A team of Lehigh University researchers has successfully predicted abnormal grain growth in simulated polycrystalline materials for the first time—a development that could lead to the creation of ...

If material design does not adequately account for ... and actual experimental synthesis success rates. While machine learning models have been developed to address this issue, they have primarily ...

Researchers have developed a machine-learning workflow to optimize the output force of photo-actuated organic crystals. Using ...

In the digital era, Puneet Gupta, a seasoned expert in semiconductor design, presents an innovative approach to resolving hold time violations in advanced System-on-Chip (SoC) designs. His research ...

Intelligent nanophotonics, combining nanophotonics and machine learning, is transforming optical information processing. This ...

The construction industry has always faced challenges like delays, cost overruns, and resource management issues. Civil Engineers in Henderson are now leveraging Machine Learning in Construction to ...

A new multimodal tool combines a large language model with powerful graph-based AI models to efficiently find new, synthesizable molecules with desired properties, based on a user's queries in plain ...

From cell phones to solar panels to quantum computers, thin films are essential to current and emerging technologies. But making functional thin films requires control. During hours-long processes, ...

The polarization response of macrophages seeded on titanium materials is influenced by multiple factors, and artificial intelligence can assist in extracting the key features of implant materials for ...