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 ...

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 ...

Catalysts play an indispensable role in modern manufacturing. More than 80% of all manufactured products, from pharmaceuticals to plastics, rely on catalytic processes at some stage of production.

The world is awash with news about artificial intelligence tools, including those intended to help chemists. But are the tools useful, a threat, or even worth the attention? It’s hard to know, ...

The 2024 Nobel Prize in chemistry recognized Demis Hassabis, John Jumper, and David Baker for using machine learning to tackle one of biology’s biggest challenges: predicting the 3D shape of proteins ...

Forbes contributors publish independent expert analyses and insights. Writes about the future of finance and technology, follow for more. We live in a world where machines can understand speech, ...

Electron density prediction for a four-million-atom aluminum system using machine learning, deemed to be infeasible using traditional DFT method. × Researchers from Michigan Tech and the University of ...

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, ...

In an interview with Technology Networks, Dr. Daniel Reker discusses how machine learning is improving data-scarce areas of drug discovery.

Data science and machine learning technologies have long been important for data analytics tasks and predictive analytical software. But with the wave of artificial intelligence and generative AI ...