Unlocking the Power of Artificial Intelligence: Accurate Zeta Potential Prediction Using Machine Learning

Nanoparticles have gained significance in modern science due to their unique characteristics and diverse applications in various fields. Zeta potential is critical in assessing the stability of nanofluids and colloidal systems but measuring it can be time-consuming and challenging. The current research proposes the use of cutting-edge machine learning techniques, including multiple regression analyses (MRAs), support vector machines (SVM), and artificial neural networks (ANNs), to simulate the zeta potential of silica nanofluids and colloidal systems, while accounting for affecting parameters such as nanoparticle size, concentration, pH, temperature, brine salinity, monovalent ion type, and the presence of sand, limestone, or nano-sized fine particles. Zeta potential data from different literature sources were used to develop and train the models using machine learning techniques. Performance indicators were employed to evaluate the models' predictive capabilities. The correlation coefficient (r) for the ANN, SVM, and MRA models was found to be 0.982, 0.997, and 0.68, respectively. The mean absolute percentage error for the ANN model was 5%, whereas, for the MRA and SVM models, it was greater than 25%. ANN models were more accurate than SVM and MRA models at predicting zeta potential, and the trained ANN model achieved an accuracy of over 97% in zeta potential predictions. ANN models are more accurate and faster at predicting zeta potential than conventional methods. The model developed in this research is the first ever to predict the zeta potential of silica nanofluids, dispersed kaolinite, sand-brine system, and coal dispersions considering several influencing parameters. This approach eliminates the need for time-consuming experimentation and provides a highly accurate and rapid prediction method with broad applications across different fields.

Chitosan-Mediated Environment-Friendly Synthesis of Gold Nanoparticles with Enhanced Photonic Reactivity

We developed a very simple, efficient and environment-friendly synthesis method for the manufacturing of high-performance chitosan-capped gold nanoparticles that could be used for biosensing applications. Gold nanoparticles were prepared through the spontaneous reduction of chloroauric acid by chitosan, which was used as both a reducing and a stabilizing agent. The samples were heated to a temperature of 60 °C under ultrasonic conditions. The composite system made of chitosan as a matrix and gold nanoparticles demonstrated a high stability in an aqueous buffer solution. The nanoparticles displayed an enhancement in photonic performance compared with the same property of individual components as a result of surface plasmon resonance at the interface between the structural phases of the hybrid structure. The enhanced photonic reactivity of the hybrid nanostructure may offer new insights for future possible biosensing applications.

Essential-Oil-Loaded Nanoemulsion Lipidic-Phase Optimization and Modeling by Response Surface Methodology (RSM): Enhancement of Their Antimicrobial Potential and Bioavailability in Nanoscale Food Delivery System

Nanoencapsulation is an attractive technique used for incorporating essential oils in foods. Thus, our main goal was to formulate a novel nanoemulsion (NE) with nanoscale droplet size and lowest interfacial tension in the oil–water interface, contributing positively to the stability and the enhancement of essential oil potential. Thereby, response surface methodology (RSM), with mixture design was used to optimize the composition of the NE lipid phase. The essential oil combinations were encapsulated through high-pressure homogenization (HPH) with the binary emulsifier system (Tween 80: Gum Arabic). Then, the electrophoretic and physical properties were evaluated. We also conducted a follow-up stability and antimicrobial study that examined the stabilization mechanism of optimal NE. Thereafter, the effect of nanoencapsulation on the essential oil composition was assessed. The RSM results were best fitted into polynomial models with regression coefficient values of more than 0.95. The optimal NE showed a nanometer-sized droplet (270 nm) and lower interfacial tension (~11 mN/m), favoring negative ζ-potential (−15 mV), showing good stability under different conditions—it synergistically enhances the antimicrobial potential. GC-MS analysis showed that the use of HPH affected the active compounds, consistent with the differences in linalool and 2-Caren-10-al content. Hence, the novel nanometric delivery system contributes to food industry fortification.

Dynamic evolution of hyperuniformity in a driven dissipative colloidal system

Hyperuniformity is evolving to become a unifying concept that can help classify and characterize equilibrium and nonequilibrium states of matter. Therefore, understanding the extent of hyperuniformity in dissipative systems is critical. Here, we study the dynamic evolution of hyperuniformity in a driven dissipative colloidal system. We experimentally show and numerically verify that the hyperuniformity of a colloidal crystal is robust against various lattice imperfections and environmental perturbations. This robustness even manifests during crystal disassembly as the system switches between strong (class I), logarithmic (class II), weak (class III), and non-hyperuniform states. To aid analyses, we developed a comprehensive computational toolbox, enabling real-time characterization of hyperuniformity in real- and reciprocal-spaces together with the evolution of several order metric features, and measurements showing the effect of external perturbations on the spatiotemporal distribution of the particles. Our findings provide a new framework to understand the basic principles that drive a dissipative system to a hyperuniform state.

Larvicide Activity on Aedes aegypti of Essential Oil Nanoemulsion from the Protium heptaphyllum Resin

The aim of this work was to prepare a nanoemulsion containing the essential oil of Protium heptaphyllum resin and to evaluate the larvicidal activity and the residual larvicidal effect against Aedes aegypti. The essential oil was identified by gas chromatography coupled to a mass spectrometer, and the nanoemulsions were prepared using a low-energy method and characterized by photon correlation spectroscopy. The results indicated the major constituents as p-cimene (27.70%) and α-Pinene (22.31%). Nanoemulsions had kinetic stability and a monomodal distribution in a hydrophilic-lipophilic balance of 14 with particle diameters of 115.56 ± 1.68 nn and zeta potential of −29.63 ± 3.46 mV. The nanoemulsion showed larvicidal action with LC₅₀ = 2.91 µg∙mL⁻¹ and residual larvicidal effect for 72 h after application to A. aegypti larvae. Consequently, the nanobiotechnological product derived from the essential oil of P. heptaphyllum resin could be used against infectious disease vectors.

Influence of the magnetic nanoparticle coating on the magnetic relaxation time

Colloidal systems consisting of monodomain superparamagnetic nanoparticles have been used in biomedical applications, such as the hyperthermia treatment for cancer. In this type of colloid, called a nanofluid, the nanoparticles tend to agglomeration. It has been shown experimentally that the nanoparticle coating plays an important role in the nanoparticle dispersion stability and biocompatibility. However, theoretical studies in this field are lacking. In addition, the ways in which the nanoparticle coating influences the magnetic properties of the nanoparticles are not yet understood. In order to fill in this gap, this study presents a numerical simulation model that elucidates how the nanoparticle coating affects the nanoparticle agglomeration tendency as well as the effective magnetic relaxation time of the system. To simulate the self-organization of the colloidal nanoparticles, a stochastic Langevin dynamics method was applied based on the effective Verlet-type algorithm. The Néel magnetic relaxation time was obtained via the Coffey method in an oblique magnetic field, adapted to the local magnetic field on a nanoparticle.

Effect of Cereclor as Rejuvenator to Enhance the Aging Resistance of Reclaimed Asphalt Pavement Binder

Asphalt is the most commonly used material for pavement construction around the world, and therefore, it is vital to acquaint a practice that restores the reclaimed asphalt pavement (RAP) binder properties to the required level of performance by adding proper rejuvenators. However, a rejuvenator may perform better in the early stages of its application but may not necessarily perform better in the long run. The aim of this study is to assess the rejuvenation effect on the aging resistance of RAP binder in long-life performance through applying artificial aging. In this study, base virgin binder of pen grade 60/70 and RAP binder rejuvenated with Cereclor were subjected to artificial aging to simulate the short- and long-term aging effects. Penetration, softening point, ductility, and viscosity; saturates, aromatics, resins, and asphaltene (SARA) fractionation; and Fourier-transform infrared (FTIR) spectroscopy, bending beam rheometer (BBR), and dynamic shear rheometer (DSR) tests were conducted to evaluate the potential improvements in various properties of RAP binder. The results indicated that the physical, fractional composition, rheological, and aging resistance of RAP binder improved through the rejuvenation mechanism. Therefore, the rejuvenator improved the chemical structure through re-balancing the constituents in the colloidal system, even after long-term re-aging, which proves it to be an aging-resistant binder. Furthermore, it has been concluded that Cereclor has substantial rejuvenation potential even after applying artificial aging, and it can be utilized in pavement recycling to achieve long-life performance. Furthermore, the results depict good correlations between the physical, rheological, and chemical parameters of virgin and RAP binder.

Novel drug delivery methods for the treatment of keratitis: moving away from surgical intervention

Introduction: Corneal ulceration is one of the leading causes of blindness especially in low- and mid-income countries (LMICs). Surgical treatment of microbial keratitis is associated with multiple challenges that include non-availability of donor corneal tissues, lack of trained corneal surgeons, and poor compliance to follow up care. As a result, the surgery fails in 70-90% cases. Therefore, improving outcome of medical treatment and thereby avoiding the need for the surgery is an unmet need in the care of corneal ulcer cases.Areas covered: In this review article, the authors have tried to compile information on the novel drug-delivery systems that have potential to enhance success of medical management. We have discussed the following systems: cyclodextrins, gel formulations, colloidal system, nanoformulations, drug-eluting contact lens, microneedle patch, and ocular inserts.Expert opinion: The goals of corneal ulcer treatment are as follows: rapid eradication of causative microorganisms, control of damage from induced inflammation and microbial toxins, and facilitation of repair. The ocular surface anatomy poses several challenges for drug delivery using standard topical therapy. The novel drug-delivery systems mentioned above aim to enhanced tear solubility; superior stability; improved bio-availability; reduced toxicity; besides facilitating targeted drug delivery and convenience of administration.

Immunoassay for Human IgG Using Antibody-functionalized Silver Nanoparticles

A simple colorimetric immunoassay for quantification of human immunoglobulin G (hIgG) is herein described. The assay is based on the aggregation inhibition of silver nanoparticles (AgNP) functionalized with hIgG antibody (anti-hIgG) on the surface. The aggregation is measured in terms of attenuance values ratio at 400 and 530 nm (A₄₀₀/A₅₃₀). A linear response between A₄₀₀/A₅₃₀ and hIgG concentration is observed in the range 25 - 200 ng mL^-1, and the detection limit is estimated as 11 ng mL^-1 hIgG.