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Enregistrement W4285397882 · doi:10.1149/ma2022-01522137mtgabs

Nanocarbon Based Chemiresistive Detection of Monochloramine in Water

2022· article· en· W4285397882 sur OpenAlexaffabout
Md Ali Akbar, P. Ravi Selvaganapathy, Peter Kruse

Notice bibliographique

RevueECS Meeting Abstracts · 2022
Typearticle
Langueen
DomaineEngineering
ThématiqueBiosensors and Analytical Detection
Établissements canadiensMcMaster University
Organismes subventionnairesnon disponible
Mots-clésChloramineChemistryChlorineTitrationDisinfectantChloraminationAqueous solutionAmperometric titrationInorganic chemistryEnvironmental chemistryOrganic chemistry

Résumé

récupéré en direct d'OpenAlex

The use of chloramine as a disinfectant in water treatment plants is becoming popular due to its lower reactivity and higher stability than free chlorine. 1–3 Chloramines are produced by the reaction of free chlorine (HOCl, OCl - ) with nitrogen compounds to form monochloramine (NH 2 Cl), dichloramine (NHCl 2 ) or nitrogen trichloride (NCl 3 ), depending on pH and N/Cl ratio. 4 Dichloramine and nitrogen trichloride tend to create odour and taste problems in drinking water. Thus, only monochloramine is preferred for disinfection. Typically, 0.5-2 mg/L of monochloramine is maintained in the water distribution system. 5 Maintaining the concentration level of monochloramine is crucial to prevent pathogen growth in the drinking water. Currently, there is no direct method to measure chloramine. However, U.S. EPA-approved amperometric titration and colorimetric methods are available which can be used to measure total and free chlorine in aqueous media. 2 An amperometric titration method (SM 4500-Cl D) is capable of distinguishing 3 common forms of chlorine: Cl 2 / HOCl / OCl - , NH 2 Cl, and NHCl 2 . However, it fails at concentrations greater than 2 mg/L (as Cl 2 ). 2,3 Even though this method is not affected by common oxidizing agents, temperature changes, turbidity, and colour, it does require a greater degree of skill. Operationally simpler, N,N-diethyl-p-phenylenediamine (DPD) methods (ferrous and colorimetric) are used to measure free and total chlorine and then their subtraction gives the concentration of monochloramine, assuming no NHCl 2 and NCl 3 are present. DPD methods are subjected to interferences like copper, manganese (oxidized), iodide and chromate. 6 Additionally, the DPD method is not suitable for continuous monitoring of monochloramine which is essential in water distribution plants to maintain the appropriate concentration of disinfectant. 2,3,7 Here we demonstrate a chemiresistive sensor array for the continuous monitoring of chloramine in the water. Chemiresistive sensors are cheap, robust and use low power. These sensors detect an analyte through changes in the electronic properties of the transducing element. A nanocarbon network was airbrushed onto the frosted side of a microscope glass slide as the transducing element between two pencil trace contact patches. Copper tapes were placed on top of the pencil patches and then covered with a dielectric. 10 mV voltage was applied for the measurements, and the changes in resistance were measured as the analyte interacted with the transducing element. The surface of the nanocarbon network is functionalized with suitable dopant molecules by submerging the sensor in the molecule solution. This array of molecules will be able to capture the parameters to be able to classify the type of chloramine present in water. Fresh chloramine solution is prepared before each experiment by adding NH 4 Cl and NaOCl in Phosphate Buffered Saline (PBS). Sensor responses are recorded as positive current change with increasing concentrations of monochloramine. Here the hole density of the inherently p-doped substrate increases when exposed to monochloramine, and thereby resulting in increasing current. Sensors can be reset with ascorbic acid or water. Sensors were tested with 0.054 ppm to 1.437 ppm of monochloramine in pH 7.5 and 8.5. Functionalized sensor devices showed a considerably higher response than the unfunctionalized ones. The tap water sample was tested with the calibrated devices. We have therefore demonstrated a robust sensor array capable of continuously monitoring chloramine in aqueous media. References: T. L. Engelhardt and V. B. Malkov, Chlorination, chloramination and chlorine measurement, p. 1–67, (2015). US Environmental Protection Agency - Office of Water, Alternative disinfectants and oxidants Guidance manual , 1st Ed., p. 1–328, (Washington, DC) US Environmental Agency, (1999). S. H. Jenkins, Water Res. , 16, 1495–1496 (1982). T. H. Nguyen et al., Sensors Actuators, B Chem ., 187, 622–629 (2013). T. H. Nguyen et al., Sensors Actuators, B Chem. , 208, 622–627 (2015). Health Canada, Chloramines in drinking water (2019). World Health Organization, Guidelines for drinking-water quality: fourth edition incorporating the first addendum , 4th Ed + 1., Geneva: World Health Organization, (2017). Figure 1

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,232
Score d'incertitude au seuil0,317

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,007
Tête enseignante GPT0,187
Écart entre enseignants0,180 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2022
Routes d'admission2
Résumé présentoui

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