Search Results (224)

Nanoparticle-mediated photothermal conversion exploits the unique light-to-heat transduction properties of engineered nanomaterials to address challenges in energy, water, and healthcare. This review first examines fundamental mechanisms—localized surface plasmon resonance (LSPR) in plasmonic metals and broadband interband transitions in semiconductors—demonstrating how tailored nanoparticle compositions can achieve >96% absorption across 250–2500 nm and photothermal efficiencies exceeding 98% under one-sun illumination (1000 W·m⁻², AM 1.5G). Next, we highlight advances in solar steam generation and desalination: floating photothermal receivers on carbonized wood or hydrogels reach >95% efficiency in solar-to-vapor conversion and >2 kg·m⁻²·h⁻¹ evaporation rates; three-dimensional architectures recapture diffuse flux and ambient heat; and full-spectrum nanofluids (LaB₆, Au colloids) extend photothermal harvesting into portable, scalable designs. We then survey photothermal-enhanced thermal energy storage: metal-oxide–paraffin composites, core–shell phase-change material (PCM) nanocapsules, and MXene– polyethylene glycol—PEG—aerogels deliver >85% solar charging efficiencies, reduce supercooling, and improve thermal conductivity. In biomedicine, gold nanoshells, nanorods, and transition-metal dichalcogenide (TMDC) nanosheets enable deep-tissue photothermal therapy (PTT) with imaging guidance, achieving >94% tumor ablation in preclinical and pilot clinical studies. Multifunctional constructs combine PTT with chemotherapy, immunotherapy, or gene regulation, yielding synergistic tumor eradication and durable immune responses. Finally, we explore emerging opto-thermal nanobiosystems—light-triggered gene silencing in microalgae and poly(N-isopropylacrylamide) (PNIPAM)–gold nanoparticle (AuNP) membranes for microfluidic photothermal filtration and control—demonstrating how nanoscale heating enables remote, reversible biological and fluidic functions. We conclude by discussing challenges in scalable nanoparticle synthesis, stability, and integration, and outline future directions: multicomponent high-entropy alloys, modular photothermal–PCM devices, and opto-thermal control in synthetic biology. These interdisciplinary innovations promise sustainable solutions for global energy, water, and healthcare demands. Full article

This work shows that the length of single-walled carbon nanotubes is critical in governing the trade-off among the rate, efficiency, and stability of pressure-driven water transport. A critical length of 1.06 nm marks the transition in the transport mechanism from a thermal-fluctuation-dominated regime to an ordered water-chain mode. This transition is driven by the evolution of the potential of mean force with tube length, which progresses from a flat landscape to a high-barrier profile and ultimately forms a low-resistance tunnel in long nanotubes. Notably, this tunnel endows the water chain with an enhanced ability to restore its continuity, allowing it to bridge fracture gaps as wide as 7 Å even in the absence of an external pressure difference. These insights reveal a length-dependent mechanism that could revolutionize CNT–hydrogel hybrids for biomedical applications. Full article

This study investigates the thermal characteristics of two hybrid nanofluids, single-walled carbon nanotubes with titanium dioxide ($SWCNT-Ti{O}_2$) and multi-walled carbon nanotubes with copper ($MWCNT-Cu$), as they flow over an inclined, porous, and longitudinally stretched cylindrical surface with kerosene as the base fluid. The model takes into consideration all of the consequences of magnetohydrodynamic (MHD) effects, thermal radiation, and Arrhenius-like energy of activation. The outcomes of this investigation hold practical significance for energy storage systems, nuclear reactor heat exchangers, electronic cooling devices, biomedical hyperthermia treatments, oil and gas transport processes, and aerospace thermal protection technologies. The proposed hybrid ANN–numerical framework provides an effective strategy for optimizing the thermal performance of hybrid nanofluids in advanced thermal management and energy systems. A set of coupled ordinary differential equations is created by applying similarity transformations to the governing nonlinear partial differential equations that reflect conservation of mass, momentum, energy, and species concentration. The boundary value problem solver bvp4c, which is based in MATLAB (R2020b), is used to solve these equations numerically. The findings demonstrate that, in comparison to the $MWCNT-Cu/kerosene$ nanofluid, the $SWCNT-Ti{O}_2$/kerosene hybrid nanofluid improves the heat transfer rate (Nusselt number) by up to $23.6\%$. When a magnetic field is applied, velocity magnitudes are reduced by almost $15\%$, and the temperature field is enhanced by around $12\%$ when thermal radiation is applied. The impact of important dimensionless variables, such as the cylindrical surface’s inclination angle, the medium’s porosity, the magnetic field’s strength, the thermal radiation parameter, the curvature ratio, the activation energy, and the volume fraction of nanoparticles, is investigated in detail using a parametric study. According to the comparison findings, at the same flow and thermal boundary conditions, the $SWCNT-Ti{O}_2$/kerosene hybrid nanofluid performs better thermally than its $MWCNT-Cu$/kerosene counterpart. These results offer important new information for maximizing heat transfer in engineering systems with hybrid nanofluids and inclined porous geometries under intricate physical conditions. With its high degree of agreement with numerical results, the ANN model provides a computationally effective stand-in for real-time thermal system optimization. Full article

The increased energy efficiency of electrified vehicles and their potential to reduce CO₂ emissions through the use of environmentally friendly materials are highlighted as reasons for the shift to electrified vehicles. Brief trends on the development of electric vehicles (EVs) have been discussed, presenting outstanding improvement towards the actualization of the green economy. The state of the art in lubrication has been thoroughly investigated as one of the factors influencing energy efficiency and the lifespan of machine components. As a result, many reports on the effectiveness of specific lubricants in electric vehicle applications have been developed. Good thermal and corrosion-resistant lubricants are necessary because of the emergence of several new tribological difficulties, especially in areas that interact with greater temperatures and currents. To avoid fluidity and frictional problems that may be experienced over its lifetime, a good viscosity level of lubricant was also mentioned as a crucial component in the formulation of EV lubricant. New lubricants are also necessary for the gearbox systems of electric vehicles. Furthermore, battery electric vehicles (BEVs) require a suitable cooling system for the batteries; thus, a compatible nano-fluid is recommended. Sustainable battery cooling options support global energy efficiency and carbon emission reduction while extending the life of EV batteries. The path for future advancements or the creation of the most useful and efficient EV lubricants is provided by this review study. Full article

The transition to a sustainable energy mix is essential to mitigate climate change. Enhanced Oil Recovery (EOR) using low-salinity water (smart water) has emerged as a promising strategy for reducing environmental impacts in the petroleum industry, producing a highly valuable energy source due to both its energy density and market value. This study critically reviews intermediate technological readiness levels (TRL), applying a patent-based approach (TRL 4–5) and a review of articles (TRL 3) to analyze various aspects of smart water for EOR, including its composition. A total of 23 patents from the European Patent Office (Questel Orbit) and 1395 articles from Elsevier’s Scopus database were analyzed, considering annual trends, country distribution, international collaborations, author and applicant affiliations, citation dependencies, and factorial analyses. Both patents and articles show exponential growth; however, international collaboration is more frequent in the scientific literature, while patents remain concentrated in a few countries aligned with their markets. Technologies are focused on wettability, surface complexation, CO₂ interactions, emulsification, aerogels, reinjection water treatment, carbonate reservoirs, effluent treatment, nanofluidics, and ASP fluids. Recent topics include CO₂ associations, permeability, fractured reservoirs, gels, reservoir water, wettability alteration, and reservoir/oil heterogeneity. The findings indicate the need for multivariated development of customized smart waters to address complex interfacial synergistic mechanisms. International Joint Industry Projects and global regulations on the safe use and composition of hybrid injections are recommended to accelerate development, reduce environmental impacts, and enhance the efficient use of existing fields, alleviating the challenges of finding new reservoirs. Full article

The integration of nanofluids into solar collectors has gained increasing attention due to their potential to enhance heat transfer and support the transition toward low-carbon energy systems. However, a systematic understanding of their photothermal performance under the direct absorption mode remains lacking. This review addresses this gap by critically analyzing the role of nanofluids in solar energy harvesting, with a particular focus on the direct absorption mechanisms. Nanofluids enhance solar radiation absorption through improved light absorption by nanoparticles, surface plasmon resonance in metals, and enhanced heat conduction and scattering effects. The novelty of this work lies in its comparative evaluation of advanced nanofluids, including magnetic nanofluids, plasma nanofluids, and nanophase change slurries, highlighting their unique capabilities in flow manipulation, thermal storage, and optical energy capture. Future research directions are identified, such as the life cycle assessment (LCA) of nanofluids in solar systems, applications of hybrid nanofluids, development of predictive models for nanofluid properties, optimization of nanofluid performance, and integration of Direct Absorption Solar Collectors (DASCs). In addition, challenges related to the stability, production cost, and toxicity of nanofluids are critically analyzed and discussed for practical applications. This paper offers guidance for the design and application of high-performance nanofluids in next-generation solar energy systems. Full article

Cutting CO₂ emissions is crucial to face of climate change, and one of the most tried and true means of post-combustion CO₂ capture is by way of chemical absorption. In this work, the effect of titanium dioxide (TiO₂) nanoparticles in a 25 wt% potassium carbonate (K₂CO₃) solution on solvent regeneration is investigated. This research follows the previous work in which the effect of nanofluids was evaluated on CO₂ absorption. Desorption was studied at three different temperatures (343.15, 348.15 and 353.15 K), using the absorbent fluid with and without 0.06 wt% TiO₂ nanoparticles. The results indicate that the nanofluid enhanced the CO₂ release rates, also reducing energy consumption. The mass transfer was intensified by the presence of nanoparticles, which in turn increased CO₂ diffusivity and influenced the liquid boundary layer, resulting in an enhanced desorption rate, because of the higher diffusivity. These enhancements were achieved with negligible modifications to the fluid properties, i.e., viscosity. In summary, application of TiO₂-enhanced K₂CO₃ solutions is a practical approach to enhance CO₂ removal performance and reduce operating costs such that CO₂ capture is beginning to be environmentally and economically more competitive for the existing system retrofit. Full article

Nanofluids are an innovative working medium in solar hot water installations (DHWs), thanks to their increased thermal conductivity and heat transfer coefficient. The aim of this work was to assess the effect of Al₂O₃ nanofluids in a water–ethylene glycol base (40:60%) and with the addition of Tween 80 surfactant (0.2 wt%) on thermal efficiency (ε) and exergy (η_ex) in a plate heat exchanger at DHW flows of 3 and 12 L/min. The numerical NTU–ε model was used with dynamic updating of thermophysical properties of nanofluids and the solution of the ODE system using the ode45 method, and the validation was carried out against the literature data. The results showed that the nanofluids achieved ε ≈ 0.85 (vs. ε ≈ 0.87 for the base fluid) and η_ex ≈ 0.72 (vs. η_ex ≈ 0.74), with higher entropy generation. The addition of Tween 80 reduced the viscosity by about 10–15%, resulting in a slight increase of Re and h-factor; however, the impact on ε and η_ex was marginal. The environmental analysis with an annual demand of Q = 3000 kWh/year and an emission factor of 0.2 kg CO₂/kWh showed that for ε < 0.87 the nanofluids increased the emissions by ≈16 kg CO₂/year, while at ε ≈ 0.92, a reduction of ≈5% was possible. This paper highlights the need to optimize nanofluid viscosity and exchanger geometry to maximize energy and environmental benefits. Nowadays, due to the growing problems of global warming, the analysis of energy efficiency and carbon footprint related to the functioning of a building seems to be crucial. Full article

This study presents an experimental evaluation of the thermal and exergetic performance of an air-to-air heat pipe heat exchanger using a cobalt oxide (Co₃O₄)-based non-Newtonian nanofluid, with the additional incorporation of carbon black (CB). Nanofluids were synthesized via a two-step method and tested under turbulent flow conditions across varying Reynolds numbers. The results demonstrated that increasing the Co₃O₄ nanoparticle concentration and adding CB substantially improved both the thermal and exergetic performance compared to deionized water. Specifically, maximum thermal efficiency improvements of 62.7% and 75.4% were recorded for nanofluids containing 1% and 2% Co₃O₄, respectively. The addition of CB further enhanced the thermal efficiency, achieving a maximum improvement of 79.2%. Furthermore, the maximum reduction in thermal resistance reached 61.4% with CB incorporation, while the 2% Co₃O₄ nanofluid achieved a maximum decrease of 50.2%. The use of nanofluids led to a significant reduction in exergy loss, with exergy-saving efficiencies reaching up to 33.6%. These findings highlight the considerable potential of Co₃O₄- and CB-based hybrid nanofluids in advancing waste heat recovery technologies and enhancing the thermodynamic performance of air-to-air heat pipe heat exchanger systems. Full article

Nanoparticle additives are used to increase the cooling efficiency of cutting fluids in machining. In this study, changing dynamic viscosity values depending on the addition of nanoparticles to cutting oils was investigated. Mono nanofluids were prepared by adding hBN (hexagonal boron nitride), ZnO, MWCNT (multi-walled carbon nanotube), TiO₂, and Al₂O₃ as nanoparticles, hybrid nanofluids were prepared by using two types of nanoparticles (ZnO + MWCNT, hBN + MWCNT etc.), and ternary nanofluids were prepared by using three types of nanoparticles. GPR (Gaussian process regression) was used to estimate unmeasured dynamic viscosity values using the dynamic viscosity values measured for different temperatures. Dynamic viscosity results are a precise determination (R² = 1). An augmented dataset was obtained by adding the dynamic viscosity values estimated with high accuracy. A fitness function based on dynamic viscosity and nanoparticle unit costs was proposed for the cost analysis. With the help of the proposed fitness function, it was observed that the best performing nanoparticles were the ZnO and ZnO hybrid mixtures according to different dynamic viscosity and cost effects. The study showed that the most suitable nanofluid selection focused on performance and cost could be made without performing experiments under various operating conditions by increasing the limited experimental measurements with strong GPR estimates and using the proposed fitness function. Full article

Exploring the dynamics of nonlinear nanofluidic flow-induced vibrations, this work focuses on single-walled branched carbon nanotubes (SWCNTs) operating in a thermal–magnetic environment. Carbon nanotubes (CNTs), renowned for their exceptional strength, conductivity, and flexibility, are modeled using Euler–Bernoulli beam theory alongside Eringen’s nonlocal elasticity to capture nanoscale effects for varying downstream angles. The intricate interactions between nanofluids and SWCNTs are analyzed using the Differential Transform Method (DTM) and validated through ANSYS simulations, where modal analysis reveals the vibrational characteristics of various geometries. To enhance predictive accuracy and system stability, machine learning algorithms, including XGBoost, CATBoost, Random Forest, and Artificial Neural Networks, are employed, offering a robust comparison for optimizing vibrational and thermo-magnetic performance. Key parameters such as nanotube geometry, magnetic flux density, and fluid flow dynamics are identified as critical to minimizing vibrational noise and improving structural stability. These insights advance applications in energy harvesting, biomedical devices like artificial muscles and nanosensors, and nanoscale fluid control systems. Overall, the study demonstrates the significant advantages of integrating machine learning with physics-based simulations for next-generation nanotechnology solutions. Full article

The widespread use of mineral cutting fluids in metalworking poses challenges due to their poor wettability, toxicity, and non-biodegradability. This study explores cactus oil-based nanofluids as sustainable alternatives for metal cutting applications. Samples of cactus oil are prepared in plain form and with 0.025 wt.%, 0.05 wt.%, and 0.1 wt.% activated carbon nanoparticles (ACNPs) from recycled plastic waste. Plain cactus oil exhibited a 34% improvement in wettability over commercial soluble oil, further enhanced by 60% with 0.05 wt.% ACNPs. Cactus oil displayed consistent Newtonian behavior with a high viscosity index (283), outperforming mineral-based cutting fluid in thermal stability. The addition of ACNPs enhanced the dynamic viscosity by 108–130% across the temperature range of 40–100 °C. The presence of nano-additives reduced the friction coefficient in the boundary lubrication zone by a maximum reduction of 32% for CO2 compared to plain cactus oil. The physical and rheological results translated directly to the observed improvements in surface finish and tool wear during machining operations on H13 steel. Cactus oil with 0.05 wt.% ACNP outperformed conventional fluids, reducing surface roughness by 35% and flank wear by 57% compared to dry. This work establishes cactus oil-based nanofluids as a sustainable alternative, combining recycled waste-derived additives and non-edible feedstock for greener manufacturing. Full article

The main objective of this study is to improve heat transfer in hydrocarbon- and geothermal-energy coproduction systems using carbon quantum dots (CQDs). Two types of 0D nanoparticles (synthesized and commercial CQDs) were used for the formulation of nanofluids to increase the heat transfer from depleted wells for the coproduction of oil and electrical energy. The synthesized and commercial CQDs were characterized in terms of their morphology, zeta potential, density, size, and heat capacity. The nanofluids were prepared using brine from an oil well of interest and two types of CQDs. The effect of the CQDs on the thermophysical properties of the nanofluids was evaluated based on their thermal conductivity. In addition, a mathematical model based on heat transfer principles to predict the effect of nanofluids on the efficiency of the organic Rankine cycle (ORC) was implemented. The synthesized and commercial CQDs had particle sizes of 25 and 16 nm, respectively. Similarly, zeta potential values of 36 and 48 mV were obtained. Both CQDs have similar functional groups and UV absorption, and the fluorescence spectra show that the study CQDs have a maximum excitation–emission signal around 360–460 nm. The characterization of the nanofluids showed that the addition of 100, 300, and 500 mg/L of CQDs increased the thermal conductivity by 40, 50, and 60 %, respectively. However, the 1000 mg/L incorporated decreased the thermal conductivities of the nanofluids. The observed behavior can be attributed to the aggregate size of the nanoparticles. Furthermore, a new thermal conductivity model for CQD-based nanofluids was developed considering brine salinity, particle size distribution, and agglomeration effects. The model showed a remarkable fit with the experimental data and predicted the effect of the nanofluid concentration on the thermal conductivity and cycle efficiency. Coupled with an ORC cycle model, CQD concentrations of approximately 550 mg/L increased the cycle efficiency by approximately 13.8% and 18.6% for commercial and synthesized CQDs, respectively. Full article

This study investigates the thermophysical properties of multi-walled carbon nanotube (MWCNT) nanofluids dispersed in a water–ethylene glycol (50:50%) mixture. The nanofluids were prepared using a two-step method involving ultrasonication and high-pressure homogenization. The stability of the nanofluids was assessed using UV-Vis spectrophotometry over a period of 30 days. The results indicated a maximum decrease of 10% in the relative concentration, with no visible agglomeration or sedimentation. Thermal conductivity, viscosity, and density were experimentally measured at different temperatures and volumetric concentrations (0.025%, 0.05%, and 0.1%). The thermal conductivity of the nanofluids increased with both concentration and temperature, showing an enhancement of up to 10% at 50 °C for 0.1% vol. MWCNTs. The viscosity measurements revealed a maximum increase of 11% at 80 °C, while the density showed a slight increase with nanoparticle concentration and a decrease with temperature. The models proposed for estimating thermal conductivity (maximum deviation 1.5%) and viscosity (maximum deviation 3%) were found to be suitable, exhibiting good agreement with the experimental results. The results align with previous studies, reinforcing the role of Brownian motion and nanoparticle interactions in heat transfer enhancement. This study provides insights into the stability and thermophysical behavior of MWCNT nanofluids, contributing to their potential applications in thermal management systems. Full article

Machining processes often face challenges such as elevated temperatures and wear, which traditional cutting fluids are insufficient to address. As a result, solutions involving nanoparticle additives are being explored to enhance cooling and lubrication performance. This study investigates the effect of thermal conductivity, an important property influenced by the densities of mono and hybrid nanofluids. To this end, various nanofluids were prepared by incorporating hexagonal boron nitride (hBN), zinc oxide (ZnO), multi-walled carbon nanotubes (MWCNTs), titanium dioxide (TiO₂), and aluminum oxide (Al₂O₃) nanoparticles into sunflower oil as the base fluid. Hybrid nanofluids were created by combining two nanoparticles, including ZnO + MWCNT, hBN + MWCNT, hBN + ZnO, hBN + TiO₂, hBN + Al₂O₃, and TiO₂ + Al₂O₃. A dataset consisting of 180 data points was generated by measuring the thermal conductivity and density of the prepared nanofluids at various temperatures (30–70 °C) in a laboratory setting. Conducting thermal conductivity measurements across different temperature ranges presents significant challenges, requiring considerable time and resources, and often resulting in high costs and potential inaccuracies. To address these issues, a feedforward artificial neural network (FFANN) method was proposed to predict thermal conductivity. Our multilayer FFANN model takes as input the temperature of the experimental environment where the measurement is made, the measured thermal conductivity of the relevant nanoparticle, and the relative density of the nanoparticle. The FFANN model predicts the thermal conductivity value linearly as output. The model demonstrated high predictive accuracy, with a reliability of R = 0.99628 and a coefficient of determination (R²) of 0.9999. The average mean absolute error (MAE) for all hybrid nanofluids was 0.001, and the mean squared error (MSE) was 1.76 × 10⁻⁶. The proposed FFANN model provides a State-of-the-Art approach for predicting thermal conductivity, offering valuable insights into selecting optimal hybrid nanofluids based on thermal conductivity values and nanoparticle density. Full article