Korea University researchers have developed a machine-learning framework that predicts solar cell efficiency from wafer quality, enabling early wafer screening and optimized production paths. Using ...
By applying new methods of machine learning to quantum chemistry research, Heidelberg University scientists have made significant strides in computational chemistry. They have achieved a major ...
Microelectromechanical systems (MEMS) electrothermal actuators are widely used in applications ranging from micro-optics and microfluidics to nanomaterial testing, thanks to their compact size and ...
In the first instalment of LCGC International's interview series exploring how artificial intelligence (AI)/machine learning ...
Orbital-free approach enables precise, stable, and physically meaningful calculation of molecular energies and electron ...
The framework predicts how proteins will function with several interacting mutations and finds combinations that work well ...
MarketMuse offers standard and unique SEO optimization tools, making it an excellent service for all your optimization needs, ...
A machine-learning loop searched 14 million battery cathode compositions and found fivefold performance gains across four metrics using fewer than 200 experiments.
ADM, Evolving Systems’ big data platform, securely stores and analyzes massive telecom data, from billing to network reports, providing the foundation for AIQ’s predictive insights. Together, ADM and ...
COLUMBUS, MD, UNITED STATES, January 27, 2026 /EINPresswire.com/ -- Prem Kireet Chowdary Nimmalapudi, an AI engineer, ...
From predictive maintenance to training, digital twins are becoming a core platform for operational efficiency in these sectors.
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