Results 211 to 220 of about 746,427 (311)

Advancing from MOFs and COFs to Functional Macroscopic Porous Constructs

Advanced Materials, EarlyView.
This review study investigates the recent progress and methodologies for manufacturing metal–organic framework (MOF) or covalent–organic framework (COF)‐based 3D structured macroscopic porous constructs with high structural integrity, providing the possibility to control their porosity across dimensions.
Seyyed Alireza Hashemi, Ahmadreza Ghaffarkhah, Ali Akbar Isari, Mahyar Panahi‐Sarmad, Feng Jiang, Orlando J. Rojas, Stefan Wuttke, Mircea Dincă, Mohammad Arjmand   +8 more
wiley   +1 more source

Correction: Checklist for Reproducibility of Deep Learning in Medical Imaging. [PDF]

J Imaging Inform Med
Moassefi M, Singh Y, Conte GM, Khosravi B, Rouzrokh P, Vahdati S, Safdar N, Moy L, Kitamura F, Gentili A, Lakhani P, Kottler N, Halabi SS, Yacoub JH, Hou Y, Younis K, Erickson BJ, Krupinski E, Faghani S.   +18 more
europepmc   +1 more source

Computational Modeling of Reticular Materials: The Past, the Present, and the Future

Advanced Materials, EarlyView.
Reticular materials are advanced materials with applications in emerging technologies. A thorough understanding of material properties at operating conditions is critical to accelerate the deployment at an industrial scale. Herein, the status of computational modeling of reticular materials is reviewed, supplemented with topical examples highlighting ...
Wim Temmerman, Ruben Goeminne, Kuber Singh Rawat, Veronique Van Speybroeck   +3 more
wiley   +1 more source

Editorial: Exploring the power of AI and ML in smart grids: advancements, applications, and challenges. [PDF]

Front Artif Intell
Kulkarni V, Sahoo SK, Nemade B, Kallam S, Termritthikun C.   +4 more
europepmc   +1 more source

Rational Design of Metal–Organic Frameworks for Pancreatic Cancer Therapy: from Machine Learning Screening to In Vivo Efficacy

Advanced Materials, EarlyView.
This work explores the MOF landscape to select a single, optimal candidate for successfully delivering cancer drugs (gemcitabine, paclitaxel, SN‐38) into tough pancreatic tumors. Machine learning and simulations guide this search, demonstrating colloidal stability, excellent biocompatibility, cellular uptake, and sustained release.
Francesca Melle, Dhruv Menon, João Conniot, Jon Ostolaza‐Paraiso, Sergio Mercado, Jhenifer Oliveira, Xu Chen, Bárbara B. Mendes, João Conde, David Fairen‐Jimenez   +9 more
wiley   +1 more source

Artificial intelligence in neurodegenerative diseases research: a bibliometric analysis since 2000. [PDF]

Front Neurol
Zhang Y, Yu L, Lv Y, Yang T, Guo Q.
europepmc   +1 more source

Hierarchically MOF‐Based Porous Monolith Composites for Atmospheric Water Harvesting

Advanced Materials, EarlyView.
This review explores the design of hierarchical porous materials for atmospheric water harvesting, focusing on metal‐organic frameworks (MOFs) and porous monoliths. Emphasis is placed on integrating MOF nanoscale porosity with the microscale channels of monolithic scaffolds to enhance sorption‐desorption performance.
Mahyar Panahi‐Sarmad, Tianyu Guo, Seyyed Alireza Hashemi, Ahmadreza Ghaffarkhah, Stefan Wuttke, Mohammad Arjmand, Orlando J. Rojas, Feng Jiang   +7 more
wiley   +1 more source

Comprehensive Global Analysis of Future Trends in Artificial Intelligence-Assisted Veterinary Medicine. [PDF]

Vet Med Sci
Elasan S, Yilmaz O.
europepmc   +1 more source

Entangled Narratives: Insights from Social and Computer Sciences on National Artificial Intelligence Infrastructures

J.P. Singh, Amarda Shehu, Manpriya Dua, Caroline F. Wesson   +3 more
openalex   +1 more source

Advancing Metal–Organic Framework‐Based Composites for Effective Chemical Warfare Agent Detoxification under Real‐World Conditions

Advanced Materials, EarlyView.
This review describes recent developments in the design and synthesis of metal–organic frameworks (MOF)/textile composites for the detoxification of chemical warfare agent and simulants with extensive discussion on the advantages and disadvantages of different methods.
Zhihua Cheng, Kira M. Fahy, Gregory W. Peterson, Kent O. Kirlikovali, Omar K. Farha   +4 more
wiley   +1 more source