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Potentiometry: Types of Electrodes

Potentiometry: Types of Electrodes

Reference electrodes serve as a stable reference point for potentiometric measurements, while indicator and working electrodes react to variations in the composition of a solution.
The Standard Hydrogen Electrode (SHE) is a widely used reference electrode that maintains zero potential across all temperatures. However, its need for a continuous hydrogen gas supply renders it impractical for everyday use.
An alternative to SHE is the Saturated Calomel Electrode (SCE). This electrode features an...

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Double-barreled and Concentric Microelectrodes for Measurement of Extracellular Ion Signals in Brain Tissue

Double-barreled and Concentric Microelectrodes for Measurement of Extracellular Ion Signals in Brain Tissue

Published on: September 5, 2015

A laboratory instrument for characterizing multiple microelectrodes.

Zhe Hu, Philip Troyk, Glenn DeMichele

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

|October 11, 2013

Summary

This summary is machine-generated.

This study introduces an automated Electrode Analyser System (EAS 2.0) for efficient microelectrode characterization. The system streamlines measurements and data processing, reducing time and errors in neural engineering applications.

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Published on: September 5, 2015

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Area of Science:

Neural Engineering
Biomedical Instrumentation

Background:

Characterizing microelectrodes in vivo is time-consuming and prone to errors.
Automated systems are needed for efficient, large-scale electrode analysis.

Purpose of the Study:

To develop an improved Electrode Analyser System (EAS 2.0).
To enhance performance, reduce size, and lower the cost of microelectrode characterization.

Main Methods:

Development of an automated lab instrument for microelectrode measurement.
Implementation of data processing for rapid electrode analysis.
Design of EAS 2.0 with improved performance and reduced footprint.

Main Results:

EAS 2.0 offers improved performance over EAS 1.0.
The system enables rapid characterization of numerous microelectrodes.
Reduced size and cost are key advancements in EAS 2.0.

Conclusions:

The EAS 2.0 provides an efficient and accurate solution for microelectrode characterization.
This automated system supports advancements in neural engineering research and manufacturing.