Bayesian active learning with SSCHA predicts phase transitions in materials like CsPbI3 using only 50-256 first-principles calculations.
Applications of natural language processing and large language modelsinmaterialsdiscovery[J].NPJComputationalMaterials
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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.
Fine-tuning the MACE-MPA-0 foundation model on 5-10 60-atom DFT configurations reproduces the barocaloric phase transformation in ammonium sulfate, while training from scratch fails at these sizes.
ChargeBD constructs a 500-question ESS-LLM Benchmark from 50 RFB tasks and evaluates 16 MBTI-inspired persona agents on DeepSeek-V3-Plus to create capability and cognitive advantage matrices for guided battery engineering.
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.
A survey of generative crystal modeling, multimodal learning, and closed-loop inverse design pipelines for crystalline solids, including failure modes and evaluation practices.
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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.