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One of the significant underlying principles of nanorobotic systems deals with the understanding and conceptualization of their respective complex nanocomponents. This paper introduces a new methodology to compute a set of optimal electronic and mathematical properties of Buckyball nanoparticle using graph algorithms based on dynamic programming and greedy algorithm.

Buckyball, C₆₀, is composed of sixty equivalent carbon atoms arranged as a highly symmetric hollow spherical cage in the form of a soccer ball. At first, Wiener, hyper‐Wiener, Harary and reciprocal Wiener indices were computed using dynamic programming and presented them as: W(Buckyball)=11870.4, WW(Buckyball)=52570.9, Ha(Buckyball)=102.2 and RW(Buckyball)=346.9. The polynomials of Buckyball, Hosoya and hyper‐Hosoya, which are in relationship with Buckyball's indices, have also been computed. The relationships between Buckyball's indices and polynomials were then computed and demonstrated a good agreement with their mathematical equations. Also, a graph algorithm based on greedy algorithms was used to find some optimal electronic aspects of Buckyball's structure by computing the Minimum Weight Spanning Tree (MWST) of Buckyball.

The computed MWST was indicated that for connecting sixty carbon atoms of Buckyball together: the minimum numbers of double bonds were 30; the minimum numbers of single bonds were 29; and the minimum numbers of electrons were 178. These results also had good agreement with the principles of the authors' used greedy algorithm.

This paper has used the graph algorithms for computing the optimal electronic and mathematical properties of BB. It has focused on mathematical properties of BB including Wiener, hyper‐Wiener, Harary and reciprocal Wiener indices as well as Hosoya and Hyper‐Hosoya polynomials and computerized them with dynamic programming graph algorithms.

The construction industry’s pursuit of sustainable and high-performance materials has led to the exploration of alternative aggregates and innovative additives. This paper investigates the combined influence of recycled aggregates (RA) and nano TiO₂ particles on M20 and M30 concretes, addressing ecological concerns and seeking to improve material properties. RA, sourced from construction and demolition waste, presents a sustainable solution to alleviate the environmental impact associated with traditional virgin aggregates (VA). However, challenges related to the mechanical strength and durability often hinder the widespread use of RA in concrete. This study aims to bridge this gap by exploring the reinforcing potential of nano TiO₂ particles.

Nanomaterial such as TiO₂ is known for its photocatalytic properties and reinforcement capabilities and has emerged as a promising additive in construction materials. The investigation herein involves the incorporation of nano TiO₂ at percentages of 0.5% and 1% in both VA- and RA-based M20 and M30 concretes. Comprehensive series of tests on mechanical, durability and microstructural properties are conducted for each concrete mix.

Results unequivocally indicate that the addition of TiO₂ significantly improves the properties of concrete, with RA-based concrete exhibiting performance comparable to that of VA-based counterparts. This breakthrough suggests a viable application of RA with TiO₂ in construction projects, promoting sustainability without compromising performance. Following experimental analyses, linear regression and multiple linear regression analyses are used to establish predictive equations correlating interfacial transition zone (ITZ) thickness with TiO₂ percentage, compressive strength, tensile strength, flexural strength and chloride penetration.

These equations serve as valuable tools for predicting ITZ thickness in future concrete formulations based on specified parameter quantities, thereby contributing to informed decision-making in sustainable construction practices. The findings of this study have the potential to contribute to the improvement of environmentally conscious construction methods while also improving the performance and durability of concrete structures.

This paper aims to study the Improvements in self-cleaning property of the white acrylic water-based paint by addition of different percentages of three commercially available titanium dioxide (TiO₂) nanoparticles as additives. Then, due to the risk of destruction of polymeric materials in the presence of nanoparticles, degradation of dry paint film samples was investigated for 15 days using two important chalking and yellowing factors. Finally, the TiO₂-modified paint sample with the best performance and optimum percentage of TiO₂ nanoparticles that produced desired self-cleaning and dry film properties was introduced.

Self-cleaning and dry film properties of white acrylic water-based paint were investigated by addition of three various types of commercial available TiO₂ nanoparticles (SSP-25, STA-100 and KA-100). X-ray diffraction, transmission electron microscopy and Brunauer–Emmett–Teller were used for characterization of TiO₂ samples. Colorimetric tests in decolourization of C.I. Basic Red 46 (BR46) were used for determination of self-cleaning properties of TiO₂-modified paints in comparison with unmodified paint sample. Also, paints defects such as chalking and yellowing were tested along two weeks.

The results indicated that, in all types of TiO₂ nanoparticles, by increasing the amount of TiO₂ in modified paint, self-cleaning property of the samples was enhanced. The paint containing SSP-25 indicated better self-cleaning properties than others due to its larger surface area. However, its usage above 3.5 weight per cent caused yellowing and chalking defects in dried paint film.

In this research, TiO₂-modified paint sample with the best performance in both self-cleaning and mechanical properties was selected among the nine sets of prepared paint samples. All the materials used in this research such as acrylic resin and three types of TiO₂ nanoparticles are of industrial grade. Therefore, the introduced TiO₂-modified paint sample has the potential for the commercial production as a building exterior paint.

In the present study, an attempt at introducing a self-cleaning paint sample with acceptable mechanical properties using three types of commercially available TiO₂ nanoparticles as additives and industrial grade of acrylic resin which is the most commonly used water-based resin in building paints, as binder. As far as it was searched in the literatures, the parallel study of the self-cleaning and mechanical properties of paints has not been reported as noteworthy. Self-cleaning property of the acrylic water-based paint samples was investigated by adding three types of the commercially available TiO₂ nanoparticles. Also considering the possible detrimental effects of TiO₂ nanoparticles on polymeric materials and consequently on physical properties of the paint, chalking and yellowing factors in dried paint samples were evaluated.

Water is a vital natural resource without which life on earth would be impossible. Properties of synthetic dyes like high stability and noxious nature make it difficult to remove them from the effluent. This review focuses on the removal of synthetic dyes using nanoparticles (NPs) based on the adsorption principle.

Adsorption technique is widely used to remove synthetic dyes from their aqueous solution for decades. Synthetic dye removal using NPs is promising, less energy-intensive and has become popular in recent years. NPs are in high demand for treating wastewater using the adsorption principle due to their tiny size and vast surface area. To maximise environmental sustainability, the utilisation of green-produced NPs as efficient catalysts for dye removal has sparked attention amongst scientists.

This review has prioritised research and development of optimal dye removal systems that can be used to efficiently remove a large quantity of dye in a short period while safeguarding the environment and producing fewer harmful by-products. The removal efficiency of synthetic dye using different NPs in wastewater treatment varies mostly between 75% to almost 100%. This review will aid in the scaling up of the wastewater treatment process.

There is a lack of research emphasis on the safe disposal of NPs once the reuse efficiency significantly drops. The relevance of cost analysis is equally critical, yet only a few papers discuss cost-related information.

Comprehensive and planned research in this area can aid in the development of long-term wastewater treatment technology to meet the growing need for safe and reliable water emphasising reuse and desorption efficiency of the NPs.

With the help of basic physics, the application of computer algorithms in the form of recent advances such as machine learning and neural networking in textile Industry has been discussed in this review. Scientists have linked the underlying structural or chemical science of textile materials and discovered several strategies for completing some of the most time-consuming tasks with ease and precision. Since the 1980s, computer algorithms and machine learning have been used to aid the majority of the textile testing process. With the rise in demand for automation, deep learning, and neural networks, these two now handle the majority of testing and quality control operations in the form of image processing.

The state-of-the-art of artificial intelligence (AI) applications in the textile sector is reviewed in this paper. Based on several research problems and AI-based methods, the current literature is evaluated. The research issues are categorized into three categories based on the operation processes of the textile industry, including yarn manufacturing, fabric manufacture and coloration.

AI-assisted automation has improved not only machine efficiency but also overall industry operations. AI's fundamental concepts have been examined for real-world challenges. Several scientists conducted the majority of the case studies, and they confirmed that image analysis, backpropagation and neural networking may be specifically used as testing techniques in textile material testing. AI can be used to automate processes in various circumstances.

This research conducts a thorough analysis of artificial neural network applications in the textile sector.

Using suspended nanoparticles in the base fluid is known as one of the most efficient ways for heat transfer augmentation and improving the thermal efficiency of various heat exchangers. Different types of nanofluids are available and used in different applications. The main purpose of this study is to investigate the effects of using hybrid nanofluid and number of plates on the performance of plate heat exchanger. In this study, TiO₂/water single nanofluid and TiO₂-Al₂O₃/water hybrid nanofluid with 1% particle weight ratio have been used to prepare hybrid nanofluid to use in plate type heat exchangers with three various number of plates including 8, 12 and 16.

The experiments have been conducted with the aim of examining the impact of plates number and used nanofluids on heat transfer enhancement. The performance tests have been done at 40°C, 45°C, 50°C and 55°C set outlet temperatures and in five various Reynolds numbers between 1,600 and 3,800. Also, numerical simulation has been applied to verify the heat and flow behavior inside the heat exchangers.

The results indicated that using both nanofluids raised the thermal performance of all tested exchangers which have a various number of plates. While the major outcomes of this study showed that TiO₂-Al₂O₃/water hybrid nanofluid has priority when compared to TiO₂/water single type nanofluid. Utilization of TiO₂-Al₂O₃/water nanofluid led to obtaining an average improvement of 7.5%, 9.6% and 12.3% in heat transfer of heat exchangers with 8, 12 and 16 plates, respectively.

In the present work, experimental and numerical analyzes have been conducted to investigate the influence of using TiO₂-Al₂O₃/water hybrid nanofluid in various plate heat exchangers. The attained findings showed successful utilization of TiO₂-Al₂O₃/water nanofluid. Based on the obtained results increasing the number of plates in the heat exchanger caused to obtain more increment by using both types of nanofluids.

The purpose of this paper is to study the optimal conditions of the mixed convection in a ventilated square cavity filled with Cu-water nanofluid using the Taguchi method. The paper aims to discuss diverse issues affecting the said model.

The numerical solutions of nonlinear coupled equations are developed by means of the Taguchi method. The Taguchi method is used as an effective way to optimize the design process engineering tests.

The governing equations are discretized using a finite volume method and solved with semi-implicit method for pressure linked equations (SIMPLE) algorithm. The effect of Richardson number (0.01-10), the volume fraction of nanofluid (0-5 per cent), distance of inlet port position from bottom wall of the cavity (0-0.9 H) and distance of outlet port position from top wall of the cavity (0-0.9 H) as effective parameters are analyzed across four levels. This analysis is done for fixed Grashof number 10⁴. The results show that the mean Nusselt number almost decreases by an increase in the Richardson number, volume fraction of nanofluid, position of the inlet port and position of the outlet port. It is found that the cavity with distance of inlet port position from bottom wall of the cavity 0 and distance of outlet port position from upper wall of the cavity 0.9 H at the Richardson number 0.01 and the volume fraction 3 per cent is the optimal design for heat transfer.

As far as the authors know, this model has been investigated for the first time.

The purpose of this study was to the synthesis of Fe₃O₄@SiO₂ nanocomposites and using it as an adsorbent for removal of diazinon from aqueous solutions. Structural characteristics of the synthesized magnetic nanocomposite were described by Fourier transform infrared spectroscopy and scanning electron microscopy.

The effects of different parameters including pH (2-10), contact time (1-180 min), adsorbent dosage (100-2000 mg L⁻¹) and initial diazinon concentration (0.5–20 mg L⁻¹) on the removal processes were studied. Finally, isotherm and kinetic and of adsorption process of diazinon onto Fe₃O₄@SiO₂ nanocomposites were investigated.

The maximum removal efficiency of diazinon (96%) was found at 180 min with 1000 mg L⁻¹ adsorbent dosage using 0.5 mg L⁻¹ diazinon concentration at pH = 7. The experimental results revealed that data were best fit with the pseudo-second-order kinetic model (R² = 0.971) and the adsorption capacity was 10.90 mg g⁻¹. The adsorption isotherm was accordant to Langmuir isotherm.

In the present study, the magnetic nanocomposites were synthesized and used as an absorbent for the removal of diazinon. The developed method had advantages such as the good ability of Fe₃O₄@SiO₂ nanocomposites to remove diazinon from aqueous solution and the magnetic separation of this absorbent that make it recoverable nanocomposite. The other advantages of these nanocomposites are rapidity, simplicity and relatively low cost.

The purpose of this paper is to investigate the efficacy of bacterial exopolysaccharides (Eps) in reactive black 5 (RB5) textile dye wastewater bioremediation.

The Eps were produced by bacteria isolated from cotton gin trash soils collected from different cotton-growing regions in Kenya for comparison purposes. A broth medium reconstituted using molasses was assessed for its capacity to produce the Eps. RB5 textile dye wastewater was optimized for dye removal under different temperatures, times and molasses concentrations. Dye removal was studied by Lovibond-Day Light Comparator, UV–Vis spectrophotometer and FTIR.

It was found that cotton gin trash soils contained Eps-producing bacteria. Three of the Eps studied were found to have the capacity to remove at least 80% of the dye from the wastewater.

This research did not assess the efficacy of the RB5 dye removal from the wastewater by mixtures of the Eps.

Bioremediation of textile dye wastewater with Eps produced by bacteria cultured from cotton gin trash soil is significant because it will offer an effective and cleaner alternative to the chemical coagulants.

Alternative treatment of textile wastewater with the Eps would result in safer water being released into the water bodies as opposed to the chemically treated wastewater that contains remnant chemicals.

Research on the use of Eps produced by bacteria isolated from cotton gin trash soils for removal of RB5 dye from textile wastewater has not been done before.