Dataset Information

Efficient Volumetric Absorption Solar Thermal Platforms Employing Thermally Stable - Solar Selective Nanofluids Engineered from Used Engine Oil.

ABSTRACT: We report a low cost and scalable method to synthesize solar selective nanofluids from 'used engine oil'. The as-prepared nanofluids exhibit excellent long-term stability (presently tested up to 6 months under undisturbed stagnant conditions at room temperature) and photo-thermal conversion efficiency. Moreover, these were found to retain their stability and functional characteristics even after extended periods (72?hours) of high temperature (300°C) heating, ultra violet light exposure and thermal cyclic loading. Building upon it, we have been able to successfully engineer an efficient volumetric absorption solar thermal platform that employs the as-prepared nanofluids and achieves higher steady state temperatures (approximately 5% higher) relative to the conventional surface absorption based solar thermal system under the sun. The developed volumetric absorption solar thermal platform could prove to be significant step in the evolution of efficient solar thermal systems which could potentially be deployed for host of applications ranging from solar driven heating, air-conditioning, and desalination units to solar energy electricity generation systems.

SUBMITTER: Singh N

PROVIDER: S-EPMC6646354 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

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Publications

Efficient Volumetric Absorption Solar Thermal Platforms Employing Thermally Stable - Solar Selective Nanofluids Engineered from Used Engine Oil.

Singh Nirmal N Khullar Vikrant V

Scientific reports 20190722 1

We report a low cost and scalable method to synthesize solar selective nanofluids from 'used engine oil'. The as-prepared nanofluids exhibit excellent long-term stability (presently tested up to 6 months under undisturbed stagnant conditions at room temperature) and photo-thermal conversion efficiency. Moreover, these were found to retain their stability and functional characteristics even after extended periods (72 hours) of high temperature (300°C) heating, ultra violet light exposure and ther ...[more]

PMID: 31332280

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Project description:Background:Radiological assessments of biologically relevant regions in glioblastoma have been associated with genotypic characteristics, implying a potential role in personalized medicine. Here, we assess the reproducibility and association with survival of two volumetric segmentation platforms and explore how methodology could impact subsequent interpretation and analysis. Methods:Post-contrast T1- and T2-weighted FLAIR MR images of 67 TCGA patients were segmented into five distinct compartments (necrosis, contrast-enhancement, FLAIR, post contrast abnormal, and total abnormal tumor volumes) by two quantitative image segmentation platforms - 3D Slicer and a method based on Velocity AI and FSL. We investigated the internal consistency of each platform by correlation statistics, association with survival, and concordance with consensus neuroradiologist ratings using ordinal logistic regression. Results:We found high correlations between the two platforms for FLAIR, post contrast abnormal, and total abnormal tumor volumes (spearman's r(67) = 0.952, 0.959, and 0.969 respectively). Only modest agreement was observed for necrosis and contrast-enhancement volumes (r(67) = 0.693 and 0.773 respectively), likely arising from differences in manual and automated segmentation methods of these regions by 3D Slicer and Velocity AI/FSL, respectively. Survival analysis based on AUC revealed significant predictive power of both platforms for the following volumes: contrast-enhancement, post contrast abnormal, and total abnormal tumor volumes. Finally, ordinal logistic regression demonstrated correspondence to manual ratings for several features. Conclusion:Tumor volume measurements from both volumetric platforms produced highly concordant and reproducible estimates across platforms for general features. As automated or semi-automated volumetric measurements replace manual linear or area measurements, it will become increasingly important to keep in mind that measurement differences between segmentation platforms for more detailed features could influence downstream survival or radio genomic analyses.

Dataset Information

Efficient Volumetric Absorption Solar Thermal Platforms Employing Thermally Stable - Solar Selective Nanofluids Engineered from Used Engine Oil.

Publications

Efficient Volumetric Absorption Solar Thermal Platforms Employing Thermally Stable - Solar Selective Nanofluids Engineered from Used Engine Oil.

Similar Datasets

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