Pretražite po imenu i prezimenu autora, mentora, urednika, prevoditelja

Napredna pretraga

Pregled bibliografske jedinice broj: 426007

From isocratic data to a gradient elution retention model in IC: An artificial neural network approach


Bolanča, Tomislav; Cerjan Stefanović, Štefica; Ukić, Šime; Luša, Melita; Rogošić, Marko
From isocratic data to a gradient elution retention model in IC: An artificial neural network approach // Chromatographia, 70 (2009), 1-2; 15-20 doi:10.1365/s10337-009-1126-8 (međunarodna recenzija, članak, znanstveni)


CROSBI ID: 426007 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
From isocratic data to a gradient elution retention model in IC: An artificial neural network approach

Autori
Bolanča, Tomislav ; Cerjan Stefanović, Štefica ; Ukić, Šime ; Luša, Melita ; Rogošić, Marko

Izvornik
Chromatographia (0009-5893) 70 (2009), 1-2; 15-20

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
ion chromatography ; retention modeling ; artificial neural network

Sažetak
Gradient elution is used in ion chromatography to achieve rapid analysis with reasonable separation. Optimization and prediction of the gradient is clearly a multidimensional problem, however. One approach to prediction of gradient retention behavior is based on isocratic experimentation. In this work a gradient model for simultaneous prediction of the retention behavior of fluoride, chlorite, chloride, chlorate, nitrate, and sulfate ions, on the basis of isocratic experimental data, is proposed. An artificial neural network was used to predict isocratic results ; the network was optimized with regard to the number of data in the training set (25) and number of neurons in the hidden layer (6). A slight systematic error was observed in the isocratic prediction, but this did not effect gradient prediction. Good predictions were achieved for all the anions investigated (average error 1.79%). Deviations were somewhat higher for prediction of sulfate retention than for the other anions, probably because of the higher charge and larger size of sulfate in comparison with the other ions examined.

Izvorni jezik
Engleski

Znanstvena područja
Kemija, Kemijsko inženjerstvo



POVEZANOST RADA


Projekti:
MZOS-125-1252970-3005 - Biokeramički, polimerni i kompozitni nanostrukturirani materijali (Ivanković, Hrvoje, MZOS ) ( CroRIS)
MZOS-125-1253092-3004 - Procesi ionske izmjene u sustavu kvalitete industrijskih voda (Bolanča, Tomislav, MZOS ) ( CroRIS)

Ustanove:
Fakultet kemijskog inženjerstva i tehnologije, Zagreb

Poveznice na cjeloviti tekst rada:

doi dx.doi.org link.springer.com

Citiraj ovu publikaciju:

Bolanča, Tomislav; Cerjan Stefanović, Štefica; Ukić, Šime; Luša, Melita; Rogošić, Marko
From isocratic data to a gradient elution retention model in IC: An artificial neural network approach // Chromatographia, 70 (2009), 1-2; 15-20 doi:10.1365/s10337-009-1126-8 (međunarodna recenzija, članak, znanstveni)
Bolanča, T., Cerjan Stefanović, Š., Ukić, Š., Luša, M. & Rogošić, M. (2009) From isocratic data to a gradient elution retention model in IC: An artificial neural network approach. Chromatographia, 70 (1-2), 15-20 doi:10.1365/s10337-009-1126-8.
@article{article, author = {Bolan\v{c}a, Tomislav and Cerjan Stefanovi\'{c}, \v{S}tefica and Uki\'{c}, \v{S}ime and Lu\v{s}a, Melita and Rogo\v{s}i\'{c}, Marko}, year = {2009}, pages = {15-20}, DOI = {10.1365/s10337-009-1126-8}, keywords = {ion chromatography, retention modeling, artificial neural network}, journal = {Chromatographia}, doi = {10.1365/s10337-009-1126-8}, volume = {70}, number = {1-2}, issn = {0009-5893}, title = {From isocratic data to a gradient elution retention model in IC: An artificial neural network approach}, keyword = {ion chromatography, retention modeling, artificial neural network} }
@article{article, author = {Bolan\v{c}a, Tomislav and Cerjan Stefanovi\'{c}, \v{S}tefica and Uki\'{c}, \v{S}ime and Lu\v{s}a, Melita and Rogo\v{s}i\'{c}, Marko}, year = {2009}, pages = {15-20}, DOI = {10.1365/s10337-009-1126-8}, keywords = {ion chromatography, retention modeling, artificial neural network}, journal = {Chromatographia}, doi = {10.1365/s10337-009-1126-8}, volume = {70}, number = {1-2}, issn = {0009-5893}, title = {From isocratic data to a gradient elution retention model in IC: An artificial neural network approach}, keyword = {ion chromatography, retention modeling, artificial neural network} }

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus


Uključenost u ostale bibliografske baze podataka::


  • CA Search (Chemical Abstracts)


Citati:





    Contrast
    Increase Font
    Decrease Font
    Dyslexic Font