Results 231 to 240 of about 284,887 (285)

The Future of Hydrogen‐Powered Aviation: Technologies, Challenges, and a Strategic Roadmap for Sustainable Decarbonization

open access: yesAdvanced Energy and Sustainability Research, EarlyView.
Hydrogen‐powered aviation offers a transformative pathway to zero‐emission flight by eliminating in‐flight CO2 emissions. Key considerations include propulsion systems (fuel cells and hydrogen combustion), cryogenic storage and insulation challenges, infrastructure and cost barriers, and supply‐chain constraints.
Mubasshira   +4 more
wiley   +1 more source

Economic Viability of Photovoltaic Systems Providing Frequency Containment Reserve

open access: yesAdvanced Energy and Sustainability Research, EarlyView.
This article investigates the feasibility of photovoltaic (PV) systems providing frequency containment reserve (FCR) in the Netherlands. The economic analysis demonstrates that a PV plant can profitably participate in FCR without battery storage by maintaining an active power reserve.
Emil Petkovski   +3 more
wiley   +1 more source

Graphene and Ti<sub>3</sub>C<sub>2</sub>T<sub><i>x</i></sub> MXene Nanomaterial-Infused Bioinks for Mechanical and Electrical Improvement of 3D Bioprinted Scaffolds. [PDF]

open access: yesACS Appl Bio Mater
Nelson ML   +14 more
europepmc   +1 more source

Decoding Tattoo and Permanent Makeup Pigments: Linking Physicochemical Properties to Absorption, Distribution, Metabolism, and Elimination Profiles Using Quantitative Structure–Activity Relationship (QSAR)‐Based New Approach Methodologies (NAMs)

open access: yesAdvanced Intelligent Discovery, EarlyView.
This study applies QSAR‐based new approach methodologies to 90 synthetic tattoo and permanent makeup pigments, revealing systemic links between their physicochemical properties and absorption, distribution, metabolism, and elimination profiles. The correlation‐driven analysis using SwissADME, ChemBCPP, and principal component analysis uncovers insights
Girija Bansod   +10 more
wiley   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

open access: yesAdvanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook

open access: yesAdvanced Intelligent Discovery, EarlyView.
Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang   +4 more
wiley   +1 more source

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