Capture of manufacturing uncertainty in turbine blades through probabilistic techniques

Efficient designing of the turbine blades is critical to the performance of an aircraft engine. An area of significant research interest is the capture of manufacturing uncertainty in the shapes of these turbine blades. The available data used for estimation of this manufacturing uncertainty inevitably contains the effects of measurement error/noise. In the present work, we propose the application of Principal Component Analysis (PCA) for de-noising the measurement data and quantifying the underlying manufacturing uncertainty. Once the PCA is performed, a method for dimensionality reduction has been proposed which utilizes prior information available on the variance of measurement error for different measurement types. Numerical studies indicate that approximately 82% of the variation in the measurements from their design values is accounted for by the manufacturing uncertainty, while the remaining 18% variation is filtered out as measurement error

Sparse random Fourier features based interatomic potentials for high entropy alloys

Computational modeling of high entropy alloys (HEA) is challenging given the scalability issues of Density functional theory (DFT) and the non-availability of Interatomic potentials (IP) for molecular dynamics simulations (MD). This work presents a computationally efficient IP for modeling complex elemental interactions present in HEAs. The proposed random features-based IP can accurately model melting behaviour along with various process-related defects. The disordering of atoms during the melting process was simulated. Predicted atomic forces are within 0.08 eV/\unicode{xC5} of corresponding DFT forces. MD simulations predictions of mechanical and thermal properties are within 7$\%$ of the DFT values. High-temperature self-diffusion in the alloy system was investigated using the IP. A novel sparse model is also proposed which reduces the computational cost by 94$\%$ without compromising on the force prediction accuracy

Using blogs to make peer-reviewed research more accessible

Discipline-based education researchers produce knowledge that aims to help instructors improve student learning and educational outcomes. Yet, the information produced may not even reach the educators it is intended to influence. Prior work has found that instructors often face barriers to implementing practices in peer-reviewed literature. Some of these barriers are related to accessing the knowledge in the first place such as difficulty finding and understanding research and a lack of time to do so. To lower these barriers, we created an online blog, PERbites, that summarizes recent discipline-based education research in short posts that use plain language. Having covered nearly 100 papers to date, we conducted a survey to see if we were addressing the need we had originally set out to address. We posted a 23-item survey on our website and received 24 usable responses. The results suggested that readers do generally agree that we are meeting our original goals. Readers reported that our articles were easier to understand and used more plain language than a typical discipline-based education research (DBER) journal article. At the same time, readers thought that all the important information was still included. Finally, readers said that this approach helped them keep up with DBER studies and read about papers they otherwise would not have. However, most readers did not indicate they changed their teaching and research practice as a result of reading our blog. Our results suggest that alternative methods of sharing research (e.g., non-peer reviewed publications or conference talks) can be an effective method of connecting research with practitioners, and future work should consider how we as a community might build on these efforts to ensure education research can make meaningful changes in the classroom.Comment: Published in the Proceedings of the 2022 Physics Education Research Conference, Grand Rapids, MI, US July 13th - July 14t

Molecular-receptor-specific, non-toxic, near-infrared-emitting Au cluster-protein nanoconjugates for targeted cancer imaging

Molecular-receptor-targeted imaging of folate receptor positive oral carcinoma cells using folic-acid-conjugated fluorescent Au25 nanoclusters (Au NCs) is reported. Highly fluorescent Au25 clusters were synthesized by controlled reduction of Au+ ions, stabilized in bovine serum albumin (BSA), using a green-chemical reducing agent, ascorbic acid (vitamin-C). For targeted-imaging-based detection of cancer cells, the clusters were conjugated with folic acid (FA) through amide linkage with the BSA shell. The bioconjugated clusters show excellent stability over a wide range of pH from 4 to 14 and fluorescence efficiency of ~5.7% at pH 7.4 in phosphate buffer saline (PBS), indicating effective protection of nanoclusters by serum albumin during the bioconjugation reaction and cell-cluster interaction. The nanoclusters were characterized for their physico-chemical properties, toxicity and cancer targeting efficacy in vitro. X-ray photoelectron spectroscopy (XPS) suggests binding energies correlating to metal Au 4f7/2˜83.97 eV and Au 4f5/2~87.768 eV. Transmission electron microscopy and atomic force microscopy revealed the formation of individual nanoclusters of size ~1 nm and protein cluster aggregates of size ~8 nm. Photoluminescence studies show bright fluorescence with peak maximum at ~674 nm with the spectral profile covering the near-infrared (NIR) region, making it possible to image clusters at the 700-800 nm emission window where the tissue absorption of light is minimum. The cell viability and reactive oxygen toxicity studies indicate the non-toxic nature of the Au clusters up to relatively higher concentrations of 500 µg ml-1. Receptor-targeted cancer detection using Au clusters is demonstrated on FR+ve oral squamous cell carcinoma (KB) and breast adenocarcinoma cell MCF-7, where the FA-conjugated Au25 clusters were found internalized in significantly higher concentrations compared to the negative control cell lines. This study demonstrates the potential of using non-toxic fluorescent Au nanoclusters for the targeted imaging of cancer

Evaluation of Tensile Bond Strength of Zinc Containing and Zinc Free Denture Adhesives on Different Denture Base Resin Materials: An in Vitro Study

Background and aim: Denture adhesives augment the retention and stability of the complete denture. The included studies have not directly compared tensile bond strength between zinc and zinc-free denture adhesives. This study compared the tensile bond strength of zinc-containing and zinc-free denture adhesives on different denture base resin materials at various intervals.Material and methods: Four groups of denture base resin materials (Acralyn H, Lucitone199- DB1, SR Ivocap-DB2, Polytray-DB3) were fabricated using different polymerization techniques. Each group had ten specimens. The control group consisted of resin cylinders coated with artificial saliva, while the test groups had denture adhesive applied between the test and control cylinders. Tensile bond strength was measured using a universal testing machine.Results: The tensile bond strength values of Fixodent with DBI &DB3 and DB2 &DB3 at 5 min (P < 0.01), 3 hours (P < 0.01), and 6 hours (P < 0.061 and P < 0.020) alongside with DB1 & DB2, DBI & DB3, and DB2 & DB3 at 12 hours (P < 0.01) were found to be statistically significant. The tensile bond strengths variations of Fittydent with DB1 & DB3 and DB2 & DB3 at 3 hours (P =0.013, P =0.012) and 6 hours (P < 0.01), and DB2 & DB3 at 12 hours (P=0.015), was statistically significant at 0.05 level.Conclusions: The zinc-containing and zinc-free denture adhesives exhibited a significant increase in tensile bond strength compared to the control group (artificial saliva) at all time intervals