Research on the Development of a Way to Modify Asphalt Mixtures with PET Recyclates

Due to the growing need to recycle plastics, new possibilities for their reuse are intensively sought. In the Asian market, waste polymers are increasingly used to modify road bitumen. This solution is beneficial in many aspects, especially in economic and ecological terms. In this work, recycled poly(ethylene terephthalate) (RPET), obtained from storage points located in Lesser Poland, was subjected to material recycling, and its properties were examined using three analyses: differential scanning calorimetry (DSC), thermogravimetric analysis (TG), and Fourier transform infrared spectroscopy (FTIR). The most important point of this research was the selection of conditions for obtaining modified asphalt mixtures through the addition of RPET. Subsequently, the effect of the polymer on the properties of road bitumens was assessed on the basis of penetration tests, softening point, elastic recovery, and structure. In the last stage of our research work, asphalt mixtures with the addition of modified waste PET (PMA) containing mineral filler in the form of basalt dust were obtained. The properties of the obtained mineral-polymer-asphalt mixtures were compared in terms of frost resistance, structure, and abrasion resistance with the properties of mineral-asphalt mixtures that were taken from damaged road surfaces in four points in the city of Tarnów (Lesser Poland) in the winter of 2022. It has been shown that the modification of road bitumen with the use of recyclate and mineral filler has a significant impact on its performance properties.

Effects of Small Deviations in Fiber Orientation on Compressive Characteristics of Plain Concrete Cylinders Confined with FRP Laminates

The effectiveness of concrete confinement by fiber-reinforced polymer (FRP) materials is highly influenced by the orientation of fibers in the FRP laminates. In general, acceptable deviation limit from the intended direction is given as 5° in most design guidelines, without solid bases and reasoning. In this paper, a numerical study using finite element modeling was conducted to assess the effects of small deviations in fiber orientation from the hoop direction on compressive behavior of concrete cylinders confined with FRP. Different fiber angles of 0°, 2°, 5°, 8°, 10° and 15° with respect to hoop direction, unconfined concrete compressive strengths of 20, 35 and 50 MPa, FRP thicknesses of 0.2, 0.5 and 1.0 mm and FRP moduli of elasticity of 50 and 200 GPa were considered. The results showed that total dissipated energy (Et), ultimate axial strain (εcu') and compressive strength (fcu') exhibited the most reduction with deviation angle. For 5° deviation in fiber orientation, the average reduction in fcu', εcu' and Et were 2.4%, 2.8% and 4.5%, respectively. Furthermore, the calculated allowable limit of deviation in fiber orientation for a 2.5% reduction in fcu', εcu' and Et were 6°, 3° and 2°, respectively, with a 95% confidence.

Electrospinning of Poly (Acrylamide), Poly (Acrylic Acid) and Poly (Vinyl Alcohol) Nanofibers: Characterization and Optimization Study on the Effect of Different Parameters on Mean Diameter Using Taguchi Design of Experiment Method

In this study, nanofibers of poly (acrylic acid) (PAAc), polyacrylamide (PAAm) and poly (vinyl alcohol) (PVOH) were prepared using the electrospinning technique. Based on the Taguchi DOE (design of experiment) method, the effects of electrospinning parameters, i.e., needle tip to collector distance, polymer solution concentration, applied voltage, polymer solution feed rate and polymer type, on the diameter and morphology of polymer nanofibers were evaluated. Analyses of the experiments for the diameters of the polymer nanofibers showed that the type of polymer was the most significant factor. The optimal combination to obtain the smallest diameters with minimum deviations for electrospun polymer nanofibers was also determined. For this purpose, the appropriate factor levels were determined as follows: polymer PAAm, applied voltage 10 kV, delivery rate 0.1 mL/h, needle tip to collector distance 10 cm, and polymer solution concentration 8%, to obtain the thinnest nanofibers. This combination was further validated by conducting a confirmation experiment, and the average diameter of the polymer nanofibers was found to be close to the optimal conditions estimated by the Taguchi DOE method.

Preparation and Characterization of Novel Microgels Containing Nano-SiO2 and Copolymeric Hydrogel Based on Poly (Acrylamide) and Poly (Acrylic Acid): Morphological, Structural and Swelling Studies

In this paper, novel microgels containing nano-SiO₂ were prepared by in situ copolymerization using nano-SiO₂ particles as a reinforcing agent, nanosilica functional monomer (silane-modified nano-SiO₂) as a structure and morphology director, acrylamide (AAm) as a monomer, acrylic acid (AAc) as a comonomer, potassium persulfate (KPS) as a polymerization initiator, and N,N'-methylene bis (acrylamide) (MBA) as a crosslinker. In addition, a conventional copolymeric hydrogel based on poly (acrylamide/acrylic acid) was synthesized by solution polymerization. The microgel samples, hydrogel and nanoparticles were characterized by transmission electron microscopy (TEM), field emission scanning electron microscopy (FESEM), Fourier transform infrared (FTIR) spectroscopy, thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC). A FESEM micrograph of copolymeric hydrogel showed the high porosity and 3D interconnected microstructure. Furthermore, FESEM results demonstrated that when nano-SiO₂ particles were used in the AAm/AAc copolymerization process, the microstructure and morphology of product changed from porous hydrogel to a nanocomposite microgel with cauliflower-like morphology. According to FESEM images, the copolymerization of AAm and AAc monomers with a nanosilica functional monomer or polymerizable nanosilica particle as a seed led to a microgel with core-shell structure and morphology. These results demonstrated that the polymerizable vinyl group on nano-SiO₂ particles have controlled the copolymerization and the product morphology. FTIR analysis showed that the copolymeric chains of polyacrylamide (PAAm) and poly (acrylic acid) (PAAc) were chemically bonded to the surfaces of the nano-SiO₂ particles and silane-modified nano-SiO₂. The particulate character of microgel samples and the existence of long distance among aggregations of particles led to rapid swelling and increasing of porosity and therefore increasing of degree of swelling.

Predicting the Mechanical Properties of RCA-Based Concrete Using Supervised Machine Learning Algorithms

Environment-friendly concrete is gaining popularity these days because it consumes less energy and causes less damage to the environment. Rapid increases in the population and demand for construction throughout the world lead to a significant deterioration or reduction in natural resources. Meanwhile, construction waste continues to grow at a high rate as older buildings are destroyed and demolished. As a result, the use of recycled materials may contribute to improving the quality of life and preventing environmental damage. Additionally, the application of recycled coarse aggregate (RCA) in concrete is essential for minimizing environmental issues. The compressive strength (CS) and splitting tensile strength (STS) of concrete containing RCA are predicted in this article using decision tree (DT) and AdaBoost machine learning (ML) techniques. A total of 344 data points with nine input variables (water, cement, fine aggregate, natural coarse aggregate, RCA, superplasticizers, water absorption of RCA and maximum size of RCA, density of RCA) were used to run the models. The data was validated using k-fold cross-validation and the coefficient correlation coefficient (R²), mean square error (MSE), mean absolute error (MAE), and root mean square error values (RMSE). However, the model's performance was assessed using statistical checks. Additionally, sensitivity analysis was used to determine the impact of each variable on the forecasting of mechanical properties.

Novel Synthesis, Characterization and Amoxicillin Release Study of pH-Sensitive Nanosilica/Poly(acrylic acid) Macroporous Hydrogel with High Swelling

The effect of SiO₂ nanoparticles on the formation of PAA (poly acrylic acid) gel structure was investigated with seeded emulsion polymerization method used to prepare SiO₂/PAA nanoparticles. The morphologies of the nanocomposite nanoparticles were studied by transmission electron microscopy (TEM). Fourier-transform infrared (FTIR) spectroscopy results indicated that the PAA was chemically bonded to the surface of the SiO₂ nanoparticles. Additionally, the resulting morphology of the nanocomposite nanoparticles confirmed the co-crosslinking role of the SiO₂ nanoparticles in the formation of the 3D structure and hydrogel of PAA. SiO₂/PAA nanocomposite hydrogels were synthesized by in situ solution polymerization with and without toluene. The morphology studies by field emission scanning electron microscopy (FESEM) showed that when the toluene was used as a pore forming agent in the polymerization process, a macroporous hydrogel structure was achieved. The pH-sensitive swelling behaviors of the nanocomposite hydrogels showed that the formation of pores in the gels structure was a dominant factor on the water absorption capacity. In the current research the absorption capacity was changed from about 500 to 4000 g water/g dry hydrogel. Finally, the macroporous nanocomposite hydrogel sample was tested as an amoxicillin release system in buffer solutions with pHs of 3, 7.2, and 9 at 37 °C. The results showed that the percentage cumulative release of amoxicillin from the hydrogels was higher in neutral and basic mediums than in the acidic medium and the amoxicillin release rate was decreased with increasing pH. Additionally, the release results were very similar to swelling results and hence amoxicillin release was a swelling controlled-release system.

Development of Prediction Model to Predict the Compressive Strength of Eco-Friendly Concrete Using Multivariate Polynomial Regression Combined with Stepwise Method

Concrete is the most widely used building material, but it is also a recognized pollutant, causing significant issues for sustainability in terms of resource depletion, energy use, and greenhouse gas emissions. As a result, efforts should be concentrated on reducing concrete’s environmental consequences in order to increase its long-term viability. In order to design environmentally friendly concrete mixtures, this research intended to create a prediction model for the compressive strength of those mixtures. The concrete mixtures that were used in this study to build our proposed prediction model are concrete mixtures that contain both recycled aggregate concrete (RAC) and ground granulated blast-furnace slag (GGBFS). A white-box machine learning model known as multivariate polynomial regression (MPR) was developed to predict the compressive strength of eco-friendly concrete. The model was compared with the other two machine learning models, where one is also a white-box machine learning model, namely linear regression (LR), and the other is the black-box machine learning model, which is a support vector machine (SVM). The newly suggested model shows robust estimation capabilities and outperforms the other two models in terms of R² (coefficient of determination) and RMSE (root mean absolute error) measurements.

Simulation of Depth of Wear of Eco-Friendly Concrete Using Machine Learning Based Computational Approaches

To avoid time-consuming, costly, and laborious experimental tests that require skilled personnel, an effort has been made to formulate the depth of wear of fly-ash concrete using a comparative study of machine learning techniques, namely random forest regression (RFR) and gene expression programming (GEP). A widespread database comprising 216 experimental records was constructed from available research. The database includes depth of wear as a response parameter and nine different explanatory variables, i.e., cement content, fly ash, water content, fine and coarse aggregate, plasticizer, air-entraining agent, age of concrete, and time of testing. The performance of the models was judged via statistical metrics. The GEP model gives better performance with R² and ρ equals 0.9667 and 0.0501 respectively and meet with the external validation criterion suggested in the previous literature. The k-fold cross-validation also verifies the accurateness of the model by evaluating R², RSE, MAE, and RMSE. The sensitivity analysis of GEP equation indicated that the time of testing is the influential parameter. The results of this research can help the designers, practitioners, and researchers to quickly estimate the depth of wear of fly-ash concrete thus shortening its ecological susceptibilities that push to sustainable and faster construction from the viewpoint of environmentally friendly waste management.

Prediction of Geopolymer Concrete Compressive Strength Using Novel Machine Learning Algorithms

The innovation of geopolymer concrete (GPC) plays a vital role not only in reducing the environmental threat but also as an exceptional material for sustainable development. The application of supervised machine learning (ML) algorithms to forecast the mechanical properties of concrete also has a significant role in developing the innovative environment in the field of civil engineering. This study was based on the use of the artificial neural network (ANN), boosting, and AdaBoost ML approaches, based on the python coding to predict the compressive strength (CS) of high calcium fly-ash-based GPC. The performance comparison of both the employed techniques in terms of prediction reveals that the ensemble ML approaches, AdaBoost, and boosting were more effective than the individual ML technique (ANN). The boosting indicates the highest value of R² equals 0.96, and AdaBoost gives 0.93, while the ANN model was less accurate, indicating the coefficient of determination value equals 0.87. The lesser values of the errors, MAE, MSE, and RMSE of the boosting technique give 1.69 MPa, 4.16 MPa, and 2.04 MPa, respectively, indicating the high accuracy of the boosting algorithm. However, the statistical check of the errors (MAE, MSE, RMSE) and k-fold cross-validation method confirms the high precision of the boosting technique. In addition, the sensitivity analysis was also introduced to evaluate the contribution level of the input parameters towards the prediction of CS of GPC. The better accuracy can be achieved by incorporating other ensemble ML techniques such as AdaBoost, bagging, and gradient boosting.

An Experimental and Empirical Study on the Use of Waste Marble Powder in Construction Material

Marble is currently a commonly used material in the building industry, and environmental degradation is an inevitable consequence of its use. Marble waste occurs during the exploitation of deposits using shooting technologies. The obtained elements most mainly often have an irregular geometry and small dimensions, which excludes their use in the stone industry. There is no systematic way of disposing of these massive mounds of waste, which results in the occurrence of landfills and environmental pollution. To mitigate this problem, an effort was made to incorporate waste marble powder into clay bricks. Different percentage proportions of marble powder were considered as a partial substitute for clay, i.e., 5-30%. A total of 105 samples were prepared in order to assess the performance of the prepared marble clay bricks, i.e., their water absorption, bulk density, apparent porosity, salt resistance, and compressive strength. The obtained bricks were 1.3-19.9% lighter than conventional bricks. The bricks with the addition of 5-20% of marble powder had an adequate compressive strength with regards to the values required by international standards. Their compressive strength and bulk density decreased, while their water absorption capacity and porosity improved with an increased content of marble powder. The obtained empirical equations showed good agreement with the experimental results. The use of waste marble powder in the construction industry not only lowers project costs, but also reduces the likelihood of soil erosion and water contamination. This can be seen to be a crucial factor for economic growth in agricultural production.

Impact of the Geometrical Parameters of Dolomite Coarse Aggregate on the Thermal and Mechanic Properties of Preplaced Aggregate Concrete

The article shows investigations on the behavior of preplaced aggregate concrete with regular and irregular coarse aggregates. The thermal properties, compressive strength, and internal structure were analyzed based on computed tomography images. The regular and irregular shapes of aggregates were obtained according to patented technology, which is possible to produce in both laboratory and industrial conditions. Based on the conducted calculations, heat storage capacity was assessed. The influence of grain shape on the material strength, porosity, and hydration gaps was determined. Debonded porosity, as a result of aggregate impurities, was shown using computer tomography analysis. It was shown that the arrangement and shape of the grains has a significant impact on the performance properties of hardened preplaced concrete.

Isotretinoin administration improves sperm production in men with infertility from oligoasthenozoospermia: a pilot study

There is currently no effective medical therapy for men with infertility due to oligoasthenozoospermia. As men with abnormal sperm production have lower concentrations of 13-cis-retinoic acid in their testes, we hypothesized that men with infertility from oligoasthenozoospermia might have improved sperm counts when treated with isotretinoin (13-cis-retinoic acid). We conducted a single-site, single-arm, pilot study to determine the effect of therapy with isotretinoin on sperm indices in 19 infertile men with oligoasthenozoospermia. Subjects were men between 21 and 60 years of age with infertility for longer than 12 months associated with sperm concentrations below 15 million sperm/mL. All men received isotretinoin 20 mg by mouth twice daily for 20 weeks. Subjects had semen analyses, physical examinations, and laboratory tests every 4 weeks during treatment. Nineteen men enrolled in the study. Median (25th, 75th) sperm concentration increased from 2.5 (0.1, 5.9) million/mL at baseline to 3.8 (2.1, 13.0) million/mL at the end of treatment (p = 0.006). No significant changes in sperm motility were observed. There was a trend toward improved sperm morphology (p = 0.056). Six pregnancies (three spontaneous and three from intracytoplasmic sperm injection) and five births occurred during the study. Four of the births, including all three of the spontaneous pregnancies, were observed in men with improvements in sperm counts with isotretinoin therapy. Treatment was well tolerated. Isotretinoin therapy improves sperm production in some men with oligoasthenozoospermia. Additional studies of isotretinoin in men with infertility from oligoasthenozoospermia are warranted.