Andreas Dreizler’s research while affiliated with Technical University of Darmstadt and other places

C1‐based synthetic fuels like oxymethylene ether (OME) are sulfur‐free, and their combustion forms negligible amounts of soot. This results in reduced ageing requirements and can enable the development of cost‐efficient catalyst technologies. This work focuses on the catalytic oxidation of formaldehyde (HCHO), which is increasingly formed during the combustion of C1‐based fuels such as OME, methanol, or CH4. The oxidation of HCHO on Pt/Al2O3 is inhibited by CO, so that in real exhaust containing CO and NO, full conversion of HCHO is only observed at ∼200 °C. The main discovery of this paper is that on Pt/ceria the oxidation of HCHO is not inhibited by CO, so that full conversion of HCHO is achieved already at ∼100 °C even in the presence of CO. To demonstrate the performance of the new catalyst under realistic operating conditions, a dynamic HCHO dosing unit was developed, allowing to reproduce transient vehicle driving cycles on a lab‐scale test rig. Using this novel setup, the Pt/ceria catalyst shows virtually full conversion of HCHO (99,8%) and CO (98,5%) over an OME cold‐start driving cycle, where the conventional Pt/Al2O3 oxidation catalyst with four‐times higher Pt loading shows only 81% and 62% conversion, respectively.

The formation of iron oxide nanoparticles (NPs) presents challenges such as efficiency losses and fine dust emissions in practical iron combustion systems, highlighting the need for deeper understanding of the formation mechanisms and thermochemical conditions. This study combines experiments and multi-scale simulations to analyze NP clouds generated by single iron particles burning in high-temperature oxidizing environments. The ambient gas conditions were provided by a laminar flat flame burner, with post-flame oxygen mole fractions varied between 20, 30, and 40 vol% at a constant temperature of ~1800K. High-speed in-situ diagnostics were used to measure particle size, NP initiation, NP cloud evolution, and microparticle surface temperature history. The experimental setup utilized three 10kHz imaging systems: one for two-color pyrometry and two for diffusive-backlight illumination (DBI), targeting particle size and NP measurements. The findings showcase the powerful capabilities of multi-physics diagnostics in quantifying NP initiation time and temperature, which depend on particle size and ambient oxygen concentration. CFD simulations revealed enhanced convection velocity driven by increased Stefan flow, which transported NPs toward parent iron particles under high-oxygen conditions. This delayed the detection of NP clouds, leading to higher microparticle temperatures at NP initiation. Molecular dynamics (MD) simulations uncovered FeO2(g) as a key NP precursor, forming when Fe atoms dissociate from the liquid phase. The initial temperature significantly influenced the resulting nanocluster composition, with Fe(II) dominating at higher temperatures and Fe(III) at lower temperatures. This integrated approach enhances understanding of NP formation in iron combustion, offering insights into the conditions affecting nanoparticle characteristics.

Stricter aviation emissions regulations have led to the desire for lean-premixed-vaporized combustors over rich-quench-lean burners. While this operation mode is beneficial for reducing NOx and particulate emissions, the interaction of the flame and hot exhaust gases with the cooling flow results in increased CO emissions. Predicting CO in computational fluid dynamics (CFD) simulations remains challenging. To assess current model performance under practically relevant conditions, Large- Eddy Simulation (LES) of a lab-scale effusion cooling test rig is performed. Flamelet-based manifolds, in combination with the Artificial Thickened Flame (ATF) approach, are utilized to model the Turbulence-Chemistry Interaction (TCI) in the test-rig with detailed chemical kinetics at reduced computational costs. Heat losses are considered via exhaust gas recirculation (EGR). Local transport effects in CO emissions are included through an additional transport equation. Additionally, a Conjugate Heat Transfer (CHT) simulation is performed for good estimations of the thermal boundary conditions. Extensive validation of this comprehensive model is conducted using the available experimental dataset for the studied configuration. Subsequently, model sensitivities for predicting CO are assessed, including the progress variable definition and the formulation of the CO source term in the corresponding transport equation. To investigate the flame thickening influence in the calculated CO, an ATF-postprocessing correction is further developed. Integrating multiple sophisticated pollutant submodels and evaluating their sensitivity offers insights for future investigations into modeling CO emissions in aero-engines and stationary gas turbines.