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Supporting Information (Data & Models) for Publication: Development of an experimental setup and a validated model for a highly integrated biocatalytic process
Citation Link: https://doi.org/10.15480/882.15908
Type
Experimental Data
Source Code
Version
1.0
Date Issued
2026-03-05
Data Collector
Language
English
Abstract
Supporting Information for the publication "Development of an experimental setup and a validated model for a highly integrated biocatalytic process" published at Chem & Bio Engineering
doi:
10.15480/882.15908
Created by:
Thomas Waluga (ORCID 0000-0001-5308-3338), Hamburg University of Technology, Institute of Process Systems Engineering
Francesca von Ziegner, Hamburg University of Technology, Institute of Process Systems Engineering
Created on:
2026-03-05
Related to:
Publication "Development of an experimental setup and a validated model for a highly integrated biocatalytic process" published at Chem & Bio Engineering (ACS)
Software used:
phyton
Hardware used:
Perkin Elmer Clarus 500® (PerkinElmer Inc.) gas chromatograph equipped with a 30 m SLB SUPELCO® (Supelco, Inc.) column with a 0.25 mm × 0.25 μm cross section
Research Context and Objective of Data Generation:
Within the framework of the associated DFG project (https://tore.tuhh.de/entities/funding/ba17805b-7d5c-4978-b6fb-642957cc6c16), a highly integrated process for the synthesis of cinnamic acid cinnamate was developed. The present dataset is associated with the aforementioned publication, which aims to validate the developed model.
Methods of Data Collection:
Concentration profiles were measured using gas chromatography (see hardware). Further details on the experimental conditions can be found in the respective files.
Description of the structure:
1. Process Model
Experimental data: Datasets for the determination of kinetic parameters for lipase
Model: Script for Matlab 2021b. Determination of kinetic parameters via spline interpolation with KineticDataLipase. Calculation of standard error for kinetic parameters with ErrorCalculation.
2. Model Validation
Experimental Data: Datasets for all 5 experiments in the miniplant
Model: Script for Python 3.9. Simulation with initial conditions from experiments and calculation of normalized residual mean squared error for simulation and experiment
Results: Results for all 5 experiments based on figure 3 in the script
doi:
10.15480/882.15908
Created by:
Thomas Waluga (ORCID 0000-0001-5308-3338), Hamburg University of Technology, Institute of Process Systems Engineering
Francesca von Ziegner, Hamburg University of Technology, Institute of Process Systems Engineering
Created on:
2026-03-05
Related to:
Publication "Development of an experimental setup and a validated model for a highly integrated biocatalytic process" published at Chem & Bio Engineering (ACS)
Software used:
phyton
Hardware used:
Perkin Elmer Clarus 500® (PerkinElmer Inc.) gas chromatograph equipped with a 30 m SLB SUPELCO® (Supelco, Inc.) column with a 0.25 mm × 0.25 μm cross section
Research Context and Objective of Data Generation:
Within the framework of the associated DFG project (https://tore.tuhh.de/entities/funding/ba17805b-7d5c-4978-b6fb-642957cc6c16), a highly integrated process for the synthesis of cinnamic acid cinnamate was developed. The present dataset is associated with the aforementioned publication, which aims to validate the developed model.
Methods of Data Collection:
Concentration profiles were measured using gas chromatography (see hardware). Further details on the experimental conditions can be found in the respective files.
Description of the structure:
1. Process Model
Experimental data: Datasets for the determination of kinetic parameters for lipase
Model: Script for Matlab 2021b. Determination of kinetic parameters via spline interpolation with KineticDataLipase. Calculation of standard error for kinetic parameters with ErrorCalculation.
2. Model Validation
Experimental Data: Datasets for all 5 experiments in the miniplant
Model: Script for Python 3.9. Simulation with initial conditions from experiments and calculation of normalized residual mean squared error for simulation and experiment
Results: Results for all 5 experiments based on figure 3 in the script
DDC Class
660: Chemistry; Chemical Engineering
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