Sensitivity improvement of aluminum-based far-ultraviolet nearly guided-wave surface plasmon resonance sensor

An aluminum (Al) based nearly guided-wave surface plasmon resonance (NGWSPR) sensor is investigated in the far-ultraviolet (FUV) region. By simultaneously optimizing the thickness of Al and dielectric films, the sensitivity of the optimized Al-based FUV-NGWSPR sensor increases from 183°/RIU to 309°/RIU, and its figure of merit rises from 26.47 RIU^-1 to 32.59 RIU^-1 when the refractive index of dielectric increases from 2 to 5. Compared with a traditional FUV-SPR sensor without dielectric, the optimized FUV-NGWSPR sensor can realize simultaneous improvement of sensitivity and figure of merit. In addition, the FUV-NGWSPR sensor with realistic materials (diamond, Ta₂O₅, and GaN) is also investigated, and 137.84%, 52.70%, and 41.89% sensitivity improvements are achieved respectively. This work proposes a method for performance improvement of FUV-SPR sensors by exciting nearly guided-wave, and could be helpful for the high-performance SPR sensor in the short-wavelength region.     

Molecular and colloidal self-assembly at the oil–water interface

Self-assembly is a versatile bottom-up approach for fabricating novel supramolecular materials with well-defined nano- or micro-structures associated with functionalities. The oil-water interface provides an ideal venue for molecular and colloidal self-assembly. This paper gives an overview of various self-assembled materials, including nanoparticles, polymers, proteins, and lipids, at the oil-water interface. Focus has been given to fundamental principles and strategies for engineering the self-assembly process, such as control of pH, ionic strength and use of external fields, to achieve complex soft materials with desired functionalities, such as nanoparticle surfactants, structured liquids, and proteinosomes. It has been shown that self-assembly at the oil-water interface holds great promise for developing well-structured complex materials useful for many research and industrial applications.     

Sandwich-like Catalyst–Carbon–Catalyst Trilayer Structure as a Compact 2D Host for Highly Stable Lithium–Sulfur Batteries

Herein, we propose the construction of a sandwich-structured host filled with continuous 2D catalysis–conduction interfaces. This MoN-C-MoN trilayer architecture causes the strong conformal adsorption of S/Li₂S_x and its high-efficiency conversion on the two-sided nitride polar surfaces, which are supplied with high-flux electron transfer from the buried carbon interlayer. The 3D self-assembly of these 2D sandwich structures further reinforces the interconnection of conductive and catalytic networks. The maximized exposure of adsorptive/catalytic planes endows the MoN-C@S electrode with excellent cycling stability and high rate performance even under high S loading and low host surface area. The high conductivity of this trilayer texture does not compromise the capacity retention after the S content is increased. Such a job-synergistic mode between catalytic and conductive functions guarantees the homogeneous deposition of S/Li₂S_x, and avoids thick and devitalized accumulation (electrode passivation) even after high-rate and long-term cycling.     

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。     

Second moment of error term of mean value for binary Egyptian fractions

We study the mean square of the error term of the mean value for binary Egyptian fractions.We get an asymptotic formula under the Riemann Hypothesis.     

An Analytical Model for Fluid Imbibition in Organic Nanopores

Transport in Porous Media - Estimating the fluid imbibition flow in natural system composed of nanopores is challenging due to the strong fluid/rock molecular scale interaction and the invalidation...     

Facet-dependent antibacterial activity of Au nanocrystals

Engineered nanomaterials have attracted significantly attention as one of the most promising antimicrobial agents for against multidrug resistant infections. The toxicological responses of nanomaterials are closely related to their physicochemical properties, and establishment of a structure-activity relationship for nanomaterials at the nano-bio interface is of great significance for deep understanding antibacterial toxicity mechanisms of nanomaterials and designing safer antibacterial nanomaterials. In this study, the antibacterial behaviors of well-defined crystallographic facets of a series of Au nanocrystals, including {100}-facet cubes, {110}-facet rhombic dodecahedra, {111}-facet octahedra, {221}-facet trisoctahedra and {720}-facet concave cubes, was investigated, using the model bacteria Staphylococcus aureus. We find that Au nanocrystals display substantial facet-dependent antibacterial activities. The low-index facets of cubes, octahedra, and rhombic dodecahedra show considerable antibacterial activity, whereas the high-index facets of trisoctahedra and concave cubes remained inert under biological conditions. This result is in stark contrast to the previous paradigm that the high-index facets were considered to have higher bioactivity as compared with low-index facets. The antibacterial mechanism studies have shown that the facet-dependent antibacterial behaviors of Au nanocrystals are mainly caused by differential bacterial membrane damage as well as inhibition of cellular enzymatic activity and energy metabolism. The faceted Au nanocrystals are unique in that they do not induce generation of reactive oxygen species, as validated for most antibiotics and antimicrobial nanostructures. Our findings may provide a deeper understanding of facet-dependent toxicological responses and suggest the complexities of the nanomaterial-cell interactions, shedding some light on the development of high performance Au nanomaterials-based antibacterial therapeutics.     

Implementing a Two-Photon Three-Degrees-of-Freedom Hyper-Parallel Controlled Phase Flip Gate Through Cavity-Assisted Interactions

Hyper-parallel quantum information processing is a promising and beneficial research field. Herein, a method to implement a hyper-parallel controlled-phase-flip (hyper-CPF) gate for frequency-, spatial-, and time-bin-encoded qubits by coupling flying photons to trapped nitrogen vacancy (NV) defect centers is presented. The scheme, which differs from their conventional parallel counterparts, is specifically advantageous in decreasing against the dissipate noise, increasing the quantum channel capacity, and reducing the quantum resource overhead. The gate qubits with frequency, spatial, and time-bin degrees of freedom (DOF) are immune to quantum decoherence in optical fibers, whereas the polarization photons are easily disturbed by the ambient noise.