[HTML][HTML] An overview of analytical models for thermal/Vis-NIR radiation transfer through nanopigment coated non-metallic materials

N Piri, AS Nateri - Results in Engineering, 2024 - Elsevier
Particulate films and coatings have received growing attention in a wide range of optical
applications, mainly those that involve passive heating and cooling strategies (eg, cool …

[HTML][HTML] Integrating artificial intelligence-based metaheuristic optimization with machine learning to enhance Nanomaterial-containing latent heat thermal energy …

A Basem, HK Abdulaali, A Alizadeh, PK Singh… - Energy Conversion and …, 2025 - Elsevier
Progress in artificial intelligence and machine learning has significantly improved the
capability to accurately predict the properties of nano-enhanced phase change materials …

[HTML][HTML] Explicit and explainable artificial intelligent model for prediction of CO2 molecular diffusion coefficient in heavy crude oils and bitumen

S Alatefi, OE Agwu, A Alkouh - Results in Engineering, 2024 - Elsevier
Optimizing CO 2 injection for enhanced oil recovery (EOR) requires a precise estimation of
the CO 2-diffusivity coefficient in porous media. This study developed a predictive model for …

[HTML][HTML] Synthesis, stability, and heat transfer applications of ternary composite nanofluids-A review over the last decade

MK Nayak, AA Pasha, BS Kamilla, DN Thatoi… - Results in …, 2025 - Elsevier
The need for more energy to cool thermal systems has increased daily. Such scenarios have
prompted researchers to look for alternative, sustainable, and emission-free techniques …

Optimizing ternary hybrid nanofluids using neural networks, gene expression programming, and multi-objective particle swarm optimization: a computational …

T Hai, A Basem, A Alizadeh, PK Singh, H Rajab… - Scientific Reports, 2025 - nature.com
The performance of nanofluids is largely determined by their thermophysical properties.
Optimizing these properties can significantly enhance nanofluid performance. This study …

Harnessing meta-heuristic, Bayesian, and search-based techniques in optimizing machine learning models for improved energy storage with microencapsulated …

LB Said, A Basem, AJ Sultan, PK Singh… - … Communications in Heat …, 2025 - Elsevier
In recent years, systems based on microencapsulated phase change materials (MPCMs)
have found applications in thermal energy storage, smart building construction, and battery …

Accurate prediction of the rheological behavior of MWCNT-Al2O3/water-ethylene glycol nanofluid with metaheuristic-optimized machine learning models

Y Ru, ABM Ali, KH Qader, HK Abdulaali, R Jhala… - International Journal of …, 2025 - Elsevier
The accurate prediction of the rheological properties of nanofluids is critical for optimizing
their application in various industrial systems. This study focuses on the dynamic viscosity …

A novel approach for optimizing a photovoltaic thermal system combined with solar thermal collector: Integrating RSM, multi-objective bat algorithm and VIKOR …

CY Hsu, H Pallathadka, P Patel, KS Yogi… - Journal of the Taiwan …, 2025 - Elsevier
Background A critical gap persists in solar technologies research regarding combining
response surface methodology (RSM) and the optimization capabilities of artificial …

[HTML][HTML] Synergizing Neural Networks with Multi-Objective Thermal Exchange Optimization and PROMETHEE Decision-Making to Improve PCM-based Photovoltaic …

Y Li, A Basem, A Alizadeh, PK Singh, S Dixit… - Case Studies in Thermal …, 2025 - Elsevier
This study addresses the integration of machine learning (ML) and artificial intelligence (AI)
for optimizing photovoltaic-thermal (PVT) systems. While ML modeling has become …