双激光脉冲打靶形成Gd等离子体的极紫外光谱辐射

高端芯片制造所需要的极紫外光刻技术位于我国当前面临35项"卡脖子"关键核心技术之首.高转换效率的极紫外光源是极紫外光刻系统的重要组成部分.本文通过采用双激光脉冲打靶技术实现较强的6.7 nm极紫外光输出.首先,理论计算Gd¹⁸⁺—Gd²⁷⁺离子最外层4d壳层的4p-4d和4d-4f能级之间跃迁、以及Gd¹⁴⁺—Gd¹⁷⁺离子最外层4f壳层的4d-4f能级之间跃迁对波长为6.7 nm附近极紫外光的贡献.其后开展实验研究,结果表明,随着双脉冲之间延时的逐渐增加,波长为6.7 nm附近的极紫外光辐射强度呈现先减弱、后增加、之后再减弱的变化趋势,在双脉冲延时为100 ns处产生的极紫外光辐射最强.并且,在延时为100 ns处产生的光谱效率最高,相比于单脉冲激光产生的光谱效率提升了33%.此外,发现双激光脉冲打靶技术可以有效地减弱等离子体的自吸收效应,获得的6.7 nm附近极紫外光谱宽度均小于单激光脉冲打靶的情形,且在脉冲延时为30 ns时刻所产生的光谱宽度最窄,约为单独主脉冲产生极紫外光谱宽度的1/3.同时...     

Terahertz generation in quantum cascade structures by two-color deriving fields: An approach to reach inversion population via optical pumping

In this paper, a quantum cascade laser (QCL) design is proposed based on GaAs/AlGaAs material system, which simultaneously operates at three widely separated wavelengths (${\lambda }_1=11.1\mu m,{\lambda }_2=14.1\mu m$ and ${\lambda }_{THz}=60\mu m$). In the design, all the wavelength radiations are achieved by the engineering of the electronic spectrum via the quantum-well widths and the applied electric field in a single active region within a same waveguide. The mid-infrared (mid-IR) wavelengths are obtained by adoption a dual-upper-state active region, and the proposed design aims to use both the mid-IR radiations as the coherent deriving fields to populate the upper THz lasing state to aid the THz-laser population inversion via optical pumping instead of direct electrical injection. A detailed analysis of electronic transport in the structure is carried out using a multi-level rate-equation model. The results show that the proposed structure offers an alternative approach to room temperature THz generation in QCLs.     

Yb:CaF2–YF3 transparent ceramics ultrafast laser at dual gain lines

Yb³⁺:CaF₂-YF₃ transparent ceramics with excellent optical quality was successfully fabricated by hot-pressed method. Pulsed laser properties of this ceramics were investigated for the first time. Laser diode (LD) was applied as the pump source to generate a dual-wavelength mode-locked (ML) laser. The maximum average output power was 310 mW, which represents the highest output power of ultrafast calcium fluoride ceramic laser. The spectrum separated at 1048.9 nm and 1049.7 nm with a total pulse duration of 8.9 ps. The interval period between the beating signals was about 4.3 ps, corresponding to a 0.23 THz beat pulse repetition rate. These results demonstrate its potential in producing dual-wavelength ultrashort pulses. These Yb³⁺:CaF₂-YF₃ ceramics with low-cost and short-preparation period are ideal candidate materials for ultrafast lasers.     

Co-Training for Visual Object Recognition Based on Self-Supervised Models Using a Cross-Entropy Regularization

Automatic recognition of visual objects using a deep learning approach has been successfully applied to multiple areas. However, deep learning techniques require a large amount of labeled data, which is usually expensive to obtain. An alternative is to use semi-supervised models, such as co-training, where multiple complementary views are combined using a small amount of labeled data. A simple way to associate views to visual objects is through the application of a degree of rotation or a type of filter. In this work, we propose a co-training model for visual object recognition using deep neural networks by adding layers of self-supervised neural networks as intermediate inputs to the views, where the views are diversified through the cross-entropy regularization of their outputs. Since the model merges the concepts of co-training and self-supervised learning by considering the differentiation of outputs, we called it Differential Self-Supervised Co-Training (DSSCo-Training). This paper presents some experiments using the DSSCo-Training model to well-known image datasets such as MNIST, CIFAR-100, and SVHN. The results indicate that the proposed model is competitive with the state-of-art models and shows an average relative improvement of 5% in accuracy for several datasets, despite its greater simplicity with respect to more recent approaches.     

阳离子交换皂石黏土在基质辅助激光解吸电离飞行时间质谱分析中的应用

将一种人工合成的无机聚合物——蒙脱石皂石黏土（smectite，Sm）应用于基质辅助激光解吸电离飞行时间质谱分析（matrix-assisted laser desorption/ionization time of flight mass spectrometry, MALDI-TOF-MS），以检测糖类化合物。 将传统的有机基质2，4，6-三羟基苯乙酮（trihydroxyacetophenone, THAP）与阳离子交换后的皂石黏土混合制备成新型复合基质，应用于糖类化合物的检测。通过比较不同的制样方法，测定不同分子直径的糖类化合物，发现由于受复合基质晶面间距的限制，只有小分子糖类化合物能进入晶面间隙充分接触有机基质并被离子化，从而实现对小分子糖类化合物的选择性检测。     

The pentacene films on the glass/ITO surface: structure and optical properties

Abstract

The structure, morphology and optical transmittance spectra of pentacene films on the (glass/ITO) surface were studied. The films were grown by two methods - the thermal vacuum deposition (TVD) and pulsed laser deposition (PLD). The electron diffraction pattern from thermally deposited pentacene films confirms their polycrystalline structure while the diffraction pattern of PLD-coated layers has a diffusion character. The results obtained showed that layers deposited by the TVD method has an optical spectrum that is characteristic for the pentacene film in contrary to the layers deposited by the PLD method. It is found a sensitivity of the optical transmittance of pentacene films to the ammonia action, which may be used for development the optical gas sensor.     

Enhanced headspace single drop microextraction method using deep eutectic solvent based magnetic bucky gels: Application to the determination of volatile aromatic hydrocarbons in water and urine samples

A facile headspace single drop microextraction method was developed using deep eutectic solvent‐based magnetic bucky gel as the extraction solvent for the first time. The hydrophobic magnetic bucky gel was formed by combining choline chloride/chlorophenol deep eutectic solvent and magnetic multiwalled carbon nanotube nanocomposite. Magnetic susceptibility, high viscosity, high sorbing ability, and tunable extractability of organic analytes are the desirable advantages of the prepared gel. Using a rod magnet as a suspensor in combination with the magnetic susceptibility of the prepared gel resulted in a highly stable droplet. This stable droplet eliminated the possibility of drop dislodgement. The prepared droplet made it possible to complete the extraction process in high temperatures and elevated agitation rates. Furthermore, using larger micro‐droplet volumes without any operational problems became possible. These facts resulted in shorter sample preparation time, higher sensitivity of the method, and lower detection limits. Under the optimized conditions, an enrichment factor of 520–587, limit of detection of 0.05–0.90 ng/mL, and linearity range of 0.2–2000 ng/mL (coefficient of determination = 0.9982–0.9995) were obtained. Relative standard deviations were < 10%. This method was successfully coupled with gas chromatography and used for the determination of benzene, toluene, ethylbenzene, and xylene isomers as harmful volatile organic compounds in water and urine samples.     

RNAGCN: RNA tertiary structure assessment with a graph convolutional network

RNAs play crucial and versatile roles in cellular biochemical reactions. Since experimental approaches of determining their three-dimensional (3D) structures are costly and less efficient, it is greatly advantageous to develop computational methods to predict RNA 3D structures. For these methods, designing a model or scoring function for structure quality assessment is an essential step but this step poses challenges. In this study, we designed and trained a deep learning model to tackle this problem. The model was based on a graph convolutional network (GCN) and named RNAGCN. The model provided a natural way of representing RNA structures, avoided complex algorithms to preserve atomic rotational equivalence, and was capable of extracting features automatically out of structural patterns. Testing results on two datasets convincingly demonstrated that RNAGCN performs similarly to or better than four leading scoring functions. Our approach provides an alternative way of RNA tertiary structure assessment and may facilitate RNA structure predictions. RNAGCN can be downloaded from https://gitee.com/dcw-RNAGCN/rnagcn.     

RAFM钢TIG焊和电子束焊疲劳性能实验和分析模拟

利用ANSYS 对低活化铁素体马氏体(RAFM)钢进行非熔化极气体保护焊(TIG 焊)与电子束焊的抗疲劳模拟分析，再利用SDS200 电液伺服疲劳试验机对TIG 焊和电子束焊的两种RAFM 钢试件进行实验。通过施加相同梯度负荷对TIG 焊和电子束焊试件进行焊缝的疲劳性能实验。与实验结果对比分析，结果显示电子束焊优于 TIG 焊，但在一定负载下可以用TIG 焊代替电子束焊。     

级联光栅结合Sagnac环的可调谐光纤激光器

提出并验证了一种单-双波长可调谐掺铒光纤激光器。利用级联光纤布拉格光栅(Cascaded Fiber Bragg gratings,Cascaded FBGs)结合Sagnac环结构所产生的复合滤波效应,实现较高精细度滤波,并通过调节环内偏振控制器(Polarization Controller,PC),引入双折射效应,得到波长可调谐的光纤激光器。基于耦合模理论并使用传输矩阵法对该结构的传输特性进行了分析,在此基础上搭建实验系统,验证了理论分析的正确性。实验结果表明:通过调节PC,激光器输出激光的波长范围约为1 555.644～1 556.112 nm,双波长间隔的可调范围约为0.108～0.452 nm,单-双波长的边模抑制比(SMSR)均高于40 dB;在稳定性测试中,输出单-双波长激光的波长最大漂移量小于0.008 nm。该方法具有结构简单、调谐方便、易于实现且精细度较高的优点,可应用于密集波分复用及全光通信系统等领域。