Materials Discovery
PulseAugur coverage of Materials Discovery — every cluster mentioning Materials Discovery across labs, papers, and developer communities, ranked by signal.
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AI materials discovery hindered by unreliable literature data
A new paper published on arXiv highlights significant issues with using scientific literature data to train AI models for materials discovery. Researchers found that data derived from literature often contains inconsist…
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Active learning refines Bayesian optimization for faster materials discovery
Researchers have developed a new framework that combines active learning with multi-objective Bayesian optimization to improve the efficiency of materials discovery. This approach refines the design space by adaptively …
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AI revolutionizes nanoparticle electron microscopy for scientific inference
A new review paper details the significant advancements of artificial intelligence (AI) in nanoparticle electron microscopy. The paper highlights how AI, particularly machine learning and deep learning techniques, is ev…
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Google DeepMind essay frames AI as a new scientific instrument
A recent essay from Google DeepMind posits that AI is evolving into a new scientific instrument, akin to the telescope or microscope. This perspective is supported by AI's recent successes in complex domains such as pro…
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AI methods bridge gap in materials discovery for chemical disorder
A new review paper addresses the challenge of representing chemical disorder in materials for AI-driven discovery. It highlights the gap between experimental observations of disorder and the fully specified configuratio…
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AI framework learns crystal concepts for novel materials discovery
Researchers have developed a new framework for generating novel crystal structures by learning and recombining reusable concepts. This approach uses a vector-quantized variational autoencoder to discover interpretable c…