dor_id: 4110144

506.#.#.a: Público

590.#.#.d: Los artículos enviados a la revista "Journal of Applied Research and Technology", se juzgan por medio de un proceso de revisión por pares

510.0.#.a: Scopus, Directory of Open Access Journals (DOAJ); Sistema Regional de Información en Línea para Revistas Científicas de América Latina, el Caribe, España y Portugal (Latindex); Indice de Revistas Latinoamericanas en Ciencias (Periódica); La Red de Revistas Científicas de América Latina y el Caribe, España y Portugal (Redalyc); Consejo Nacional de Ciencia y Tecnología (CONACyT); Google Scholar Citation

561.#.#.u: https://www.icat.unam.mx/

650.#.4.x: Ingenierías

336.#.#.b: article

336.#.#.3: Artículo de Investigación

336.#.#.a: Artículo

351.#.#.6: https://jart.icat.unam.mx/index.php/jart

351.#.#.b: Journal of Applied Research and Technology

351.#.#.a: Artículos

harvesting_group: RevistasUNAM

270.1.#.p: Revistas UNAM. Dirección General de Publicaciones y Fomento Editorial, UNAM en revistas@unam.mx

590.#.#.c: Open Journal Systems (OJS)

270.#.#.d: MX

270.1.#.d: México

590.#.#.b: Concentrador

883.#.#.u: https://revistas.unam.mx/catalogo/

883.#.#.a: Revistas UNAM

590.#.#.a: Coordinación de Difusión Cultural

883.#.#.1: https://www.publicaciones.unam.mx/

883.#.#.q: Dirección General de Publicaciones y Fomento Editorial

850.#.#.a: Universidad Nacional Autónoma de México

856.4.0.u: https://jart.icat.unam.mx/index.php/jart/article/view/690/663

100.1.#.a: Marzbali, Mojtaba Hedayati; Esmaieli, Mohamad

524.#.#.a: Marzbali, et al. (2017). Fixed bed adsorption of tetracycline on a mesoporous activated carbon: Experimental study and neuro-fuzzy modeling. Journal of Applied Research and Technology; Vol. 15 Núm. 5. Recuperado de https://repositorio.unam.mx/contenidos/4110144

245.1.0.a: Fixed bed adsorption of tetracycline on a mesoporous activated carbon: Experimental study and neuro-fuzzy modeling

502.#.#.c: Universidad Nacional Autónoma de México

561.1.#.a: Instituto de Ciencias Aplicadas y Tecnología, UNAM

264.#.0.c: 2017

264.#.1.c: 2019-06-14

653.#.#.a: Apricot shell; Tetracycline; Column adsorption; Machine learning; Neuro-fuzzy

506.1.#.a: La titularidad de los derechos patrimoniales de esta obra pertenece a las instituciones editoras. Su uso se rige por una licencia Creative Commons BY-NC-SA 4.0 Internacional, https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode.es, para un uso diferente consultar al responsable jurídico del repositorio por medio del correo electrónico gabriel.ascanio@icat.unam.mx

884.#.#.k: https://jart.icat.unam.mx/index.php/jart/article/view/690

001.#.#.#: 074.oai:ojs2.localhost:article/690

041.#.7.h: eng

520.3.#.a: This study investigates the use of synthesized mesoporous carbon in the fixed bed adsorption, as a promising process, to eliminate tetracycline from wastewater. In order to study the adsorptive capability of adsorbent, particles were embedded in a laboratory-scale Pyrex glass tube. An increase in initial concentration and decrease in bed height and flow rate led to the higher adsorption capacity. The highest bed capacity of 76.97 mg g?1 was obtained using 4 cm bed depth, 4 mL min?1 and 50 mg L?1 influent concentration. The initial part of breakthrough curve perfectly matched the Adams–Bohart model at all experimental conditions. However, it was anticipated that Yoon–Nelson model could predict the whole curve acceptably, the results showed an inaccurate fitting. Therefore, the adaptive neuro-fuzzy inference system (ANFIS) was used to predict the breakthrough curve using data series of adsorption experiments. This model indicated a good statistical prediction in terms of relative errors.

773.1.#.t: Journal of Applied Research and Technology; Vol. 15 Núm. 5

773.1.#.o: https://jart.icat.unam.mx/index.php/jart

022.#.#.a: ISSN electrónico: 2448-6736; ISSN: 1665-6423

310.#.#.a: Bimestral

264.#.1.b: Instituto de Ciencias Aplicadas y Tecnología, UNAM

doi: https://doi.org/10.1016/j.jart.2017.05.003

harvesting_date: 2023-11-08 13:10:00.0

856.#.0.q: application/pdf

file_creation_date: 2017-11-23 17:16:59.0

file_modification_date: 2017-11-23 11:55:34.0

file_creator: Mojtaba Hedayati Marzbali

file_name: 5d233ba43129345e5ca4a7b1d11ba309c8ce3d93ebee85465f8bc0846cff47ee.pdf

file_pages_number: 10

file_format_version: application/pdf; version=1.7

file_size: 1555583

last_modified: 2023-11-08 13:00:00

license_url: https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode.es

license_type: by-nc-sa

No entro en nada

No entro en nada 2

Artículo

Fixed bed adsorption of tetracycline on a mesoporous activated carbon: Experimental study and neuro-fuzzy modeling

Marzbali, Mojtaba Hedayati; Esmaieli, Mohamad

Instituto de Ciencias Aplicadas y Tecnología, UNAM, publicado en Journal of Applied Research and Technology, y cosechado de Revistas UNAM

Licencia de uso

Procedencia del contenido

Cita

Marzbali, et al. (2017). Fixed bed adsorption of tetracycline on a mesoporous activated carbon: Experimental study and neuro-fuzzy modeling. Journal of Applied Research and Technology; Vol. 15 Núm. 5. Recuperado de https://repositorio.unam.mx/contenidos/4110144

Descripción del recurso

Autor(es)
Marzbali, Mojtaba Hedayati; Esmaieli, Mohamad
Tipo
Artículo de Investigación
Área del conocimiento
Ingenierías
Título
Fixed bed adsorption of tetracycline on a mesoporous activated carbon: Experimental study and neuro-fuzzy modeling
Fecha
2019-06-14
Resumen
This study investigates the use of synthesized mesoporous carbon in the fixed bed adsorption, as a promising process, to eliminate tetracycline from wastewater. In order to study the adsorptive capability of adsorbent, particles were embedded in a laboratory-scale Pyrex glass tube. An increase in initial concentration and decrease in bed height and flow rate led to the higher adsorption capacity. The highest bed capacity of 76.97 mg g?1 was obtained using 4 cm bed depth, 4 mL min?1 and 50 mg L?1 influent concentration. The initial part of breakthrough curve perfectly matched the Adams–Bohart model at all experimental conditions. However, it was anticipated that Yoon–Nelson model could predict the whole curve acceptably, the results showed an inaccurate fitting. Therefore, the adaptive neuro-fuzzy inference system (ANFIS) was used to predict the breakthrough curve using data series of adsorption experiments. This model indicated a good statistical prediction in terms of relative errors.
Tema
Apricot shell; Tetracycline; Column adsorption; Machine learning; Neuro-fuzzy
Idioma
eng
ISSN
ISSN electrónico: 2448-6736; ISSN: 1665-6423

Enlaces