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In memoriam Willy Lehnert
(2023)
Lignin ist ein aromatisches Biopolymer, das in den Zellwänden von Pflanzen vorkommt. Es ist hauptsächlich aus drei sogenannten Monolignolen (p-Hydroxyphenyl (H), Guajakol (G) und Syringol (S)) aufgebaut, die über verschiedene Bindungen miteinander verknüpft sein können, und enthält eine Vielzahl an funktionellen Gruppen. Interessant für die Verwendung von Lignin sind dabei insbesondere die vielen phenolischen Hydroxygruppen, die als Ausgangsstoff bei der Synthese neuer Produkte dienen können, daneben aber auch für seine antioxidativen Eigenschaften verantwortlich sind. Da Struktur und Eigenschaften von vielen Faktoren wie Biomasse und Aufschlussprozess abhängen, ist eine detaillierte Charakterisierung der Lignine nötig, um Struktur-Eigenschafts-Beziehungen aufzuklären und so einen Schritt näher an eine mögliche stoffliche Nutzung zu kommen. Mit dieser Arbeit soll der Einfluss der Biomasse inklusive der verwendeten Partikelgröße sowie des Organosolv-Aufschlussprozesses auf die Monomerzusammensetzung, das Molekulargewicht und die Antioxidanz der isolierten Lignine untersucht werden.
Als Rohstoffe zur Ligningewinnung dienen die drei mehrjährigen lignocellulosereichen Low-Input-Pflanzen Miscanthus x giganteus, Silphium perfoliatum und Paulownia tomentosa, die momentan hauptsächlich zur Energiegewinnung genutzt werden. Im Rahmen der Bioökonomiestrategie der Europäischen Union soll der Schwerpunkt zukünftiger Bioraffinerien jedoch auf eine ganzheitliche Nutzung von Biomassen gelegt und so auch die stoffliche Nutzung fokussiert werden. Zusätzlich zu diesen drei Pflanzen werden auch Organosolv-Lignine aus den in der Literatur bereits gut beschriebenen Biomassen Weizenstroh und Buchenholz isoliert, und zwei Nadelholz-Kraft-Lignine als Vergleich herangezogen. Die Ergebnisse zeigen, dass die Art der Biomasse hauptsächlich die Monomerzusammensetzung beeinflusst: Gräser bestehen aus allen drei Monolignolen, Laubhölzer mehrheitlich aus S- und G-Einheiten, während Nadelhölzer nur aus G-Einheiten aufgebaut sind. Die Holzlignine besitzen zudem höhere Molekulargewichte sowie bessere antioxidative Eigenschaften als die Gras- und Krautlignine. Mit der feineren Vermahlung der Biomasse kann die Monomerzusammensetzung beeinflusst werden: der Einsatz kleinerer Partikelgrößen führt zu Ligninen mit einem höheren Gehalt an H-Einheiten, sowohl für Miscanthus als auch für Paulownia. Außerdem kann bei Paulownia die Ausbeute gesteigert und eine Zunahme des Molekulargewichtes beobachtet werden, wenn die kleinste Siebfraktion für den Organosolv-Aufschluss verwendet wird. Einen größeren Einfluss als der Mahlgrad der Biomasse haben die Autohydrolyse sowie der Organosolv-Aufschlussprozess selbst. Die Monomerzusammensetzung ändert sich aufgrund derselben Biomasse zwar kaum, die Bindungstypen zwischen den Monolignolen dagegen schon. Mit höherer Prozessstärke (Zeit, Temperatur, Ethanol-Konzentration) werden Etherbindungen gespalten, was den Anteil an phenolischen Hydroxygruppen und somit die Antioxidanz erhöht. Neben dieser Depolymerisation werden partiell auch Rekondensationsreaktionen beobachtet.
Die erzielten Ergebnisse liefern einen Beitrag zum Verständnis des Zusammenhangs zwischen Ligninquelle und -gewinnung mit der daraus resultierenden Ligninstruktur und Antioxidanz und bieten damit eine Grundlage für den Wandel von der energetischen hin zu einer nachhaltigen stofflichen Nutzung dieses nachwachsenden Biopolymers. Gerade über die Wahl der Aufschlussparameter können Struktur und Antioxidanz gezielt beeinflusst werden, was in zukünftigen Studien weiter fokussiert werden sollte.
Electrical signal transmission in power electronic devices takes place through high-purity aluminum bonding wires. Cyclic mechanical and thermal stresses during operation lead to fatigue loads, resulting in premature failure of the wires, which cannot be reliably predicted. The following work presents two fatigue lifetime models calibrated and validated based on experimental fatigue results of an aluminum bonding wire and subsequently transferred and applied to other wire types. The lifetime modeling of Wöhler curves for different load ratios shows good but limited applicability for the linear model. The model can only be applied above 10,000 cycles and within the investigated load range of R = 0.1 to R = 0.7. The nonlinear model shows very good agreement between model prediction and experimental results over the entire investigated cycle range. Furthermore, the predicted Smith diagram is not only consistent in the investigated load range but also in the extrapolated load range from R = −1.0 to R = 0.8. A transfer of both model approaches to other wire types by using their tensile strengths can be implemented as well, although the nonlinear model is more suitable since it covers the entire load and cycle range.
Microorganisms not only contribute to the spoilage of food but can also cause illnesses through consumption. Consumer concerns and doubts about the shelf life of the products and the resulting enormous amounts of food waste have led to a demand for a rapid, robust, and non-destructive method for the detection of microorganisms, especially in the food sector. Therefore, a rapid and simple sampling method for the Raman- and infrared (IR)-microspectroscopic study of microorganisms associated with spoilage processes was developed. For subsequent evaluation pre-processing routines, as well as chemometric models for classification of spoilage microorganisms were developed. The microbiological samples are taken using a disinfectable sampling stamp and measured by microspectroscopy without the usual pre-treatments such as purification separation, washing, and centrifugation. The resulting complex multivariate data sets were pre-processed, reduced by principal component analysis, and classified by discriminant analysis. Classification of independent unlabeled test data showed that microorganisms could be classified at genus, species, and strain levels with an accuracy of 96.5 % (Raman) and 94.5 % (IR), respectively, despite large biological differences and novel sampling strategies. As bacteria are exposed to constantly changing conditions and their adaptation mechanisms may make them inaccessible to conventional measurement methods, the methods and models developed were investigated for their suitability for microorganisms exposed to stress. Compared to normal growth conditions, spectral changes in lipids, polysaccharides, nucleic acids, and proteins were observed in microorganisms exposed to stress. Models were developed to discriminate microorganisms, independent of the involvement of various stress factors and storage times. Classification of the investigated bacteria yielded accuracies of 97.6 % (Raman) and 96.6 % (IR), respectively, and a robust and meaningful model was developed to discriminate different microorganisms at the genus, species, and strain levels. The obtained results are very promising and show that the methods and models developed for the discrimination of microorganisms as well as the investigation of stress factors on microorganisms by means of Raman- and IR-microspectroscopy have the potential to be used, for example, in the food sector for the rapid determination of surface contamination.
There & Back again: Developing a tool for testing of antimicrobial surfaces for space habitat design
(2023)
The French–Italian Concordia Research Station, situated on the Antarctic Polar Plateau at an elevation of 3233 m above sea level, offers a unique opportunity to study the presence and variation of microbes introduced by abiotic or biotic vectors and, consequently, appraise the amplitude of human impact in such a pristine environment. This research built upon a previous work, which explored microbial diversity in the surface snow surrounding the Concordia Research Station. While that study successfully characterized the bacterial assemblage, detecting fungal diversity was hampered by the low DNA content. To address this knowledge gap, in the present study, we optimized the sampling by increasing ice/snow collected to leverage the final DNA yield. The V4 variable region of the 16S rDNA and Internal Transcribed Spacer (ITS1) rDNA was used to evaluate bacterial and fungal diversity. From the sequencing, we obtained 3,352,661 and 4,433,595 reads clustered in 930 and 3182 amplicon sequence variants (ASVs) for fungi and bacteria, respectively. Amplicon sequencing revealed a predominance of Basidiomycota (49%) and Ascomycota (42%) in the fungal component; Bacteroidota (65.8%) is the main representative among the bacterial phyla. Basidiomycetes are almost exclusively represented by yeast-like fungi. Our findings provide the first comprehensive overview of both fungal and bacterial diversity in the Antarctic Polar Plateau’s surface snow/ice near Concordia Station and to identify seasonality as the main driver of microbial diversity; we also detected the most sensitive microorganisms to these factors, which could serve as indicators of human impact in this pristine environment and aid in planetary protection for future exploration missions.