theories, in particular reactions rate theories. We present a review where it is gathered together the variational nature of many types of reaction paths: steepest descent, Newton trajectories, artificial force induced reaction (AFIR) paths, gradient extremals, and gentlest ascent dynamics (GAD) curves. The variational basis permits to select the best optimisation technique in order to locate important theoretical objects on a potential energy surface.     

Multi-variable special polynomials using an operator ordering method

Using an operator ordering method for some commutative superposition operators, we introduce two new multi-variable special polynomials and their generating functions, and present some new operator identities and integral formulas involving the two special polynomials. Instead of calculating complicated partial differential, we use the special polynomials and their generating functions to concisely address the normalization, photocount distributions and Wigner distributions of several quantum states that can be realized physically, the results of which provide real convenience for further investigating the properties and applications of these states.     

基于无人机多光谱图像的土壤水分检测方法研究

以表层土壤为对象,探究土壤的多光谱反射率与土壤水分含量相关性,进行基于无人机多光谱图像的土壤水分含量预测模型方法的探究。选取中国农业大学通州实验站为研究区域,实地采集试验田的土壤样本100组,按照一定梯度配制土壤含水量,配成的土壤含水率为10%~50%之间,土壤含量的真实值采用土壤烘干法进行测定。多光谱相机灵巧便捷,可搭载在无人机上对土壤进行监测。将RedEdged-M型多光谱相机搭载在Phantom 3型无人机上,选择阳光充足的采集环境,实时采集土壤样本的多光谱图像,建立土壤多光谱信息与水分含量之间的模型。利用处理光谱数据的ENVI5.3软件提取土壤样本多光谱信息,以多光谱相机自带的标准白板反射率为100%,计算出土壤样本在蓝、绿、红、红边、近红外五个波段的光谱反射率。采用BP神经网络算法、支持向量机算法、偏最小二乘算法分别建立基于无人机多光谱图像的土壤水分含量的预测模型。以80组土壤样本数据作为训练集,建立基于多光谱图像的土壤水分含量预测模型。采用莱文贝格-马夸特算法对BPNN进行改进,提高了其训练速度,当网络结构为5-10-1时,训练效果最好,本文选择该网络结构;SVM采取高斯核函数,当参数为0.56时,模型效果最好。本研究采用归一化均方根误差(NRMSE)和决策系数(R 2)对三种土壤水分含量的预测模型进行定量对比。以20组土壤样本数据作为测试集,结果可知,基于BP神经网络土壤水分含量预测模型的NRMSE为0.268,R 2为0.872;基于支持向量机的土壤水分含量预测模型的NRMSE为0.298,R 2为0.821;基于偏最小二乘土壤水分含量预测模型的NRMSE为0.316,R 2为0.789。对三种模型分析可知,基于BPNN的土壤水分含量预测模型效果均较好。结果可知,土壤的光谱反射率与含水率间存在较密切的相关性,将多光谱相机搭载在无人机上可以对土壤水分含量进行有效的实时监测,对监测土壤墒情提供技术支持和理论支撑。     

Advances in stable and flexible perovskite solar cells

Roll-to-roll (R2R) production is an innovative approach and is fast becoming a very popular industrial method for high throughput and mass production of solar cells. Replacement of costly indium tin oxide (ITO), which conventionally has served as the transparent electrode would be a great approach for roll to roll production of flexible cost effective solar cells. Indium tin oxide (ITO) and fluorine-doped tin oxide (FTO) are brittle and ultimately limit the device flexibility. Perovskite solar cells (PSCs) have been the centre of photovoltaic research community during the recent years owing to its exceptional performance and economical prices. The best reported PSCs fabricated by employing mesoporous TiO₂ layers require elevated temperatures in the range of 400–500 °C which limits its applications to solely glass substrates. In such a scenario developing flexible PSCs technology can be considered a suitable and exciting arena from the application point of view, them being flexible, lightweight, portable, and easy to integrate over both small, large and curved surfaces.