Biomaterial– tag –
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AI Materials Discovery Faces New Bottleneck in ‘Verification’: Only 0.2% of DeepMind GNoME Predictions Experimentally Validated
AI Invasion USA Overview While AI has effectively solved the 'generation problem' in protein structure prediction (AlphaFold) and material candidate discovery (GNoME), 'verification' has emerged as the new bottleneck. Only approximately ... -
Geometry-Guided Model CDSM Achieves DFT-Comparable Accuracy in Collagen Structure Prediction, Cutting Computational Cost by 400-790x
bioRxiv USA Overview CDSM (Empirical Geometry-Guided Model) enables robust, high-throughput collagen structure prediction by explicitly encoding empirical geometric constraints. The model significantly compresses the structure-prediction... -
AI Revolutionizes Biomaterial Design for Tissue Engineering, Overcoming Empirical Limitations in Property Prediction, Inverse Design, and Manufacturing Optimization
IntechOpen Croatia Overview This comprehensive review highlights AI's transformative applications in biomaterial design for tissue engineering, encompassing machine learning, deep learning, and generative models. AI provides data-driven ... -
arXiv: New ML Potential ‘TWIN’ Achieves Ab Initio Accuracy and Transferability in Biomolecular Simulations
arXiv Global Overview A new arXiv preprint introduces TWIN (Transferable Water Implicit Network), a highly transferable implicit solvent machine-learning potential (MLP) for biomolecular systems. TWIN, trained solely on ab initio and exp... -
IntuitionLabs Compares AlphaFold 3 and ESM3, Highlighting Evolution of AI Biology Foundation Models and Generative Diffusion Superiority
IntuitionLabs Unknown Overview An IntuitionLabs analysis provides a detailed comparison of leading AI biology foundation models like AlphaFold 3 and ESM3. The article focuses on models such as AlphaFold 3, a generative diffusion model fo... -
arXiv Paper: SciReasoner Boosts Multi-Modal Structural Reasoning for Proteins, Molecules, and Crystals with Enhanced Accuracy
arXiv International Overview SciReasoner has been introduced as an innovative multi-modal scientific foundation model enabling structural reasoning for proteins, molecules, and crystals. By discretizing structural elements into a unified... -
Machine Learning Designs Biomedical High-Entropy Alloys for Additive Manufacturing, Selecting Optimal Zr Alloys from 15 Million Compositions
Taylor & Francis Group - Figshare International Overview A machine learning framework has been successfully introduced and validated for designing biomedical high-entropy alloys (BioHEAs) for additive manufacturing (AM), identifying opti... -
Materials Informatics and ML Clustering Accelerate Data-Driven Discovery of Calcium Phosphate Biomaterial Scaffolds
Indonesian Applied Physics Letters (e-Journal UNAIR) Indiaネシア Overview A recent study published in Indonesian Applied Physics Letters demonstrates a novel data-driven approach for discovering calcium phosphate biomaterial scaffolds, i... -
Apoha Raises $36 Million to Scale AI Platform for Designing Proteins, Food Ingredients, and Novel Materials
PPTI News USA Overview AI startup Apoha successfully secured $36 million in funding to expand its AI platform for designing proteins, food ingredients, and new materials. Its 'Liquid State Intelligence' generates data from materials' beh... -
bioRxiv: ORIGAMI, an Orientation-Aware GNN, Developed for Assessing Multimeric Interfaces of Protein Complex Structures
bioRxiv Unknown Overview A study published on bioRxiv introduces "ORIGAMI," an orientation-aware graph neural network (GNN) for evaluating multimeric interfaces of protein complex structures. ORIGAMI innovatively utilizes both scalar and...
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