Results 261 to 270 of about 5,916,094 (333)

Planar Solid‐State Nanopores Toward Scalable Nanofluidic Integration Based on CMOS Technology

open access: yesAdvanced Engineering Materials, EarlyView.
We present a scalable silicon‐based fabrication strategy for planar solid‐state nanopores to enable their integration with complex nanofluidic systems. Prototype devices demonstrate normal voltage‐current characteristics, good noise performance, and appreciable streaming currents. Our CMOS‐compatible fabrication process offers precise geometric control
Ngan Hoang Pham   +7 more
wiley   +1 more source

Electrochemical Evaluation of Compressed Selective Laser Melted AlSi7Mg and AlSi10Mg Alloys in Chloride Environment

open access: yesAdvanced Engineering Materials, EarlyView.
The corrosion performance of AlSi7Mg and AlSi10Mg alloys produced through selective laser melting (SLM) was examined under compressive stress in a chloride environment. Electrochemical analyses, including open‐circuit potential (OCP), potentiodynamic polarization (CPP), and electrochemical impedance spectroscopy (EIS), were complemented by scanning ...
Femi John Akinfolarin   +2 more
wiley   +1 more source

A Compact Spin‐Coated Graphene UWB Antenna for Breast Tumor Detection

open access: yesAdvanced Engineering Materials, EarlyView.
A compact, spin‐coated graphene ultra‐wideband patch antenna designed for breast tumor detection, capable of distinguishing between malignant and benign tumors. This innovative antenna can serve as an effective initial screening tool, particularly in resource‐limited settings such as rural areas, where access to advanced medical equipment like MRI and ...
Raja Rashidul Hasan   +9 more
wiley   +1 more source

Prediction of Surface Topography Parameters in Direct Laser Interference Patterning of Stainless Steel Using Infrared Monitoring and Convolutional Neural Networks

open access: yesAdvanced Engineering Materials, EarlyView.
This study presents an infrared monitoring approach for direct laser interference patterning (DLIP) combined with a convolutional neural network (CNN). Thermal emission data captured during structuring are used to predict surface topography parameters.
Lukas Olawsky   +5 more
wiley   +1 more source

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