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 ...

The framework predicts how proteins will function with several interacting mutations and finds combinations that work well ...

A machine-learning loop searched 14 million battery cathode compositions and found fivefold performance gains across four metrics using fewer than 200 experiments.

Machine learning has rapidly become integral to the advancement of geoscience, a field inundated with complex and multivariate data from myriad sources such ...

A new study introduces a global probabilistic forecasting model that predicts when and where ionospheric disturbances—measured by the Rate of total electron content (TEC) Index (ROTI)—are likely to ...

A biomimetic synapse built from water droplets and biological ion channels achieves synaptic plasticity and performs machine learning tasks.

Multifidelity optimization can inform decision-making during process development and reduce the number of experiments ...

As the 3D content landscape continues to evolve and grow, these five trends will likely shape its trajectory in 2026.

Researchers at the University of Tuebingen, working with an international team, have developed an artificial intelligence that designs entirely new, sometimes unusual, experiments in quantum physics ...

As AI demand outpaces the availability of high-quality training data, synthetic data offers a path forward. We unpack how synthetic datasets help teams overcome data scarcity to build production-ready ...