Microfabricated Crevice Former with a Sensor Array

AbstractMicrofabrication of crevice corrosion samples is of importance in developing an accurate, comprehensive, and reliable crevice corrosion model, and real-time acquisition of corrosion information is also essential. Solid-state microsensor arrays have been used for detecting potential, pH, and ion concentrations, and their integration into crevice corrosion testing samples will provide real-time spatial information of crevice corrosion. The crevice corrosion testing sample is constructed by coupling a crevice former to a crevice substrate and has a uniform crevice gap. In this paper we present a crevice former incorporating a potentiometric, ion- selective membrane microelectrode pH sensor array. The crevice former is built on a silicon wafer using microelectromechanical systems (MEMS) fabrication and thin film semiconductor processing techniques, and consists of an array of five independent sensing microelectrodes. The array configuration allows for in-situ spatial pH analysis of crevice corrosion based on information from each sensor. The fabrication details of the crevice former with microelectrode sensor will be elaborated.

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Fabrication of a Conductometric Sensor for Crevice Corrosion Studies

MRS Proceedings ◽

10.1557/proc-729-u3.13 ◽

2002 ◽

Vol 729 ◽

Cited By ~ 1

Author(s):

Xiaoyan Wang ◽

Robert G. Kelly ◽

Jason S. Lee ◽

Michael L. Reed

Keyword(s):

Thin Film ◽

Real Time ◽

Crevice Corrosion ◽

Metal Ion ◽

Microelectromechanical Systems ◽

Spatial Information ◽

Ion Concentration ◽

Potentiometric Sensors ◽

Conductometric Sensor

AbstractMicrofabricated crevice corrosion samples have been employed in experiments that provided important information necessary for developing an accurate, comprehensive, and reliable crevice corrosion model. Acquiring real-time spatial information of crevice corrosion is also essential in analyzing corrosion processes. Integration of arrays of solid-state microsensors, such as conductometric sensors, pH and other ion concentration potentiometric sensors, into the crevice corrosion samples will allow for in-situ real-time data acquisition. In the present work, crevice corrosion samples with conductometric sensor arrays are made using the techniques developed for thin film semiconductor processing and microelectromechanical systems (MEMS) fabrication. The crevice corrosion testing sample is constructed by coupling a crevice former to a crevice substrate and has a uniform crevice gap. A conductometric sensor array built on a silicon wafer is incorporated into the crevice former. Each of these sensors is composed of a pair of thin film gold electrodes, which enables in-situ spatial conductivity analysis of crevice corrosion. Information about metal ion concentration and active chemistry inside the crevice can also be obtained.

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Microfabrication of Crevice Corrosion Samples

MRS Proceedings ◽

10.1557/proc-657-ee5.31 ◽

2000 ◽

Vol 657 ◽

Cited By ~ 1

Author(s):

Xiaoyan Wang ◽

Robert G. Kelly ◽

Jason S. Lee ◽

Michael L. Reed

Keyword(s):

Crevice Corrosion ◽

Computational Models ◽

Microelectromechanical Systems ◽

Spatial Information ◽

Semiconductor Device ◽

Device Fabrication ◽

Metal Electrodes ◽

Electrical Connections ◽

Microfabrication Techniques

ABSTRACTA major challenge in developing computer models for crevice corrosion lies in fabricating appropriate experimental crevice samples. The geometry and dimensions of these samples must be controlled to a high order of precision in order to be amenable for comparison to computational models. In this work we report an effort to construct crevice samples with rigorously defined dimensions by using microfabrication techniques developed for microelectromechanical systems (MEMS). These techniques include microfabrication with SU- 8, electroplating, and other standard semiconductor device fabrication techniques as well. The crevice substrates contain one-dimensional arrays of metal electrodes to be studied, which are isolated by walls of SU-8. The electrodes have individual electrical connections so that spatial information of the in-situ corrosion process can be obtained. The crevice formers with SU-8 posts were coupled to crevice substrates to maintain a uniform crevice gap. Further, crevice formers with regular rectangular subcrevices were fabricated to study the roles of subcrevices in crevice corrosion.

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Integration of Spatial Information in Hyperspectral Imaging for Real Time Quality Control in an Andalusite Processing Line

Lecture Notes in Computer Science - Knowledge-Based Intelligent Information and Engineering Systems ◽

10.1007/11893011_38 ◽

2006 ◽

pp. 292-299

Author(s):

A. Prieto ◽

F. Bellas ◽

F. López-Peña ◽

R. J. Duro

Keyword(s):

Quality Control ◽

Real Time ◽

Hyperspectral Imaging ◽

Spatial Information ◽

Processing Line

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Multi-step real-time wind speed prediction based on convolution memory network

Wind Engineering ◽

10.1177/0309524x21998266 ◽

2021 ◽

pp. 0309524X2199826

Author(s):

Guowei Cai ◽

Yuqing Yang ◽

Chao Pan ◽

Dian Wang ◽

Fengjiao Yu ◽

...

Keyword(s):

Feature Extraction ◽

Wind Speed ◽

Real Time ◽

Wind Power ◽

Spatial Correlation ◽

Prediction Accuracy ◽

Spatial Information ◽

Spatial Association ◽

Spatial Feature ◽

Time Prediction

Multi-step real-time prediction based on the spatial correlation of wind speed is a research hotspot for large-scale wind power grid integration, and this paper proposes a multi-location multi-step wind speed combination prediction method based on the spatial correlation of wind speed. The correlation coefficients were determined by gray relational analysis for each turbine in the wind farm. Based on this, timing-control spatial association optimization is used for optimization and scheduling, obtaining spatial information on the typical turbine and its neighborhood information. This spatial information is reconstructed to improve the efficiency of spatial feature extraction. The reconstructed spatio-temporal information is input into a convolutional neural network with memory cells. Spatial feature extraction and multi-step real-time prediction are carried out, avoiding the problem of missing information affecting prediction accuracy. The method is innovative in terms of both efficiency and accuracy, and the prediction accuracy and generalization ability of the proposed method is verified by predicting wind speed and wind power for different wind farms.

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A Set of Integral Grid-Coding Algebraic Operations Based on GeoSOT-3D

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi10070489 ◽

2021 ◽

Vol 10 (7) ◽

pp. 489

Author(s):

Kaihua Hou ◽

Chengqi Cheng ◽

Bo Chen ◽

Chi Zhang ◽

Liesong He ◽

...

Keyword(s):

Real Time ◽

Spatial Information ◽

Data Retrieval ◽

Geospatial Data ◽

Algebraic Operation ◽

Real Time Processing ◽

C Language ◽

Time Processing ◽

Binary Operations ◽

Set Operations

As the amount of collected spatial information (2D/3D) increases, the real-time processing of these massive data is among the urgent issues that need to be dealt with. Discretizing the physical earth into a digital gridded earth and assigning an integral computable code to each grid has become an effective way to accelerate real-time processing. Researchers have proposed optimization algorithms for spatial calculations in specific scenarios. However, a complete set of algorithms for real-time processing using grid coding is still lacking. To address this issue, a carefully designed, integral grid-coding algebraic operation framework for GeoSOT-3D (a multilayer latitude and longitude grid model) is proposed. By converting traditional floating-point calculations based on latitude and longitude into binary operations, the complexity of the algorithm is greatly reduced. We then present the detailed algorithms that were designed, including basic operations, vector operations, code conversion operations, spatial operations, metric operations, topological relation operations, and set operations. To verify the feasibility and efficiency of the above algorithms, we developed an experimental platform using C++ language (including major algorithms, and more algorithms may be expanded in the future). Then, we generated random data and conducted experiments. The experimental results show that the computing framework is feasible and can significantly improve the efficiency of spatial processing. The algebraic operation framework is expected to support large geospatial data retrieval and analysis, and experience a revival, on top of parallel and distributed computing, in an era of large geospatial data.

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A multi-magneto-inductive sensor array system for real-time magnetic field imaging of ferromagnetic targets

Review of Scientific Instruments ◽

10.1063/5.0039894 ◽

2021 ◽

Vol 92 (3) ◽

pp. 035113

Author(s):

Huan Liu ◽

Changfeng Zhao ◽

Xiaobin Wang ◽

Zehua Wang ◽

Jian Ge ◽

...

Keyword(s):

Magnetic Field ◽

Real Time ◽

Sensor Array ◽

Inductive Sensor ◽

Magnetic Field Imaging ◽

Field Imaging

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Metal Oxide Nanorods-Based Sensor Array for Selective Detection of Biomarker Gases

Sensors ◽

10.3390/s21051922 ◽

2021 ◽

Vol 21 (5) ◽

pp. 1922

Author(s):

Gwang Su Kim ◽

Yumin Park ◽

Joonchul Shin ◽

Young Geun Song ◽

Chong-Yun Kang

Keyword(s):

Real Time ◽

Sensor Array ◽

High Sensitivity ◽

Gas Analysis ◽

Diagnostic Methods ◽

Real Time Monitoring ◽

Non Invasive ◽

Sensitivity And Selectivity ◽

Breath Gas Analysis ◽

Angle Method

The breath gas analysis through gas phase chemical analysis draws attention in terms of non-invasive and real time monitoring. The array-type sensors are one of the diagnostic methods with high sensitivity and selectivity towards the target gases. Herein, we presented a 2 × 4 sensor array with a micro-heater and ceramic chip. The device is designed in a small size for portability, including the internal eight-channel sensor array. In2O3 NRs and WO3 NRs manufactured through the E-beam evaporator’s glancing angle method were used as sensing materials. Pt, Pd, and Au metal catalysts were decorated for each channel to enhance functionality. The sensor array was measured for the exhaled gas biomarkers CH3COCH3, NO2, and H2S to confirm the respiratory diagnostic performance. Through this operation, the theoretical detection limit was calculated as 1.48 ppb for CH3COCH3, 1.9 ppt for NO2, and 2.47 ppb for H2S. This excellent detection performance indicates that our sensor array detected the CH3COCH3, NO2, and H2S as biomarkers, applying to the breath gas analysis. Our results showed the high potential of the gas sensor array as a non-invasive diagnostic tool that enables real-time monitoring.

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