Bayesian active learning with SSCHA predicts phase transitions in materials like CsPbI3 using only 50-256 first-principles calculations.
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A new NMF variant estimates integer and non-integer temporal shifts plus stretching in the frequency domain to improve brain tissue delineation in emission tomography data.
An ontology-aligned framework for atomistic simulations that integrates over 750,000 triples to enable interoperable data querying and automated provenance tracking.
Derives corrected orbital magnetic moment matrix elements for non-degenerate Bloch states including Berry connection contributions and shows reduced orbital Hall conductivity in bilayer TMDC and graphene systems.
A backward-mapping framework with chemical-genome descriptors and ML reduces 13,088 compositions to seven DFT-validated lead-free double perovskite candidates with phase stability and functional electronic properties.
Synthesis of (Cr,Mo,Ta,V,W)C high-entropy carbides yields thermal conductivity rising from 7 to 12 W/mK between room temperature and 200°C, electrical resistivity tunable by excess carbon from 137 to 120 μΩ·cm, and Vickers hardness of ~29 GPa.
An integrated IoT and CNN system detects cracks in additive manufacturing with 99.54% accuracy and supports predictive maintenance via digital twins.
Bayesian optimization automates the scientific discovery cycle by modeling observations with surrogate models and using acquisition functions to select experiments that balance known information with new exploration.
citing papers explorer
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Predicting challenging phase transitions with Bayesian active learning
Bayesian active learning with SSCHA predicts phase transitions in materials like CsPbI3 using only 50-256 first-principles calculations.
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Shift- and stretch-invariant non-negative matrix factorization with an application to brain tissue delineation in emission tomography data
A new NMF variant estimates integer and non-integer temporal shifts plus stretching in the frequency domain to improve brain tissue delineation in emission tomography data.
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Ontology-based knowledge graph infrastructure for interoperable atomistic simulation data
An ontology-aligned framework for atomistic simulations that integrates over 750,000 triples to enable interoperable data querying and automated provenance tracking.
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Orbital Hall effect from orbital magnetic moments of Bloch states: the role of a new correction term
Derives corrected orbital magnetic moment matrix elements for non-degenerate Bloch states including Berry connection contributions and shows reduced orbital Hall conductivity in bilayer TMDC and graphene systems.
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Backward Mapping from Device Targets to Chemical Genomes for Interpretable Discovery of Phase-Stable Lead-Free Double Perovskites with DFT-Validated Design Rules
A backward-mapping framework with chemical-genome descriptors and ML reduces 13,088 compositions to seven DFT-validated lead-free double perovskite candidates with phase stability and functional electronic properties.
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Thermal and Electrical Properties of (Cr,Mo,Ta,V,W)C High-Entropy Carbide Ceramics
Synthesis of (Cr,Mo,Ta,V,W)C high-entropy carbides yields thermal conductivity rising from 7 to 12 W/mK between room temperature and 200°C, electrical resistivity tunable by excess carbon from 137 to 120 μΩ·cm, and Vickers hardness of ~29 GPa.
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IoT-Enhanced CNN-Based Labelled Crack Detection for Additive Manufacturing Image Annotation in Industry 4.0
An integrated IoT and CNN system detects cracks in additive manufacturing with 99.54% accuracy and supports predictive maintenance via digital twins.
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Efficient and Principled Scientific Discovery through Bayesian Optimization: A Tutorial
Bayesian optimization automates the scientific discovery cycle by modeling observations with surrogate models and using acquisition functions to select experiments that balance known information with new exploration.