Enhancement of adsorptive removal efficiency of an anionic dye from aqueous solutions using carboxylic acid-modified mulberry leaves: Artificial neural network modeling, isotherm, and kinetics evaluation

MakaleAçık Erişim
  • SDG 6 · Temiz Su ve Sanitasyon
  • SDG 12 · Sorumlu Üretim ve Tüketim

Özet

Natural mulberry leaves and carboxylic acid-modified mulberry (Morus alba L.) leaves were used for the first time to scrutinize the effects of modification on the retention efficiency of an anionic dye (Remazol Brilliant Blue R (RBBR)) from aqueous solutions to suggest an economical and promising adsorbent for the treatment of dye-contaminated water. The characterization of the adsorbents was accomplished through common techniques including SEM, FTIR, and pHpzc determination. Several parameters studied in batch experiments pointed out that the initial pH of 2.0 and the contact time of 240 min were optimum conditions for all the developed RBBR uptake processes. An artificial neural network (ANN) model was applied to formulate a forecast model for the uptake efficiency of RBBR. The experimental data were assessed by different kinetic and isotherm models to explain the mechanism of the developed processes in more detail. Maximum monolayer adsorption capacities of natural mulberry leaves and acetic acid-, citric acid-, and oxalic acid-modified mulberry leaves were determined as 64.5, 95.2, 84.8, and 91.7 mg g1, respectively, by the Langmuir isotherm model. These results demonstrated that the modification with carboxylic acids significantly increases the anionic dye adsorption capacity of the mulberry leaves.

Anahtar Kelimeler

RDL Kalıcı Bağlantı (PID)
https://rdlopen.rawdatalibrary.net/r/gumushane/11539Resmi atıflarda kullanılan kalıcı adres
DOI
https://doi.org/10.2166/wh.2023.025Yayıncı resmi DOI adresi
Tam Kayıt
AlanDeğerDil
dc.contributor.authorDuran, Celal
dc.contributor.authorOzeken, Sengul Tugba
dc.contributor.authorCamoglu, Aslihan Yilmaz
dc.contributor.authorOzdes, Duygu
dc.date.accessioned2026-10-22T10:19:07.350177080Z
dc.date.available2026-10-22T10:19:07.350177080Z
dc.date.issued2023
dc.description.abstractNatural mulberry leaves and carboxylic acid-modified mulberry (Morus alba L.) leaves were used for the first time to scrutinize the effects of modification on the retention efficiency of an anionic dye (Remazol Brilliant Blue R (RBBR)) from aqueous solutions to suggest an economical and promising adsorbent for the treatment of dye-contaminated water. The characterization of the adsorbents was accomplished through common techniques including SEM, FTIR, and pHpzc determination. Several parameters studied in batch experiments pointed out that the initial pH of 2.0 and the contact time of 240 min were optimum conditions for all the developed RBBR uptake processes. An artificial neural network (ANN) model was applied to formulate a forecast model for the uptake efficiency of RBBR. The experimental data were assessed by different kinetic and isotherm models to explain the mechanism of the developed processes in more detail. Maximum monolayer adsorption capacities of natural mulberry leaves and acetic acid-, citric acid-, and oxalic acid-modified mulberry leaves were determined as 64.5, 95.2, 84.8, and 91.7 mg g1, respectively, by the Langmuir isotherm model. These results demonstrated that the modification with carboxylic acids significantly increases the anionic dye adsorption capacity of the mulberry leaves.
dc.description.sponsorshipKaradeniz Teknik Üniversitesi, KTU
dc.identifier.doi10.2166/wh.2023.025
dc.identifier.eissn1996-7829
dc.identifier.endpage883
dc.identifier.issn1477-8920
dc.identifier.issue7
dc.identifier.pmid37515559
dc.identifier.scopus2-s2.0-85165949478
dc.identifier.startpage869
dc.identifier.urihttps://rdlopen.rawdatalibrary.net/r/gumushane/11539
dc.identifier.volume21
dc.identifier.wosWOS:001015467600001
dc.language.isoen
dc.publisherIWA Publishing
dc.relation.ispartofJournal of Water and Health
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectadsorption
dc.subjectartificial neural network
dc.subjectisotherm
dc.subjectkinetics
dc.subjectmulberry leaves
dc.subjectRemazol brilliant blue R
dc.subject.classificationEnvironmental Sciences
dc.subject.classificationPublic, Environmental & Occupational Health
dc.subject.classificationMicrobiology
dc.subject.classificationWater Resources
dc.subject.classificationEnvironmental Sciences & Ecology
dc.subject.otherAdsorption
dc.subject.otherCarboxylic Acids
dc.subject.otherColoring Agents
dc.subject.otherHydrogen-Ion Concentration
dc.subject.otherKinetics
dc.subject.otherMorus
dc.subject.otherMorus alba
dc.subject.otherNeural Networks, Computer
dc.subject.otherPlant Leaves
dc.subject.otherThermodynamics
dc.subject.otherWater
dc.subject.otherWater Pollutants, Chemical
dc.subject.otheracetic acid
dc.subject.otheradsorbent
dc.subject.otheranion
dc.subject.otherbrilliant blue
dc.subject.othercitric acid
dc.subject.otheroxalic acid
dc.subject.othercarboxylic acid
dc.subject.othercoloring agent
dc.subject.otheraqueous solution
dc.subject.otherartificial neural network
dc.subject.otherdeciduous tree
dc.subject.otherdye
dc.subject.otherreaction kinetics
dc.subject.otheradsorption kinetics
dc.subject.otherArticle
dc.subject.otherchemical modification
dc.subject.otherchemisorption
dc.subject.othercontrolled study
dc.subject.otherdecolorization
dc.subject.otherFourier transform infrared spectroscopy
dc.subject.otherisotherm
dc.subject.othermodel
dc.subject.othermulberry
dc.subject.otherpH
dc.subject.otherplant leaf
dc.subject.otherscanning electron microscopy
dc.subject.otherwaste component removal
dc.subject.otherwater contamination
dc.subject.otherchemistry
dc.subject.otherwater pollutant
dc.titleEnhancement of adsorptive removal efficiency of an anionic dye from aqueous solutions using carboxylic acid-modified mulberry leaves: Artificial neural network modeling, isotherm, and kinetics evaluation
dc.typeArticle
dspace.entity.typePublication
rdl.citation.openalex4
rdl.citation.scopus4
rdl.citation.wos4
rdl.departmentGumushane Vocational School, Chemistry and Chemical Processing Technologies Department, Gumushane University, 29100 Gumushane, Türkiye
rdl.oa.statusgold
rdl.oa.urlhttps://iwaponline.com/jwh/article-pdf/doi/10.2166/wh.2023.025/1241308/jwh2023025.pdf
rdl.sdgSDG06
rdl.sdgSDG12
rdl.source.indexSCOPUS
rdl.source.indexWOS
rdl.source.indexPUBMED
rdl.wos.indexScience Citation Index Expanded (SCI-EXPANDED)