Large‐area epitaxy of layered materials is one of the cornerstones for a successful exploitation of van der Waals (vdW) materials in the semiconductor industry. The formation of 60° twin stacking faults and 60° grain boundaries is of major concern for the defect‐free epitaxial growth. Although strategies to overcome the occurrence of these defects are being considered, more fundamental understanding on the origin of these defects is highly essential. This work focuses on understanding the formation of 60° twins in (quasi‐)vdW epitaxy of 2D chalcogenides. Molecular beam epitaxy (MBE) experiments reveal the striking difference in 60° twin occurrence between WSe2 and Bi2Se3 in both quasi‐vdW heteroepitaxy and vdW homoepitaxy. Density functional theory (DFT) calculations link this difference to the interlayer vdW coupling strength at the unit cell level. The stronger interlayer vdW coupling in Bi2Se3 unit cells compared to WSe2 unit cells is explained to result in a reduced twin occurrence. Hence, such compounds show significantly more promise for defect‐free epitaxial integration. This interesting aspect of (quasi‐)vdW epitaxy reveals that the strength of interlayer vdW coupling is key for workable 2D materials and opens perspectives for other strongly coupled vdW materials.

This paper presents a multi-sensor data fusion model for measurement of temperature. The proposed paper puts forward an objective to develop a temperature measuring instrument (a) having improved performance characteristics like sensitivity and linearity (b) that produces accurate measurement even though a sensor is faulty. The technique is designed using the framework of multi-sensor data fusion consisting of sensor like thermistor, thermocouple, and resistance temperature detector. Output from all these sensors are converted to a common representation format using radiometric normalization. Pau's framework is used for implementing the task of fusion in the proposed paper. Implemented laboratory model is tested for functionality using extensive set of data. Output shows that the proposed technique was able to produce improved linear and sensitive output as compared to system with individual sensor. Root mean square of percentage error obtained for tests conducted is about 0.86%, which is a significant improvement.