Stanford University researchers created an inverse design codebase called SPINS that can help researchers explore different design methodologies to find fabricable optical and nanophotonic structures.
Nowadays, artificial neural networks have an impact on many areas of our day-to-day lives. They are used for a wide variety of complex tasks, such as driving cars, performing speech recognition (for example, Siri, Cortana, ...
Ever wish your computer could think like you do or perhaps even understand you?
A team of researchers has developed a new technique to map the three-dimensional forces that clusters of human cells exert on their surrounding environment. The method could potentially help scientists better understand how ...
Organic-inorganic halide perovskite quantum dots (PQDs) form an attractive class of materials for optoelectronic applications. Their charge transport properties are, however, inferior compared to materials such as graphene. ...
As machine learning continues to surpass human performance in a growing number of tasks, scientists at Skoltech have applied deep learning to reconstruct quantum properties of optical systems.
An international team of scientists, including physicists from the University of Luxembourg, have reported a comprehensive view-point on how machine learning approaches can be used in Nanoscience to analyze and extract new ...
University of Wisconsin–Madison researchers have developed a computational tool that can accurately predict the three-dimensional interactions between regions of human chromosomes.
Researchers at the University of Waterloo have developed a method that could pave the way to establishing universal standards for measuring the performance of quantum computers.
In a new report on Science Advances, Hui Kwon Kim and interdisciplinary researchers at the departments of Pharmacology, Electrical and Computer Engineering, Medical Sciences, Nanomedicine and Bioinformatics in the Republic ...
