This dataset highlights a specialized application of automation and optimization of infill structures using the Synera platform. By developing a Synera code to automatically apply infill structures to any model, the design process becomes significantly more efficient, allowing engineers to expedite the transition from concept to production. The practical relevance of this technology is demonstrated in its application to injection molds for bipolar plates within the Metal Injection Molding (MIM) process. Bipolar plates are critical components in fuel cells that require precisely manufactured parts to ensure structural integrity and optimal material usage. Furthermore, the use of Material Extrusion of Metals (MEX/M) processes emphasizes the interdisciplinary integration of additive and traditional manufacturing technologies. Insights from automated infill generation can thus be directly applied to the physical production of prototypes or end-use parts, showcasing the potential of Synera in design automation and the synergy between digital design and conventional manufacturing methods.

Experimental data corresponding to the manuscript "Chemical Interface Damping by Electrochemical Gold Oxidation". The dataset contains ellipsometric measurements and fits together with electrochemical potential and current curves that indicate the chemical itnerface damping effect originating from electrochemical oxidation of gold samples.

The dataset contains concentration data from the aldol reaction between benzaldehyde and glycine, catalyzed by L-threonine aldolase, yielding L-threo- and L-erythro-β-phenylserine. Measurements were performed using benchtop NMR and are used for progress curve analysis in the context of a scientific publication. The data are provided as supplementary information to this publication.

This 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.

This dataset contains the raw and processed experimental data, along with the analysis code, for the publication titled “A Method for Optical Quantification of Local Oxygen Limitations in Multiphase Bioreactors.” The data were obtained from optical measurements based on the reversible redox reaction of methylene blue in gas–liquid stirred tank bioreactors. They include time-resolved colourisation data used to derive spatial information on oxygen supply heterogeneities under varying hydrodynamic conditions (e.g. different impeller speeds). The dataset is structured into raw measurement files, processed results, and scripts for data evaluation and visualisation, enabling reproducibility and further analysis. (2026-04)

This dataset contains experimental and numerical results supporting a 30 L stirred-tank mixing-time study conducted at the Institute of Multiphase Flows, Hamburg University of Technology (TUHH). It includes raw and processed measurements from laboratory mixing experiments, M-Star LBM-LES simulations, and complementary Fluent CFD runs. The data are organized into subdirectories covering experimental probe time series, simulation outputs, post-processing scripts, and final compiled tables and figures used in the associated publication. Together, they enable the reproduction of key analyses on macro-scale flow dynamics, mixing-time evaluation, and grid-resolution sensitivity. All files are documented with folder-level README files explaining their structure, naming conventions, and relevance to the published results. Related Publication: https://doi.org/10.1016/j.compchemeng.2026.109615 Related Repository hosted by Darus: https://doi.org/10.18419/DARUS-5523

This artefact provides data and a detailed description of a wave flume experiment with and without an artifical Gaussian-shaped bathymetry. Provided a wave height measurements at four sensor points over time. Included in this data set are (1) the data itself in TXT format, (2) a video showing the waves in the flume in MP4 format and (3) a description of the experimental setup in PDF format.

This dataset contains the underlying measurement data and Python-based analysis scripts supporting the publication “Millimeter-Scale Lagrangian Sensor Spheres for Local State Monitoring in SMART Reactors: Towards Energy-Autonomous Operation”. It includes raw and intermediate data for selected quantitative evaluations, such as power consumption, transmission behavior, energy harvesting, and trajectory-related analysis. The dataset is intended to support traceability and practical reuse of the reported evaluation workflows. Manuscript text and final publication graphics are not the primary subject of this dataset release and should be consulted in the associated journal publication.

Over the past two decades, light sheet fluorescence microscopy has developed to a powerful tool for studies of dynamics in biological systems. In a new development, we apply light sheet fluorescence microscopy as a novel experimental measurement technology within the field of multiphase process engineering and fluid dynamics. The technology enables a number of novel studies of single- and multiphase transport phenomena on a microscopic scale. In the current publication, we introduce the first implementation of light sheet fluorescence microscopy in the field and demonstrate its applicability on one exemplary measurement of diffusive oxygen mass transfer from an oxygen bubble to degassed water. The results prove that such measurements can be conducted with a high spatial resolution with a submicron pixel pitch and enable precise studies on microscopic transport phenomena. Besides measurements of mass transfer, on which we lay the focus here, light sheet fluorescence microscopy further enables studies of fluid dynamics on a microscopic scale.

The TUHH Open Research (TORE) repository contains raw and processed data associated with the publication "Comprehensive study of 3D liquid flow fields in additively manufactured structures for SMART reactors using large-scale vertical magnetic resonance imaging and computational fluid dynamics". The dataset comprises experimental magnetic resonance imaging velocimetry data, numerical results from OpenFOAM simulations, and corresponding design files. The publication investigates the flow behaviour in additively manufactured TPMS structures using a large-bore vertical 3 T MRI system. Cross-validation between experimental measurements and numerical simulations is performed. Three different TPMS geometries are analysed within the Darcy-Forchheimer regime. The folder is accompanied by a ReadMe file and a separate folder structure file, which provide detailed information on file organisation, naming conventions, and their relation to the reported results.

The TUHH Open Research (TORE) repository entails the raw files and the result files for the publication "Wireless and passive pressure detection using magneto-mechanical resonances in process engineering". A custom-developed magneto-mechanical resonator (MMR) for wireless pressure measurement is investigated for potential applications in process engineering. The MMR sensor utilises changes in the resonance frequency caused by pressure on a flexible 3D printed membrane. The thickness of the printed membrane plays a crucial role in determining the performance and sensitivity of MMRs, and can be tailored to meet the requirements of specific applications. The study includes static and dynamic measurements to determine the pressure sensitivity and temporal resolution of the sensor. The results show a minimum sensitivity of 0.06 Hz/mbar and are in agreement with theoretical calculations and measurements. The maximum sensor readout frequency is 2 Hz in this study. Additionally, the temperature dependence of the sensor is investigated, revealing a significant dependence of the resonance frequency on temperature. The developed MMR offers a promising and versatile method for precise pressure measurements in process engineering environments.

Understanding how various ice shapes affect loads experienced by a ship hull or structure is crucial. Therefore, ice-structure interaction with a focus on the shape of the impacting ice was investigated. In the study drop tower experiments were conducted at the Institute of Ship Structural Design and Analysis of the Hamburg University of Technology to investigate ice impacts on a small scale. Ice specimens with diverse shapes (cylinder, cone, dome, wedge, ellipse, and other variations) were subjected to single impacts against a steel plate. Analysis revealed two main failure modes based on ice geometry, showcasing significant differences in load magnitude. Correlations between contact area, cone angle, specimen length to peak force, pressure, and energy were observed. The experimental setup, test matrix including the dimensions of the tested ice shapes and the data analysis are soon to be published. The experimental data are provided here. The data include the summed up force signal of the load cells and the displacement signal of the drop hammer. The data have been cropped to focus on the relevant portion around the impact load peak. Each file contains a single test run encompassing the time signal in seconds, force signal in kilo Newtons, and displacement signal in millimeters.

This data repository provides experimental datasets for biopolymer-based hydrogel particles under uniaxial compression, including monotonic and cyclic loading as well as stress-relaxation tests across multiple compression rates. It also includes the corresponding tetrapod-based discrete element method (DEM) simulations, along with simulation outputs and calibrated parameters, enabling direct experiment–simulation comparison. This upload contains all information required to reproduce the experimental analysis and DEM simulations reported in the related paper (DOI: ???). The accompanying README describes the file structure and documents the research context, methods, and measured variables in detail.

The datasets included in this work focus on the study of the imbibition dynamics of water in nanoporous Vycor glass. Specifically, this refers to the filling dynamics of water, driven by capillary forces, into a hydrophilic nanoporous Vycor glass sample (porous silica glass). The samples (2) used in these experiments are cylindrical monoliths. Both are identical (mean pore size , porosity), differing only in length. The experiments were designed to study capillary rise dynamics. Since Vycor glass is translucent, this can be directly observed by tracking the filling front via changes in the transparency of the samples (optical experiments). It can also be indirectly monitored by measuring properties of the sample that change proportionally to the filling front length. For this, we performed mass uptake experiments, measuring the changes in the mass of the sample during filling. We also used a high-precision dilatometer to measure changes in the length of the sample (strain) during imbibition (dilatometry).

A novel methodology combining theoretical and experimental techniques for analyzing agglomerate growth in fluidized bed granulators has been developed. The approach integrates (i) population balance modeling (PBM) of agglomerate growth, (ii) hydrodynamic modeling of gas–solid flow using CFD-DEM, (iii) surrogate modeling of particle flow behavior and agglomerate formation, (iv) the use of material properties as a collision success criterion and (v) experimental studies of agglomeration in a pilot scale fluidized bed. A simplified CFD-DEM model of the gas–solid flow was first developed, followed by a PBM for agglomeration. Fluidized bed agglomeration experiments with the common food ingredient maltodextrin revealed that agglomerate growth was influenced by the moisture-dependent glass transition of the material. The experimental data is used to calibrate and validate the PBM, demonstrating its high accuracy in predicting agglomerate growth dynamics.

This dataset is supplementary material to the dissertation titled: "Development of an Aerated High-Pressure Reactor for Biotechnological Applications". It includes the raw data from this study, the processed data, the corresponding MATLAB scripts, and the figures presented in the dissertation. Abstract: A key element in the development of sustainable chemical products is the biotechnologization of chemical synthesis processes. One approach to intensifying biotechnological processes to make them competitive with established synthesis methods involves utilizing the process parameter of pressure. This is particularly of interest for enzymatically catalyzed oxidation reactions, which often face limitations due to low oxygen solubility, resulting in mass transport limitations. This work presents and characterizes an aerated high-pressure batch reactor designed for the investigation of enzymatic systems at laboratory scale up to a pressure of 15.0 MPa. The characterisation is divided into three parts: Firstly, the use of optical sensors for online measurement of dissolved oxygen concentration under pressure is considered. Showing that the optical sensors used can reliably measure an oxygen concentration of up to 227 mg l−1 even under significant pressure fluctuations. The second section deals with the characterisation of mass transfer in the used high-pressure bubble column. Through optical access to the bubble column, the bubble size distribution is measured, and essential factors for mass transport, such as gas hold-up and interfacial area for mass transfer, are determined, highlighting in particular the influence of pressure on bubble diameter. The volumetric mass transfer coefficient is also determined using optical sensors. In the context of validation experiments, the results of the preceding sections are combined, and the functionality of the setup with immobilized glucose oxidase is demonstrated. It is shown that the reaction can be monitored using optical sensors and that process intensification can be achieved through increased oxygen availability. It also becomes evident that the mass transport performance of the used bubble column is not sufficient to circumvent mass transport limitation. Based on these results, a scaled-up reactor concept of 2 liters is finally presented, based on a compact and high-performance jet loop reactor.

The dataset presented here belong to an electrochemical impedance spectroscopy (EIS) study of mesoporous silicon in aqueous electrolyte solution (perchloric acid). The dataset contains EIS measurements performed at various static applied potentials so that a Mott-Schottky analysis of the electrode can be performed. Moreover, the dataset has an EIS study on a bulk silicon electrode, synthesized under equal conditions as the porous silicon electrode, so that a direect comparison between the two electrode types is possible.

Appendix containing experimental data

In this dataset, responsive hydrogels from N-isopropylacrylamide and itaconic acid are investiated for their responsive behavior and performance as enzyme carrier material. This dataset is the first of this study; in the proceeding study, the gels are employed as enzyme carriers in a smart reactor (DOI: https://doi.org/10.15480/882.16797)

In this dataset, responsive hydrogels from N-isopropylacrylamide and itaconic acid are employed as enzyme carriers in a smart reactor. This dataset is the second of this study; in the previous study, the gels investiated for their responsive behavior and performance as enzyme carrier material (DOI: https://doi.org/10.15480/882.16752).