基于荧光原位杂交技术的全自动病理染色系统结构设计

荧光原位杂交(FISH)技术是检测恶性肿瘤细胞核酸序列的常用方法,在癌症的诊疗领域有广泛应用。为实现FISH实验的全自动化,设计了一种全自动病理染色系统。该系统设置有多轴操纵臂、试剂加样器、载玻片、盖玻片夹具、辅助模块等。多轴操纵臂定位误差不大于±0.1 mm,提取及丢弃移液枪头准确率大于99.5%,抽取盖玻片成功率大于99%,微量试剂加样误差不大于0.6μL,大量试剂加样误差不大于0.5 mL,载玻片夹具控温误差不大于±1℃且无试剂泄漏。生物实验结果表明,该系统荧光染色效果良好,信号点清晰可见,荧光图像可判读率超过90%,具有较好的人工替代性。

基于改进YOLOv5的荧光图像细胞智能检测研究

为解决人工对荧光原位杂交(Fluorescence In Situ Hybridization,FISH)荧光图像进行结果判读存在的效率低、劳动强度大等问题,针对FISH荧光图像细胞智能检测提出一种融合空域图像增强的改进YOLOv5算法。算法在原始YOLOv5神经网络模型基础上,加入了空域图像增强模块,并选择了模块最佳增强系数,扩大了模型对荧光图像的对比度适应范围,提高了模型的特征提取能力和细胞检测准确率。实验结果显示,改进YOLOv5模型的平均精度均值(Mean Average Precision,mAP)为0.983,达到了比原始模型更优的训练效果和收敛速度,并且,改进YOLOv5模型的细胞识别率达到91.65%,比原始YOLOv5模型提升了9.19%。将细胞智能检测算法嵌入自主开发的荧光图像智能检测软件,结合荧光点检测算法,可给出有效判读结果。

稀疏重构SAM芯片焊点检测方法研究

提出了基于稀疏表示的声扫描显微镜(Scanning acoustic microscope,SAM)图像超分辨率重构方法,以解决其空间检测分辨率受超声波频率和穿透深度的限制,原始SAM图像分辨率较低,不利于封装缺陷辨识等问题。通过字典设计训练和稀疏系数α求解获得了重构的高分辨率SAM图像,利用Levenberg-Marquardt算法改进BP神经网络(LM-BP),并用于倒装芯片焊点缺陷识别。与原始图像及双三次插值图像相比,稀疏重构图像的峰值信噪比明显增大,提高了SAM图像质量,减小了芯片焊点的错误识别数目,错误率降至2.76%。试验结果表明稀疏表示的SAM重构算法和LM-BP神经网络训练速度快、识别精度高,可用于高密度半导体封装缺陷的检测及可靠性评估。

基于CuPc的反式钙钛矿太阳能电池低温制备

引入一种典型的p型半导体材料CuPc,采用反式钙钛矿太阳能电池结构,利用热蒸发沉积方法将其作为电池的空穴传输层,在低温条件下制备电池器件.对不同厚度CuPc膜对钙钛矿电池性能的影响进行了优化,采用电流-电压测试、扫描电镜、原子力显微镜和X-射线衍射等方法分析了电池的光电性能和薄膜质量.研究结果表明:热蒸发沉积的CuPc层具有良好的平整性和覆盖性,当其厚度为10 nm时,器件在刚性基底上取得了15.37%的最高光电转化效率,在柔性基底上取得了12.66%的最高光电转化效率.该电池制备过程简单、成本低且重复性高,为进一步制备大面积、高效率以及柔性化的钙钛矿太阳能电池提供了参考.

铜微互连线原子迁移仿真研究

研究具有弯折结构的铜微互连线在不同条件下的原子迁移现象,基于原子通量散度理论构建了结构-热-电耦合的多物理场有限元模型,静态分析了铜微互连线结构的电流、温度及应力分布情况,动态模拟了原子迁移全过程.分析了原子迁移过程中电迁移、热迁移及应力迁移各自的作用,揭示了电流密度、环境温度、退火温度和缺陷对原子迁移行为及寿命的影响规律.分析仿真结果发现：电迁移和应力迁移在原子迁移过程中促进了孔洞的生长且占主导作用,热迁移起到了一定抑制作用但所占比例不大.

Automated X-ray recognition of solder bump defects based on ensemble-ELM

Solder bumps realize the mechanical and electrical interconnection between chips and substrates in surface mount components,such as flip chip, wafer level packaging and three-dimensional integration. With the trend to smaller and lighter electronics,solder bumps decrease in dimension and pitch in order to achieve higher I/O density. Automated and nondestructive defect inspection of solder bumps becomes more difficult. Machine learning is a way to recognize the solder bump defects online and overcome the effect caused by the human eye-fatigue. In this paper, we proposed an automated and nondestructive X-ray recognition method for defect inspection of solder bumps. The X-ray system captured the images of the samples and the solder bump images were segmented from the sample images. Seven features including four geometric features, one texture feature and two frequency-domain features were extracted. The ensemble-ELM was established to recognize the defects intelligently. The results demonstrated the high recognition rate compared to the single-ELM. Therefore, this method has high potentiality for automated X-ray recognition of solder bump defects online and reliable.

Au modified ZnO nanowires for ethanol gas sensing

We demonstrated the application of sensors for ethanol gas detection.The ZnO nanowires based sensors with interdigital electrodes were fabricated,and a platform was constructed to test the properties of the sensors.To acquire better response and shorter response/recovery time,the ZnO nanowires were modified with Au.The ethanol gas sensing performance of the pure sensors and those modified with Au nanoparticles were investigated for comparison,and the optimal test temperature of 350℃ was obtained.We found that the response/recovery time for the modified sensor towards 500 ppm of the ethanol gas was reduced by 1.35 and1.42 times compared with the pure sensors,and the sensitivities towards 500 and 10 ppm of the ethanol gas were also increased by 3.18 and 1.35 times,respectively.These proved the enhancement of the Au nanoparticles in the ZnO nanowires based sensors for ethanol gas sensing.

Bio-inspired manufacturing of superwetting surfaces for fog collection and anti-icing applications

As a century-old concept,superwettability has aroused the interest of researchers in the past decades,attributed to the discoveries of the mechanisms of special wetting phenomena in nature.Bio-inspired manufacturing of superwetting surfaces for fog collection and anti-icing applications has become mainstream research,potentially alleviating the problem of water shortage and ice accidents.Superwetting surfaces for fog collection and anti-icing applications involve a reverse process,in which the former gathers water spontaneously,while the latter repels water.Contrastive analysis of the two is essential for the comprehensive understanding of superhydrophilic/superhydrophobic surfaces and boosting their applications.Herein,wetting theories and basic mechanisms for fog collection and anti-icing are briefly introduced.Then,manufacturing methods of bionic structures and surfaces are systematically reviewed after discussing the typical organisms with superwettability.Finally,conclusions are drawn and prospects for future development are proposed.

Investigation on color variation of Morpho butterfly wings hierarchical structure based on PCA

Morpho butterfly wings show brilliant blue color,which has a close relationship with the hierarchical micro/nano structures on the surface of scales.When liquids such as methanol,ethanol and isopropanol with different refractive indexes drop onto the scales,the reflectance of wings would decrease.The main peaks of reflectance shift to the right and the scales turn to yel-low-green.After the liquids volatilizes completely,the scales revert to the original blue color.The typical micro/nano struc-tures of Morpho butterfly wing scales are modeled,and the reflectance variation in the course of dropping liquids is simulated.Furthermore,the principal component analysis(PCA) method is employed to analyze the experimental and simulation reflec-tance data,extract principal components and reduce dimensions.As a result,the curves mapping the reflectance variation are clearly shown in the coordinate system consisting of three principal components.The typical color variation of scales during the dropping process could be monitored,and different kinds of liquids could be obviously distinguished according to the dis-tributed regions of mapping points.This study provides guidance to environmental media detecting as well as data processing,and enhances the fabrication and application of the mimic Morpho butterfly wings micro/nano structures.

Intelligent diagnosis of the solder bumps defects using fuzzy C-means algorithm with the weighted coefficients

Solder bump technology has been widely used in electronic packaging. With the development of solder bumps towards higher density and finer pitch, it is more difficult to inspect the defects of solder bumps as they are hidden in the package. A nondestructive method using the transient active thermography has been proposed to inspect the defects of a solder bump, and we aim at developing an intelligent diagnosis system to eliminate the influence of emissivity unevenness and non-uniform heating on defects recognition in active infrared testing. An improved fuzzy c-means(FCM) algorithm based on the entropy weights is investigated in this paper. The captured thermograms are preprocessed to enhance the thermal contrast between the defective and good bumps. Hot spots corresponding to 16 solder bumps are segmented from the thermal images. The statistical features are calculated and selected appropriately to characterize the status of solder bumps in FCM clustering. The missing bump is identified in the FCM result, which is also validated by the principle component analysis. The intelligent diagnosis system using FCM algorithm with the entropy weights is effective for defects recognition in electronic packages.

Linear Liquid Responses of Morpho Butterfly Structural Color： Experiment and Modeling

This paper investigates the selective liquid response for Morpho didius butterfly wing scales and propose an optical model to explain the effect of different components on the liquid response. It is found out that the reason of the selective response is that the liquid media forms nanometre-thick films between ridge-lamellae nanostructures and changes the constructive interference wavelength. There is linear relation between the structural color of ridge-lamellae structure and index of liquid background media. The reason of vapor＇s responses is that the nanometre-thick liquid fi lms on ridge-lamellae nanostructures change the constructive interference wavelength. These liquid films are formed due to vapor adsorption. Therefore,the selective linear liquid response can be applied to design nano-engineered photonic liquid and vapor sensors.

基于拉胀结构的柔性应变传感器制备及应用

为使柔性应变传感器兼具高灵敏度和优异稳定性,在聚二甲基硅氧烷(PDMS)基底背面引入具有负泊松比特性的拉胀结构,利用聚乙烯亚胺优异的黏附性和多壁碳纳米管的应变传感特性,采用层层自组装技术沉积聚乙烯亚胺-多壁碳纳米管敏感层,再制备电极并进行聚二甲基硅氧烷封装,得到基于拉胀结构的柔性应变传感器.传感器应变系数达499,为无结构应变传感器应变系数的13倍,响应速度快(响应时间为37 ms,弛豫时间为38ms),稳定性好(超过1.5×10^(4)次循环).该柔性应变传感器能够检测人体肢体动作和手腕脉搏等微小生理信号,成功应用于手掌与机械手的实时控制,充分展示出在肢体动作检测和人机交互领域的应用价值.