Chronoamperometry with Room-Temperature Ionic Liquids: Sub-Second Inference Techniques

TL;DR

This paper introduces a mathematical regression method that reduces chronoamperometry measurement times to under one second in ionic liquids, enabling faster electrochemical analysis without hardware changes.

Contribution

A novel inference algorithm that predicts steady-state electrochemical parameters from sub-second transient data in ionic liquids.

Findings

Reduces measurement window from 1-4 seconds to under 1 second.

Maintains accuracy comparable to standard techniques.

Applicable to rapid electrochemical sensing and analysis.

Abstract

Chronoamperometry (CA) is a fundamental electrochemical technique used for quantifying redox-active species. However, in room-temperature ionic liquids (RTILs), the high viscosity and slow mass transport often lead to extended measurement durations. This paper presents a novel mathematical regression approach that reduces CA measurement windows to under 1 second, significantly faster than previously reported methods, which typically require 1-4 seconds or longer. By applying an inference algorithm to the initial transient current response, this method accurately predicts steady-state electrochemical parameters without requiring additional hardware modifications. The approach is validated through comparison with standard chronoamperometric techniques and is demonstrated to maintain reasonable accuracy while dramatically reducing data acquisition time. The implications of this technique are explored in analytical chemistry, sensor technology, and battery science, where rapid electrochemical quantification is critical. Our technique is focused on enabling faster multiplexing of chronoamperometric measurements for rapid olfactory and electrochemical analysis.