Results 171 to 180 of about 266,020 (304)

Responses of Methane Emissions to Different Soil Amendments in Paddy Soil: Soil Properties, Microbial Communities, and Functional Genes. [PDF]

Biology (Basel)
Wu Q, Deng D, Zhang Y, Liang W, Li Y, Zhang Y, Wang Y.   +6 more
europepmc   +1 more source

Exploring Quantum Support Vector Regression for Predicting Hydrogen Storage Capacity of Nanoporous Materials

Advanced Intelligent Discovery, EarlyView.
In this study we employed support vector regressor and quantum support vector regressor to predict the hydrogen storage capacity of metal–organic frameworks using structural and physicochemical descriptors. This study presents a comparative analysis of classical support vector regression (SVR) and quantum support vector regression (QSVR) in predicting ...
Chandra Chowdhury
wiley   +1 more source

Measuring Local Exothermic Effects During the Oxidative Coupling of Methane Using Operando Luminescence Thermometry

Angewandte Chemie, EarlyView.
Operando luminescence thermometry shows that the local catalyst temperature can exceed the set oven temperature by almost 250°C during the exothermic oxidative coupling of methane process. We demonstrate how the reactor dimensions, catalyst grain size, and reactant feed mixture affect the local temperature.
Daniël W. Groefsema, Freddy T. Rabouw, D. Michiel Boele, A.N. René Bos, Alexander P. van Bavel, Bert M. Weckhuysen   +5 more
wiley   +2 more sources

Editorial: Assessing the environmental impact of ruminants: mitigation strategies and climate change implications. [PDF]

Front Microbiol
Cherdthong A, Foiklang S, Altermann E.
europepmc   +1 more source

A Generalized Framework for Data‐Efficient and Extrapolative Materials Discovery for Gas Separation

Advanced Intelligent Discovery, EarlyView.
This study introduces an iterative supervised machine learning framework for metal‐organic framework (MOF) discovery. The approach identifies over 97% of the best performing candidates while using less than 10% of available data. It generalizes across diverse MOF databases and gas separation scenarios.
Varad Daoo, Jayant K. Singh
wiley   +1 more source

High sensitive methane sensor based on a photonic bandgap fiber [PDF]

Monitoring methane (CH) concentration is essential in many industrial and environmental applications. Hollow-core photonic bandgap fibers (HC-PBF) have emerged as a promising technology in the field of gas sensing.
Cubillas, Ana M., Lazaro, José M., Silva-Lopez, Manuel, Petrovich, Marco, Conde, Olga M., López-Higuera, José M.   +5 more
core  

Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion

Advanced Intelligent Discovery, EarlyView.
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, Christian Mark Pelicano   +1 more
wiley   +1 more source

Diversity, mutagenesis and recombinant expression of the soluble methane monooxygenase [PDF]

Methanotrophic bacteria convert methane to methanol using a methane monooxygenase enzyme (MMO). Two types of MMO exist: a membrane bound enzyme (PMMO) and a cytoplasmic enzyme (sMMO).
Dumont, Marc G.
core  

Energy Transfer‐Mediated Magnetoluminescence of an Octahedral MnII Complex Ligated With Bis(Diphenylphosphino)Methane Dioxide

Angewandte Chemie, EarlyView.
Energy‐transfer‐mediated magnetoluminescence of paramagnetic transition metal complexes: dope solids of an octahedral MnII complex into the corresponding ZnII complex exhibited a pronounced magnetic field response of emission spectra under the application of magnetic fields.
Asato Mizuno, Takuto Mibu, Ryota Matsuoka, Takema Hikawa, Shojiro Kimura, Tetsuro Kusamoto   +5 more
wiley   +2 more sources

Apple pomace and hempseed cake can reduce methane intensity (CH₄/DMI) and alter the rumen microbiome in dairy cows: a shotgun metagenomic approach. [PDF]

J Anim Sci Biotechnol
Gorji AE, Xue B, Yan T, Sadkowski T, Chen X, Cristobal-Carballo O, Morrison S, Razban V, Smith L, Stergiadis S, Theodoridou K, Shirali M.   +11 more
europepmc   +1 more source