Conductive polymer‐carbon black composites‐based sensor arrays for use in an electronic nose

Munoz, B. C.; Steinthal, Gregory; Sunshine, Steven A.

doi:10.1108/02602289910294745

Cited by 64 publications

(42 citation statements)

References 11 publications

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“…To better control the applications of these materials, it is necessary to develop fundamental knowledge about the factors that control the conductivity in composites. These can then be used to find and develop new composites used for new fields [1][2][3][4][5].…”

Section: Introductionmentioning

confidence: 99%

Electrical Conductivity Modeling of Polypropylene Composites Filled with Carbon Black and Acetylene Black

Merzouki

Haddaoui

2012

ISRN Polymer Science

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Composites of polypropylene filled with carbon black or acetylene black at different concentrations were prepared by melt mixing followed by compression molding. The influences of filler type and filler concentration on the composites conductivity were studied. It was found that the percolation threshold is located at a lower concentration in composites filled with the acetylene black, than that of the composites filled with carbon black. The model of Mamunya gives a fairly good agreement in the evaluation of the conductivity of polymeric composites loaded with carbon black or acetylene black, beyond the percolation threshold. The Boltzman equation was adopted to develop a model that represents more faithfully all results obtained. The expressions of the electrical conductivity, calculated with the model developed, are in good agreement with experimental results for the entire concentration range studied in linear or semilogarithmic scale.

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Section: Introductionmentioning

confidence: 99%

Electrical Conductivity Modeling of Polypropylene Composites Filled with Carbon Black and Acetylene Black

Merzouki

Haddaoui

2012

ISRN Polymer Science

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“…However, recent advances in odor-sensing technology, signal processing, and diagnostic algorithms have created chemical sensing and identification devices called "electronic noses," which promise to resurrect olfaction as an important diagnostic option. Electronic noses rely on arrays of chemical vapor sensors that respond to specific stereochemical characteristics of an odorant molecule, particularly volatile organic compounds (VOCs) (1). Multidimensional data obtained from the sensor array can be analyzed by statistical algorithms (e.g., principal components analysis, discriminant function analysis, factor analysis) or by structural algorithms (neural networks) to discriminate and identify odorant samples (2)(3)(4).…”

mentioning

confidence: 99%

Detection of Lung Cancer by Sensor Array Analyses of Exhaled Breath

Machado

Laskowski²,

Deffenderfer³

et al. 2005

Am J Respir Crit Care Med

527

429

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Rationale: Electronic noses are successfully used in commercial applications, including detection and analysis of volatile organic compounds in the food industry. Objectives: We hypothesized that the electronic nose could identify and discriminate between lung diseases, especially bronchogenic carcinoma. Methods: In a discovery and training phase, exhaled breath of 14 individuals with bronchogenic carcinoma and 45 healthy control subjects or control subjects without cancer was analyzed. Principal components and canonic discriminant analysis of the sensor data was used to determine whether exhaled gases could discriminate between cancer and noncancer. Discrimination between classes was performed using Mahalanobis distance. Support vector machine analysis was used to create and apply a cancer prediction model prospectively in a separate group of 76 individuals, 14 with and 62 without cancer. Main Results: Principal components and canonic discriminant analysis demonstrated discrimination between samples from patients with lung cancer and those from other groups. In the validation study, the electronic nose had 71.4% sensitivity and 91.9% specificity for detecting lung cancer; positive and negative predictive values were 66.6 and 93.4%, respectively. In this population with a lung cancer prevalence of 18%, positive and negative predictive values were 66.6 and 94.5%, respectively. Conclusion: The exhaled breath of patients with lung cancer has distinct characteristics that can be identified with an electronic nose. The results provide feasibility to the concept of using the electronic nose for managing and detecting lung cancer.

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“…Kompoziti sa metalnim puniocima su našli primenu kao elektromagnetna zaštita raču-nara i elektronske opreme, provodni lepkovi za elektronsku opremu, hladni lemovi, prekidači, materijali za rasipanje statičkog elektriciteta i u uređajima za zaštitu od naponskih udara [1, [13][14][15][16]. Takođe su pronašli brojne tehnološke primene kao samoregulacioni grejači, fototermalni optički snimači, hemijski senzori i elektronski nosevi, hemijski i elektrohemijski katalizatori i adsorbenti [17][18][19][20][21].…”

Section: Uvodunclassified

The effect of filler morphology on thermal characteristics of lignocellulose and metal powders composites

Pavlović¹,

Ćosović²,

Stajić-Trošić³

et al. 2015

Zas Mat

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Conductive polymer‐carbon black composites‐based sensor arrays for use in an electronic nose

Cited by 64 publications

References 11 publications

Electrical Conductivity Modeling of Polypropylene Composites Filled with Carbon Black and Acetylene Black

Electrical Conductivity Modeling of Polypropylene Composites Filled with Carbon Black and Acetylene Black

Detection of Lung Cancer by Sensor Array Analyses of Exhaled Breath

The effect of filler morphology on thermal characteristics of lignocellulose and metal powders composites

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