During post-silicon validation and debug, manufactured integrated circuits (ICs) are tested in actual system environments to detect and fix design flaws (bugs). Existing techniques are costly due to ad hoc, manual methods.
The Foundational QED embodies a set of source code files for performing the basic EDDI, CFCSS, and CFTSS QED transformations for creating tests with extremely short error detection latencies and high error detection coverage.
Stanford researchers in The Tang Group have developed a reproducible, high throughput device that dices tissue into uniformly sized sub-millimeter sample fragments.
Chimeric antigen receptor (CAR) T-cells targeting CD19 (or CAR19 T-cells) are an emerging, active therapy for patients with lymphomas. Despite high response rates to therapy, most patients will ultimately have disease progression after CAR19 T-cell therapy.
Stanford engineers have prototyped and tested a flexible, soft growing robot that can deploy sensor networks for investigation in constrained spaces (see video below). Existing sensors for growing robots have focused on moving with the tip of the robot.
Stanford inventors have discovered that applying a hydrogel containing an inhibitor of mechanotransduction pathways on top of a skin graft reduces scarring and promotes healing after repair of traumatic injuries like severe burn wounds.
A common hurdle for many drug delivery applications is getting the desired compounds to the targeted cells or receptors. Additional barriers of achieving the therapeutic drug concentration and necessary drug diffusion are also present even after successful targeted delivery.
Researchers at Stanford have developed an approach to dramatically improve the efficiency of microwave-to-optical quantum transduction – a significant step towards realizing efficient communication between distant superconducting quantum systems.
Image sensors are used across the board in high-resolution image sensing technologies, and critically rely on their ability to separate colors of light.
Remotely operated robotic devices are becoming increasingly important in fields such as medicine, space and field research. However, their widespread application is hampered by distance between the robot and its operator which results in communication delays.
Researchers at the Stanford Robotics Lab have developed new methods for modeling multi-contact collisions and steady physical interactions between multiple rigid bodies.
Near-infrared (NIR) imaging is a valuable research tool that produces quality images with high spatial and temporal resolution through millimeter tissue depths.