Results 211 to 220 of about 28,830,363 (302)

An Integrated NLP‐ML Framework for Property Prediction and Design of Steels

open access: yesAdvanced Science, EarlyView.
This study presents a data‐driven framework that uses language‐processing techniques to interpret steel processing descriptions and machine‐learning models to predict mechanical properties. By organising complex process histories into meaningful groups and enabling rapid property forecasts, the work supports faster, more informed steel design through ...
Kiran Devraju   +5 more
wiley   +1 more source

Aminated Wood Aerogel via Tannic Acid/Polyethylenimine Co-Deposition for Enhanced Congo Red Removal. [PDF]

open access: yesGels
Li Z   +10 more
europepmc   +1 more source

Adult Sex Ratio as a Demographic Feedback Linking Mating Systems, Parental Care, and Evolution

open access: yesAdvanced Science, EarlyView.
Breeding systems are some of the most diverse social behavior, and our team is investigation the evolutionary causes of this diversity. This review summarises our research carried out at the University of Bath. We argue that demographic components of wild populations, especially the adult sex ratio, plays a key role driving breeding system variation ...
Tamás Székely, Oscar G. Miranda
wiley   +1 more source

Underground Signals: The Ecological Power of Root Volatiles

open access: yesAdvanced Science, EarlyView.
Root volatiles mediate rhizosphere chemical communication, shaping interactions among plants, microbes, herbivores, and natural enemies. Their production, transport, and perception underpin ecological adaptation, multitrophic interactions, and plant resilience, offering opportunities for sustainable crop protection, resilient agroecosystems, and ...
Xueyao Cao   +31 more
wiley   +1 more source

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

open access: yesAdvanced Science, EarlyView.
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray   +3 more
wiley   +1 more source

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