Results 211 to 220 of about 58,557 (260)

Machine Learning‐Enabled Prediction of pH‐Responsive Curcumin Release From Self‐Assembled Nanomicelles

open access: yesJournal of Applied Polymer Science, Volume 143, Issue 36, September 20, 2026.
Curcumin encapsulation in nanomicelles coupled with a machine learning–guided model for predicting its release profile. ABSTRACT This work, leveraging machine‐learning algorithms, focuses on the design and in vitro evaluation of oil‐in‐water surfactant‐based nanomicelles as a novel curcumin formulation with comparable cytotoxic effects against MCF‐7 ...
Abbas Rahdar   +3 more
wiley   +1 more source

A Ceramic Network for Hybrid Solid Electrolyte Lithium Metal Batteries

open access: yesAdvanced Science, Volume 13, Issue 50, 7 September 2026.
An in‐plane aligned Ta‐LLZO ceramic network exhibits superior performance compared to conventional fillers, including single ceramic fibers and particles. The tortuosity within the polymeric phase of hybrid solid electrolytes is identified as a key parameter governing lithium‐ion transport pathways and dendrite suppression.
Luca Weckelmann   +10 more
wiley   +1 more source

Machine Learning-Based Prediction of Sleep Quality in Patients with Multiple Sclerosis. [PDF]

open access: yesMed Sci (Basel)
Cucu LE   +13 more
europepmc   +1 more source

Insights from a two‐decade study of crop rotation and biocover impact on yield in no‐till corn

open access: yesAgronomy Journal, Volume 118, Issue 5, September/October 2026.
Abstract Crop rotation and cover crop (biocover) management can improve the productivity and yield stability of no‐till corn, yet long‐term evidence for humid subtropical silt loams remains limited. This study evaluated corn (Zea mays L.) grain yield across a 20‐year period (2002–2021) under varying crop sequences and biocovers at two Tennessee ...
Isaac Mirahki, Virginia R. Sykes
wiley   +1 more source

Artificial Intelligence Tools for Carbon Nanotube Research: Opportunities From Synthesis to Applications

open access: yesCarbon and Hydrogen, Volume 28, Issue 3, Page 304-319, September 2026.
Artificial intelligence tools are reshaping carbon nanotube research by connecting synthesis, characterization, and application‐oriented design. This review outlines how supervised learning, deep learning, Bayesian optimization, and large language models accelerate data extraction, experiment planning, and structure–property discovery for carbon ...
Yanlong Zhao   +6 more
wiley   +1 more source

Artificial Intelligence and Machine Learning for Oxygen Reduction Reaction: A Review on Catalyst Discovery and Durability Modeling

open access: yesElectroanalysis, Volume 38, Issue 9, September 2026.
The oxygen reduction reaction (ORR) at the proton exchange membrane fuel cells (PEMFC) cathode suffers from sluggish kinetics, high platinum loading requirements, and progressive catalyst degradation. This review examines how artificial intelligence (AI) and machine learning (ML) are reshaping the discovery and durability assessment of ORR ...
Aaditya Sharma   +4 more
wiley   +1 more source

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