Stanford researchers have designed and tested an electrochemical gas sensor which can detect volatile organic species in the gas phase and differentiate multiple species with a single chip.
Researchers at Stanford have developed, for the first time, a component analysis algorithm that does not require any assumption on the data structure or data generation process to find out the important components or trends in data.
Stanford researchers at the Camarillo Lab have developed a neural-network based model that can provide real-time calculation of brain strain based on instrumented mouthguard kinematics signals.
Researchers at Stanford have developed a distributed digital "black box" audit trail design for connected and automated vehicle data and software assurance.
Stanford researchers have developed a scanning mirror and method for Rhodonea (Rose) scanning patterns, which are superior to Lissajous patterns for almost all imaging and ranging applications.
Researchers in the Dionne group at Stanford have designed a nanoscale laser capable of self-isolated Raman Lasing, where lasing and isolation occurs within the same pumping mechanism.
The Murmann lab has developed a method for an extraction information from acoustic signals that utilizes low power consumption. N-path filters are used to decompose the original acoustic signals' waveform before downconverting to lower their Nyquist-rate bandwidth.
The Dionne lab has developed ultrathin and compact devices for electrically driven beamsteering that fit on a semiconductor chip. These devices rely on resonant dielectric nanostructured surfaces known as "high quality factor" (high-Q) metasurfaces.
Stanford researchers have developed a simple optical device for low-power, active light tuning. The device tunes the color of light across the visible spectrum and at select wavelengths by electrical biasing an array of micron sized pixels or nanowires.
Researchers in the Arbabian Lab have developed a system that uses a combination of radio frequency (RF) electromagnetic and ultrasound (US) waves to detect, localize, and identify multiple battery-free tags.
Stanford researchers at the Bao Research Group have patented a body area sensor network (bodyNET) that can be used to monitor human physiological signals for next-generation personalized healthcare.