Gast ::
| Hauptseite > Publikationsdatenbank > Model-based process design of a ternary protein separation using multi-step gradient ion-exchange SMB chromatography > print |
| Hauptseite > Publikationsdatenbank > Model-based process design of a ternary protein separation using multi-step gradient ion-exchange SMB chromatography > print |
| 001 | 875084 | ||
| 005 | 20210113100813.0 | ||
| 024 | 7 | _ | |a 10.1016/j.compchemeng.2020.106851 |2 doi |
| 024 | 7 | _ | |a 0098-1354 |2 ISSN |
| 024 | 7 | _ | |a 1873-4375 |2 ISSN |
| 024 | 7 | _ | |a 2128/24983 |2 Handle |
| 024 | 7 | _ | |a WOS:000538049100009 |2 WOS |
| 037 | _ | _ | |a FZJ-2020-01793 |
| 082 | _ | _ | |a 660 |
| 100 | 1 | _ | |a He, Qiao-Le |0 P:(DE-Juel1)165710 |b 0 |
| 245 | _ | _ | |a Model-based process design of a ternary protein separation using multi-step gradient ion-exchange SMB chromatography |
| 260 | _ | _ | |a Amsterdam [u.a.] |c 2020 |b Elsevier Science |
| 336 | 7 | _ | |a article |2 DRIVER |
| 336 | 7 | _ | |a Output Types/Journal article |2 DataCite |
| 336 | 7 | _ | |a Journal Article |b journal |m journal |0 PUB:(DE-HGF)16 |s 1610473283_22196 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a ARTICLE |2 BibTeX |
| 336 | 7 | _ | |a JOURNAL_ARTICLE |2 ORCID |
| 336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
| 520 | _ | _ | |a Model-based process design of ion-exchange simulated moving bed (iex-smb) chromatography for center-cut separation of proteins is studied. Use of nonlinear binding models that describe more accurate adsorption behaviors of macro-molecules could make it impossible to utilize triangle theory to obtain operating parameters. Moreover, triangle theory provides no rules to design salt profiles in iex-smb. In the modeling study here, proteins (i.e., ribonuclease, cytochrome and lysozyme) on chromatographic columns packed with strong cation-exchanger SP Sepharose FF is used as an example system. The general rate model with steric mass-action kinetics was used; two closed-loop iex-smb network schemes were investigated (i.e., cascade and eight-zone schemes). Performance of the iex-smb schemes was examined with respect to multi-objective indicators (i.e., purity and yield) and productivity, and compared to a single column batch system with the same amount of resin utilized. A multi-objective sampling algorithm, Markov Chain Monte Carlo (mcmc), was used to generate samples for constructing Pareto optimal fronts. mcmc serves on the sampling purpose, which is interested in sampling the Pareto optimal points as well as those near Pareto optimal. Pareto fronts of the three schemes provide full information on the trade-off between the conflicting indicators, purity and yield here. The results indicate that the cascade iex-smb scheme and the integrated eight-zone iex-smb scheme have similar performance and that both outperforms the single column batch system. |
| 536 | _ | _ | |a 583 - Innovative Synergisms (POF3-583) |0 G:(DE-HGF)POF3-583 |c POF3-583 |f POF III |x 0 |
| 588 | _ | _ | |a Dataset connected to CrossRef |
| 700 | 1 | _ | |a von Lieres, Eric |0 P:(DE-Juel1)129081 |b 1 |u fzj |
| 700 | 1 | _ | |a Sun, Zhaoxi |0 P:(DE-Juel1)173771 |b 2 |
| 700 | 1 | _ | |a Zhao, Liming |0 P:(DE-HGF)0 |b 3 |e Corresponding author |
| 773 | _ | _ | |a 10.1016/j.compchemeng.2020.106851 |g p. 106851 - |0 PERI:(DE-600)1499971-7 |p 106851 |t Computers & chemical engineering |v 138 |y 2020 |x 0098-1354 |
| 856 | 4 | _ | |u https://juser.fz-juelich.de/record/875084/files/1910.05568.pdf |y Published on 2020-04-13. Available in OpenAccess from 2022-04-13. |
| 856 | 4 | _ | |u https://juser.fz-juelich.de/record/875084/files/1910.05568.pdf?subformat=pdfa |x pdfa |y Published on 2020-04-13. Available in OpenAccess from 2022-04-13. |
| 909 | C | O | |o oai:juser.fz-juelich.de:875084 |p openaire |p open_access |p VDB |p driver |p dnbdelivery |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 1 |6 P:(DE-Juel1)129081 |
| 913 | 1 | _ | |a DE-HGF |b Key Technologies |l Key Technologies for the Bioeconomy |1 G:(DE-HGF)POF3-580 |0 G:(DE-HGF)POF3-583 |3 G:(DE-HGF)POF3 |2 G:(DE-HGF)POF3-500 |4 G:(DE-HGF)POF |v Innovative Synergisms |x 0 |
| 914 | 1 | _ | |y 2020 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0200 |2 StatID |b SCOPUS |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1160 |2 StatID |b Current Contents - Engineering, Computing and Technology |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0600 |2 StatID |b Ebsco Academic Search |
| 915 | _ | _ | |a Embargoed OpenAccess |0 StatID:(DE-HGF)0530 |2 StatID |
| 915 | _ | _ | |a JCR |0 StatID:(DE-HGF)0100 |2 StatID |b COMPUT CHEM ENG : 2017 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0150 |2 StatID |b Web of Science Core Collection |
| 915 | _ | _ | |a WoS |0 StatID:(DE-HGF)0110 |2 StatID |b Science Citation Index |
| 915 | _ | _ | |a WoS |0 StatID:(DE-HGF)0111 |2 StatID |b Science Citation Index Expanded |
| 915 | _ | _ | |a IF < 5 |0 StatID:(DE-HGF)9900 |2 StatID |
| 915 | _ | _ | |a Peer Review |0 StatID:(DE-HGF)0030 |2 StatID |b ASC |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0300 |2 StatID |b Medline |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0199 |2 StatID |b Clarivate Analytics Master Journal List |
| 920 | 1 | _ | |0 I:(DE-Juel1)IBG-1-20101118 |k IBG-1 |l Biotechnologie |x 0 |
| 980 | _ | _ | |a journal |
| 980 | _ | _ | |a VDB |
| 980 | _ | _ | |a I:(DE-Juel1)IBG-1-20101118 |
| 980 | _ | _ | |a UNRESTRICTED |
| 980 | 1 | _ | |a FullTexts |
| Library | Collection | CLSMajor | CLSMinor | Language | Author |
|---|