Molecular machine learning (ML) underpins critical workflows in drug discovery, material science, and catalyst optimization by rapidly predicting molecular interactions and properties. For instance, ...

Understanding what complex chemical measurements reveal about materials and reactions can take weeks or months of analysis. But now, an AI-powered platform developed by researchers at the Department ...

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 ...

A web application for use by experimental chemists created by us. Uploading a file calculated with commercially available software, and the electronic state can be analyzed. We are working on creating ...

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 ...

A new trick for modeling molecules with quantum accuracy takes a step toward revealing the equation at the center of a popular simulation approach, which is used in fundamental chemistry and materials ...

New forms of fentanyl are created every day. For law enforcement, that poses a challenge: How do you identify a chemical you've never seen before? Researchers at Lawrence Livermore National Laboratory ...

Chemical engineering researchers have a powerful new tool at their disposal: active machine learning. In a recent perspective article published in Engineering, Kevin M. Van Geem’s research team at ...

The Chemical Sciences Roundtable (CSR) explores cutting-edge topics to inform and advance the fields of chemistry and chemical engineering. We foster collaboration among experts from government, ...