Results 221 to 230 of about 25,851 (312)

The Necessity of Dynamic Workflow Managers for Advancing Self‐Driving Labs and Optimizers

open access: yesAdvanced Intelligent Discovery, EarlyView.
We assess the maturity and integration readiness of key methodologies for Materials Acceleration Platforms, highlighting the need for dynamic workflow managers. Demonstrating this, we integrate PerQueue into a color‐mixing robot, showing how flexible orchestration improves coordination and optimization.
Simon K. Steensen   +6 more
wiley   +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

Structure and Spectroscopic Characterisation of Phenanthroline‐Based Iodobismuthate(III) Complexes Utilised for Raw Acoustic Signal Classification

open access: yesAdvanced Intelligent Discovery, EarlyView.
Memristors based on trimethylsulfonium (phenanthroline)tetraiodobismuthate have been utilised as a nonlinear node in a delayed feedback reservoir. This system allowed an efficient classification of acoustic signals, namely differentiation of vocalisation of the brushtail possum (Trichosurus vulpecula).
Ewelina Cechosz   +4 more
wiley   +1 more source

Deep Learning‐Assisted Design of Mechanical Metamaterials

open access: yesAdvanced Intelligent Discovery, EarlyView.
This review examines the role of data‐driven deep learning methodologies in advancing mechanical metamaterial design, focusing on the specific methodologies, applications, challenges, and outlooks of this field. Mechanical metamaterials (MMs), characterized by their extraordinary mechanical behaviors derived from architected microstructures, have ...
Zisheng Zong   +5 more
wiley   +1 more source

Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook

open access: yesAdvanced Intelligent Discovery, EarlyView.
Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang   +4 more
wiley   +1 more source

The Discovery of Oral Cancer Prognostic Factor Ranking Using Association Rule Mining. [PDF]

open access: yesEur J Dent
Chaowchuen S   +4 more
europepmc   +1 more source

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