Single-crystalline silicon thin-film transistor on glass

Single-crystalline silicon-on-glass (cSOG) has been obtained using an "ion-cutting" based layer-transfer technique. Compared to previous attempts of realizing cSOG, extended silicon etching is not required and bulk silicon, instead of the relatively more expensive silicon-on-insulator donor wafers, can be used. Thin-film transistors based on cSOG have been fabricated and characterized. The stability of cSOG Thin-film transistors with or without laser-induced annealing is reported. ©2004 IEEE

Comparison of thermally and mechanically induced Si layer transfer in hydrogen-implanted Si wafers

Hydrogen ion-implantation into Si and subsequent heat treatment has been shown to be an effective means of cleaving thin layer of Si from its parent wafer. This process has been called Smart CutTM or ion-cut. We investigated the cleavage process in H-implanted silicon samples, in which the ion-cut was provoked thermally and mechanically, respectively. A 〈1 0 0〉 oriented p-type silicon wafer was irradiated at room temperature with 100 keV H2+-ions to a dose of 5 × 1016 H2/cm2 and subsequently joined to a handle wafer. Ion-cutting was achieved by two different methods: (1) thermally by annealing to 350 °C and (2) mechanically by insertion of a razor blade sidewise into the bonded wafers near the bond interface. The H-concentration and the crystal damage depth profiles before and after the ion-cut were investigated through the combined use of elastic recoil detection analysis and Rutherford backscattering spectroscopy (RBS). The location at which the ion-cut occurred was determined by RBS in channeling mode and cross-section transmission electron spectroscopy. The ion-cut depth was found to be independent on the cutting method. The gained knowledge was correlated to the depth distribution of the H-platelet density in the as-implanted sample, which contains two separate peaks in the implantation zone. The obtained results suggest that the ion-cut location coincides with the depth of the H-platelet density peak located at a larger depth

Smart farming application using knowledge embedded-graph convolutional neural network (KEGCNN) for banana quality detection

The appearance of fruits is crucial in their quality grading and consumer choices. Colour, texture, size, and shape determine fruit quality. Existing computer vision systems have been implemented for external quality control, relying on observations for fruit grading and classification. Banana quality detection systems, which employ advanced algorithms and sensors to evaluate the ripeness and general quality of bananas throughout their life cycle, are an innovative application of smart farming technology. In this proposed system, Knowledge Embedded-Graph Convolutional Neural Networks (KEGCNNs) are employed to classify and grade banana fruit. The approach aims to detect banana fruit quality by converting banana images into a knowledge graph, applying knowledge embedding to transform them into a continuous vector space, and using Graph Convolution Neural Networks (GCNNs) to analyze the graph structure and make accurate detections. KEGCNNs are especially useful for detecting the quality of banana fruits because they provide a form for capturing the contextual interactions between distinct nodes. KEGCNNs can learn from the data within the graph in an unsupervised manner, allowing them to use the knowledge inherent in the graph structure. KEGCNNs enable more accurate and efficient diagnosis of banana quality as they can discover patterns in data that conventional machine learning algorithms cannot. The suggested technique demonstrates an impressive performance score, indicating its suitability for detecting the quality or grade of banana fruit

Silicon layer transfer using plasma hydrogenation

In this work, we demonstrate a novel approach for the transfer of Si layers onto handle wafers, induced by plasma hydrogenation. In the conventional ion-cut process, hydrogen ion implantation is used to initiate layer delamination at a desired depth, which leads to ion damage in the transferred layer. In this study, we investigated the use of plasma hydrogenation to achieve high-quality layer transfer. To place hydrogen atoms introduced during plasma hydrogenation at a specific depth, a uniform trapping layer for H atoms must be prepared in the substrate before hydrogenation. The hydrogenated Si wafer was then bonded to another Si wafer coated with a thermal oxide, followed by thermal annealing to induce Si layer transfer. Cross-section transmission electron microscopy showed that the transferred Si layer was relatively free of lattice damage. The H trapping during plasma hydrogenation, and the subsequent layer delamination mechanism, are discussed. These results show direct evidence of the feasibility of using plasma hydrogenation to transfer relatively defect-free Si layers