A technique could enable processing speeds a million to a billion times faster than today's computers and spur quantum computing progress.
Computational analysis to predict how optical properties of semiconductor materials change could speed the process of identifying and creating materials useful in quantum applications.
Bursts of superfluorescence that occurred at room temperature and regular intervals could lead to the development of faster microchips, neurosensors, or materials for use in quantum computing applications.
DP patterning provides flexible conductive pattern technology by leveraging PC-based control, EtherCAT, and artificial intelligence (AI) to meet high-precision machining requirements.
A smart chip that has transistors made out of molybdenum disulfide will be able to better protect someone's data with less battery drain.
Caltech researchers have developed an optical, rather than electronic, switch, which could aid efforts to achieve ultrafast all-optical signal processing and computing.
The intelligent battery pack can be made safer by using soft computing techniques to make process variables more reliable and consistent.
The Dragos 2021 Year In Review highlighted four key findings on: OT network visibility, poor security perimeters, external connections to the industrial control systems (ICS) environments, and separation of IT and OT user management.
Researchers at Duke University and the University of Maryland have used the frequency of measurements on a quantum computer to get a glimpse into the quantum computing phenomena of phase changes – something analogous to water turning to steam.
Texas A&M researchers are working on electronic design automation (EDA) technology with machine-learning techniques to keep pace with chip design complexity.