AIMC Journal:
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Showing 11 to 20 of 55 articles

Predictive modelling and experimental analysis of radiation-resistant MXene-silicon heterojunction solar cells.

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MXene-silicon heterojunction solar cells (Ti3C2Tx-Si) have become a potential candidate for radiation-tolerant photovoltaic (PV) applications, specifically in harsh space conditions. In this study, a combination of predictive modeling and experimenta...

Numerical modeling of 2D sutterby fluid stagnation-point flow over a stretching surface using levenberg-marquardt backpropagation.

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Two-dimensional (2D) prediction of Sutterby fluid flow is important in polymer synthesis, industrial coatings, aviation and thermal regulation, and this work utilizes the Levenberg-Marquardt backpropagation (LMBP) method. The calculation of Sutterby ...

Intelligent neuro computing paradigm for thermophoresis in carboxymethyl cellulose-water trihybrid nanoliquid with heat generation effects.

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This research uses thermophoretic particle deposition and a heat source to examine the effects of heat production on a trihybrid nanofluid based on carboxymethyl cellulose and water. A fundamental technique in electrical and aero solution engineering...

Artificial neural network prediction of nonlinear radiative heat transfer and entropy generation in tangent hyperbolic tetra hybrid nanofluid flow over a porous wedge.

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An artificial neural network (ANN)-based surrogate modelling approach for forecasting entropy production and heat transfer properties in a tetra-hybrid tangent-hyperbolic nanofluid flow over expanding and contracting wedge surfaces under nonlinear th...

Analytical and artificial neural network modeling of double-diffusive magnetized electroosmotic ellis nanofluid flow through a tapered non-uniform channel.

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This study investigates the nonlinear transport dynamics of an Ellis nanofluid in a tapered asymmetric peristaltic channel embedded in a Darcy porous medium under electroosmotic effects. The mathematical model incorporates double-diffusive transport,...

Next generation materials for environmental remediation through advanced mechanisms and future perspectives.

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Escalating environmental pollution and the increasing complexity of contaminants pose significant challenges to conventional remediation technologies, necessitating the development of innovative, sustainable solutions. This review critically examines...

Next generation graphene based MXene metamaterial multicylinder resonator solar absorber optimized with machine learning for conceptual solar dryer mining applications.

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In the field of industry and mining sectors, energy demand is rapidly increasing, and it is very necessary to develop a durable, scalable, and broadband solar thermal absorber. And a conventional absorber has a narrowband absorptance and low thermal ...

Predicting and analyzing the dielectric constant of polyvinyl alcohol reinforced with different nanofillers using machine learning modeling.

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Polyvinyl alcohol (PVA) is a widely used polymer in many applications. The nanoparticles' incorporation into the polyvinyl alcohol structure can significantly modify the electrical characteristics by benefiting the properties of both polymer and nano...

Sensitive detection of unopposed estrogen using estrogen receptor functionalized nanoprobes for cancer diagnosis.

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Unopposed estrogen refers to prolonged estrogenic stimulation in the absence of adequate progesterone-mediated counter-regulation. Unopposed estrogen is strongly implicated in endometrial hyperplasia and type I endometrial carcinogenesis, and it is a...

Intelligent prediction of thermodynamic performance in MHD Oldroyd B trihybrid nanofluids using artificial neural networks.

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This research aims to describe the flow characteristics and entropy creation of an Oldroyd-B tri hybrid nanofluid under conditions of MHD with heat transfer through a hybrid numerical-machine learning framework. The nonlinear boundary layer governing...