Results 131 to 140 of about 28,141 (256)

Machine Learning for Green Solvents: Assessment, Selection and Substitution

open access: yesAdvanced Science, EarlyView.
Environmental regulations have intensified demand for green solvents, but discovery is limited by Solvent Selection Guides (SSGs) that quantify solvent sustainability. Training a machine learning model on GlaxoSmithKline SSG, a database of sustainability metrics for 10,189 solvents, GreenSolventDB is developed. Integrated with Hansen solubility metrics,
Rohan Datta   +4 more
wiley   +1 more source

Physical Origin of Temperature Induced Activation Energy Switching in Electrically Conductive Cement

open access: yesAdvanced Science, EarlyView.
The temperature‐induced Arrhenius activation energy switching phenomenon of electrical conduction in electrically conductive cement originates from structural degradation within the biphasic ionic‐electronic conduction architecture and shows percolation‐governed characteristics: pore network opening dominates the low‐percolation regime with downward ...
Jiacheng Zhang   +7 more
wiley   +1 more source

Microbially driven methane and sulfur cycling processes and coupling mechanisms in mangrove sediments. [PDF]

open access: yesEnviron Microbiome
Tao M   +10 more
europepmc   +1 more source

Diversity of microbial community and its metabolic potential for nitrogen and sulfur cycling in sediments of Phu Quoc island, Gulf of Thailand. [PDF]

open access: yesBraz J Microbiol, 2021
Quach NT   +14 more
europepmc   +1 more source

Cross Kingdom Metabolic Engineering Paradigm Elevating Sustainable Protein Production

open access: yesAdvanced Science, EarlyView.
ABSTRACT Confronting the dual crisis of escalating global protein demand and unsustainable agriculture necessitates transformative solutions. Here, we pioneer evolutionary insights from maize nitrogen optimization via asparagine synthetase (ASNS) to rewire metabolism in Pichia pastoris.
Yuanyuan Du   +4 more
wiley   +1 more source

Nanocellulose Alleviates Intrahepatic Cholestasis of Pregnancy via Gut Microbiota‐Mediated Bile Acid Homeostasis

open access: yesAdvanced Science, EarlyView.
Nanocellulose, derived from microcrystalline cellulose (MCC) through sulfuric acid hydrolysis or mechanical grinding to produce CNC or CNF, was tested in a rat ICP model. Particularly, CNF improved gut microbiota composition, reduced secondary bile acid metabolism, and restored bile acid homeostasis through modulation of the gut–liver axis.
Muhua Yu   +18 more
wiley   +1 more source

Sulfur-enriched sub-arc fluids drive deep sulfur cycling in subduction zones. [PDF]

open access: yesNat Commun
Tan DB   +10 more
europepmc   +1 more source

Mitochondria and Neuromast Tagging With Fluorescent Gallium‐Triapine Analogues: In Cellulo MP FLIM and Zebrafish Live Imaging

open access: yesAdvanced Science, EarlyView.
Fluorescent BODIPY‐conjugated thiosemicarbazone ligands and their Ga(III), In(III), and Fe(III) complexes, inspired by Triapine, are developed as theranostic agents. Multiphoton FLIM and confocal microscopy in cancer cells and zebrafish reveal real‐time uptake, mitochondrial localisation, and whilst spectroscopic assays indicated preserved complex ...
Megan J. Green   +15 more
wiley   +1 more source

Time‐Multiplexed Organic Electrochemical Transistor for Saliva‐Based Rapid Detection of Viral Proteins

open access: yesAdvanced Science, EarlyView.
A time‐multiplexed nanobody‐functionalized organic electrochemical transistor enables rapid and sensitive detection of three respiratory viral proteins from saliva. Sequentially addressed multi‐gate electrodes on a shared channel achieve around 1 fm detection within 15 min without sample preprocessing. Clinical validation demonstrates high specificity,
Tianrui Chang   +13 more
wiley   +1 more source

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

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