Robotic-based Experimental Procedure for Colorimetric Gas Sensing Development

Summary

Here, we present a protocol to develop colorimetric gas sensors using a robotic-based Design-Build-Test-Learn (DBTL) approach. This protocol integrates high-throughput automation, machine learning, and multi-objective optimization to efficiently discover and optimize sensor formulations for detecting gases like CO₂, enabling rapid, cost-effective, and precise sensor development.

Abstract

This paper presents a robot-based experimental program aimed at developing an efficient and fast colorimetric gas sensor. The program employs an automated Design-Build-Test-learning (DBTL) approach, which optimizes the search process iteratively while optimizing multiple recipes for different concentration intervals of the gas. In each iteration, the algorithm generates a batch of recipe suggestions based on various acquisition functions, and with the increase in the number of iterations, the values of weighted objective function for each concentration interval significantly improve.

The DBTL method begins with parameter initialization, setting up the hardware and software environment. Baseline tests establish performance standards. Subsequently, the DBTL method designs the following round of optimization based on the proportion of recipes in each round and tests performance iteratively. Performance evaluation compares baseline data to assess the effectiveness of the DBTL method. If the performance improvement does not meet expectations, the method will be performed iteratively; if the objectives are achieved, the experiment concludes. The entire process maximizes system performance through the DBTL iterative optimization process.

Compared to the traditional manual developing process, the DBTL method adopted by this experimental process uses multi-objective optimization and various machine learning algorithms. After defining the upper and lower limits of component volume, the DBTL method dynamically optimizes iterative experiments to obtain the optimal ratio with the best performance. This method greatly improves efficiency, reduces costs, and performs more efficiently within the multi-formulation variable space when finding the optimal recipe.

Introduction

The practical applications of gas sensors are very extensive and have been used in various fields such as environmental monitoring, aerospace, and waste gas treatment^1,2,3. The working principle of gas sensors typically relies on multiple mechanisms, such as electrochemistry, gas chromatography, and optical. Among many detection mechanisms, one based on color change has evolved into an acid-base mechanism that stands out uniquely. Due to its low cost and simple application, it is widely used in the design of many portable and disposable gas sensors, such as CO₂ sen....

Protocol

1. Preliminary experiment (feasibility test)

NOTE: Based on Zhang's paper⁸, the relevant variables of chemical colorimetric sensors for the target gas, such as carbon dioxide, can be selected. Before performing the on-demand optimization of the colorimetric sensor formulations, a preliminary experiment using the following procedures can be conducted to establish the variable space.

1. Determine the concentration range of the target gas and establish a gas test configuration.
   NOTE: The concentration of the target gas within the gas test configuration increases linearly or exponenti....

Discussion

This article proposes an experimental design that can develop colorimetric gas sensors more quickly and accurately. This experimental process can be used to develop colorimetric sensors for various gases, such as humidity, CO₂, and ammonia^1,4,5. Through the method of this platform, it can meet the needs of users with various preferences, such as high sensitivity, low detection limit, required response time, considerin.......

Materials

Name	Company	Catalog Number	Comments
96-Well Deep Well Plate	NEST	NEST 2 mL 96-Well Deep Well Plate, V Bottom
96-Well PCR Plate	NEST	NEST 0.1 mL 96-Well PCR Plate
cresol red	sigma aldrich	1.05225	Dyes for colorimetric reagents
Ethyl cellulose	sigma aldrich	200689	Dyes for colorimetric reagents
Ethyl cellulose	Aladdin	E110670-100g	Additive
Industrial Camera	HKVision	MV-CS060-10UM/C-PRO	used for recording color changes
Liquid handler	Opentrons	OT2	liquid handler
Mass Flow Controller	ASERT	AST10-DLCMX-500C-042-A2B2-48VY	used in controlling analytes gas mixtures
m-cresol purple	sigma aldrich	1.05228	Dyes for colorimetric reagents
Opentrons OT-2 Tips	Opentrons	OT-2 Tips, 300µL
Opentrons OT-2 Tips	Opentrons	OT-2 Tips, 20µL
phenol red	sigma aldrich	1.07241	Dyes for colorimetric reagents
polyethylene glycol	sigma aldrich	P1458	Dyes for colorimetric reagents
PTFE film	Interstate Specialty Products	PM15M	PTFE mambrane
Tetrabutylammonium hydroxide	sigma aldrich	86854	Base for colorimetric reagents
thymol blue	sigma aldrich	1.08176	Dyes for colorimetric reagents