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Rayence, a specialist in digital X-ray components and materials, recently presented a paper at the International Solid-State Circuits Conference (ISSCC) 2023, the world’s leading semiconductor conference, successfully applying the ‘SPAD-GS’ technology to 3D detectors. The technology enables the development of 3D detectors that are at least 2.5 times more sensitive and 4 times faster in acquisition speed than existing detectors of the same class.
The ‘SPAD-GS (Global Shutter)’ technology is the next-generation 3D detector technology that provides optimal image quality even in low-dose/high-speed driven environments. The ‘SPAD’ device amplifies photons (particles of light) to recognize very small levels of photons as if many photons have entered. By applying ‘SPAD’ digital pixels to detectors, X-ray images can be acquired even in extreme low-dose environments, and the detection speed is significantly increased. The ‘SPAD’ device is a next-generation semiconductor technology that is being used in 3D image sensors (LiDAR) for autonomous driving, smartphones, drones, robots, and more. Rayence is the first to successfully introduce ‘SPAD’ digital pixels to X-ray detectors.
In addition, Rayence has applied GS technology, which captures high-quality images by eliminating motion blur when the object moves quickly. Rayence has minimized the degradation of image quality caused by object motion by combining ‘GS’ technology with the fast response speed of ‘SPAD’. In addition, Rayence has demonstrated its high technological capabilities by overcoming major obstacles to the application of ‘SPAD-GS’ technology, such as low robustness (resistance to X-rays), high power consumption, and image distortion.
Rayence’s next-generation 3D detector technology is expected to attract attention in fields where X-ray imaging results need to be utilized as ultra-fast 3D images. The technology could be implemented in battery and electronic component testing as well as aerospace and nuclear component inspection markets, where inspection time for images can impact production costs.
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