Complementary Metal-Oxide-Semiconductor Potentiometric Field-Effect Transistor Array Platform Using Sensor Learning for Multi-ion Imaging
Complementary Metal-Oxide-Semiconductor Potentiometric Field-Effect Transistor Array Platform Using Sensor Learning for Multi-ion Imaging
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DOI：
10.1021/acs.analchem.9b05836
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发表时间：
2020-04-07
影响因子：
7.4
通讯作者：
Georgiou, Pantelis
中科院分区：
文献类型：
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作者：
Moser, Nicolas;Leong, Chi Leng;Georgiou, Pantelis
这项工作描述了一个1024离子敏感场效应晶体管（ISFET）的阵列，使用传感器学习技术进行多离子成像，同时检测钾，钠，钙和氢。在ISFET阵列芯片的表面上沉积Anal[特异性离子载体膜，产生对K+、Na+或Ca2+具有准能斯特灵敏度的像素。未涂覆的像素显示来自标准Si3N4钝化层的pH敏感性。然后通过诱导单离子浓度的变化并测量所有像素的响应来训练平台。传感器学习依赖于离线训练算法，包括k均值聚类和基于密度的空间聚类，以产生膜映射和每个像素对目标电解质的灵敏度。我们证明了多离子成像，每个离子的平均误差分别为3.7%（K+），4.6%（Na+）和1.8%（pH值），而Ca2+引起的误差更大，为24.2%，因此被包括在内，以证明多功能性。我们用脑透析液样本验证了该平台，并通过与金标准光谱技术进行比较来展示阅读。
This work describes an array of 1024 ion-sensitive field-effect transistors (ISFETs) using sensor-learning techniques to perform multi-ion imaging for concurrent detection of potassium, sodium, calcium, and hydrogen. Anal[pecific ionophore membranes are deposited on the surface of the ISFET array chip, yielding pixels with quasi-Nernstian sensitivity to K+, Na+, or Ca2+. Uncoated pixels display pH sensitivity from the standard Si3N4 passivation layer. The platform is then trained by inducing a change in single-ion concentration and measuring the responses of all pixels. Sensor learning relies on offline training algorithms including k-means clustering and density-based spatial clustering of applications with noise to yield membrane mapping and sensitivity of each pixel to target electrolytes. We demonstrate multi-ion imaging with an average error of 3.7% (K+), 4.6% (Na+), and 1.8% (pH) for each ion, respectively, while Ca2+ incurs a larger error of 24.2% and hence is included to demonstrate versatility. We validate the platform with a brain dialysate fluid sample and demonstrate reading by comparing with a gold-standard spectrometry technique.