含氯离子硫酸铜溶液中铝表面的点蚀观察

利用SEM辅以EDS分析,对铜-铝置换反应下铝的氯离子点蚀的过程进行了元素的分析及形貌上的观察。点蚀核处没有铜的析出,并且点蚀核外壳部分氧含量达到50%,铝含量仅有15%;而点蚀核破裂的内部铝含量达到54%,而氧含量下降到16%。对于点蚀孔则发现了铜仅集中分布在蚀坑的周围与内部的浅层区域,并且蚀坑内部发现了铝形成了近乎直角的规则交叉棱柱结构。参考以往的研究成果,在文章中对点蚀过程中的这一系列现象给出了初步的理论解释。     

基于X射线量变化评估真空灭弧室真空度的方法

为了找到一种操作简便且准确度高的方法来进行真空度评估,笔者提出了一种不需外施磁场、利用测量X射线量变化来判断真空灭弧室内部真空度的方法。对于真空灭弧室在指定开距下施加工频电压时,场致发射电子会以很高的速度从阴极表面逸出,在触头间电场的作用下加速轰击阳极,基于轫致辐射的原理会从阳极表面释放出X射线。这时,真空度的差异会使产生的X射线释放强度以及变化情况有所不同,因此,利用测量释放的X射线量的变化可判断真空灭弧室内部的真空度。笔者通过理论分析,得出了X射线量与真空度的关系,并进行了试验验证。     

低能过滤X射线神经网络解谱方法研究

利用神经网络算法实现对PIPS探测器测量得到的低能过滤X射线脉冲幅度谱的快速解谱.首先根据PIPS探测器的计算机断层扫描图像,在MCNP5中建立该探测器的蒙特卡罗(MC)模型.并通过实验、MC效率刻度以及能谱展宽,对该探测器模型进行验证.之后计算PIPS探测器对单能光子(5～30?keV)的响应函数,并将其作为单层线性...     

The Impact of X-Ray Radiation on Chemical and Optical Properties of Triple-Cation Lead Halide Perovskite: from the Surface to the Bulk

Understanding the effects of X-rays on halide perovskite thin films is critical for accurate and reliable characterization of this class of materials, as well as their use in detection systems. In this study, advanced optical imaging techniques are employed, both spectrally and temporally resolved, coupled with chemical characterizations to obtain a comprehensive picture of the degradation mechanism occurring in the material during photoemission spectroscopy measurements. Two main degradation pathways are identified through the use of local correlative physico-chemical analysis. The first one, at low X-Ray fluence, shows minor changes of the surface chemistry and composition associated with the formation of electronic defects. Moreover, a second degradation route occurring at higher fluence leads to the evaporation of the organic cations and the formation of an iodine-poor perovskite. Based on the local variation of the optoelectronic properties, a kinetic model describing the different mechanisms is proposed. These findings provide valuable insight on the impact of X-rays on the perovskite layers during investigations using X-ray based techniques. More generally, a deep understanding of the interaction mechanism of X-rays with perovskite thin films is essential for the development of perovskite-based X-ray detectors and solar for space applications.     

Recognition and segmentation of teeth and mandibular nerve canals in panoramic dental X-rays by Mask RCNN

This study proposes a method based on the instance segmentation algorithm Mask RCNN for recognizing and segmenting 32 teeth and 2 mandibular nerve canals in panoramic dental X-rays. Compared with Faster RCNN, Mask RCNN has an additional semantic segmentation branch, which could directly obtain the position of teeth and the information about mandibular nerve canals in this study. At the same time, Mask RCNN introduces ROI Align, making Mask segmentation more accurate. A total of 120 training sets, 40 validation sets, and 120 test sets were used in the training and testing process. Forty of the test sets were used to test the full-tooth panoramic dental X-rays, and 40 were used for the edentulous panoramic dental X-rays, with 40 for the mandibular canals. The average precision, recall, and F1-score values of the full teeth were 96.59 %, 96.4 %, and 96.5 %, respectively. The P_m value of the defined edentulous panoramic dental X-rays was 95.41 %, and the average precision, recall, and F1-score values of mandibular canals were 76.05 %, 83.70 %, and 78.10 %, respectively. The results showed that the algorithm could effectively identify each tooth, including missing teeth and mandibular nerve canals in panoramic dental X-rays, solving the problem of too many oral structures in panoramic dental X-rays, which makes it difficult to determine the overall oral state. This study will help other researchers promote the research on artificial intelligence-assisted diagnosis in the oral field.