Aqueous Ammonia Sensor with Neuromorphic Detection

Abstract A hybrid inorganic–organic neuromorphic sensor utilizing a thin film zinc oxide (ZnO) detector with organic neuromorphic pre‐processing is developed to quantify ammonia in aqueous environments, including biological analytes. Impedimetric ZnO sensor, connected to an organic somatic circuit,...

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Main Authors: Kateryna Vyshniakova, Mohammad Javad Mirshojaeian Hosseini, Huiwen Bai, Masoome Fatahi, Victor Marco Rocha Malacco, Shawn S Donkin, Richard M Voyles, Robert A. Nawrocki
Format: Article
Language:English
Published: Wiley-VCH 2024-12-01
Series:Advanced Electronic Materials
Subjects:
Online Access:https://doi.org/10.1002/aelm.202400509
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author Kateryna Vyshniakova
Mohammad Javad Mirshojaeian Hosseini
Huiwen Bai
Masoome Fatahi
Victor Marco Rocha Malacco
Shawn S Donkin
Richard M Voyles
Robert A. Nawrocki
author_facet Kateryna Vyshniakova
Mohammad Javad Mirshojaeian Hosseini
Huiwen Bai
Masoome Fatahi
Victor Marco Rocha Malacco
Shawn S Donkin
Richard M Voyles
Robert A. Nawrocki
author_sort Kateryna Vyshniakova
collection DOAJ
description Abstract A hybrid inorganic–organic neuromorphic sensor utilizing a thin film zinc oxide (ZnO) detector with organic neuromorphic pre‐processing is developed to quantify ammonia in aqueous environments, including biological analytes. Impedimetric ZnO sensor, connected to an organic somatic circuit, reliably and accurately detects changes in electrical impedance to measure and quantify variations in the concentration of ammonia. The sensing mechanism of the ZnO thin film sensor is hypothesized to be the cause of the decrease in resistance of a solution with an increase in ammonia concentration. It is found that the surface oxide of the ZnO layer reacts with even very low concentrations of ammonia (NH3), leading to changes in resistivity. This makes the sensor capable of detecting ammonia in a range of concentrations between 0.0001 and 0.1 M. A neuromorphic circuit converts the analog change of ammonia concentration expressed as a change of sensor impedance to the digitized frequency of spikes. Detecting such a low ammonia concentration is critical for environmental monitoring and medical diagnosis. The digitized nature of neuromorphic signal pre‐processing makes it more resilient for signal transmission in the presence of noise and serves as a demonstration of “smart sensing.”
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issn 2199-160X
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publisher Wiley-VCH
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spelling doaj-art-56835e19fdea4ab3ba094691fc25930d2025-08-20T02:26:51ZengWiley-VCHAdvanced Electronic Materials2199-160X2024-12-011012n/an/a10.1002/aelm.202400509Aqueous Ammonia Sensor with Neuromorphic DetectionKateryna Vyshniakova0Mohammad Javad Mirshojaeian Hosseini1Huiwen Bai2Masoome Fatahi3Victor Marco Rocha Malacco4Shawn S Donkin5Richard M Voyles6Robert A. Nawrocki7School of Engineering Technology, Purdue Polytechnic Institute Purdue University West Lafayette IN 47906 United States of AmericaSchool of Engineering Technology, Purdue Polytechnic Institute Purdue University West Lafayette IN 47906 United States of AmericaSchool of Engineering Technology, Purdue Polytechnic Institute Purdue University West Lafayette IN 47906 United States of AmericaSchool of Engineering Technology, Purdue Polytechnic Institute Purdue University West Lafayette IN 47906 United States of AmericaDepartment of Animal Science, College of Agriculture Purdue University West Lafayette IN 47907 United States of AmericaDepartment of Animal Science, College of Agriculture Purdue University West Lafayette IN 47907 United States of AmericaSchool of Engineering Technology, Purdue Polytechnic Institute Purdue University West Lafayette IN 47906 United States of AmericaSchool of Engineering Technology, Purdue Polytechnic Institute Purdue University West Lafayette IN 47906 United States of AmericaAbstract A hybrid inorganic–organic neuromorphic sensor utilizing a thin film zinc oxide (ZnO) detector with organic neuromorphic pre‐processing is developed to quantify ammonia in aqueous environments, including biological analytes. Impedimetric ZnO sensor, connected to an organic somatic circuit, reliably and accurately detects changes in electrical impedance to measure and quantify variations in the concentration of ammonia. The sensing mechanism of the ZnO thin film sensor is hypothesized to be the cause of the decrease in resistance of a solution with an increase in ammonia concentration. It is found that the surface oxide of the ZnO layer reacts with even very low concentrations of ammonia (NH3), leading to changes in resistivity. This makes the sensor capable of detecting ammonia in a range of concentrations between 0.0001 and 0.1 M. A neuromorphic circuit converts the analog change of ammonia concentration expressed as a change of sensor impedance to the digitized frequency of spikes. Detecting such a low ammonia concentration is critical for environmental monitoring and medical diagnosis. The digitized nature of neuromorphic signal pre‐processing makes it more resilient for signal transmission in the presence of noise and serves as a demonstration of “smart sensing.”https://doi.org/10.1002/aelm.202400509inorganic–organic hybridneuromorphic pre‐processingorganic neuromorphicssensor
spellingShingle Kateryna Vyshniakova
Mohammad Javad Mirshojaeian Hosseini
Huiwen Bai
Masoome Fatahi
Victor Marco Rocha Malacco
Shawn S Donkin
Richard M Voyles
Robert A. Nawrocki
Aqueous Ammonia Sensor with Neuromorphic Detection
Advanced Electronic Materials
inorganic–organic hybrid
neuromorphic pre‐processing
organic neuromorphics
sensor
title Aqueous Ammonia Sensor with Neuromorphic Detection
title_full Aqueous Ammonia Sensor with Neuromorphic Detection
title_fullStr Aqueous Ammonia Sensor with Neuromorphic Detection
title_full_unstemmed Aqueous Ammonia Sensor with Neuromorphic Detection
title_short Aqueous Ammonia Sensor with Neuromorphic Detection
title_sort aqueous ammonia sensor with neuromorphic detection
topic inorganic–organic hybrid
neuromorphic pre‐processing
organic neuromorphics
sensor
url https://doi.org/10.1002/aelm.202400509
work_keys_str_mv AT katerynavyshniakova aqueousammoniasensorwithneuromorphicdetection
AT mohammadjavadmirshojaeianhosseini aqueousammoniasensorwithneuromorphicdetection
AT huiwenbai aqueousammoniasensorwithneuromorphicdetection
AT masoomefatahi aqueousammoniasensorwithneuromorphicdetection
AT victormarcorochamalacco aqueousammoniasensorwithneuromorphicdetection
AT shawnsdonkin aqueousammoniasensorwithneuromorphicdetection
AT richardmvoyles aqueousammoniasensorwithneuromorphicdetection
AT robertanawrocki aqueousammoniasensorwithneuromorphicdetection