On the Mechanism of BaSi2 Thin Film Formation on Si Substrate by Vacuum Evaporation

AbstractWe report on the formation mechanism of BaSi2 thin film on Si substrate grown by vacuum evaporation using BaSi2 granules as source materials. Since the vapor flux at the initial stage of evaporation is known to be Ba-rich, Si supply from the substrate is of crucial importance to obtain homogeneous BaSi2 thin film. In fact, low substrate temperature and/or thick film deposition led to formation of rough film with voids, and the oxidation proceeded upon exposure to air. We revealed that appropriate choice of substrate temperature, film thickness, and post-growth in-situ annealing can provide enough diffusion of Si and Ba, leading to realization of homogeneous BaSi2 thin film

Deep Neural Networks for Dental Implant System Classification

In this study, we used panoramic X-ray images to classify and clarify the accuracy of different dental implant brands via deep convolutional neural networks (CNNs) with transfer-learning strategies. For objective labeling, 8859 implant images of 11 implant systems were used from digital panoramic radiographs obtained from patients who underwent dental implant treatment at Kagawa Prefectural Central Hospital, Japan, between 2005 and 2019. Five deep CNN models (specifically, a basic CNN with three convolutional layers, VGG16 and VGG19 transfer-learning models, and finely tuned VGG16 and VGG19) were evaluated for implant classification. Among the five models, the finely tuned VGG16 model exhibited the highest implant classification performance. The finely tuned VGG19 was second best, followed by the normal transfer-learning VGG16. We confirmed that the finely tuned VGG16 and VGG19 CNNs could accurately classify dental implant systems from 11 types of panoramic X-ray images