Results 111 to 120 of about 1,068,325 (276)

Biodegradable and Recyclable Luminescent Mixed‐Matrix‐Membranes, Hydrogels, and Cryogels based on Nanoscale Metal‐Organic Frameworks and Biopolymers

open access: yesAdvanced Functional Materials, EarlyView.
The study presents biodegradable and recyclable mixed‐matrix membranes (MMMs), hydrogels, and cryogels using luminescent nanoscale metal‐organic frameworks (nMOFs) and biopolymers. These bio‐nMOF‐MMMs combine europium‐based nMOFs as probes for the status of the materials with the biopolymers agar and gelatine and present alternatives to conventional ...
Moritz Maxeiner   +4 more
wiley   +1 more source

Combinatorial Synthesis of Next Generation Water‐Soluble Quaternized N‐Halamine Oligomers with Long‐Lasting Antiviral Properties

open access: yesAdvanced Functional Materials, EarlyView.
A combinatorial library of dual‐functional antiviral oligomers incorporating N‐halamine and quaternary ammonium functionalities is developed for long‐lasting antiviral activity. The lead materials exhibit rapid and durable antiviral activity against SARS‐CoV‐2 variants and influenza H1N1, with 4 to 5 log reduction in viral copies at 5 mg mL−1 ...
Eid Nassar‐Marjiya   +14 more
wiley   +1 more source

Laser‐Induced Graphene from Waste Almond Shells

open access: yesAdvanced Functional Materials, EarlyView.
Almond shells, an abundant agricultural by‐product, are repurposed to create a fully bioderived almond shell/chitosan composite (ASC) degradable in soil. ASC is converted into laser‐induced graphene (LIG) by laser scribing and proposed as a substrate for transient electronics.
Yulia Steksova   +9 more
wiley   +1 more source

Biomass Native Structure Into Functional Carbon‐Based Catalysts for Fenton‐Like Reactions

open access: yesAdvanced Functional Materials, EarlyView.
This study indicates that eight biomasses with 2D flaky and 1D acicular structures influence surface O types, morphology, defects, N doping, sp2 C, and Co nanoparticles loading in three series of carbon, N‐doped carbon, and cobalt/graphitic carbon. This work identifies how these structural factors impact catalytic pathways, enhancing selective electron
Wenjie Tian   +7 more
wiley   +1 more source

Electroactive Metal–Organic Frameworks for Electrocatalysis

open access: yesAdvanced Functional Materials, EarlyView.
Electrocatalysis is crucial in sustainable energy conversion as it enables efficient chemical transformations. The review discusses how metal–organic frameworks can revolutionize this field by offering tailorable structures and active site tunability, enabling efficient and selective electrocatalytic processes.
Irena Senkovska   +7 more
wiley   +1 more source

AN E-BROKERAGE APPROACH BASED ON MULTI-AGENT TECHNOLOGY [PDF]

open access: yes
In this paper the author shows the importance of multi-agent system in the e-commerce domain, specially for brokerage. He also propose an agent-based architecture for brokerage and a structure for the intelligent broker.
Radu Ioan MOGOS
core  

Smart, Bio‐Inspired Polymers and Bio‐Based Molecules Modified by Zwitterionic Motifs to Design Next‐Generation Materials for Medical Applications

open access: yesAdvanced Functional Materials, EarlyView.
Bio‐based and (semi‐)synthetic zwitterion‐modified novel materials and fully synthetic next‐generation alternatives show the importance of material design for different biomedical applications. The zwitterionic character affects the physiochemical behavior of the material and deepens the understanding of chemical interaction mechanisms within the ...
Theresa M. Lutz   +3 more
wiley   +1 more source

AI-Supported Decision Making in Multi-Agent Production Systems Using the Example of the Oil and Gas Industry

open access: yesApplied Sciences
This study focuses on the development of a decision support system for complex production systems. As a promising approach to resource allocation challenges, the application of AI tools, particularly the multi-agent approach, is proposed.
Polina A. Sharko   +4 more
doaj   +1 more source

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

open access: yesAdvanced Functional Materials, EarlyView.
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore   +7 more
wiley   +1 more source

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