Materials Informatics– tag –
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AI to Accelerate Energy Materials Discovery: NUS Announces 2026 Workshop
National University of Singapore (NUS) Singapore Overview The National University of Singapore (NUS) will host an "AI for Energy Materials" workshop on July 10, 2026, co-located with the Solid State Ionics Conference 2026. Bringing toget... -
Materials Informatics Weekly Report June 27, 2026
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Orbital Industries, ‘AlphaFold for Materials Science,’ Raises $50M, Bringing Total Funding to $71M
Resilience Media USA Overview Orbital Industries, a deep tech startup dubbed 'AlphaFold for materials science,' has raised an additional $50 million, bringing its total funding to $71 million. The company focuses on industrial tech hardw... -
Institute of Science Tokyo Dramatically Enhances Material Prediction Interpretability with ALIGNN and Clustering AI, Precisely Forecasting Optical Absorption Spectra
Lab Manager Japan Overview Researchers at the Institute of Science Tokyo have developed a novel method combining a graph neural network (ALIGNN) with hierarchical clustering to significantly improve the interpretability of AI-driven mate... -
CVC Analyzes 8 Leading AI Material Development Companies: Investment Strategies and Public Market Proxies Explored
note Japan Overview From a Corporate Venture Capital (CVC) perspective, eight key AI material development companies—Cusp AI, DeepMind, Microsoft, Orbital, Matlantis, Citrine Informatics, Aionics, and Kebotix—have been analyzed. This arti... -
Materials Informatics Weekly Report May 20, 2026
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Purdue University Seeks Postdoctoral Researchers in Computational Materials Design and Materials Informatics, Bolstering DFT and MLIPs Research
ApplyKite USA Overview Purdue University has announced a postdoctoral researcher opening in computational materials design and materials informatics. This strategic hire targets researchers with strong expertise in atomistic simulation m... -
Unlocking AI’s ‘Why’: Visualizing Prediction Rationale for Rapid Materials Discovery
不明 Japan Overview Researchers from Science Tokyo and Tohoku University have developed a novel interpretable AI (XAI) method that demystifies how AI models predict material properties. This breakthrough technique visualizes the intricat... -
Materials Informatics Weekly Report May 13, 2026
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Materials Informatics Weekly Report May 7, 2026
📄 Weekly Report June 07, 2026 (PDF) — Download Weekly Report June 07, 2026 (PDF) — DownloadDownload 🎙 Podcast June 07, 2026 (MP3) — Play & Download MaterialsInformaticsEnglishPodcast_20260607.mp3Download View Past Weekly Reports→
