Whether you are an aspiring Chemistry student or just a normal know-it-all geek, the Periodic Table offers you the simplest way to keep tabs on the atomic elements and their chemical properties. And ...

The ACS Green Chemistry Institute and Beyond Benign have partnered together to launch the Green Chemistry Teaching and Learning Community (GCTLC). Established in 2023, GCTLC is a new online community ...

Six popular machine learning models. (a) Decision tree; (b) feedforward neural network (Trans: transformation; Activ Func: activation functions); (c) convolution neural network (Conv: convolution; ...

As the COVID-19 pandemic dies down, its effects will echo throughout the STEM field. Physics and chemistry students will be faced with new challenges and opportunities. Students will need to embrace ...

As the threat of COVID-19, the disease caused by the novel coronavirus, became apparent in early March, US universities and colleges rushed to implement contingency plans that protected their students ...

Machine learning-based neural network potentials often cannot describe long-range interactions. Here the authors present an approach for building neural network potentials that can describe the ...

Foundations in Chemistry: Chemistry is conveniently divided into several widely recognized subfields. The chemistry major at Willamette University requires all students to take courses in analytical ...

In the production of chemical compounds, the success of each individual reaction depends on numerous parameters. It is not always possible, even for experienced chemists, to predict whether a reaction ...

A chemist’s impact extends far beyond the lab. With an advanced degree in chemistry, you’ll be a problem-solver. You’ll make a meaningful impact on people and places around the world by ...

Undergraduate learning assistants are now helping first-year students in University of Iowa chemistry courses — some of the most notoriously difficult classes on campus. UI chemistry professor Adam ...

Computational chemistry methods with an optimal balance between predictive accuracy and computational cost hold major promise for accelerating the discovery of new molecules and materials. We at ...