Influence of Si-Doping on the Performance of InGaN/GaN Multiple Quantum Well Solar Cells

Semiconductors - The performance of InGaN/GaN multiple quantum well (MQW) solar cells with five different Si-doping concentrations, namely 0, 4 × 1017 cm–3, 1 × 1018 cm–3, 3...     

除尘器新型褶式滤筒的结构优化及系列化设计

以新型褶式滤筒为研究对象,选取滤筒褶数N_2、褶夹角θ、褶高h、过滤风速v为影响因子,除尘器压力损失为响应值,基于响应曲面法分析影响因子对压力损失的影响,建立滤筒除尘器压力损失的预测模型并得到滤筒褶皱结构最优参数。以滤筒内径D、筒体高度D_1为标准尺寸,依据相关国家标准设计滤筒筒体部分;以锥体高度D_2、锥体上圆直径D_3为系列尺寸,利用尺寸变化法设计锥体部分;通过Access软件建立滤筒产品数据库。结果表明:当θ=5.2°,N_2=50,v=0.01 m/s,h=0.035 m时,除尘器压力损失最低;当D_1=1 000 mm,D=320 mm时,D_2和D_3最佳值分别为600,130 mm,故采用D_2/D_1=0.6,D_3/D=0.4的比值设计相应滤筒锥体系列。     

并联有源滤波器的改进重复控制策略研究

针对三相整流负载产生的6k±1次谐波,提出静止坐标系下的改进型6k±1重复控制策略。同时将比例控制与改进型重复控制相结合,设计改进重复控制并联比例的复合控制结构。为减小改进重复控制中延时环节不为整数的影响,采用基于Lagrange插值近似的FIR滤波器逼近分数延时特性。最后对系统进行稳定性分析和详细设计方法进行推导。通过Matlab仿真验证改进重复控制策略能有效跟踪6k±1次谐波且具有良好的补偿效果,动态响应较快。     

秸秆微晶纤维素用作片剂崩解剂的初步评价

对实验室自制秸秆微晶纤维素用作片剂崩解剂进行了初步评价。参照《中国药典》(2010版)中微晶纤维素的有关规定,评估自制秸秆微晶纤维素的质量;以阿司匹林为模型药物,以市售微晶纤维素(PH-101)为对照,测定秸秆微晶纤维素的溶胀性、崩解性。结果表明,自制的秸秆微晶纤维素质量符合《中国药典》有关规定,且溶胀性和崩解性优于市售微晶纤维素(PH-101),可用作片剂崩解剂。在秸秆微晶纤维素含量为20%时,崩解速度最快。     

基于萤石溶解/表面转化的含钙矿物表面定向调控浮选技术及机理研究

研究了萤石在白钨矿和方解石表面溶解和转化的可能性, 发现萤石可以在特定的捕收剂体系下作为抑制剂实现含钙矿物的浮选分离。浮选实验结果表明, 萤石作为抑制剂, 在白钨矿和方解石的浮选中, 用量小、作用效果明显; 动电位检测结果证实了萤石能明显降低方解石的动电位, 但对白钨矿基本没有影响; XPS检测结果证明了萤石对方解石的作用主要在于对Ca-O键能的减弱和Ca-F基团的生成, 即在方解石表面生成CaF2膜; AFM检测则可直观观察到方解石表面经过萤石处理之后出现明显的起伏, 印证了离子的侵蚀与CaF₂膜的生成。     

Automatic breast tumor detection in ABVS images based on convolutional neural network and superpixel patterns

Breast cancer is one of the most common female malignancies, as well as the second leading cause of mortality for women. Early detection and treatment can dramatically decrease the mortality rate. Recently, automated breast volume scanner (ABVS) has become one of the most frequently used diagnose methods for breast tumor screening because of its operator-independent and reproducible advantages. However, it is a challenging job to obtain the tumors’ accurate locations and shapes by reviewing hundreds of ABVS slices. In this paper, a novel computer-aided detection (CADe) system is developed to reduce clinicians’ reading time and improve the efficiency. The CADe system mainly contains three parts: tumor candidate acquisition, false-positive reduction and tumor segmentation. Firstly, a local phase-based approach is built to obtain breast tumor candidates for further recognition. Subsequently, a convolutional neural network (CNN) is applied to reduce false positives (FPs). The introduction of CNN can help to avoid complicated feature extraction as well as elevate the accuracy and efficiency. Finally, superpixel-based segmentation is used to outline the breast tumor. Here, superpixel-based local binary pattern (SLBP) is proposed to assist the segmentation, which improves the performance. The methods were evaluated on a clinical ABVS dataset whose abnormal cases were manually labeled by an experienced radiologist. The experiment results were mainly composed of two parts. At the FP reduction stage, the proposed CNN achieved 100% and 78.12% sensitivity with FPs/case of 2.16 and 0. At the segmentation stage, our SLBP obtained 82.34% true positive, 15.79% false positive and 83.59% Dice similarity. In summary, the proposed CADe system demonstrated promising potential to detect and outline breast tumors in ABVS images.

     

In-situ crystal growth and photoluminescence properties of YBO3: Tb3+ microstructures

Three-dimensional (3D) YBO₃:Tb³⁺ flower-like and dense flower-like hierarchitecture constituted of nanoflakes are solvothermally synthesized in the presence of polyborate precursors in the mixture of ethanol and water. The growth process of the YBO₃:Tb³⁺ flowers and dense flowers was explored based on the time-dependent experiment and the results showed that the growth mechanism follows an in situ growth rather than self-assembly process as reported previously. YBO₃:Tb³⁺ morphologies composed of nanoflakes are achieved by controlling the concentration of ethanol and dependence of photoluminescence on morphology was studied. Remarkable photoluminescence enhancement was observed for YBO₃:Tb³⁺ with flower-like morphology demonstrating the potential of the microstructure in future applications as a green phosphor. Such a synthetic method and growth mechanism may be applied to fabricate complex 3D architectures of other materials.     

某高校既有建筑室内人员相关VOCs目标污染物的实测分析

为研究高校既有建筑室内人群散发对室内VOCs的影响，对高校不同人群样本的教室及会议室两类典型人群密集房间，共82个人群样本对象进行了VOCs采样分析，得到不同实际场景下的人员相关的VOCs浓度水平，并对其潜在的影响因素进行分析。结果表明，共确认了29种与室内人员相关的高检出率且较高浓度值的物质，包括芳香族化合物9种，烷烯烃类9种，酮类和醛类8种，醇酯类以及卤化物3种，并得到主要VOCs物质的浓度水平和I/O比。对影响因素的统计分析表明，室内人员密度、季节和房间类型对不同VOCs物质存在显著性影响，其中季节性因素对目标VOCs污染物影响最为广泛，其次是房间类型与室内人员密度。该研究可为进一步了解人员密集室内VOCs污染现状及控制策略提供一定的科学参考。