Machine-learning-based predictions of polymer and postconsumer recycled polymer properties: a comprehensive review

N Andraju, GW Curtzwiler, Y Ji, E Kozliak… - … Applied Materials & …, 2022 - ACS Publications
There has been a tremendous increase in demand for virgin and postconsumer recycled
(PCR) polymers due to their wide range of chemical and physical characteristics. Despite …

Recent application developments of water-soluble synthetic polymers

K Halake, M Birajdar, BS Kim, H Bae, CC Lee… - Journal of Industrial and …, 2014 - Elsevier
In the history of man-made macromolecules, water-soluble polymers have primarily
maintained passive roles; examples include the uses of water-soluble polymers for viscosity …

Synthesizes, characterization, measurements and modeling thermal conductivity and viscosity of graphene quantum dots nanofluids

F Sedaghat, F Yousefi - Journal of Molecular Liquids, 2019 - Elsevier
The present study is aimed to measure the thermophysical properties of graphene quantum
dots (GQDs) nanoparticles that dispersed in water, ethylene glycol and water-ethylene …

Machine learning model and input batch management tool for the composition of new recycled polypropylene plastic material with reduced variability in target …

R Teruel, N Alcalá, C Crespo, M Laspalas - Journal of Cleaner Production, 2024 - Elsevier
Reducing the variability of recycled plastic materials is a prerequisite to encourage the safe
substitution of virgin materials in new components manufacturing, hence promoting the …

Thermal conductivity and structuring of multiwalled carbon nanotubes based nanofluids

M Moghaddari, F Yousefi, S Aparicio… - Journal of Molecular …, 2020 - Elsevier
Abstract the thermal conductivity of OH functionalized multiwalled carbon nanotube and its
composites with Ag, Au and Pd in water, ethylene glycol and ethylene glycol-water (60: 40 …

[HTML][HTML] A simple approach for the sonochemical loading of Au, Ag and Pd nanoparticle on functionalized MWCNT and subsequent dispersion studies for removal of …

M Moghaddari, F Yousefi, M Ghaedi… - Ultrasonics sonochemistry, 2018 - Elsevier
In this study, the artificial neural network (ANN) and response surface methodology (RSM)
based on central composite design (CCD) were applied for modeling and optimization of the …

Modeling the viscosity of ionic liquids using combined friction theory with perturbed hard-chain equation of state and neural network approaches

H Moslehi, SM Hosseini, M Pierantozzi… - Journal of Molecular …, 2023 - Elsevier
Fast and accurate prediction and correlation of thermophysical properties are always
important concerns for researchers and engineers. This work is the extension of our earlier …

Density and viscosity modeling of liquid adipates using neural network approaches

M Pierantozzi, SM Hosseini - Journal of Molecular Liquids, 2024 - Elsevier
Liquid Dialkylesters of adipic acid (adipates) have achieved prominence as alternative
green solvents due to their special properties. To enhance their utilization, accurate …

NNEoS: Neural network-based thermodynamically consistent equation of state for fast and accurate flash calculations

J Qu, S Yousef, T Faney, JC de Hemptinne, P Gallinari - Applied Energy, 2024 - Elsevier
Equations of state (EOS) correlate thermodynamic properties and are essential for flash
calculations. However, solving for an EOS can be time-consuming, and EOS do not …

State‐of‐the‐Art Review on the Applications of Nonlinear and Artificial Intelligence‐Based Controllers in Petrochemical Processes

TS Ansari, SAA Taqvi - ChemBioEng Reviews, 2023 - Wiley Online Library
Petrochemical industries are facing severe challenges in controlling nonlinear processes
which are to be analyzed and monitored to develop efficient control models for improved …