Today's energy-intensive processes are looking to artificial intelligence (AI) technologies, including machine learning (ML), to help deliver smart automation capabilities needed to decrease machine ...

Recent advancements in machine learning have substantially transformed the optimisation of the steelmaking process. Traditional methods, often limited by complex thermodynamic interactions and ...

In recent years, the integration of machine learning and robotics technologies in chemical analysis has transformed the landscape of scientific research and industry practices. This revolution is not ...

This presentation will focus on how machine learning is assisting in solving process chemistry challenges. Multiple use-cases will be presented, along with an overview of emerging techniques. The ...

Researchers have used machine learning to create a model that simulates reactive processes in organic materials and conditions. Researchers from Carnegie Mellon University and Los Alamos National ...

The drug development pipeline is a costly and lengthy process. Identifying high-quality "hit" compounds-those with high potency, selectivity, and favorable metabolic properties-at the earliest stages ...

(Nanowerk News) Researchers from Carnegie Mellon University and Los Alamos National Laboratory have used machine learning to create a model that can simulate reactive processes in a diverse set of ...