Results 141 to 150 of about 3,170,729 (273)

Electroactive Metal–Organic Frameworks for Electrocatalysis

Advanced 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, Yutong Luo, Ruyan Zhao, Jianjun Zhang, Mingchao Wang, Xinliang Feng, Eike Brunner, Stefan Kaskel   +7 more
wiley   +1 more source

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

Advanced 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, Jonas De Breuck, Sahar Salehi, Meike N. Leiske   +3 more
wiley   +1 more source

MolQuery: Prediction of Lipid Synthesizability Using Active Learning. [PDF]

ACS Omega
Broadbent J, Vymětal J, Moayedpour S, Bailey M, Riahi S, Balsubramani A, Mikochik P, Even L, Gunaganti N, Dasari R, Karmakar S, Deng H, Agarwal V, Bar-Joseph Z, Jager S.   +14 more
europepmc   +1 more source

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

Advanced 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, Cristiano Pesce, Antonietta Greco, Claudia Pisante, Greta Avancini, Valentina Di Francesco, Yosi Shamay, Paolo Decuzzi   +7 more
wiley   +1 more source

Automated active learning to optimize hydrogel drug release profiles. [PDF]

J Control Release
Cheong E, Radford DC, Gormley AJ.
europepmc   +1 more source

Region‐to‐Region Unidirectional Connection In Vitro Brain Model for Studying Directional Propagation of Neuropathologies

Advanced Functional Materials, EarlyView.
A unidirectional cerebral organoid–organoid neural circuit is established using a microfluidic platform, enabling controlled directional propagation of electrical signals, neuroinflammatory cues, and neurodegenerative disease–related proteins between spatially separated organoids.
Kyeong Seob Hwang, Hui‐Wen Liu, Hyogeun Shin, Hyun Wook Kang, Minjin Kang, Jongbaeg Kim, Il‐Joo Cho, Nakwon Choi, Seok Chung, Hong Nam Kim   +9 more
wiley   +1 more source

Predictive Quantum Vibrational Spectra through Active Learning 4G-NNPs. [PDF]

J Phys Chem Lett
Faruque MO, Limbu DK, London N, Momeni MR.   +3 more
europepmc   +1 more source

Ultrahigh‐Yield, Multifunctional, and High‐Performance Organic Memory for Seamless In‐Sensor Computing Operation

Advanced Functional Materials, EarlyView.
Molecular engineering of a nonconjugated radical polymer enables a significant enhancement of the glass transition temperature. The amorphous nature and tunability of the polymer, arising from its nonconjugated backbone, facilitates the fabrication of organic memristive devices with an exceptionally high yield (>95%), as well as substantial ...
Daeun Kim, Jaehyoung Ko, Namju Kim, Quynh H. Nguyen, Hoyeon Lee, Joohwan Eo, Seongeon Jin, Ji Eon Kwon, Seung‐Yeol Jeon, Youngdo Jeong, Dongseok Kwon, Sung Gap Im, Sanghan Lee, Byung Chul Jang, Yongho Joo   +14 more
wiley   +1 more source

An Effective Team: Active Learning Also Needs the Sage on a Stage. [PDF]

J Med Educ Curric Dev
Bordonaro M.
europepmc   +1 more source

Chemoselective Sequential Polymerization: An Approach Toward Mixed Plastic Waste Recycling

Advanced Functional Materials, EarlyView.
Inspired by biological protein metabolism, this study demonstrates the closed‐loop recycling of mixed synthetic polymers via ring‐closing depolymerization followed by a chemoselective sequential polymerizations process. The approach recovers pure polymers from mixed feedstocks, even in multilayer formats, highlighting a promising strategy to overcome a
Gadi Slor, Youwei Ma, Hyunwoo Park, Tae‐Lim Choi, Damien Guironnet, Francesco Stellacci   +5 more
wiley   +1 more source