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- Artificial neural networks (1)
- BAM-P109 (1)
- Biofilms (1)
- Flüssigmetallversprödung (1)
- Gleeble (1)
- Heißzug (1)
- Interlaboratory study (1)
- Liquid Metal Embrittlement (1)
- Nanoporous carbon (1)
- Reference isotherm (1)
- VAMAS (1)
- Widerstandpunktschweißen (1)
- X-ray reflectivity (1)
Organisationseinheit der BAM
Ziel des Forschungsprojekts ist es, eine Korrelation zwischen Gleeble-Heißzug-Prüfverfahren und Widerstandspunktschweiß-basierten Prüfverfahren herzustellen. Es soll die Effektivität von Methoden zu Vermeidung von Liquid Metal Embrittlement an realitätsnahen Prinzipbauteilen bewertet werden. Weiterhin soll Kenntnis über Auswirkungen von LME Rissen auf das Tragverhalten von realitätsnahen Prinzipbauteilen gewonnen werden.
This paper reports the results of an international interlaboratory study sponsored by the Versailles Project on Advanced Materials and Standards (VAMAS) and led by the National Institute of Standards and Technology (NIST) on the measurement of water vapor sorption isotherms at 25 °C on a pelletized nanoporous carbon (BAM-P109, a certified reference material). Thirteen laboratories participated in the study and contributed nine pure water vapor isotherms and four relative humidity isotherms, using nitrogen as the carrier gas. From these data, reference isotherms, along with the 95% uncertainty interval (Uk=2), were determined and are reported in a tabular format.
X-ray reflectivity (XRR) is a powerful and popular scattering technique that can give valuable insight into the growth behavior of thin films. This study Shows how a simple artificial neural network model can be used to determine the thickness, roughness and density of thin films of different organic semiconductors [diindenoperylene, copper(II) phthalocyanine and alpha-sexithiophene] on silica from their XRR data with millisecond computation time and with minimal user input or a priori knowledge. For a large experimental data set of 372 XRR curves, it is shown that a simple fully connected model can provide good results with a mean absolute percentage error of 8–18% when compared with the results obtained by a genetic least mean squares fit using the classical Parratt formalism. Furthermore, current drawbacks and prospects for improvement are discussed.
Pseudomonas aeruginosa MPAO1 is the parental strain of the widely utilized transposon mutant collection for this important clinical pathogen. Here, we validate a model system to identify genes involved in biofilm growth and biofilm-associated antibiotic resistance. Our model employs a genomics-driven workflow to assemble the complete MPAO1 genome, identify unique and conserved genes by comparative genomics with the PAO1 reference strain and genes missed within existing assemblies by proteogenomics. Among over 200 unique MPAO1 genes, we identified six general essential genes that were overlooked when mapping public Tn-seq data sets against PAO1, including an antitoxin. Genomic data were integrated with phenotypic data from an experimental workflow using a user-friendly, soft lithography-based microfluidic flow chamber for biofilm growth and a screen with the Tn-mutant library in microtiter plates. The screen identified hitherto unknown genes involved in biofilm growth and antibiotic resistance. Experiments conducted with the flow chamber across three laboratories delivered reproducible data on P. aeruginosa biofilms and validated the function of both known genes and genes identified in the Tn-mutant screens. Differential Protein abundance data from planktonic cells versus biofilm confirmed the upregulation of candidates known to affect biofilm formation, of structural and secreted proteins of type VI secretion systems, and provided proteogenomic evidence for some missed MPAO1 genes. This integrated, broadly applicable model promises to improve the mechanistic understanding of biofilm formation, antimicrobial tolerance, and resistance evolution in biofilms.