Progress in data-driven self-driving laboratories for solving materials grand challenges has
accelerated with the advent of machine learning, robotics, and automation, but they are …

Science, especially experimental science, has always depended on the careful capture of
plans, actions, raw and processed data and conclusions. With scientific research now so …

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Accelerating materials research by integrating automation with artificial intelligence is
increasingly recognized as a grand scientific challenge to discover and develop materials …

A two-way street to science's future | Nature Skip to main content Thank you for visiting
nature.com. You are using a browser version with limited support for CSS. To obtain the best …

This is a report on the early years of combinatorial materials science and technology. High-
throughput technologies (HTTs) are found in life-and materials-science laboratories …

Over the past decades, continual advancement of computational power has led to the
prevalence of automation across science, industry, and society, whereby digital solutions …

Before leveraging big data methods like machine learning and artificial intelligence (AI) in
chemistry, there is an imperative need for an affordable, universal digitization standard. This …

High-throughput experimentation (HTE) can be a powerful tool in chemical research, and
the large datasets it generates could play a role in applying machine-learning methods to …

Sustainable chemistry for renewable energy generation and green synthesis is a timely
research topic with the vision to provide present needs without compromising future …