直拉法单晶硅生长原理、工艺及展望

碳达峰、碳中和理念提出后,太阳能作为一种可再生绿色能源备受关注。单晶硅作为主要的光伏材料,其质量决定着太阳能电池效率的高低,为了降低成本和提高产能,人们对单晶硅提出越来越高的要求。直拉法(CZ法)是单晶硅的主要制备方法,其生产效率高,可实现自动化,直拉单晶硅市场占比超过90%,目前正朝着大尺寸、N型、薄片化、低氧低碳的方向发展。然而随着晶棒尺寸增大,热场变化更加复杂,现有CZ工艺难以满足市场需求。未来降低度电成本仍是晶硅光伏发展的驱动力,应通过技术革新、产业标准化、成本控制等手段推动光伏产业发展。本文介绍了CZ法生长单晶硅的基本原理和生长工艺,分别对缺陷控制、热场优化、氧含量控制等进行了分析,在总结工艺现状和单晶生长特点的基础上对直拉法生长单晶硅的发展方向进行了展望。

基于机器学习的材料弹性性能预测及可视化分析

在工程材料的应用中,弹性模量是重要的性能参数,找到特定弹性性能的材料是新材料合成领域的热点问题,如何快速且准确的预测弹性在工程上具有重要意义.通过实际实验测量大量材料的弹性性能并不现实.因此,通过计算机模拟筛选材料数据,选出候选材料,再通过实际实验进行验证,是一种理想的新材料发现方法.目前材料性能预测的主要计算方法是基于第一性原理的高通量计算,这类方法效率低下,难以高效地完成大批量的材料筛选任务.而基于材料统计学的机器学习预测方法,可通过大数据挖掘,快速预测材料性能,成为一种有可能替代高通量计算的方案.本文将特征选择方法和机器学习模型进行组合,从中选择最有效的弹性模量预测组合方案,并设计交互界面对输入特征和材料弹性性能的关系进行可视化分析.实验表明Pearson/RFE和GBDT的组合模型性能最好,同时通过可视化分析发现每原子能量、熔点、密度等特征对于预测结果的影响较大.这些重要的特征可以从特征–目标关系中初步预测弹性模量的范围,目标属性值也可反过来估计材料的重要特征.这些研究成果可应用于探究弹性的影响因素、预测大批量材料性能和可视化分析指导材料合成.

多孔硅制备及在太阳能电池中的应用研究进展

多孔硅是通过对单晶硅片进行电化学腐蚀或适当的化学腐蚀而形成的一种纳米结构半导体材料。多孔硅纳米材料因其巨大的表面积、可调谐的光学性质和良好的相容性,被广泛应用于电子器件、生物传感、化学传感、药物传递、生物芯片等诸多领域。当前研究的挑战主要在于开发更简单高效的多孔硅纳米材料合成方法以及提高其在实际应用中的表现。综述了多孔硅纳米材料的制备方法及其光致发光在太阳能电池领域中的应用。

计算机类专业数字图像工程类专业课程的建设与改革

数字图像工程类专业课程是高等学校计算机类专业的基础课程,该课程理论性强、概念抽象、学习难度大。为了提高学生的学习兴趣和学习效果,本文通过反思教学实际,分析了数字图像工程类专业课程在教授时所存在问题的形成原因,然后就此提出解决方法。并且将解决方法应用到本校实际教学之中,取得了良好的教学效果。

Preliminary study of an open-air water-contacting discharge for direct nitrogen fixation

Efficient nitrogen fixation through a reactive plasma process attracts intense interest due to the environmental issues induced by the conventional Haber–Bosch method. In this work, we present a direct and simple fixation routine without any catalysts for nitrogen in open air using an atmospheric-pressure pin-to-solution plasma electrolytic system. Nitrate, nitrite, and ammonia as the nitrogen-derived chemicals in solution were analyzed as indicators under various discharge conditions to estimate the energy efficiency of this process. The results show that the nitrogen fixation process was much more efficient by the pin-positive discharge compared to the negative one. N chemicals preferred to be formed when the solution was of negative polarity. It was also found that, with the help of solution circulation, the energy efficiency was enhanced compared to that of static liquid. However, an inverse trend was observed with the increase of the discharge current. Further study by optical emission spectroscopy indicates the important roles of active N2* and water vapour and their derived species near the plasma–water interface in the fixation process.

Super-hydrophobic film deposition by an atmospheric-pressure plasma process and its anti-icing characteristics

In this work,the super-hydrophobic(SH)surface was prepared through chemical vapor deposition process by an argon atmospheric pressure plasma jet source with HMDSN(hexamethyldisilazane)as the polymerization precursor.Plasma synthesized organosilicon(SiOxCyHz)thin films with water contact angle over 160°and sliding angle below 5°,were able to be achieved.FTIR and XPS analysis indicates a large number of hydrocarbon compositions were polymerized in the thin films enduing the latter very-low surface free energy.SEM shows the SH films display micro-nanostructure and with high degree of averaged surface roughness 190 nm evaluated by AFM analysis.From experiments under controlled low-temperature and moisture conditions,the prepared SH surface exhibits good anti-icing effects.Significantly prolonging freezing time was achievable on the SH thin films for both static and sliding water droplets.This investigation demonstrates the anti-icing potentials of SH surface prepared through low-cost simple atmospheric-pressure plasma polymerization process.

未来的电池之星——锂-空气电池

锂空气电池具有极高的理论比容量,应用在电动汽车中可以获得和汽油相当的续航能力,因而获得了人们广泛的关注。在最近十几年的研究中,人们对于锂空气电池的理解逐渐深入,制备得到的电池性能也得到了极大的提高。本文从锂空气电池的发展历史入手,介绍了其基本原理,以及最近几年在电解质、空气电极、催化剂等方面的最新研究成果。对目前的研究现状进行了简单的剖析,并对未来的应用前景进行了展望。

In situ quantification of NO synthesis in a warm air glow discharge by WMS-based Mid-IR QCL absorption spectroscopy

Nitric oxide(NO)is one of the most crucial products in the plasma-based nitrogen fixation process.In this work,in situ measurements were performed for quantifying the NO synthesis spatially in a warm air glow discharge,through the method of Mid-infrared quantum cascade laser absorption spectroscopy(QCL-AS).Two ro-vibrational transitions at 1900.076 cm^(-1) and 1900.517 cm^(-1) of the ground-state NO(X)were probed sensitively by the help of the wavelength modulation spectroscopy(WMS)approach to increase the signal/noise(S/N)level.The results show a decline trend of NO synthesis rate along the discharge channel from the cathode to the anode.However,from the point of energy efficiency,the cathode region is of significantly low energy efficiency of NO production.Severe disproportionality was found for the high energy consumption but low NO production in the region of cathode area,compared to that in the positive column zone.Further analysis demonstrates the high energy cost of NO production in the cathode region,is ascribed to the extremely high reduced electric field E/N therein not selectively preferable for the processes of vibrational excitation or dissociation of N_(2) and O_(2) molecules.This drags down the overall energy efficiency of NO synthesis by this typical warm air glow discharge,particularly for the ones with short electrode gaps.Limitations of further improving the energy cost of NO synthesis by variations of the discharge operation conditions,such as discharge current or airflow rate,imply other effective manners able to tune the energy delivery selectively to the NO formation process,are sorely needed.

The mechanism of Wumei Wan on treating diabetes enteropathy based on the network pharmacology

Objective:To explore the potential mechanism of Wumei Wan(WMW)in treating diabetes enteropathy(DE)basing on network pharmacology.Methods:The effective compound of WMW were collected by TCMSP,the potential target of WMW was obtained by means of PubChem and Swiss target prediction online tools,and the disease target of DE was obtained by Genecards,TTD and DisGeNET databases,Cytoscape 3.7.2 software was used to construct active ingredients of WMW-potential target-DE network,protein interaction network(PPI)was constructed by STRING database.In order to understanding the mechanism of WMW treating in DE,Omicshare platform was used for GO analysis and KEGG pathway enrichment analysis.The analysis results were verified through docking by Discovery Studio 2016.Results:Total of 128 active components and 139 targets of WMW were screened out from the ten drugs.A total of 714 disease targets were screened out from the disease databases.24 common targets were identified from both WMW and DE.AKT1,MMP9,SRC,PTGS2,PPARG,NOS2,etc.are potential major targets of WMW in the treatment of DE.61 entries(p<0.05)were enriched in GO biological process function related to fatty acid anabolism and ligand receptor binding,as unsaturated fatty acid metabolic process,icosanoid metabolic process,enzyme linked receptor protein signaling pathway,protein amino acid phosphorylation,cellular response to insulin stimulus.A total of 72 signaling pathways were obtained through KEGG pathway analysis(p<0.05).The signaling pathways closely related to DE are including relaxin signaling pathway,EGFR tyrosine kinase inhibitor resistance,CLRs signaling pathway,and VEGF signaling pathway.Conclusion:This study preliminarily revealed the material basis and mechanism of WMW in the treatment of DE from the synergistic aspects of intestinal immune balance,gastrointestinal wall structure reconstruction,intestinal microvascular disorder and neuronal activity.

Automated identification of steel weld defects,a convolutional neural network improved machine learning approach

This paper proposes a machine-learning-based methodology to automatically classify different types of steel weld defects,including lack of the fusion,porosity,slag inclusion,and the qualified(no defects)cases.This methodology solves the shortcomings of existing detection methods,such as expensive equipment,complicated operation and inability to detect internal defects.The study first collected percussed data from welded steel members with or without weld defects.Then,three methods,the Mel frequency cepstral coefficients,short-time Fourier transform(STFT),and continuous wavelet transform were implemented and compared to explore the most appropriate features for classification of weld statuses.Classic and convolutional neural network-enhanced algorithms were used to classify,the extracted features.Furthermore,experiments were designed and performed to validate the proposed method.Results showed that STFT achieved higher accuracies(up to 96.63%on average)in the weld status classification.The convolutional neural network-enhanced support vector machine(SVM)outperformed six other algorithms with an average accuracy of 95.8%.In addition,random forest and SVM were efficient approaches with a balanced trade-off between the accuracies and the computational efforts.

Antioxidation of Anthocyanins in Photosynthesis Under High Temperature Stress

Chlorophyll fluorescence and antioxidative capability in detached leaves of the wild type Arabidopsis thaliana L. ecotype Landsberg erecta （Ler） and three mutants deficient in anthocyanins biosynthesis （tt3, tt4, and tt3tt4） were investigated during treatment with temperatures ranging 25-45 ℃. In comparison with the wild type, chlorophyll fluorescence parameters Fv/Fm, φps,, electron transport rate （ETR）, Fv/Fo and qP in three anthocyanin-deficient mutants showed a more rapidly decreasing rate when the temperature was over 35 ℃. Non-photochemical quenching （NPQ） in these mutants was almost completely lost at 44 ℃, whereas the content of heat stable protein dropped and the rate of the membrane leakage increased. Fo-temperature curves were obtained by monitoring Fo levels with gradually elevated temperatures from 22 ℃ to 72 ℃ at 0.5 ℃/min. The inflexion temperatures of Fo were 45.8 ℃ in Ler, 45.1℃ in tt3, 44.1℃ in tt4 and 42.3 ℃ in tt3tt4, respectively. The temperatures of maximal Fo in three mutants were 1.9-3.8℃ lower than the wild type plants. Meanwhile, three mutants had lower activities of superoxide dismutase （SOD） and ascorbate peroxidase （APX） and an inferior scavenging capability to DPPH （1.1-diphenyl-2-picrylhy.drazyl） radical under heat stress, and in particular tt3tt4 had the lowest antioxidative potential. The results of the diaminobenzidine-H2O2 histochemical staining showed that H2O2 was accumulated in the leaf vein and mesophyll cells of mutants under treatment at 40 ℃, and it was significantly presented in leaf cells of tt3tt4. The sensitivity of Arabidopsis anthocyanins-deficient mutants to high temperatures has revealed that anthocyanins in normal plants might provide protection from high temperature injury, by enhancing its antioxidative capability under high temperature stress.