Results 191 to 200 of about 36,022 (270)
Selective Benzene Capture by Metal‐Organic Frameworks
Metal‐organic frameworks (MOFs) hold significant potential for capturing benzene from air emissions and hydrocarbon mixtures in liquid phases. This capability stems from their precisely engineered structures, versatile chemistries, and diverse binding interactions.
Zongsu Han +4 more
wiley +1 more source
Assessing the digital health readiness questionnaire Japanese version: insights from cardiovascular patients in Japan. [PDF]
Ozaki S, Kaihara T, Akashi Y.
europepmc +1 more source
Electroactive Metal–Organic Frameworks for Electrocatalysis
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
Learnability of the LAHSHAL Classification for Oral Clefts: Results of an International Webinar. [PDF]
Houkes RP +11 more
europepmc +1 more source
I want to argue that there is a task of ‘culture research’ other than what is practised in the empirical disciplines such as Social Anthropology or historical disciplines such as Literary Studies. Suppose ‘Cultures’ are looked upon as different legacies of ways of going about in the world resulting from the different pasts of different groups of people.
openaire +1 more source
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
Expert Views on Criteria for Evaluation of Human Factors Methods: Qualitative Interview Study. [PDF]
Awad S +4 more
europepmc +1 more source
Unleashing the Power of Machine Learning in Nanomedicine Formulation Development
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
Perceptual Learning and Predictability of Children's Speech. [PDF]
Tetzloff KA +3 more
europepmc +1 more source
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 +9 more
wiley +1 more source

