Accelerating the discovery of new molecules and materials, as well as develo** green
and sustainable ways to synthesize them, will help to address global challenges in energy …

Self-driving laboratories (SDLs) promise an accelerated application of the scientific method.
Through the automation of experimental workflows, along with autonomous experimental …

Exceptional molecules and materials with one or more extraordinary properties are both
technologically valuable and fundamentally interesting, because they often involve new …

The physical sciences community is increasingly taking advantage of the possibilities
offered by modern data science to solve problems in experimental chemistry and potentially …

The ability to integrate resources and share knowledge across organisations empowers
scientists to expedite the scientific discovery process. This is especially crucial in addressing …

Contemporary materials discovery requires intricate sequences of synthesis, formulation,
and characterization that often span multiple locations with specialized expertise or …

The urgency of finding solutions to global energy, sustainability, and healthcare challenges
has motivated rethinking of the conventional chemistry and material science workflows. Self …

Advancements in artificial intelligence (AI) for science are continually expanding the value
proposition for automation in materials and chemistry experiments. The advent of …

The vastness of the materials design space makes it impractical to explore using traditional
brute-force methods, particularly in reticular chemistry. However, machine learning has …

Web ontologies are important tools in modern scientific research because they provide a
standardized way to represent and manage web-scale amounts of complex data. In …