Explore Stanford technologies available for licensing:

Engineers in Prof. Fritz Prinz's laboratory have developed a low cost, scalable method to fabricate anti-reflective, highly conductive metal silicide nanowires electrodes for photovoltaic cells.

Stanford researchers at the Dahl Lab have developed a method to reduce artifacts in ultrasound image reconstruction using a trained convolutional neural network (CNN).

Engineers in Prof. Yi Cui's laboratory have developed a stretchable, stable, high energy density anode to be used in lithium ion batteries that power stretchable electronic devices (e.g., wearable electronics, bendable phones or flexible displays).

Researchers in Prof. Brian Feldman's laboratory have developed a patented drug screen to identify compounds that could potentially treat obesity and metabolic disease by converting cells to calorie-burning brown fat.

Stanford researchers have developed several research tools to help study the role of a novel gene in the developing endoderm of embryonic stem cells.

Stanford researchers in the SHAPE lab have patented a virtual reality, haptic device called 'Grabity' that simulates weight, stiffness, and torque.

Summary: Stanford researchers at the Melosh Lab have proposed a non-invasive, high electrode density, high resolution (100 micrometers to 10 nanometers) neural device implantation for electrical stimulation of neural/biological tissues.

Researchers at Stanford developed a method to improve both the efficiency and the performance of MRI optimal trajectory design.

Stanford researchers patented a method to design, computationally optimize and fabricate efficient optical devices using semiconducting and dielectric nanostructures.

Please see the issued US patent, below, for details.

Please see issued patent and publication, below, for details.

Researchers in Profs. Jonathan Fan and Jim Plummer's laboratory have patented a generalized, CMOS-compatible process to fabricate single crystal metal components on amorphous insulator substrates.

Stanford researchers have developed a method of assigning a “glucotype” to patients based on their temporal glycemic patterns. This algorithm classifies people with glycemic dysregulation through constant monitoring.

Researchers in Prof. Amin Arbabian's laboratory have developed a modular RF-Ultrasound architecture to download data, upload data or wirelessly charge devices implanted deep in the body.

These light trapping solar cell structures increase optical absorption and carrier collection, improving efficiency by 24%, while significantly reducing the solar cell active layer thickness and thus lowering cost.