Optimization of stripping voltammetric sensor by mixture design-artificial neural network-genetic algorithm for determination of trace copper(II) based on iodoquinol-carbon nanotube modified carbon paste electrode
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- 作者：Azizollah Nezhadalia ; b ; aziz_nezhadali@yahoo.com" class="auth_mail" title="E-mail the corresponding author ; aziz_nezhadali@pnu.ac.ir" class="auth_mail" title="E-mail the corresponding authorAuthor Vitae ; Samira Sadeghzadeha ; bAuthor Vitae
- 关键词：Differential pulse voltammetry ; Carbon paste electrode ; Copper (II) ; Genetic algorithm ; Artificial neural network
- 刊名：Sensors & Actuators: B. Chemical
- 出版年：2016
- 出版时间：1 March 2016
- 年：2016
- 卷：224
- 期：Complete
- 页码：134-142
- 全文大小：1006 K
文摘
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Multivariate optimization of electrode composition and pH of measurements.
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Application of ANN-GA for optimization of sensor response.
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Proposing an easy to prepare and cheap sensor to determine trace copper(II).
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Selective sensor to determine copper(II) in presence of some heavy metals.
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Solvent free method of trace copper(II) determination in some real samples.