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Item type:Research Data, Access status: with files , Python code for: Modeling and Optimization of Complex Enzymatic Reactions: A Practical Guide for Biotechnologists and Bioprocess Engineers(2026-06-18); The Python codes accompanying the publication 'Modeling and Optimization of Complex Enzymatic Reactions: A Practical Guide for Biotechnologists and Bioprocess Engineers' are provided in this repository. The codes are used to solve the application example within the tutorial.Data Type: Software70 133 - Some of the metrics are blocked by yourconsent settings
Item type:Research Data, Access status: with files , GAMS code for: Reactor network synthesis of enzymatic cascades using superstructure optimization(2026-06-16); ; ; This repository contains the GAMS optimization scripts and include files used to implement a nonlinear programming (NLP) framework for superstructure-based reactor network synthesis. The framework handles flexible network configurations combining Continuous Stirred-Tank Reactors (CSTR) and tubular Cross-Flow Reactors (CFR) without relying on binary or integer choices. The implementation includes scripts for framework validation via the classical Van de Vusse reaction network and application to a multi-enzyme cascade following the oxidative Weimberg pathway.Data Type: Software30 22 - Some of the metrics are blocked by yourconsent settings
Item type:Research Data, Access status: with files , Python Scripts for: The Steam Barrier as a Design Constraint in Carbon Capture: Pathways to Low-Temperature Regeneration(2026-06-16)The Python scripts accompannying the publication: The steam barrier as a design constraint in carbon capture: pathways to low-temperature regeneration, submitted to Chemical Engineering and Processing - Process Intensification is presented here. The following scripts are included: Davies.py - it calculates the chemical and gas-liquid equilibrium using the semi-empirical Davies activity coefficient model. Debye_Hückel.py - it calculates the chemical and gas-liquid equilibrium using the Debye Hückel activity coefficient model. Ideal.py - it calculates the chemical and gas-liquid equilibrium assuming an ideal liquid phase. contour_creation.py - iterates accross different parameter values to create the contour plots of Figure 4 in the main article. water_exergy_vs_T_vs_p.py - performs the exergy calculations.Data Type: Software30 47 - Some of the metrics are blocked by yourconsent settings
Item type:Research Data, Access status: with files , CO₂-Driven pH Control in the Enzymatic Hydrolysis of Urea: A Coupled Modeling–Experiment ApproachThis dataset contains data from the investigation of CO₂ as a pH regulator in enzyme-catalyzed urea hydrolysis. It includes the analytical results of the experiments, the source code for simulations used in experimental design, and a descriptive README file explaining the contents of the dataset.Data Type: Experimental Data ; Data Type: Source Code77 140 - Some of the metrics are blocked by yourconsent settings
Item type:Research Data, Access status: with files , Supporting Information (Data & Models) for Publication: Development of an experimental setup and a validated model for a highly integrated biocatalytic process(2026-03-05)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 scriptData Type: Experimental Data ; Data Type: Source Code31 18 - Some of the metrics are blocked by yourconsent settings
Item type:Research Data, Access status: with files , Experimental data of the corresponding publication of Debottlenecking a 2-Phase Multi-Enzymatic Cascade by an Enzyme Membrane Reactor – Modelling and Experimental Validation(2025-08-11)This is an Excel file with the corresponding experimental measured values (concentrations) of the enzyme kinetic experimentsData Type: Experimental Data61 46 - Some of the metrics are blocked by yourconsent settings
Item type:Research Data, Access status: with files , EnzymeVision - Automated Kinetic Model Identification of Biocatalysts Under Process Conditions(2024-04-02); ; ; The python scripts are used to automatically control four syringe pumps (AL-1000, World Precision Instruments, Saragosa, USA) to perform continuous experiments (reduction of NAD+ with sodium formate to NADH) with a packed bed reactor with immobilized formate dehydrogenase. For monitoring, a flow through cuvette (170.700 QS, Hellma GmbH & Co. KG, Müllheim) is applied with a UV light source (DH-2000-BAL, Ocean Insight, Orlando, USA) and spectrometer (HR4000, Ocean Insight, Orlando, USA). The volume flow is monitored with a flow meter (SLF3S-0600F, Sensirion, Stäfa, Switzerland). The flow meter, spectrometer and daisy-chained syringe pumps are applied via USB to a Laptop. The MATLAB scource codes allow the optimal experimental planning for model discrimination and parameter estimation of the formate dehydrogenase. In addition, the evaluation of the model identifcation are produced in a comprehensive results report. Includes: Python scripts for the automated execution of experiments. Matlab scripts for the kinetic model identification and optimal experimental design.Data Type: Software155 201