‘Artificial Chemist’ Combines AI, Robotics to Conduct Autonomous R&D

Researchers have developed a technology called “Artificial Chemist,” which incorporates artificial intelligence and an automated system for performing chemical reactions to accelerate R&D and manufacturing of commercially desirable materials.

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Scientists Aim Gene-Targeting Breakthrough Against COVID-19

Scientists at Berkeley Lab and Stanford have joined forces to aim a gene-targeting, antiviral agent called PAC-MAN against COVID-19.

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Making a Material World Better, Faster Now: Q&A With Materials Project Director Kristin Persson

Berkeley Lab’s Kristin Persson shares her thoughts on what inspired her to launch the Materials Project online database, the future of materials research and machine learning, and how she found her own way into a STEM career.

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Uranium, thorium debut in dual aromatic-antiaromatic molecule

Aromaticity and antiaromaticity are important concepts in organic chemistry, helping to define and explain how molecules vary in their stability and reactivity. Researchers previously identified these concepts together in organic biphenylenes. Now, new research has created metallic biphenylenes that incorporate uranium and thorium.

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Scientists learn how to make oxygen “perform” for them

Chemists have figured out how to keep “the wave” of one particular isotope of oxygen – among the most abundant elements on the planet and a crucial building block for materials like glass and ceramics – going during nuclear magnetic resonance spectroscopy long enough to learn some things about its structure and function.

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Machine-Learning Analysis of X-ray Data Picks Out Key Catalytic Properties

Scientists seeking to design new catalysts to convert carbon dioxide (CO2) to methane have used a novel artificial intelligence (AI) approach to identify key catalytic properties. By using this method to track the size, structure, and chemistry of catalytic particles under real reaction conditions, the scientists can identify which properties correspond to the best catalytic performance, and then use that information to guide the design of more efficient catalysts.

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