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Pregled bibliografske jedinice broj: 1046991

Monitoring of cellulose oxidation level by electrokinetic phenomena and numeric prediction model


(Department of Textile Engineering, Faculty of Technology and Metallurgy, Ss. Cyril and Methodius University, Skopje, Republic of North Macedonia) Tarbuk, Anita; Grgić, Katia; Toshikj, Emilija; Domović, Daniel; Dimitrovski, Dejan; Dimova, Vesna; Jordanov, Igor
Monitoring of cellulose oxidation level by electrokinetic phenomena and numeric prediction model // Cellulose, 27 (2020), 3107-3119 doi:10.1007/s10570-020-03028-6 (međunarodna recenzija, članak, znanstveni)


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Naslov
Monitoring of cellulose oxidation level by electrokinetic phenomena and numeric prediction model

Autori
Tarbuk, Anita ; Grgić, Katia ; Toshikj, Emilija ; Domović, Daniel ; Dimitrovski, Dejan ; Dimova, Vesna ; Jordanov, Igor

Kolaboracija
Department of Textile Engineering, Faculty of Technology and Metallurgy, Ss. Cyril and Methodius University, Skopje, Republic of North Macedonia

Izvornik
Cellulose (0969-0239) 27 (2020); 3107-3119

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

Ključne riječi
Cotton ; oxidation system ; electrokinetic phenomena, machine learning

Sažetak
Cellulose with a low level of oxidation is suitable for producing stable long-lasting materials with high added value, while extensively oxidized once is applicable for disposable products. In our previous comprehensive research, the fundamental behavior of the cotton under the action of different oxidants has been explored. Different levels of oxidation, as well as the type of functional groups, have been achieved by properly selected oxidants while controlling their concentration and treatment time. In this research, the electrokinetic ζ-potential of KIO4 and TEMPO- oxidized cotton and the isoelectric point are measured by the streaming potential method, while the surface charge is calculated from the adsorbed cationic surfactant by the back- titration method. The results of electrokinetic phenomena are compared with the amount of created carboxyl groups determined by the calcium acetate method. The machine learning algorithms Waikato Environment for Knowledge Analysis for regression analysis is employed to develop models that make numeric predictions of the ζ-potential values based on the known number of carboxyl groups. The model with the correlation coefficient between the actual and the predicted value of ζ-potential is given for the first time.

Izvorni jezik
Engleski

Znanstvena područja
Tekstilna tehnologija



POVEZANOST RADA


Projekti:
HRZZ-UIP-2017-05-8780 - Bolničke zaštitne tekstilije (HPROTEX) (Flinčec Grgac, Sandra, HRZZ - UIP-2017-05) ( POIROT)

Ustanove:
Tekstilno-tehnološki fakultet, Zagreb

Profili:

Avatar Url Anita Tarbuk (autor)

Avatar Url Daniel Domović (autor)

Avatar Url Katia Grgić (autor)

Citiraj ovu publikaciju

(Department of Textile Engineering, Faculty of Technology and Metallurgy, Ss. Cyril and Methodius University, Skopje, Republic of North Macedonia) Tarbuk, Anita; Grgić, Katia; Toshikj, Emilija; Domović, Daniel; Dimitrovski, Dejan; Dimova, Vesna; Jordanov, Igor
Monitoring of cellulose oxidation level by electrokinetic phenomena and numeric prediction model // Cellulose, 27 (2020), 3107-3119 doi:10.1007/s10570-020-03028-6 (međunarodna recenzija, članak, znanstveni)
(Department of Textile Engineering, Faculty of Technology and Metallurgy, Ss. Cyril and Methodius University, Skopje, Republic of North Macedonia) (Department of Textile Engineering, Faculty of Technology and Metallurgy, Ss. Cyril and Methodius University, Skopje, Republic of North Macedonia) Tarbuk, Anita, Grgić, K., Toshikj, E., Domović, D., Dimitrovski, D., Dimova, V. & Jordanov, I. (2020) Monitoring of cellulose oxidation level by electrokinetic phenomena and numeric prediction model. Cellulose, 27, 3107-3119 doi:10.1007/s10570-020-03028-6.
@article{article, year = {2020}, pages = {3107-3119}, DOI = {10.1007/s10570-020-03028-6}, keywords = {Cotton, oxidation system, electrokinetic phenomena, machine learning}, journal = {Cellulose}, doi = {10.1007/s10570-020-03028-6}, volume = {27}, issn = {0969-0239}, title = {Monitoring of cellulose oxidation level by electrokinetic phenomena and numeric prediction model}, keyword = {Cotton, oxidation system, electrokinetic phenomena, machine learning} }
@article{article, year = {2020}, pages = {3107-3119}, DOI = {10.1007/s10570-020-03028-6}, keywords = {Cotton, oxidation system, electrokinetic phenomena, machine learning}, journal = {Cellulose}, doi = {10.1007/s10570-020-03028-6}, volume = {27}, issn = {0969-0239}, title = {Monitoring of cellulose oxidation level by electrokinetic phenomena and numeric prediction model}, keyword = {Cotton, oxidation system, electrokinetic phenomena, machine learning} }

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


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