单晶硅晶格间距的测量技术进展及应用

单晶硅晶格间距是许多重要物理常数测量的基础。本文介绍了硅晶格间距测量技术的发展历程,包括X射线干涉仪直接测量和晶格比较仪间接测量两种方法,以及影响测量结果不确定度的关键因素。得益于晶格间距测量的进展,在纳米尺度,硅晶格间距被国际计量局(BIPM)批准成为新的米定义复现形式。最后介绍了硅晶格在计量学中的应用,以及基于硅晶格实现纳米几何量测量的溯源体系的研究趋势。     

Polyvinylpyrrolidone and graphene-modified hematite nanoparticles for efficient electrocatalytic oxidation of p-nitrophenol

Journal of Solid State Electrochemistry - Polyvinylpyrrolidone (PVP) and graphene (G)-modified iron oxides (Fe2O3-PVP-G) are prepared by a simple hydrothermal reaction. Their morphology and...     

Hierarchical motion planning at the acceleration level based on task priority matrix for space robot

Nonlinear Dynamics - A capacitive micromachined ultrasonic transducer (CMUT) due to many benefits is being considered as an imaging and therapeutic technology recently. The critical challenge is to...     

Portfolio Selection and Risk Control for an Insurer With Uncertain Time Horizon and Partial Information in an Anticipating Environment

Methodology and Computing in Applied Probability - This paper is devoted to the study of an optimal investment and risk control problem for an insurer. The risky asset process and the insurance...     

喷雾干燥-固相煅烧法制备球形钛酸狸负极材料的研究

通过喷雾干燥-固相煅烧法制备了球形钛酸钾.不同于传统喷雾干燥工艺采用固态钛源进行制备,本文采用的前驱体是钾盐,分散剂和钛酸四丁酯制备出的硝酸氧钛的混合溶液.由于制备方法中前驱体为原子级均匀分布,化学计量比可精确控制,制备出的材料颗粒细小,粒径、成分分布均匀,电化学性能优异.同时研究了不同钾钛摩尔比以及煅烧温度对球形钛酸钾的形貌和成分的影响,并研究了其作为钾离子电池电极材料的电化学性能.结果表明,钾钛摩尔比为0.816,煅烧温度为 800 ℃时钛酸钾的电化学性能最好,首圈容量 185.1 mAh/g,30 圈后容量为173.9 mAh/g,循环100圈后还有169.7 mAh/g的容量.     

A self-penetrating and chemically stable zinc (ii)-organic framework as multi-responsive chemo-sensor to detect pesticide and antibiotics in water

Guided by the self-penetrating features can improve the stability of metal organic frameworks (MOFs), an unprecedented 3D self-penetrated framework, {[Zn (tptc)_0.5(bimb)]·H₂O}_n ( NUC-6 , here NUC corresponding to North University of China), with 3D (4,4)-c {8⁶} net, was designed. Benefit from the high chemical stability and excellent luminescent property, NUC-6 can be act as an efficient multi-response chemo-sensor in detecting dichloronitroaniline pesticide and nitrofuran antibiotics in water with the detection limits are 116 ppb for DCN pesticide, 16 ppb for NFT antibiotic, and 12 ppb for NTZ antibiotic. Besides, the mechanisms of luminescence quenching were revealed from the viewpoint of internal filter effect (IFE) and photo-induced electron transfer (PET), implied by the optical spectroscopy and quantum chemical calculation. This work provides a promising strategy to design stable MOFs by improving the self-penetrating features and to expand their practical applications in the detection of organic pollutants in aqueous medium.     

The first excited single-proton resonance in 15F by complex-scaled Green's function method

The complex-scaled Green's function(CGF)method is employed to explore the single-proton resonance in 15F.Special attention is paid to the first excited resonant state 5/2+,which has been widely studied in both theory and experiments.However,past studies generally overestimated the width of the 5/2+state.The predicted energy and width of the first excited resonant state 5/2+by the CGF method are both in good agreement with the experimental value and close to Fortune's new estimation.Furthermore,the influence of the potential parameters and quadruple deformation effects on the resonant states are investigated in detail,which is helpful to the study of the shell structure evolution.     

卷积神经网络用于近红外光谱古筝面板木材分级

目前,我国乐器制作行业在古筝面板用木材等级的筛选上主要依赖于技师主观评判,但此法缺少科学理论的依据,效率低,客观性及出材率的提高等方面受到限制,无法满足乐器市场的大量需求。实现古筝面板用木材快速、智能化的分级工作是一个急需解决的课题。近红外光谱非常适用于测量含氢的有机物质。古筝面板木材主要化学成分的化学键均由含氢基团组成,不同等级板材的化学成分存在差异,这些差异反映在近红外光谱中,为判断木材等级提供了可能。同时卷积神经网络对非线性数据具有较强的特征提取能力,所以提出一种应用卷积神经网络模型对光谱数据进行分析的方法,进而判别木材的等级。应用了Savitzky Golay一阶、二阶微分两种预处理方法和核主成分分析、连续投影算法两种数据压缩方法,通过所设计的卷积神经网络模型以样本识别准确率和模型构建过程中的损失值作为判定指标选出最佳预处理和数据压缩方法。为了提高模型提取分析光谱数据的能力和避免过拟合现象,应用了多通道卷积核、批量归一化和early stopping策略,将通过两层卷积层提取的特征信息送入全连接层,从而充分提取剩余信息,通过Softmax函数获得板材的最终预测等级,从而确定了最终模型。最终Savitzky Golay一阶微分和核主成分分析为最佳数据处理方法,同时得出用于区分不同等级的古筝面板用木材的主要关键谱带,分别为1 163~1 243, 1 346~1 375和1 525~1 584 nm。将该模型应用于测试集样本,古筝面板用木材的等级识别准确率为95.5%。实验结果表明所提出的方法可以高效地处理光谱数据,有效识别区分不同等级的古筝面板用木材的关键特征,从而为广阔的乐器市场提供一定的技术支持。