VOXTEL, INC.

AlInAsSb multistage APDs will be designed to achieve avalanche gain up to M = 1024, and excess noise of k < 0.02. The APD structure will be based on a staircase APD architecture, where composition and ...

To enable small drones to navigate by natural nighttime skyglow, Voxtel is developing an ultra-low-leakage, 9-m-pitch, 1080p-format InGaAs photodiode array for compact, lightweight low-light (LL) shor ...

A high-sensitivity, narrow-field-of-view ladar receiver, optimized for long-range target detection and identification will be developed, characterized, and demonstrated.In Phase I avalanche photodetec ...

Voxtel proposes to develop, characterize, and demonstrate a coherent-ladar optimized readout integrated circuit (ROIC) consisting of 40-micron pixel elements, including circuits designed for snapshot- ...

Today, dismounted squad-level units do not have the capability to hand off targets during the day and at night, covertly and rapidly, and between squad members and supporting vehicles. To address this ...

Low‐cost, power‐efficient, time‐resolved imaging is increasingly important for Department of Energy remote‐sensing operations. Today’s remote‐sensing operations use photocathode‐based te ...

Future optical systems for NASA's low-cost missions such as CubeSat and other small-scale payloads are constrained by the traditional spherical form of optics. As such, there is a movement away from t ...

A lander mission to Europa?Europa clipper mission?is planned to launch in the mid-2020s by NASA JPL. The mission presents multiple challenges, such as: ubiquitous presence of hazards at all scales, i ...

To meet the U.S. military need for a near-single-photon low-light-level passive imager, a large-format, near-infrared (NIR)-sensitive silicon single-photon avalanche-diode (SPAD) digital imager capabl ...

To address the need for 1-m^2, scaled, cost-effective hogel optics, scalable inkjet-print additive manufacturing of three-dimensional freeform gradient-index nanocomposite hogel optics will be demonst ...