Machine Learning-Based Optimization Of Chiral Photonic Nanostructures: Evolution- And Neural Network-Based Design


Chiral photonics opens new pathways to manipulate light-matter interactions and tailor the optical response of metasurfaces and -materials by nanostructuring nontrivial patterns. Chirality of matter, such as that of molecules, and light, which in the simplest case is given by the handedness of circular polarization, have attracted much attention for applications in chemistry, nanophotonics and ... » read more

UT Dallas: Electronic, Thermodynamic & Dielectric Properties of Two Novel vdW Materials


New technical paper titled "A First-Principles Study on the Electronic, Thermodynamic and Dielectric Properties of Monolayer Ca(OH)2 and Mg(OH)2," from University of Texas at Dallas. With funding support from National Science Foundation and U.S. Department of Defense,  Defense Threat Reduction Agency. Abstract "We perform first-principles calculations to explore the electronic, thermodynam... » read more

Power/Performance Bits: June 4


Flexible high-temp dielectric Researchers at Rice University, Georgia Institute of Technology, and Cornell University developed a new high-temperature dielectric nanocomposite for flexible electronics, energy storage, and electric devices that combines one-dimensional polymer nanofibers and two-dimensional boron nitride nanosheets. The polymer nanofibers act as a structural reinforcement, w... » read more

One Micron Damascene Redistribution for Fan-Out Wafer Level Packaging Using a Photosensitive Dielectric Material


Authors: Warren W. Flack, Robert Hsieh, Ha-Ai Nguyen Ultratech, a division of Veeco 3050 Zanker Road, San Jose, CA 95134 USA [email protected] John Slabbekoorn, Samuel Suhard, Andy Miller IMEC Kapeldreef 75 B-3001 Leuven, Belgium [email protected] Akito Hiro, Romain Ridremont JSR MICRO NV Technologielaan 8 B-3001 Leuven, Belgium [email protected] Abstract This... » read more

Using AI In Chip Manufacturing


David Fried, CTO at Coventor, a Lam Research Company, sat down with Semiconductor Engineering to talk about how AI and Big Data techniques will be used to improve yield and quality in chip manufacturing. What follows are excerpts of that conversation. SE: We used to think about manufacturing data in terms of outliers, but as tolerances become tighter at each new node that data may need to b... » read more