Bio-inspired gas sensing: boosting performance with sensor optimization guided by “machine learning”

Potyrailo, Radislav A.; Brewer, Joleyn; Cheng, Baokai; Carpenter, Michael A.; Houlihan, Nora; Kolmakov, Andrei

doi:10.1039/d0fd00035c

Cited by 14 publications

(14 citation statements)

References 96 publications

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“…Through this technique, one can find a combination of optimal antigen sensors to diagnose Lyme disease, 616 find the best placement of electrodes on the skin, 616 as well as optimize the material, structural, and excitation characteristics of gas sensors. 639 Upon finding an optimal configuration, one must recollect new data, extract features, and retrain the model (Figure 41e). 620 This process can be repeated multiple times, performing a gradient-descent search as one refines the final experimental parameters.…”

Section: Model Selectionmentioning

confidence: 99%

Skin-Interfaced Wearable Sweat Sensors for Precision Medicine

Min

et al. 2023

Chem. Rev.

134

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Wearable sensors hold great potential in empowering personalized health monitoring, predictive analytics, and timely intervention toward personalized healthcare. Advances in flexible electronics, materials science, and electrochemistry have spurred the development of wearable sweat sensors that enable the continuous and noninvasive screening of analytes indicative of health status. Existing major challenges in wearable sensors include: improving the sweat extraction and sweat sensing capabilities, improving the form factor of the wearable device for minimal discomfort and reliable measurements when worn, and understanding the clinical value of sweat analytes toward biomarker discovery. This review provides a comprehensive review of wearable sweat sensors and outlines stateof-the-art technologies and research that strive to bridge these gaps. The physiology of sweat, materials, biosensing mechanisms and advances, and approaches for sweat induction and sampling are introduced. Additionally, design considerations for the system-level development of wearable sweat sensing devices, spanning from strategies for prolonged sweat extraction to efficient powering of wearables, are discussed. Furthermore, the applications, data analytics, commercialization efforts, challenges, and prospects of wearable sweat sensors for precision medicine are discussed.

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Section: Model Selectionmentioning

confidence: 99%

Skin-Interfaced Wearable Sweat Sensors for Precision Medicine

Min

et al. 2023

Chem. Rev.

134

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“…Various types of sensors, such as microring resonators and surface plasmon resonance-based sensors [29,30], have benefited from machine learning. Machine learning is employed to boost the selectivity of gas sensors [31] and improve the performance of low-cost and mobile plasmonic sensing platforms by reducing the inter-device variability [32].…”

Section: Introductionmentioning

confidence: 99%

Smart ring resonator–based sensor for multicomponent chemical analysis via machine learning

Li¹,

Zhang²,

Nguyễn³

et al. 2021

Photon. Res.

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“…It has been considered that by using sensor arrays with different characteristics, gas recognition results can be improved, which is a potential solution to this problem. (3,4) Polymer-based sensing materials are usually fabricated in the form of membranes. In addition to excellent adaptability with microstructure sensors, membrane sensors can also enhance the adsorption and desorption capabilities of aerosols, improving sensor sensitivity and rapid reuse capabilities.…”

Section: Introductionmentioning

confidence: 99%

Gas Sensor Array with Polymer-Carbon Glue Composite Structures for Neural Network Application

Yang¹,

Hsiao²

2021

Sensors and Materials

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In this study, we focus on the gas sensor array with semiconductor and neural network applications. Two different sensing membranes, namely, diluted conductive water-soluble carbon glue and polymer-carbon glue stacked membranes, were used for experiments to compare the differences and correlations between multiple polymers and multiple gases. In the experiments, the reactions of 13 different polymers with five gases (air, ethanol, CO, NO 2 , and NH 3 ) were tested. A set of sixteen array sensors with a line width of 50 µm and a sensing diameter of 3 mm were used, and such sensors were coated with a 300-nm-thick aluminum-doped zinc oxide (AZO) layer on the wafer surface. The gas sensitivity obtained using various polymers dripped on the sensing area was tested, and the sensitivity of small low-energy heterogeneous gassensing elements is discussed. It is concluded that the various gases considered have good separation properties and excellent selectivity and reproducibility. Among the two different sensing membranes, the gas reaction ratio of (ΔR/R) max = 149% is the most prominent relative to the resistance of carbon glue in reference to the air baseline; as a result, the carbon membrane showed a higher gas sensitivity than the polymer-carbon membrane.

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Bio-inspired gas sensing: boosting performance with sensor optimization guided by “machine learning”

Abstract: Existing sensors for gaseous species often degrade their performance because of the loss of the measurement accuracy in the presence of interferences. Thus, new sensing approaches are required with improved...

Cited by 14 publications

References 96 publications

Skin-Interfaced Wearable Sweat Sensors for Precision Medicine

Skin-Interfaced Wearable Sweat Sensors for Precision Medicine

Smart ring resonator–based sensor for multicomponent chemical analysis via machine learning

Gas Sensor Array with Polymer-Carbon Glue Composite Structures for Neural Network Application

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