Microstructural evolution of a delta containing nickel-base superalloy during heat treatment and isothermal forging

The next generation of aerospace gas turbine engines need to operate at higher temperatures and stresses to improve their efficiency and reduce emissions. These operating conditions are beyond the capability of existing nickel-base superalloys, requiring the development of new high temperature materials. Controlling the microstructures of these new materials is key to obtaining the required properties and, therefore, it is critical to understand how these alloys respond to processing and heat treatment. Here, the microstructural evolution of V207M, a new δ containing, nickel-base superalloy, has been investigated following heat treatment and forging. The solvus temperatures of the γ′ and δ phases, determined by differential scanning calorimetry and microscopy, were found to be ~985 and ~1060 °C respectively. Isothermal forging of the alloy was conducted at 1000, 1050 and 1100 °C, corresponding to different volume fractions of retained δ. Considerable softening was observed prior to steady state flow when forging at 1000 °C, whilst only steady state flow occurred at 1050 and 1100 °C. The steady state flow process was believed to be dominated by dynamic recovery in the γ phase, with an activation energy of 407 kJmol−1. Samples that exhibited flow softening also showed a significant change in the orientation of the δ precipitates, preferentially aligning normal to the forging axis, and this reorientation was thought to be the cause of the observed flow softening

Tejaas: reverse regression increases power for detecting trans-eQTLs

Trans-acting expression quantitative trait loci (trans-eQTLs) account for ≥70% expression heritability and could therefore facilitate uncovering mechanisms underlying the origination of complex diseases. Identifying trans-eQTLs is challenging because of small effect sizes, tissue specificity, and a severe multiple-testing burden. Tejaas predicts trans-eQTLs by performing L2-regularized “reverse” multiple regression of each SNP on all genes, aggregating evidence from many small trans-effects while being unaffected by the strong expression correlations. Combined with a novel unsupervised k-nearest neighbor method to remove confounders, Tejaas predicts 18851 unique trans-eQTLs across 49 tissues from GTEx. They are enriched in open chromatin, enhancers, and other regulatory regions. Many overlap with disease-associated SNPs, pointing to tissue-specific transcriptional regulation mechanisms.Fil: Banerjee, Saikat. Max Planck Institute For Biophysical Chemistry; AlemaniaFil: Simonetti, Franco Lucio. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; Argentina. Max Planck Institute For Biophysical Chemistry; AlemaniaFil: Detrois, Kira E.. Max Planck Institute For Biophysical Chemistry; Alemania. Universität Göttingen; AlemaniaFil: Kaphle, Anubhav. Universität Göttingen; Alemania. Max Planck Institute For Biophysical Chemistry; AlemaniaFil: Mitra, Raktim. Indian Institute of Technology; IndiaFil: Nagial, Rahul. Indian Institute of Technology; IndiaFil: Söding, Johannes. Max Planck Institute For Biophysical Chemistry; Alemania. University of Göttingen; Alemani

Effect of Molybdenum on the Corrosion Behavior of High-Entropy Alloys CoCrFeNi 2

The corrosion behavior of high-entropy alloys (HEAs) CoCrFeNi2 and CoCrFeNi2Mo0.25 was investigated in 3.5 wt. percent sodium chloride (NaCl) at 25°C by electrochemical methods. Their corrosion parameters were compared to those of HASTELLOY® C-276 (UNS N10276) and stainless steel 316L (UNS 31600) to assess the suitability of HEAs for potential industrial applications in NaCl simulating seawater type environments. The corrosion rates were calculated using corrosion current determined from electrochemical experiments for each of the alloys. In addition, potentiodynamic polarization measurements can indicate active, passive, and transpassive behavior of the metal as well as potential susceptibility to pitting corrosion. Cyclic voltammetry (CV) can confirm the alloy susceptibility to pitting corrosion. Electrochemical impedance spectroscopy (EIS) elucidates the corrosion mechanism under studied conditions. The results of the electrochemical experiments and scanning electron microscopy (SEM) analyses of the corroded surfaces revealed general corrosion on alloy CoCrFeNi2Mo0.25 and HASTELLOY C-276 and pitting corrosion on alloy CoCrFeNi2 and stainless steel 316L

Untersuchungen zur Dehnrheologie und Verarbeitbarkeit von Halbzeugen beim Thermoformen sowie Simulation und Optimierung der Umformphase

This thesis focuses on the influence of the material rheology on the quality and the prediction and optimisation of the wall thickness distribution of thermoformed parts. In particular, the technique of the Membrane-Inflation Rheometer was improved. In this rheological test thermoplastic samples are deformed in an equibiaxial strain mode under process relevant conditions for temperature and strain rate. The rheological properties of thermoforming sheets were correlated with the quality of thermoformed parts. The rheological data was additionally used to calibrate a viscoelastic material model. The material constants are used as input for Finite-Element-Analysis of the deformation step in the thermoforming process. Based on the simulation of deformation in the thermoforming process, an optimisation algorithm is presented, which is used to calculate the temperature distribution in the thermoforming sheet to obtain the most even final wall thickness distribution. For different thermoforming parts an improvement of the final wallt hickness distribution could be achieved

Marketing in football influenced by the New Media using the example of VfL Wolfsburg

Die vorliegende Bachelor-Thesis hat das Ziel, den Einfluss der durch den digitalen Prozess beeinflussten Neuen Medien auf das Sportmarketing, insbesondere das Marketing im deutschen Profi-Fußball, zu untersuchen. Dabei wurden drei Teilbereiche der Neuen Medien genauer untersucht: virtuelle Realität, E-Sport und soziale Medien. Da Sportmarketing ein weites Feld umfasst, wurde in dieser Arbeit v.a. der Fokus auf virtuelle Werbung, Sportsponsoring und Social Media Marketing gelegt. Durch die Entstehung von gemeinsamen Schnittpunkten zwischen den Themen Neue Medien und Marketing im Fußball, ergaben sich interessante Blickwinkel, wie weit sich das Sportmarketing bereits geändert hat und zukünftig entwickeln kann. Von Connected Stadiums mithilfe von AI und Beacons, über virtuelle Bandenwerbung im Stadion oder E-Sport als innovativer Sponsorship-Treiber, bis hin zu Instagram-Marketing als eine große Chance im Online-Marketing Bereich, sind für den ersten Moment nur die bedeutsamen Erkenntnisse dieser Arbeit. Die Ergebnisse und Einblicke, inwiefern sich der Fußball-Marketing-Bereich durch Neue Medien verändert, bezieht sich gegen Ende dieser Thesis auf den deutschen Bundesligisten VfL Wolfsburg. Dabei wurde untersucht, in welchen Ausprägungen der Bundesligist Neue Medien in seinen Marketingaktivitäten nutzt. Im Anschluss entwickelt der Verfasser aus den erarbeiteten Erfolgsfaktoren belegbare Handlungsempfehlungen, die dem Leser in diesem Bereich zukünftig helfen können

Untersuchungen zur Dehnrheologie und Verarbeitbarkeit von Halbzeugen beim Thermoformen sowie Simulation und Optimierung der Umformphase

This thesis focuses on the influence of the material rheology on the quality and the prediction and optimisation of the wall thickness distribution of thermoformed parts. In particular, the technique of the Membrane-Inflation Rheometer was improved. In this rheological test thermoplastic samples are deformed in an equibiaxial strain mode under process relevant conditions for temperature and strain rate. The rheological properties of thermoforming sheets were correlated with the quality of thermoformed parts. The rheological data was additionally used to calibrate a viscoelastic material model. The material constants are used as input for Finite-Element-Analysis of the deformation step in the thermoforming process. Based on the simulation of deformation in the thermoforming process, an optimisation algorithm is presented, which is used to calculate the temperature distribution in the thermoforming sheet to obtain the most even final wall thickness distribution. For different thermoforming parts an improvement of the final wallt hickness distribution could be achieved

Disease Onset Prediction of 18 Diseases in FinnGen using Polygenic Risk Sco

Background/Objectives: Various studies have shown the advantage when incorporating polygenic risk scores (PRSs) in models with classic risk factors. However, systematic comparisons of PRSs with non-genetic factors are lacking. In particular, many studies on PRSs do not even report the predictive performance of the confounders, such as age and sex, included in the model, which are already very predictive for most diseases. We looked at the ability of PRSs to predict the onset of 18 diseases in FinnGen R8 (N=342,499) and compared PRSs with the known non-genetic risk factors, age, sex, Education, and Charlson Comorbidity Index (CCI). Methods: We set up individual studies for the 18 diseases. A single study consisted of an exposure (1999-2009), a washout (2009-2011), and an observation period (2011-2019). Eligible individuals could not have the selected disease of interest inside the disease-free period, which ranged from birth until the beginning of the observation period. We then defined the case and control status based on the diagnoses in the observation period and calculated the phenotypic scores during the exposure period. The PRSs were calculated using MegaPRS and the latest publicly available genome-wide association study summary statistics. We then fitted separate Cox proportional hazards models for each disease to predict disease onset during the observation period. Results: In FinnGen, the model’s predictive ability (c-index) with all predictors ranged from 0.565 (95%CI: 0.552-0.576) for Acute Appendicitis to 0.838 (95% CI: 0.834-0.841) for Atrial Fibrillation. The PRSs outperformed the phenotypic predictors, CCI, and Education, for 6/18 diseases and still significantly enhance onset prediction for 13/18 diseases when added to a model with only non-genetic predictors. Conclusion: Overall, we showed that for many diseases PRSs add predictive power over commonly used predictors - such as age, sex, CCI, and Education. However, many important challenges must be addressed before implementing PRSs in clinical practice. Notably, we will need disease-specific cost- benefit analyses and studies to assess the direct impact of including PRSs in clinical use. Nonetheless, as more research is being conducted, PRSs could play an increasingly valuable role in identifying individuals at higher risk for certain diseases and enabling targeted interventions to improve health outcomes