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SQUID-based superconducting microcalorimeter with in-situ tunable gain for high-resolution X-ray emission spectroscopy
No full textCO-Abscheidung - Technologien für eine klimaneutrale Zukunft
No full textDie Reduktion von CO-Emissionen ist eine der zentralen Herausforderungen im Kampf gegen den Klimawandel. Neben der Vermeidung von Emissionen durch Effizienzsteigerung und den Einsatz
erneuerbarer Energien gewinnt die Abscheidung zwecks Speicherung oder Nutzung von CO (CCS/CCU) zunehmend an Bedeutung. Im Fokus aktueller Entwicklungen stehen u. a. Prozessketten zur Abscheidung von CO aus Rauchgas sowie neue Verfahren zur direkten Gewinnung von CO aus der Atmosphäre (Direct Air Capture, DAC)
A Tandem Chemical Vapor Deposition Platform for the Solvent‐Free Synthesis of Polypeptide Architectures
No full textThe precise engineering of surfaces decorated with polypeptides is critical for advanced diagnostics, biomedical coatings, and cellular interfaces. However, conventional methods are plagued by the need for solvents, multistep procedures, substrate limitations, and the abundance of side reactions. Here, we report that two-step chemical vapor polymerization can result in the fast, efficient, and substrate-independent synthesis of polypeptide films without the use of solvents or excipients. The first step involves deposition of an initiator layer, i.e., poly(4-amino-p-xylylene), via chemical vapor deposition (CVD) polymerization of 4,16-diamino[2.2]paracyclophane. The second step involves evaporation and ring-opening polymerization of N-carboxy anhydrides. This fully integrated CVD approach ensures substrate-independent, conformal growth of poly(propargyl-(S)-glycine) and poly(O-propargyl-(S)-tyrosine) films of up to 198 nm thickness. The use of CVD processes eliminates the concern of side reactions, such as transfer and termination reactions, and is a prerequisite for the successful peptide micropatterning, demonstrated in this study. Successful peptide growth and post-polymerization modifications via click chemistry were confirmed by time-of-flight secondary mass spectrometry, x-ray photoelectron spectroscopy, and infrared spectroscopy. The application of entirely solvent-free workflows to develop biomacromolecular coatings, such as the polypeptide films demonstrated in this study, addresses a critical gap in the pursuit of advanced and scalable biologization methods
What meaningful tomorrow can we shape with the courage to leave yesterday’s recipes behind?
No full textProtecting the Environment and Climate - Creating Living Space - Improving Quality of Life - UBA and KNBau Recommendations for Sustainable Housing and Urban Development
No full textNon-targeted analysis of lipophilic and hydrophilic metabolites to distinguish between fresh and frozen-thawed fish of certain fish species using comprehensive 1H NMR spectroscopy and multivariate data analysis
No full textFood fraud along the production chain is a well-known issue that requires an effective authenticity control. For the differentiation of fresh and frozen-thawed fish, H nuclear magnetic resonance (NMR) spectroscopy based methods in combination with multivariate data analysis have proven to be suitable in principle. Here, from a total of 317 samples (cod, rainbow trout, mackerel; fresh and frozen-thawed), the lipid and polar fractions of the fish flesh were analyzed, and classification models based on a principal components analysis with linear discriminant analysis (PCA-LDA) including cross-validation were generated. Additionally, data fusions were carried out. The obtained average accuracies of > 90% (94.0% based on the lipid fraction, 92.8% based on the polar fraction) and > 95% (95.6% based on a low-level data fusion, 95.5% based on a mid-level data fusion) demonstrated a promising differentiation. Further examinations confirmed that the non-targeted analysis appears to be mandatory as no marker substances were indicated in the loadings plots of the models. To evaluate whether the generated classification models are suitable to be used in a broader manner, they were applied to 13 fresh and 13 frozen-thawed samples from twelve other common edible fish species in a preliminary study. The classification model based on the low-level data fusion gave the best results (84.6% of all 26 samples correctly predicted). Thus, although these models are very suitable for analyzing cod, rainbow trout, or mackerel for a classification as fresh or frozen-thawed, they cannot generally be applied to samples of other fish species
Supplementary Material - Sustainability Self-Experiments
No full textDieser Anhang stellt die Definition, die Struktur sowie eine exemplarische Anwendung von Nachhaltigkeits-Selbstexperimenten (Sustainability Self-Experiments, SSE) vor, einem transformativen Lehrformat, das am Karlsruher Transformationszentrum (KAT) des Karlsruher Instituts für Technologie (KIT) entwickelt und im Reallabor „Quartier Zukunft – Labor Stadt“ umgesetzt wurde. Darüber hinaus bietet der Anhang vertiefende Einblicke in die Ergebnisse der qualitativen Inhaltsanalyse, in der die durch diese Selbstexperimente erworbenen Nachhaltigkeitskompetenzen bei Studierenden untersucht wurden.
Damit bietet er vertiefende Einblicke in die Analyse, die dem Paper “Assessing competency development in transformative teaching – A real-world lab case study on Sustainability Self-Experiments”, zugrunde liegt