Electrocatalysts and photocatalysts are key to a sustainable future, generating clean fuels,
reducing the impact of global warming, and providing solutions to environmental pollution …

Using sunlight to power CO2 conversion into value-added chemicals and fuels is a
promising technology to use anthropogenic CO2 emissions for alleviating our dependence …

Deep learning (DL) is one of the fastest-growing topics in materials data science, with
rapidly emerging applications spanning atomistic, image-based, spectral, and textual data …

Materials for extreme environments can help to protect people, structures and the planet.
Extreme temperatures in aeroplane engines, hypervelocity micrometeoroid impacts on …

Closed-loop, autonomous experimentation enables accelerated and material-efficient
exploration of large reaction spaces without the need for user intervention. However …

A closed-loop, autonomous molecular discovery platform driven by integrated machine
learning tools was developed to accelerate the design of molecules with desired properties …

Breakthroughs in molecular and materials discovery require meaningful outliers to be
identified in existing trends. As knowledge accumulates, the inherent bias of human intuition …

Over the past few years, the adoption of machine learning (ML) techniques has rapidly
expanded across many fields of research including formulation science. At the same time …

In the last five years, there has been tremendous growth in machine learning and artificial
intelligence as applied to polymer science. Here, we highlight the unique challenges …

For many decades, experimental solid mechanics has played a crucial role in characterizing
and understanding the mechanical properties of natural and novel artificial materials …