• Title/Summary/Keyword: smart nanofluids

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Differentiation among stability regimes of alumina-water nanofluids using smart classifiers

  • Daryayehsalameh, Bahador;Ayari, Mohamed Arselene;Tounsi, Abdelouahed;Khandakar, Amith;Vaferi, Behzad
    • Advances in nano research
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    • v.12 no.5
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    • pp.489-499
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    • 2022
  • Nanofluids have recently triggered a substantial scientific interest as cooling media. However, their stability is challenging for successful engagement in industrial applications. Different factors, including temperature, nanoparticles and base fluids characteristics, pH, ultrasonic power and frequency, agitation time, and surfactant type and concentration, determine the nanofluid stability regime. Indeed, it is often too complicated and even impossible to accurately find the conditions resulting in a stabilized nanofluid. Furthermore, there are no empirical, semi-empirical, and even intelligent scenarios for anticipating the stability of nanofluids. Therefore, this study introduces a straightforward and reliable intelligent classifier for discriminating among the stability regimes of alumina-water nanofluids based on the Zeta potential margins. In this regard, various intelligent classifiers (i.e., deep learning and multilayer perceptron neural network, decision tree, GoogleNet, and multi-output least squares support vector regression) have been designed, and their classification accuracy was compared. This comparison approved that the multilayer perceptron neural network (MLPNN) with the SoftMax activation function trained by the Bayesian regularization algorithm is the best classifier for the considered task. This intelligent classifier accurately detects the stability regimes of more than 90% of 345 different nanofluid samples. The overall classification accuracy and misclassification percent of 90.1% and 9.9% have been achieved by this model. This research is the first try toward anticipting the stability of water-alumin nanofluids from some easily measured independent variables.

Nanobio Colloidal Materials for Dermatological Applications (피부과학 나노바이오 콜로이드 개발 동향)

  • Kim, Ji Eun;Park, Daehwan;Lee, Jin Yong;Seo, Hyemin;Choi, Sang Koo;Kim, Jin Woong
    • Prospectives of Industrial Chemistry
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    • v.20 no.6
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    • pp.2-12
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    • 2017
  • 최근 피부산업은 미용적인 관점뿐만 아니라 피부질환치료에 대한 관심까지 폭넓게 성장하고 있어 피부의 건강을 개선하고 치료할 수 있는 새로운 신기술 개발이 다각적으로 이루어지고 있다. 특히 기술의 고도화와 체계화를 통한 피부과학기술의 진보가 화학, 화학공학, 재료공학을 기반으로 하는 전통학문분야와 조직공학, 바이오나노공학, 감성공학 등을 기반으로 하는 신학문분야가 융복합되어 이루어지고 있다. 따라서, 본 고에서는 피부산업에서 전략적인 응용이 가능한 피부 나노바이오 콜로이드의 연구개발에 대한 최근 현황을 소개하고자 한다.