Metal oxide nanoparticles offer great merits over controlling rheological, thermal, chemical and physical properties of solutions. The effectiveness of a nanoparticle to modify the properties of a fluid depends on its diffusive properties with respect to the fluid. In this study, rheological properties of aqueous fluids (i.e. water) were enhanced with the addition of CeO₂ nanoparticles. This study was characterized by the outcomes of simulation and experimental results of nanofluids. The movement of nanoparticles in the fluidic media was simulated by a large-scale molecular thermal dynamic program (i.e. LAMMPS). The COMPASS force field was employed with smoothed particle hydrodynamic potential (SPH) and discrete particle dynamics potential (DPD). However, this study develops the understanding of how the rheological properties are affected due to the addition of nanoparticles in a fluid and the way DPD and SPH can be used for accurately estimating the rheological properties with Brownian effect. The rheological results of the simulation were confirmed by the convergence of the stress autocorrelation function, whereas experimental properties were measured using a rheometer. These rheological values of simulation were obtained and agreed within 5 % of the experimental values; they were identified and treated with a number of iterations and experimental tests. The results of the experiment and simulation show that 10 % CeO₂ nanoparticles dispersion in water has a viscosity of 2.0–3.3 mPas.

Interest in nanoparticle modification using functional chemicals has increased rapidly, as it allows more freedom of physiochemical tuning of the nanoparticle’s surface into biomedically oriented and designated properties. However, the observation and detection of the thin molecular layers on the nanoparticle surface are very challenging under current analytical facilities. The focus of this research is to demonstrate fundamental interactions between the surface treated nanoparticles and their host liquid media using lab-based experimentation and simulation. In this research, investigation has been carried out on analyzing the surface compatibility and the diffusivity of modified CuO nanoparticles (CuONPs) with short-chain carboxylate-terminated molecules in biofluids. Moreover, during the current Covid-19 pandemic, the Cu/CuONPs have proved effective in killing SARS-CoV1/2 and other airborne viruses. This research was conducted at the molecular level with joint consideration of experimental and simulation studies for characterization of variables. Experimental tests conducted using Fourier Transform Infrared (FTIR) spectroscopy demonstrated several spectral ranges of interest, specifically, detection of three major carboxylate attachments (i.e., 1667–1609 cm⁻¹, 1668–1557 cm⁻¹, etc.) were found. From simulation, similar attachment styles were observed by the LAMMPS simulation package that mimicked similar agglomerations with a predicted diffusion coefficient as recorded to be 2.28E−9 m²/s. Viscosities of modified nanofluids were also compared with unmodified nanofluids for defining aggregation kinetics.

The space-time correlation function has been obtained in strongly coupled dusty plasmas (SCDPs) using equilibrium molecular dynamics (EMD) simulations. The simulated results for three-dimensional (3D) SCDPs with suitable normalization are computed over a wide domain of plasma parameters (Γ, κ) in a microcanonical ensemble. The EMD simulations indicate that different modes of propagated wave in SCDPs are analyzed for four different values of wave number (k). New investigations of normalized longitudinal current correlation function C_L(k, t) show that the amplitude of oscillation and frequency of propagated modes increase with an increase in k. The obtained results for longitudinal modes of oscillation indicate that the dust particles remain in damping behavior at the low Γ, damped oscillation with decreasing amplitude inside decaying exponential envelope at intermediate Г, and sinusoidal oscillation at high Г, depending on κ. The system size (N) does not significantly affect the propagated modes of oscillation, while the periodic oscillation shifts toward higher Γ with increasing N and κ. The computations show that normalized longitudinal C_L(k, t) current correlation particularly depend on Coulomb coupling (Γ), Debye screening (κ), and wave number (k). In our simulations, the frequency and the amplitude of oscillation of the dust particles decrease with an increment of κ and system size (N), but the frequency increases and the amplitude decreases with increasing Γ, as expected. It has been demonstrated that the EMD method is used to study the different propagated modes in dusty plasma systems and can be used to predict the damping behavior, damped oscillation, and periodic phenomena in 3D strongly coupled SCDPs.

The addition of metal oxide nanoparticles to fluids has been used as a means of enhancing the thermal conductive properties of base fluids. This method formulates a heterogeneous fluid conferred by nanoparticles and can be used for high-end fluid heat-transfer applications, such as phase-change materials and fluids for internal combustion engines. These nanoparticles can enhance the properties of both polar and nonpolar fluids. In the current paper, dispersions of nanoparticles were carried out in hydrocarbon and aqueous-based fluids using molecular dynamic simulations (MDS). The MDS results have been validated using the autocorrelation function and previous experimental data. Highly concurrent trends were achieved for the obtained results. According to the obtained results of MDS, adding CuO nanoparticles increased the thermal conductivity of water by 25% (from 0.6 to 0.75 W·m⁻¹·K⁻¹). However, by adding these nanoparticles to hydrocarbon-based fluids (i.e., alkane) the thermal conductivity was increased three times (from 0.1 to 0.4 W·m⁻¹·K⁻¹). This approach to determine the thermal conductivity of metal oxide nanoparticles in aqueous and nonaqueous fluids using visual molecular dynamics and interactive autocorrelations demonstrate a great tool to quantify thermophysical properties of nanofluids using a simulation environment. Moreover, this comparison introduces data on aqueous and nonaqueous suspensions in one study.