Hosted on MSN1mon
Machine learning method improves semiconductor band gap predictionsThat's the kind of technology that researchers at Kyoto University have developed for the band gap of semiconductor materials. The work is published in the journal Computational Materials Science.
Techniques for Band Gap Engineering vary, including doping, the introduction of impurities into a semiconductor to alter its electrical properties; strain engineering, where stress is applied to ...
Graphyne is a crystalline form of carbon that is distinct from both diamond and graphite. Unlike diamond, where each atom ...
The researchers embedded nanodots made of a 2D material called molybdenum diselenide inside another 2D material, tungsten ...
US President Donald J. Trump's threat to defund the CHIPS Act and impose tariffs could hurt small tech start-ups by limiting ...
New research from materials scientist Chris Van de Walle illuminates the path to superior electro-optic performance in ...
Silicon carbide (SiC) semiconductors are just such a technology, and have already begun to revolutionise the industry. A graph showing the relationship between band gap and temperature for various ...
In semiconductors, valence electrons occupy energy bands, with the valence band (lower energy) and the conduction band (higher energy) separated by an energy gap. Electrons in lower energy levels can ...
However, this would only be possible by using wide-band-gap semiconductors, which have not been considered for solar cells used for land-based applications because their band gaps are too large.
Power semiconductors are categorized into different product families, including power MOSETs, IGBTs, GaN power devices and SiC MOSFETs. There are many other power device families. Gallium oxide has a ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results