Results 171 to 180 of about 15,875,601 (337)

Microplastics from Wearable Bioelectronic Devices: Sources, Risks, and Sustainable Solutions

open access: yesAdvanced Functional Materials, EarlyView.
Bioelectronic devices (e.g., e‐skins) heavily rely on polymers that at the end of their life cycle will generate microplastics. For research, a holistic approach to viewing the full impact of such devices cannot be overlooked. The potential for devices as sources for microplastics is raised, with mitigation strategies surrounding polysaccharide and ...
Conor S. Boland
wiley   +1 more source

Enhancing Hemoglobin Levels in Moderately Acute Malnourished Children Aged 6-59 Months: A Randomized Controlled Trial of a Novel Ready-to-Use Food (RUF). [PDF]

open access: yesAnemia
Makori N   +15 more
europepmc   +1 more source

Roll‐to‐Roll Mechanical Exfoliation for Large‐Area van der Waals Films with Preserved Crystallographic Alignment

open access: yesAdvanced Functional Materials, EarlyView.
A roll‐to‐roll exfoliation method is demonstrated that preserves the crystallographic alignment of anisotropic 2D materials over large areas, enabling scalable fabrication of directional electronic and optoelectronic devices. Abstract Anisotropic 2D materials such as black phosphorus (BP), GeS or CrSBr, exhibit direction‐dependent optical and ...
Esteban Zamora‐Amo   +14 more
wiley   +1 more source

Integrative Approaches for DNA Sequence‐Controlled Functional Materials

open access: yesAdvanced Functional Materials, EarlyView.
DNA is emerging as a programmable building block for functional materials with applications in biomimicry, biochemical, and mechanical information processing. The integration of simulations, experiments, and machine learning is explored as a means to bridge DNA sequences with macroscopic material properties, highlighting current advances and providing ...
Aaron Gadzekpo   +4 more
wiley   +1 more source

Smarter Sensors Through Machine Learning: Historical Insights and Emerging Trends across Sensor Technologies

open access: yesAdvanced Functional Materials, EarlyView.
This review highlights how machine learning (ML) algorithms are employed to enhance sensor performance, focusing on gas and physical sensors such as haptic and strain devices. By addressing current bottlenecks and enabling simultaneous improvement of multiple metrics, these approaches pave the way toward next‐generation, real‐world sensor applications.
Kichul Lee   +17 more
wiley   +1 more source

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