Adsorption kinetics of Eu(III) and Am(III) onto bentonite: analysis and application of the liquid membrane tidal diffusion model

Journal of Radioanalytical and Nuclear Chemistry - A new liquid membrane tidal diffusion model (LMTD) was applied based on three assumptions to analyze the kinetics of Eu(III) adsorption on...     

Graphene and graphene like 2D graphitic carbon nitride: Electrochemical detection of food colorants and toxic substances in environment

Excessive consumption of substances such as food colorants, exposure to doses of metal ions, antibiotic residues and pesticides residues above maximum tolerance limit have a detrimental effect on human health. Hence in detecting these harmful substances, the development of sensitive, selective and convenient analytical tools is an essential step. Graphene and graphene like 2D graphitic carbon nitride have shown great promise in the development of electrochemical sensors for determining the levels of these substances in different samples. In this paper, graphene and graphene like 2D graphitic carbon nitride applications on the determination of various food colorants in foods and drinks such as azo dyes (tartrazine, allura red, amaranth, carmine and sunset yellow); metal ions contaminants, antibiotic and pesticide residues in the environment are reviewed.     

微量Ag元素对TiAlN涂层摩擦学性能的影响

采用电弧离子镀技术利用Ti₅₀Al₅₀、Ti₅₀Al₄₉Ag₁、Ti₅₀Al₄₅Ag₅合金靶沉积制备出了TiAlN及不同Ag含量的TiAlAgN涂层. 利用球-盘式摩擦磨损试验机研究了室温、200、400和600 ℃等温度下的摩擦学性能；通过扫描电子显微镜(SEM)、X射线衍射仪(XRD)、显微硬度计、表面轮廓仪和划痕仪对磨损前后涂层的表面形貌、微观结构、硬度及涂层结合力进行了分析. 结果表明:TiAlN、TiAlAgN(Ag原子百分数0.12%)、TiAlAgN(Ag原子百分数0.30%)涂层的厚度分别为为4.18、5.31和4.69 μm，硬度分别为HV_0.2 2 049.4、HV_0.2 1 672.9、HV_0.2 1 398.5；TiAlN、TiAlAgN涂层的衍射峰位与面心立方的TiN相同，掺入Ag后TiAlN涂层的择优取向变为N(220)面. 三种涂层在不同温度下的磨损机理主要为黏着磨损与磨粒磨损. 室温时TiAlN涂层的摩擦系数比其他两种涂层要小约0.3，200 ℃时三种涂层的磨损率较大，400 ℃时掺Ag涂层的耐磨效果达到最佳. 此外，当Ag原子百分数在0.12%~0.30%范围时，随着Ag含量增加，涂层的结合力降低.      

不同浓度的尾砂胶结充填体破坏过程 声发射特性试验研究*

制备了3种不同质量浓度的充填体试件，进行了单轴压缩声发射试验，分析了不同浓度的充填体力学特性，重点研究了试件破坏过程中的声发射振铃计数、声发射累计撞击数与声发射累计能量的比值(r值)、主频及其相对高频信号激增响应系数特征。研究表明：随着浓度的增加，充填体的峰值强度与弹性模量呈增大趋势，充填体中出现的声发射累计振铃计数越多；r值先升高再持续减小到一个较低值，随着外载荷的增加，进入缓慢升高阶段，峰值前均保持在该阶段。充填体破裂前兆信息在声发射信号主频分布中呈现主频段增多现象，表现为由加载初期的1~2个主频段，在临界主破裂时增多到3~5个主频段；且随着浓度的增加，声发射信号主频频段分布越宽，声发射相对高频信号(160~180 kHz)的激增响应系数呈递减趋势。以上特征可为不同浓度的尾砂胶结充填体稳定性监测、预测提供依据。     

Controllable soliton transition and interaction in nonlocal nonlinear media

Nonlinear Dynamics - Two kinds of controllable evolutions of optical solitons are predicted in nonlocal nonlinear media by gradually tuning the characteristic length of response function. On the...     

冲击速度和轴向静载对红砂岩破碎及能耗的影响

地下岩体工程爆破开挖中，距爆源不同距离处岩体承受的地应力和动载荷大小不同，从动载荷的角度表征岩石动态破坏结果与工程实际更吻合。为研究动载荷和地应力大小对岩体破碎和能量耗散特性的影响，利用动静组合加载试验装置，分别设置7个冲击速度和轴向静应力等级，对红砂岩试件进行冲击试验。根据试件的破碎状况，分析不同静应力工况下冲击速度对岩石破坏模式和机理的影响。计算不同工况下的应力波能量值，研究冲击速度和轴向静应力对岩石能耗特性的影响。对破坏试件进行筛分试验，研究岩石破碎分形维数随冲击速度和轴向静应力的变化关系。结果表明，随着冲击速度的增大，试件的破坏程度逐渐加大。无轴压时岩石试件破坏后整体仍是一个圆柱体，属于张拉破坏；有轴压时岩石试件宏观破坏后呈沙漏状，属于拉剪破坏。岩石耗散能随冲击速度的升高呈二次函数关系递增；轴向静应力越高，递增幅度越小。随着冲击速度的升高，岩石分形维数由零逐渐增加；随着轴向静应力的升高，分形维数由零转为大于零的临界冲击速度先升高后降低。     

The chemical profile of active fraction of Kalimeris indica and its quantitative analysis

Kalimeris indica (L) Sch-Bip is a medicinal plant used by the Miao ethnic group in the Guizhou province of China. It is widely used as a fresh vegetable to treat colds, diarrhea and gastric ulcers. However, few studies have been conducted on the mechanism of its effect on colds, and its quality control. The anticomplement and antitussive activities of different polar extracts of K. indica were evaluated. Fifty-nine compounds, mainly including phenols and flavonoids, were identified in K. indica extract by ultra-high-performance liquid chromatography quadrupole time-of-flight tandem mass spectrometry. A method was established through ultra-high-performance liquid chromatography with a photodiode array to simultaneously determine the anticomplement and antitussive activity of five compounds in K. indica combining chemical identification with chemometrics for discrimination and quality assessment. Also, 3,5-dicaffeoylquinic acid and 4,5-dicaffeoylquinic acid exhibited significantly higher anticomplementary activity than the other three compounds. The quantitative data were further analyzed by principal component analysis and orthogonal partial least-squares discriminant analysis. Heatmap visualization was conducted to clarify the distribution of the major compounds in different geographical origins. Screening pharmacological activities by a combination of chemometrics and chemical identification might be an effective method for the quality control of K. indica.     

Engineering Carbon Distribution in Silicon-Based Anodes at Multiple Scales

The successful commercialization of promising silicon-based anode materials has been hampered by their poor cycling stability caused by the huge volume change. Integration of the carbon matrix with silicon-based (C/Si-based) anode materials has been demonstrated to be a powerful solution to achieve satisfactory electrochemical performance. This minireview aims to outline recent developments on C/Si-based composites, with the emphasis on the importance of carbon distribution at multiple scales. In addition, the forms of the carbon framework (carbon sources and doping of heteroatoms) have been summarized. Particularly, a novel C/Si-based hybrid with carbon distributed at the atomic scale has been highlighted.     

单层n型MoS2/p型c-Si异质结太阳电池数值模拟

单层二硫化钼(MoS₂)是一种具有优异光电性能的半导体材料,在太阳能能量转换中表现出很大的应用潜力。本文基于AMPS模拟软件,对单层n型MoS₂/p型c-Si异质结太阳电池进行了数值模拟与分析。通过模拟优化,n型MoS₂的电子亲和能为3.75 eV、掺杂浓度为10¹⁸ cm^-3,p型c-Si的掺杂浓度为10¹⁷ cm^-3时,太阳电池能够取得最高22.1%的转换效率。最后模拟了n型MoS₂/p型c-Si异质结界面处的界面态对太阳电池性能的影响,发现界面态密度超过10¹¹ cm^-2·eV^-1时会严重影响太阳电池的光伏性能。     

A survey on HHL algorithm: From theory to application in quantum machine learning

The Harrow-Hassidim-Lloyd (HHL) algorithm is a method to solve the quantum linear system of equations that may be found at the core of various scientific applications and quantum machine learning models including the linear regression, support vector machines and recommender systems etc. After reviewing the necessary background on elementary quantum algorithms, we provide detailed account of how HHL is exploited in different quantum machine learning (QML) models, and how it provides the desired quantum speedup in all these models. At the end, we briefly discuss some of the remaining challenges ahead for HHL-based QML models and related methods.