Results 201 to 210 of about 70,093 (314)
Intensive ground vegetation growth mitigates the carbon loss after forest disturbance. [PDF]
Zehetgruber B +5 more
europepmc +1 more source
Faster phenol photolysis at the air–water interface arises from two cooperative factors: a more favorable initial microenvironment for solvent‐side electron stabilization, which lowers CI access, and a more labile hydrogen‐bond network, which more readily reorganizes to stabilize the dark‐state intermediate.
Qiang Yin +8 more
wiley +1 more source
Machine‐Learning Framework for Designing Stable Interfaces in All‐Solid‐State Lithium‐Ion Batteries
A data‐driven strategy is developed to discover coating materials for all‐solid‐state lithium batteries. Using calculations of interfacial reactivity, unsupervised pattern recognition, and machine‐learning prediction, the study identifies low‐reactivity compositional patterns and screens new lithium‐based oxide and polyanion candidates, extending ...
Sehyeok Park +4 more
wiley +1 more source
Eucalyptus beyond Its Native Range: Environmental Issues in Exotic Bioenergy Plantations
John A. Stanturf +3 more
doaj +1 more source
Forest Disturbance Monitoring Using Cloud-Based Sentinel-2 Satellite Imagery and Machine Learning. [PDF]
Molnár T, Király G.
europepmc +1 more source
A compact QASRR‐based THz metamaterial absorber enables polarization‐insensitive dual‐band absorption and skin‐cancer‐related refractive‐index sensing through measurable resonance shifts. Field, surface‐current, and circuit analyses clarify the dual‐resonance mechanism, while StackNet‐assisted prediction accurately estimates the simulated absorption ...
Md. Murad Kabir Nipun +5 more
wiley +1 more source
Deciphering Intricacies in Directional CO2 Conversion From Electrolysis to CO2 Batteries
This review will delve into the inherent connections and distinctions of CO2‐directed conversion in ECO2RR and CO2 batteries, in terms of product types, catalyst selection, catalytic mechanisms, and electrochemical performances, while proposing a benchmarking framework for the evaluation of CO2 batteries and innovative CO2 battery configurations for ...
Changfan Xu +5 more
wiley +1 more source
A sequential deep learning framework is developed to model surface roughness progression in multi‐stage microneedle fabrication. Using real‐world experimental data from 3D printing, molding, and casting stages, an long short‐term memory‐based recurrent neural network captures the cumulative influence of geometric parameters and intermediate outputs ...
Abdollah Ahmadpour +5 more
wiley +1 more source
Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion
This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia +1 more
wiley +1 more source
An AI‐assisted approach is introduced to decode synthesis–performance relationships in metal‐organic framework‐derived supercapacitor materials using Bayesian optimization and predictive modeling, streamlining the search for optimal energy storage properties.
David Gryc +8 more
wiley +1 more source

