August 2023 Issue of Electronic Device Failure Analysis, a quarterly publication providing a technical condensation of information of interest to electronic device failure analysis technicians, engineers, and managers.
Artificial neural networks are a key technology in the domain of AI and machine learning. Many applications need the rapid parallel processing of vast amounts of data—with correspondingly high energy demand. A new project in which physicist Dr. Andreas Tittl plays an important role, is seeking to develop an energy-saving alternative through a specially tailored combination of materials science and photonics.
Now an international team of scientists led by physicists at MIT reports a powerful new tool for quantifying — and controlling — a key parameter in moiré systems.
More efficient computing—potentially room temperature quantum computing—and recyclable rigid plastics are two projects to be undertaken by a new materials research science and engineering center at the University of Michigan.
Inspired by the hinge of bivalve Cristaria plicata, a research team from the University of Science and Technology of China (USTC) proposed their tactics to improve the fatigue resistance of structural materials.
