Results 251 to 260 of about 38,524 (343)

Solid‐State Nanopore Characterization of Dendrimer‐Peptide Conjugates Across Defined Peptide Loadings

open access: yesAdvanced Materials Interfaces, EarlyView.
Solid‐state nanopores are used to interrogate dendrimer‐peptide conjugates with systematically varied peptide loading. Single‐particle ionic current signatures reveal how ligand density modulates deformability, transport pathways, and electromechanical coupling during translocation.
Chaoming Gu   +7 more
wiley   +1 more source

Advanced Design for Weakly Coupled Resonators by Automatic Active Optimization

open access: yesAdvanced Materials Technologies, EarlyView.
An Automatic Active Optimization (AAO) strategy integrates machine learning predictors and genetic algorithms in a closed‐loop workflow. By iteratively expanding its dataset with new discoveries, AAO overcomes the limits of conventional methods. This approach finds superior microstructural designs beyond the initial sample space. We demonstrate this on
Wei Yue   +8 more
wiley   +1 more source

Parallel Electrical Integration of Photo Bio Electrochemical Systems (photo‐BESs): Performance Gains and Load Dependency

open access: yesAdvanced Materials Technologies, EarlyView.
Parallel wiring of bioelectrochemical devices with conventional generators unexpectedly boosts output. A biophotovoltaic paired with a solar cell delivers up to 50% more power at low loads than their separate contributions; a plant microbial fuel cell shows similar current gains.
Valeria Marsaglia   +4 more
wiley   +1 more source

Overcoming Printing and Interfacial Challenges in Liquid Metal Direct Writing for Integrated Stretchable Electronics

open access: yesAdvanced Materials Technologies, EarlyView.
Liquid metal direct writing is advanced from a technological and fundamental point. Utilizing a kinematic bed, printing on large surfaces with irregularities is enabled. Furthermore, a pressure‐driven flow during printing is discovered that affects the thickness of traces.
Maximilian Krack   +15 more
wiley   +1 more source

Characterization of Droplet Formation in Ultrasonic Spray Coating: Influence of Ink Formulation Using Phase Doppler Anemometry and Machine Learning

open access: yesAdvanced Materials Technologies, EarlyView.
This study explores how machine learning models, trained on small experimental datasets obtained via Phase Doppler Anemometry (PDA), can accurately predict droplet size (D32) in ultrasonic spray coating (USSC). By capturing the influence of ink complexity (solvent, polymer, nanoparticles), power, and flow rate, the model enables precise droplet control
Pieter Verding   +5 more
wiley   +1 more source

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