Results 151 to 160 of about 61,046 (248)
Harnessing Phase Separation for the Development of High‐Performance Hydrogels
ABSTRACT Hydrogels are indispensable for the development of next‐generation bioelectronics, soft robotics, and biomedical devices, where their mechanical properties determine performance and reliability. Among strategies to enhance hydrogel mechanics, phase separation enables controlled heterogeneity resulting in gel networks that are reinforced by ...
Yue Shao +3 more
wiley +1 more source
Study design and protocol for a mixed methods evaluation of an intervention to reduce and break up sitting time in primary school classrooms in the UK: The CLASS PAL (Physically Active Learning) Programme. [PDF]
Routen AC +11 more
europepmc +1 more source
WS2‐based in‐memory sensing reservoir computing integrates sensing, memory, and computation in one compact device. It achieves ∼94% N‐MNIST, ∼93% eye motion perception, and ∼89% speech recognition with ultra‐low energy (∼25.5 fJ/spike). The system shows stability at 95% humidity, endurance over 1.5M cycles, and supports synaptic plasticity, enabling ...
Dayanand Kumar +9 more
wiley +1 more source
CMOS‐Integrated Synaptic Photoreceptor Chip Inspired by Insect Visual Processing
CMOS‐integrated Si QDs/ReS2 synaptic photoreceptor array mimics the parallel processing and wavelength‐selective strategy of insect vision. By combining intrinsic ultraviolet‐violet sensitivity with synaptic plasticity, the chip enables frontend sensory redundancy reduction without external filters, offering a scalable pathway toward lowpower ...
Jian Chai +25 more
wiley +1 more source
Organoid Brain‐Machine‐Interface Devices for Central Nervous System Repair
We envision organoid brain‐machine‐interface (Organoid‐BMI) devices as new biohybrid bidirectional communication pathways to connect the human CNS and the external world for personalized CNS repair and regeneration. ABSTRACT Central nervous system (CNS) repair and regeneration suffer from tremendous clinical challenges due to current limitations in ...
Yantao Xing +10 more
wiley +1 more source
Natural science: Active learning in dynamic physical microworlds.
In this paper, we bring together research on active learningand intuitive physics to explore how people learn about“microworlds” with continuous spatiotemporal dynamics.Participants interacted with objects in simple two-dimensionalworlds governed by a physics simulator, with the goal ofidentifying latent physical properties such as mass, and forcesof ...
Bramley, Neil +2 more
openaire +1 more source
Interpretable machine learning reveals how composition and processing govern the formation and microstructural burden of Fe‐rich intermetallic compounds in recycled Al–Si–Fe–Mn alloys. By separating morphology selection from morphology‐conditioned burden partitioning, this framework shows that identical Fe contents can yield different intermetallic ...
Jaemin Wang +2 more
wiley +1 more source
Inspired by Nostoc, a crack‐based one‐dimensional microspheres array (COMA) sensor is developed, which stabilizes crack geometry under isotropic expansion, enabling a predictable, monotonic thermal response from which true strain can be accurately extracted. The COMA sensor exhibits high sensitivity at ultralow deformation (gauge factor up to 89) and a
Wanqing Xu +7 more
wiley +1 more source
Nuclear mechanical properties are inherently scale‐dependent, arising from a hierarchical architecture that spans DNA, chromatin, the nuclear envelope, and condensates. Experimental techniques and theoretical models are integrated into a cohesive multiscale framework linking nanoscale structural features to organelle‐level mechanical behavior.
Xinran Liu +15 more
wiley +1 more source
This study establishes an interpretable machine learning framework that disentangles the intrinsic molecular efficacy of passivators from experimental platform effects—enabling unbiased, high‐throughput discovery of effective perovskite surface modifiers.
Jing Zhang +5 more
wiley +1 more source

