ORCID Profile
0000-0002-9641-0033
Current Organisation
Macquarie University
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Publisher: National Library of Serbia
Date: 2015
Abstract: This article presents results from a numerical study of a turbulent slot jet impinging on a concave surface. Five different low Reynolds number k-? models were evaluated to predict the heat transfer under a two dimensional steady turbulent jet. The effects of flow and geometrical parameters (e.g. jet Reynolds number and jet-to-target separation distance) have been investigated. The Yap correction is applied for reducing the over-prediction of Nusselt number in the near wall region. It is shown that among the models tested in this study, the LS-Yap model is capable of predicting local Nusselt number in good agreement with the experimental data in both stagnation and wall jet region. Moreover, after implementation of Yap correction, no significant effect of the nozzle-to-surface distance, h/B, on the predicted stagnation Nusselt number has been found. Finally it is demonstrated that the higher values of turbulent Prandtl number reduces the heat diffusion along the wall and consequently the predicted local Nusselt number is reduced especially in the wall jet region.
Publisher: Elsevier BV
Date: 02-2014
Publisher: IEEE
Date: 12-2019
Publisher: Elsevier BV
Date: 2016
Publisher: Wiley
Date: 05-10-2020
Abstract: Lithium consumption is estimated to face a considerable rise in the next decade thus, finding new reproducible lithium resources such as brine deposits and seawater has become a fast‐growing research topic. However, Li + extraction from these resources is challenging due to its low concentration and presence of other monovalent cations exhibiting identical chemical properties. Here, it is discovered that tannic acid (TA) inside graphene oxide (GO) nanochannel acts as natural ion trapper, which possesses lithiophilic elements. The lithium‐rich feed is achieved by using the potential‐driven TA‐GO membrane by excluding lithium ions from other monovalent cations. The results showed that the ion trapping capability of inexpensive TA‐GO membrane is Li + Na + K + with Li trapping energy of − 593 KJ mol −1 , respectively, where its trapping efficiency goes into a top rank among their expensive synthetic counterparts. Evaluating the combined effect of three key parameters, including barrier energy, hydration energy, and binding energy illustrates that required energy to transport Li‐ion through the membrane is higher than that for other monovalent. This proof‐of‐concept work opens up an avenue of research for designing a new class of ion‐selective membranes, based on the incorporation of naturally low cost available lithiophilic guest molecules into 2D membranes.
Publisher: Elsevier BV
Date: 04-2021
Publisher: American Chemical Society (ACS)
Date: 13-09-2021
Abstract: With an ageing population, hearing disorders are predicted to rise considerably in the following decades. Thus, developing a new class of artificial auditory system has been highlighted as one of the most exciting research topics for biomedical applications. Herein, a design of a biocompatible piezoresistive-based artificial hair cell sensor is presented consisting of a highly flexible and conductive polyvinyl alcohol (PVA) nanocomposite with vertical graphene nanosheets (VGNs). The bilayer hydrogel sensor demonstrates excellent performance to mimic biological hair cells, responding to acoustic stimuli in the audible range between 60 Hz to 20 kHz. The sensor output demonstrates stable mid-frequency regions (∼4-9 kHz), with the greatest sensitivity as high frequencies (∼13-20 kHz). This is somewhat akin to the mammalian auditory system, which has remarkable sensitivity and sharp tuning at high frequencies due to the "active process". This work validates the PVA/VGN sensor as a potential candidate to play a similar functional role to that of the cochlear hair cells, which also operate over a wide frequency domain in a viscous environment. Further characterizations of the sensor show that increasing the sound litude results in higher responses from the sensor while taking it to the depth drops the sensor outputs due to attenuation of sound in water. Meanwhile, the acoustic pressure distribution of sound waves is predicted through finite element analysis, whereby the numerical results are in perfect agreement with experimental data. This proof-of-concept work creates a platform for the future design of susceptible, flexible biomimetic sensors to closely mimic the biological cochlea.
No related grants have been discovered for Hadi Ahmadi.