The integration of machine learning techniques into microstructure design and the prediction of material properties has ushered in a transformative era for materials science. By leveraging advanced ...
Until now, designing complex metamaterials with specific mechanical properties required large and costly experimental and simulation datasets. The method enables ...
More aggressive feature scaling and increasingly complex transistor structures are driving a steady increase in process complexity, increasing the risk that a specified pattern may not be ...
Researchers from Imperial and its spinout company SOLVE Chemistry have presented a chemical dataset at the prestigious AI conference NeurIPS that could help accelerate the use of machine learning to ...
For decades, scientists have relied on structure to understand protein function. Tools like AlphaFold have revolutionized how researchers predict and design folded proteins, allowing for new ...
With climate change posing an unprecedented global challenge, the demand for environmentally friendly solvents in green chemical processes and carbon dioxide capture has surged. Ionic liquids (ILs) ...
In my previous blog, I reached out to this community of engineers to gauge the experiences and expectations you have regarding artificial intelligence (AI) at work. The feedback was interesting and ...
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