The monitoring of certain gases is crucial for obtaining Air quality indicators promoting the environmental monitoring. The detection of greenhouse gases (GHG) is especially on the forefront of heath related issues, also dictated by ambitious climate worldwide accords. Currently used spectroscopic solutions remain coslty and bulky, limiting their widespread adoption. We present a study of a MID-IR spectroscopy system developed on a silicon photonics platform, utilizing a Bragg grating mirror cavity, between an optical Bragg source and grating mirror.
The integration of atomically thin materials into semiconductor and photonic foundries is crucial for their use in commercial devices. However, current integration approaches are not compatible with industrial processing on wafer level, which is one of the bottlenecks hindering the breakthrough of 2D materials. Here, we present a generic methodology for the large-area transfer of 2D materials and their heterostructures by adhesive wafer bonding for use at the back end of the line (BEOL). Our approach exclusively uses processes and materials readily available in most largescale semiconductor manufacturing lines. Experimentally, we demonstrated the transfer of CVD graphene from Cu foils to 100-mm-diameter silicon wafers, the stacking of two monolayers of graphene to 2-layer graphene, and the formation of MoS2/graphene heterostructures by two consecutive transfers. We expect that our methodology is an important step towards the commercial use of 2D materials for a wide range of applications in optics and photonics.
In this paper key challenges posed on metrology by feature dimensions of 20nm and below are discussed. In detail, the need for software-based tools for SEM image acquisition and image analysis in environments where CD-SEMs are not available and/or not flexible enough to cover all inspection tasks is outlined. These environments include research at universities as well as industrial R and D environments focused on non-IC applications. The benefits of combining automated image acquisition and analysis with computational techniques to simulate image generation in a conventional analytical SEM with respect to the overall reliability, precision and speed of inspection will be demonstrated using real-life inspection tasks as demonstrators.
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