...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>American journal of applied sciences >Knowledge Representation of Ion-Sensitive Field-Effect Transistor Voltage Response for Potassium Ion Concentration Detection in Mixed Potassium/Ammonium Ion Solutions | Science Publications
【24h】

Knowledge Representation of Ion-Sensitive Field-Effect Transistor Voltage Response for Potassium Ion Concentration Detection in Mixed Potassium/Ammonium Ion Solutions | Science Publications

机译：钾/铵离子混合溶液中钾离子浓度检测的离子敏感场效应晶体管电压响应的知识表示科学出版物

获取原文
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

> Problem statement: The Ion-Sensitive Field-Effect Transistor (ISFET) is a metal-oxide field-effect transistor-based sensor that reacts to ionic activity at the electrolye/membrane/gate interface. The ionic sensor faces issue of selectivity from interfering ions that contribute to the sensor electrical response in mixed solutions. Approach: We present the training data collection of ISFET voltage response for the purpose of post-processing stage neural network supervised learning. The role of the neural network is to estimate the main ionic activity from the interfering ion contribution in mixed solutions given time-independent input voltages. In this work, potassium ion (K+) and ammonium ion (NH4+) ISFET response data are collected with readout interface circuit that maintains constant voltage and current bias levels to the ISFET drain-source terminals. Sample solutions are prepared by keeping the main ion concentration fixed while the activity of an interfering ion varied based on the fixed interference method. Results: Sensor demonstrates linear relationship to the ion concentration within detection limit but has low repeatability of 0.52 regression factor and 0.16 mean squared error between similarly repeated measurements. We find that referencing the voltage response to the sensor response in DIW prior to measurement significantly improves the repeatability by 15.5% for correlation and 98.3% for MSE. Demonstration of multilayer perceptron feed-forward neural network estimation of ionic concentration from the data collection shows a recognition of >0.8 regression factor. Conclusion: Time-independent DC voltage response of ISFET of the proposed setup can be used as training data for neural network supervised learning for the estimation of K+ in mixed K+/NH4+ solutions.
机译： > 问题陈述：离子敏感场效应晶体管（ISFET）是一种基于金属氧化物场效应晶体管的传感器，对电解质/膜上的离子活性起反应/ gate接口。离子传感器面临来自干扰离子的选择性问题，这些干扰离子在混合溶液中对传感器的电响应有贡献。 方法：我们介绍了ISFET电压响应的训练数据，以用于后期处理神经网络监督学习。神经网络的作用是根据给定时间独立的输入电压，根据混合溶液中的干扰离子贡献来估算主要离子活性。在这项工作中，使用读出接口电路收集钾离子（K + ）和铵离子（NH 4 + ）ISFET响应数据，以保持到ISFET漏源极端子的电压和电流偏置电平恒定。样品溶液是通过固定主要离子浓度，同时根据固定干扰方法使干扰离子的活性变化而制备的。 结果：传感器在检出限内显示出与离子浓度的线性关系，但在类似的重复测量之间具有0.52回归因子和0.16均方误差的低重复性。我们发现，在测量之前将电压响应与DIW中的传感器响应相关联，可将相关性的可重复性和MSE的可重复性分别提高15.5％和98.3％。多层感知器前馈神经网络从数据收集中估算离子浓度的演示显示了对> 0.8回归因子的识别。 结论：所提出装置的ISFET的与时间无关的直流电压响应可用作神经网络监督学习的训练数据，以估计混合K 中的K + > + / NH 4 + 解决方案。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号