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.
Scientists at Berkeley Lab and Stanford have joined forces to aim a gene-targeting, antiviral agent called PAC-MAN against COVID-19.
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.
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.
Bone and mollusk shells are composite systems that combine living cells and inorganic components. This allows them to regenerate and change structure while also being very strong and durable. Borrowing from this amazing complexity, researchers have been exploring a new class of materials called engineered living materials (ELMs).
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.
Lanthanum strontium manganite (LSMO) is a widely applicable material, from magnetic tunnel junctions to solid oxide fuel cells. However, when it gets thin, its behavior changes for the worse. The reason why was not known. Now, using two theoretical methods, a team determined what happens.
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.