The development of gas sensor array for selective detection of ammonia

Suprapto*, Gabriel Denis Devian, Yatim Lailun Ni'Mah

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review


Ammonia was known as a chemical marker that can be found in the urine of patients with chronic kidney disease. The ammonia detection, usually, based on spectrophotometric method that require sample preparation such as derivatization which was complex and time-consuming. Chromatographic method was very accurate, but the investment and operation of this method was relatively expensive. Therefore, research to detects ammonia using gas sensor array in two types of testing: qualitatively and quantitatively, was carried out. This study emphasizes that the combination of sensor array with cross selective and cross sensitive characteristics, namely MQ-3, MQ-4, MQ-6, and MQ-8 sensors, capable to qualitatively and quantitatively to determine ammonia. In the qualitative test, the research was carried out by injecting 100?μL of ammonia, acetone, ethanol, and acetic acid in a gas sensor array chamber with 10 replications. Clustering analysis such as Principal Component Analysis (PCA) and K-Means Clustering, shows that gas sensor array can distinguish ammonia from the other test compounds. The quantitative analysis was done by injecting ammonia: distilled water in four different ratios i.e., 25%, 50%, 75%, and 100% as much as 100?μL with 5 replications. PCA, Agglomerative Clustering, and Decision Tree Classifier show that the sensor array can detect the ammonia based on their ratio accurately.

Original languageEnglish
Article number020005
JournalAIP Conference Proceedings
Issue number1
Publication statusPublished - 21 Aug 2023
Event3rd International Conference on Chemistry and Material Science, IC2MS 2021 - Virtual, Online, Indonesia
Duration: 12 Oct 202113 Oct 2021


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