American Institute of Physics– tag –
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Predictive First-Principles Simulations and AI Accelerate Co-Design of Next-Gen Energy-Efficient AI Hardware
Applied Physics Letters | AIP Publishing USA Overview Predictive first-principles simulations are playing a crucial role in the co-design of next-generation energy-efficient AI system hardware. Machine learning-based material representat... -
Machine Learning Revolutionizes Magnetic Functional Alloy Design: Generative GNNs and High-Throughput DFT Discover 2D Magnets
AIP Advances USA Overview This article details recent advancements in the design of magnetic functional alloys (MFAs) leveraging machine learning (ML), highlighting how ML has contributed to the design of magnetocaloric, magnetostrictive... -
AIP Publishing Reveals New Vibrational Entropy Metric Dramatically Improves Empirical Interatomic Potential Accuracy by 80%, Revolutionizing MLIP Validation
AIP Publishing USA Overview A new study published by AIP Publishing introduces a novel method for developing and validating empirical interatomic potentials, achieving an 80% error reduction in dynamic properties compared to existing MOF... -
Lysozyme-PVA Composite Films Develop Flexible Piezoelectric Biosensors for Wearable Bio-Integrated Electronics
Applied Physics Letters | AIP Publishing USA Overview A novel flexible and biocompatible piezoelectric bio-composite film has been developed by integrating lysozyme (LSZ), a natural protein, into a polyvinyl alcohol (PVA) matrix. This ma... -
Ferroelectric ScAlN Epilayers Enable Ultrathin, Fully Strained GaN HEMTs for High-Performance 5G and Radar Systems with Suppressed Leakage
Applied Physics Letters (AIP Publishing) Unknown Overview Research in Applied Physics Letters demonstrates high-performance, fully strained GaN channel high electron mobility transistors (HEMTs) on AlN-on-sapphire templates, integrating ... -
Innovative Hexagonal Fins Boost Latent Heat Thermal Energy Storage System Efficiency by 13.25%, Aiding Electronic Component Thermal Management
AIP Publishing (Journal of Applied Physics) International Overview The use of innovative hexagonal fins has been proposed and numerically demonstrated to improve the efficiency of Phase Change Material (PCM)-based Latent Heat Thermal Ene... -
Josephson Junction Array Functions as Tunable Metamaterial: Microwave Resonances Controlled by Temperature and Power
Applied Physics Letters (AIP Publishing) USA Overview A study in "Applied Physics Letters" demonstrates an electrically isolated Josephson junction array, composed of ~30,000 coupled "meta-atoms," functions as a tunable metamaterial. Thi... -
Functional Classification and XGBoost Integration with 10,000+ Semiconductor/Insulator Data Significantly Boosts Electronic Bandgap Prediction Accuracy
AIP Publishing USA Overview This research systematically investigates how functional classification of electronic bandgaps in over 10,000 semiconductors and insulators significantly improves machine learning model accuracy. Utilizing a P... -
Scalable Isotropic Message Passing ML Accelerates Electronic Structure and Atomistic Property Modeling by Efficiently Describing Non-Local Effects
The Journal of Chemical Physics | AIP Publishing USA Overview A new study demonstrates a scalable machine learning approach for isotropic message passing, leveraging continuous products of external potentials to model electronic structur...
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