An imprinted crystalline colloidal array chemical-sensing material for detection of trace diethylstilbestrol

The Analyst ◽  
2013 ◽  
Vol 138 (9) ◽  
pp. 2720 ◽  
Author(s):  
Na Sai ◽  
Baoan Ning ◽  
Guowei Huang ◽  
Yuntang Wu ◽  
Zhijiang Zhou ◽  
...  
Keyword(s):  
Chemical Sensing ◽  
Sensing Material ◽  
Crystalline Colloidal Array

A New Chemical Sensing Material for Ethanol Detection: Graphene-Like Film

2017 ◽  
pp. 59-65
Author(s):  
B. Alfano ◽  
M. Alfè ◽  
V. Gargiulo ◽  
T. Polichetti ◽  
E. Massera ◽  
...  
Keyword(s):  
Chemical Sensing ◽  
Sensing Material

Study on a Photonic Crystal Hydrogel Material for Chemical Sensing

2015 ◽  
Vol 14 (01n02) ◽  
pp. 1460025
Author(s):  
Jia-Yu Xu ◽  
Chun-Xiao Yan ◽  
Xiao-Chun Hu ◽  
Chao Liu ◽  
Hua-Min Tang ◽  
...  
Keyword(s):  
Photonic Crystal ◽  
Ionic Strength ◽  
Chemical Modification ◽  
Chemical Sensing ◽  
Electrostatic Interactions ◽  
Carboxyl Groups ◽  
Polystyrene Spheres ◽  
Crystalline Colloidal Arrays ◽  
Crystalline Colloidal Array ◽  
Monodisperse Polystyrene

There is intense interest in the applications of photonic crystal hydrogel materials for the detection of glucose, metal ions, organophosphates and so on. In this paper, monodisperse polystyrene spheres with diameters between 100 ~ 440 nm were synthesized by emulsion polymerization. Highly charged polystyrene spheres readily self-assembled into crystalline colloidal array because of electrostatic interactions. Photonic crystal hydrogel materials were formed by polymerization of acrylamide hydrogel around the crystalline colloidal arrays of polystyrene spheres. After chemical modification of hydrogel backbone with carboxyl groups, our photonic crystals hydrogel materials are demonstrated to be excellent in response to pH and ionic strength changes.

Polymerized crystalline colloidal array chemical-sensing materials for detection of lead in body fluids

2002 ◽  
Vol 373 (7) ◽  
pp. 632-638 ◽  
Author(s):  
Sanford A. Asher ◽  
Serban F. Peteu ◽  
Chad E. Reese ◽  
Ming Lin ◽  
David Finegold
Keyword(s):  
Chemical Sensing ◽  
Body Fluids ◽  
Crystalline Colloidal Array

Review of Microfluidic Devices for On-Chip Chemical Sensing

2016 ◽  
Vol 136 (6) ◽  
pp. 244-249
Author(s):  
Takahiro Watanabe ◽  
Fumihiro Sassa ◽  
Yoshitaka Yoshizumi ◽  
Hiroaki Suzuki
Keyword(s):  
Chemical Sensing ◽  
Microfluidic Devices ◽  
On Chip

scholarly journals Optimization of a Low-Power Chemoresistive Gas Sensor: Predictive Thermal Modelling and Mechanical Failure Analysis

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 783 ◽  
Author(s):  
Andrea Gaiardo ◽  
David Novel ◽  
Elia Scattolo ◽  
Michele Crivellari ◽  
Antonino Picciotto ◽  
...  
Keyword(s):  
Low Power ◽  
Failure Analysis ◽  
Gas Sensors ◽  
High Performance ◽  
Gas Sensing ◽  
Mechanical Failure ◽  
Sensing Applications ◽  
Theoretical Approaches ◽  
Sensing Material ◽  
Silicon Bulk

The substrate plays a key role in chemoresistive gas sensors. It acts as mechanical support for the sensing material, hosts the heating element and, also, aids the sensing material in signal transduction. In recent years, a significant improvement in the substrate production process has been achieved, thanks to the advances in micro- and nanofabrication for micro-electro-mechanical system (MEMS) technologies. In addition, the use of innovative materials and smaller low-power consumption silicon microheaters led to the development of high-performance gas sensors. Various heater layouts were investigated to optimize the temperature distribution on the membrane, and a suspended membrane configuration was exploited to avoid heat loss by conduction through the silicon bulk. However, there is a lack of comprehensive studies focused on predictive models for the optimization of the thermal and mechanical properties of a microheater. In this work, three microheater layouts in three membrane sizes were developed using the microfabrication process. The performance of these devices was evaluated to predict their thermal and mechanical behaviors by using both experimental and theoretical approaches. Finally, a statistical method was employed to cross-correlate the thermal predictive model and the mechanical failure analysis, aiming at microheater design optimization for gas-sensing applications.

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