Research projects
Research area B: Process analysis and characterization
Research area B focuses on investigations into the model-based description of a complex wastewater system and metrological process analyses of physical mechanisms in P recovery from wastewater and sewage sludge. The physical properties of wastewater as a complex mixture of different, poorly specified substances are investigated by thermodynamic modeling using hybrid gray-box models with the application of machine learning methods (project B1). The basic elementary processes and complex mechanisms of adsorption and desorption of phosphates on the surfaces of the adsorber materials (from research area A) are investigated using molecular dynamic simulations (project B2). The influences of impurities and wastewater temperature are also considered. The knowledge gained from microscale mechanisms is transferred to models for the macroscopic description of the separation processes in P recovery in research area C. For the characterization of P-recovery processes in research areas C and D, special measurement techniques are being developed in research area B. On the one hand, 57Fe-Mössbauer spectroscopy is used to investigate microscopic mechanisms of precipitation reactions (project B3) and on the other hand, extinction spectroscopy is used for dispersity and kinetics analysis during precipitation and crystallization (project B4). The development of fluorescent phosphate sensors based on zinc complexes (project B5) enables detailed investigations of process kinetics and process control.
Supervisor: Prof. Fabian Jirasek
PhD: Zeno Romero
The thermodynamic modeling of complex mixtures is the basis for and challenge in developing processes for recovering valuable substances from wastewater. An understanding of the thermodynamic properties of the mixtures and the components they contain is a prerequisite for designing new processes or optimizing existing processes.
This project aims to develop thermodynamic models to describe complex mixtures containing both molecular substances and electrolytes as they occur in wastewater treatment processes. A particular focus will be the simulation of processes for phosphorus recovery from wastewater by crystallization. For this purpose, novel predictive thermodynamic models for electrolyte solutions will be developed by combining classical physical models with data-driven algorithms from machine learning to yield powerful hybrid models. Furthermore, the question of dealing with uncertainties, e.g., regarding incomplete knowledge of the composition of the mixtures (so-called poorly specified mixtures), will be addressed.
Supervisor: Jun.-Prof. Simon Stephan
PhD: Shaharyar Jamali
The behavior of phosphate ions on adsorbent surfaces is of central importance for the technical processes addressed in WERA for P recovery from wastewater.
In this project, the adsorption of phosphate on adsorbent surfaces will be studied using molecular simulations based on classical force fields, which provides insights into the elementary processes at the interface that are difficult to study by experiments. In a first step, a model for the aqueous phosphate solution bulk phase will be developed and the macroscopic properties obtained from that model will be compared to experimental data. Then, the model will be used for the prediction of adsorption and desorption processes on adsorbent surfaces to elucidate the interfacial structure and process kinematics.
Supervisor: Prof. Volker Schünemann
PhD: Hannah Akhtar
In this project, the decisive processes in phosphate precipitation with iron salts are to be tracked. A set-up is to be realized that allows samples for Mössbauer spectroscopy to be taken from an experimental reactor for precipitation and crystallization reactions of phosphates. The project focuses on precipitation reactions with FeCl3, FeSO4 and K2FeO4.
The metal-oxide phases thus formed as a function of the process conditions and the size distribution of the micro- and nanoparticles formed during precipitation are to be determined within the framework of WERA using temperature- and field-dependent Mössbauer spectroscopy, Raman spectroscopy and supplementary electron microscopy and X-ray diffraction. A further focus of the project is on the temporal development of the nucleation process including the first fast steps in which aggregates of only a few iron centers and/or very small or amorphous particles are formed. With the help of pH jump experiments with 57Fe-containing salt solutions and freezing of the mixture down to the millisecond range, the decisive first steps of the nucleation process during precipitation will also be investigated with the help of 57Fe-Mössbauer spectroscopy and synchrotron-based nuclear inelastic scattering (NIS). By simulating the NIS data with the aid of quantum chemical density functional calculations, structural models for the reaction intermediates will be obtained.
Supervisor: Prof. Sergiy Antonyuk
PhD: Jan Ludorf
A central aspect of the project is a deeper understanding of the kinetics and dynamics of crystallization and precipitation processes. These processes are largely controlled by influencing factors such as temperature, concentration of flocculants, pH value and flow conditions. In order to precisely analyze these influencing factors, an innovative sensor system based on dynamic extinction spectroscopy (DES) is being developed and implemented. This high-resolution measurement method enables in-situ recording of particle size, particle distribution and their changes over time.
The data obtained by DES not only provide insights into the dynamics of aggregation and breakage of the particles, but also serve as a basis for modeling the underlying microprocesses. Here, the population balance method (PBM) and the discrete element method (DEM) are used to determine growth rates and decay probabilities of the particles and to optimize the overall processes.
Supervisor: Prof. Sabine Becker
PhD: Oliver Müller
Reliable P detection in wastewater is an important prerequisite for evaluating the effectiveness of P recovery. Optical sensors are of advantageous, as they enable a simple readout procedure. Current detection methods of phosphates are mostly based on the blue method, which enables a photometric quantification. However, in the trace analysis range, this method is inaccurate. It also is susceptible to other ions and the heterogeneity of the sample. To overcome these difficulties, fluorescent sensors based on zinc complexes, which enable a rapid detection and high selectivity, shall be developed.