Oil-palm and Rainforest Phytoliths Dissolve at Different Rates - with Implications for Silicon Cycling After Transformation of Rainforest Into Oil-palm Plantation

Silicon - Phytoliths make up the predominant fraction of biogenic silica in plant litter and soils. Thus, they represent a major source of dissolved silicon (Si) in soil-plant systems. Dissolution...     

Digital Twin of a Hierarchical CO2 Electrolyzer Gas Diffusion Electrode

The electrochemical reduction of CO₂ provides a pathway to a sustainable carbon cycle, allowing for the production of hydrocarbons critical for both chemical industry and mobility. Major engineering challenges need to be met in order to achieve efficient and large-scale CO₂ electrolysis. One central challenge is to find the optimum structure for the gas diffusion electrode at the heart of the electrolyzer. An optimum structure will achieve higher conversion efficiencies, lifetime, and product selectivity at lower cost. Critical structural properties of the electrode span the scale from nanometers to millimeters. To rationalize the optimization process, it behooves us to obtain a fully resolved multi-scale model of the electrode. This digital twin, produced by bridging scale and employing multiple imaging methods, enables the digital study, simulation, and modification of the structure of the electrode. The model is used to simulate the transport processes vital to the functioning of the electrode thus further advancing the digital twin. Subsequently, it is explored how changes to the structure affect the predicted transport properties. The digital twin presented is only supposed to be the kernel and will be complemented by numerous future works.     

Simulative Determination of Effective Mechanical Properties for Digitally Generated Foam Geometries

Metal foams constitute a promising and emerging material class in the context of lightweight construction. There exists a variety of different foam topologies, on which resulting mechanical properties depend. To maximize the potential of foams in material use under mechanical load, the present work addresses the question how different geometrical parameters influence the material behaviour. Therefore, an algorithm for digital generation and design of open pore foam structures is presented, that allows to regulate the geometry precisely. A method for retrieving effective mechanical properties from numerical simulations of compression tests in the elastic regime is introduced. Additionally, the representativeness of foam volumes considered for simulations is investigated. This yields a fully digital workflow, which enables the investigation of geometry influence on mechanical properties. This approach is used to conduct simulation studies on generated foam structures with a systematic variation of geometrical parameters. Herein, a range of effective Young's moduli varying by up to a factor of 1.3 for different foam structures at the same porosity is found. This shows a significant impact of the foam geometry on the elastic properties of metal foams. The presented methodology yields insights, which can guide design and optimization of materials for specific applications.     

Synthesis of 2-Deoxy-maltooligosaccharides with Phosphorylase and Their Degradation with Amylases

By reaction of phosphorylase with D-glucal and inorganic phosphate instead of the natural substrate α-D-glucosyl phosphate novel 2-deoxy-maltooligosaccharides could be synthesized. Their properties and characterization by NMR spectroscopy, mass spectrometry and HPLC are described. Under similar conditions, except a higher phosphate concentration, 2-deoxy-α-D-glucosyl phosphate is obtained. This can also serve for the enzymatic elongation of the primer with 2-deoxy-glucosyl residues. The unnatural 2-deoxy-maltooligomers could be applied successfully as substrates for the exo-cleaving enzymes glucoamylase and β-amylase.     

Expertensysteme zur Unterstützung der Analytischen Chemie: Verwechslungsprüfung und Schrott-Identifizierung in der Qualitätssicherung

Expert Systems to Assist Analytical Chemistry: Confounding Tests and Scrap Identification in Industrial Quality Control Quality control in the steel industry has to ensure the identity of semi-finished products and of scrap. This means to make a decision among about 2000 or more possibilities. The inductive learning algorithm ID3 is used to build the necessary decision tree, the main problem being overlap of the metal concentrations specifying the different alloys. Local attributes are introduced to split up remaining clusters without destroying the other parts of the tree. The system ist designed for use with industrial (mobile) spectrometers.