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The superconducting nanowire single-photon detector (SNSPD or SSPD) is a type of optical and near-infrared single-photon detector based on a current-biased superconducting nanowire. [1] It was first developed by scientists at Moscow State Pedagogical University and at the University of Rochester in 2001.
Schematic of silicon nanowire. Silicon nanowires, also referred to as SiNWs, are a type of semiconductor nanowire most often formed from a silicon precursor by etching of a solid or through catalyzed growth from a vapor or liquid phase. Such nanowires have promising applications in lithium-ion batteries, thermoelectrics and sensors.
The first digital camera to use a Foveon X3 sensor was the Sigma SD9, a digital SLR launched in 2002. [5] It used a 20.7 × 13.8 mm, 2268 x 1512 × 3 (3.54 × 3 MP) iteration of the sensor and was built on a Sigma-designed body using the Sigma SA mount.
Nanowire lasers can be grown site-selectively on Si/SOI wafers with conventional MBE techniques, allowing for pristine structural quality without defects. Nanowire lasers using the group-III nitride and ZnO materials systems have been demonstrated to emit in the visible and ultraviolet, however infrared at the 1.3–1.55 μm is important for telecommunication bands. [3]
Corn-like nanowire is a one-dimensional nanowire with interconnected nanoparticles on the surface, providing a large percentage of reactive facets. TiO 2 corn-like nanowires were first prepared by a surface modification concept using surface tension stress mechanism through a two consecutive hydrothermal operation, and showed an increase of 12% ...
Piezoelectric sensors either convert mechanical force into electric force or vice versa. This force is then transduced into a signal. MIP spectroscopic sensors can be divided into three subcategories, which are chemiluminescent sensors, surface plasmon resonance sensors, and fluorescence sensors. As the name suggests, these sensors produce ...
The specificity and sensitivity can be controlled by the appropriate choice of materials and their interaction with the analytes, that can achieve even label-free sensors. [11] The concentration of chemical species in vapor or liquid phases as well as in more complex mixtures can be determined with high confidence. [12] [13]
Visual sensor networks are most useful in applications involving area surveillance, tracking, and environmental monitoring.Of particular use in surveillance applications is the ability to perform a dense 3D reconstruction of a scene and storing data over a period of time, so that operators can view events as they unfold over any period of time (including the current moment) from any arbitrary ...