Results 181 to 190 of about 2,359,523 (296)

Limitations of Foundation Models in Energy Materials Simulations: A Case Study in Polyanion Sodium Cathode Materials

open access: yesAdvanced Intelligent Discovery, EarlyView.
Several simulation techniques are used to explore static and dynamic behavior in polyanion sodium cathode materials. The study reveals that universal machine learning interatomic potentials (MLIPs) struggle with system‐specific chemistry, emphasizing the need for tailored datasets.
Martin Hoffmann Petersen   +5 more
wiley   +1 more source

Reconstruction of Deep Partial-Thickness Burns With Ovine Forestomach Matrix: Results From a Prospective Observational Study. [PDF]

open access: yesCureus
Kennedy PJ   +10 more
europepmc   +1 more source

Deep Learning‐Assisted Coherent Raman Scattering Microscopy

open access: yesAdvanced Intelligent Discovery, EarlyView.
The analytical capabilities of coherent Raman scattering microscopy are augmented through deep learning integration. This synergistic paradigm improves fundamental performance via denoising, deconvolution, and hyperspectral unmixing. Concurrently, it enhances downstream image analysis including subcellular localization, virtual staining, and clinical ...
Jianlin Liu   +4 more
wiley   +1 more source

Advancements in psoriasis classification using custom transfer learning algorithms. [PDF]

open access: yesSci Rep
Lakshmi L   +5 more
europepmc   +1 more source

Identification of Exhaled Volatile Organic Compounds Biomarkers for Lung Cancer Under Data‐Limited Conditions Using Data Augmentation and Multi‐View Feature Selection

open access: yesAdvanced Intelligent Discovery, EarlyView.
This work introduces a novel framework for identifying non‐small cell lung cancer biomarkers from hundreds of volatile organic compounds in breath, analyzed via gas chromatography‐mass spectrometry. This method integrates generative data augmentation and multi‐view feature selection, providing a stable and accurate solution for biomarker discovery in ...
Guancheng Ren   +10 more
wiley   +1 more source

A Physics Constrained Machine Learning Pipeline for Young's Modulus Prediction in Multimaterial Hyperelastic Cylinders Guided by Contact Mechanics

open access: yesAdvanced Intelligent Discovery, EarlyView.
A physics‐guided machine learning framework estimates Young's modulus in multilayered multimaterial hyperelastic cylinders using contact mechanics. A semiempirical stiffness law is embedded into a custom neural network, ensuring physically consistent predictions. Validation against experimental and numerical data on C.
Christoforos Rekatsinas   +4 more
wiley   +1 more source

Taguchi–Bayesian Sampling: A Roadmap for Polymer Database Construction Toward Small Representative Machine Learning

open access: yesAdvanced Intelligent Discovery, EarlyView.
This article establishes a Taguchi–Bayesian sampling strategy to reconstruct polymer processing–property landscape at minimal sampling cost, generically building the roadmap for materials database construction from sampling their vast design space. This sampling strategy is featured by an alternating lesson between uniformity and representativeness ...
Han Liu, Liantang Li
wiley   +1 more source

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