Introduction Globally, energy consumption, CO2 emissions, depletion of natural resources, and plastic waste are significant environmental issues. The demand for plastics has increased significantly in recent decades, leading to approximately 300 million tons of plastic waste being generated annually [1, 2]. Various initiatives have been implemented to reduce plastic waste accumulation, such as recycling and banning singleuse plastics. However, recycling thermoplastic waste remains inefficient due to labor-intensive processes and low recycling rates, with only about 10% of total plastic waste being recycled [3]. Utilizing simple recycling processes, such as cleaning and shredding to produce raw materials for construction and insulation, is more appealing to recycling companies and consumers. Despite their low biodegradability and inability to decompose naturally [4, 5], plastics have beneficial properties such as light weight, low water absorption, high compressive strength [6, 7], high chemical resistance, weather resistance, insulation properties, and low cost [8, 9].

Furthermore, replacing traditional materials with lighter and cheaper materials not only saves production and transportation costs [10] but also reduces the mass and weight of construction projects, thus lowering the structural load. This concept of using plastics as a substitute material in construction has emerged [11]. Nowadays, many studies support the reuse of plastic waste in building materials. Recycling polyethylene (PE) and polypropylene (PP) plastics is preferred over other thermoplastics because they not only constitute a large proportion of household waste but also have low melting points [12]. The use of incineration technology to process municipal solid waste is becoming a common trend worldwide due to benefits suchasvolumereduction,landconservation,reducedleachate and odor, and energy recovery for electricity production.

However, this process generates a large amount of solid waste in the form of ash. This ash is not considered hazardous waste and can be reused as a potential raw material in the production of building materials [13]. Researchers have made efforts to utilize this ash in building materials. For example, Huỳnh Trọng Phước et al. developed self-compacting concrete blocks using incineration ash that met technical standards for water absorption and surface abrasion resistance with grades M300 – M500 [14]. However, this method still uses traditional materials such as cement, sand, and water. Plastic waste, especially thermoplastic waste, has also received significant attention for recycling and reuse, being considered a valuable resource.

In 2017, Nguyễn Võ Châu Ngân et al. proposed a solution to process plastic waste into granular material for mixing with concrete. In Kenya, plastic waste is shredded and mixed with sand at 350°C to produce paving blocks using a hot-pressing method [5]. In 2019, M.K. Mondal et al. used 10% thermoplastic waste and 60%- 70% fly ash with 15% ordinary Portland cement to produce paving blocks [16]. Similarly, Rajarapu Bhushaiah et al. used thermoplastic with fly ash, cement, and sand in the production of paving blocks [17]. Ilyas Ennahal et al. created materials using 70% minerals (sediments) and 30% thermoplastic waste containing polypropylene, polyethylene, and polystyrene [18]. Recycling polyethylene (PE) and polypropylene (PP) plastics is prioritized over other types of thermoplastics because they not only constitute a large proportion of household waste but also have low melting points [19].

Although there have been many inventions and solutions using fly ash from power plants to produce building materials, such as fillers in artificial stone, cement, and paving blocks from fly ash and plastic waste, the use of incineration ash and thermoplastic waste from municipal waste treatment plants to produce paving blocks by hot-pressing has not been reported. Typically, clay, sand, and cement are commonly used to produce paving blocks. However, this study replaces these materials with recycled thermoplastic waste and ash from municipal waste incineration. This represents a further step towards a circular economy and environmental protection. The production parameters of paving blocks from recycled thermoplastic waste and incineration ash using the hotpressing method, such as mixing temperature, mixing time, compression force, etc., significantly affect the properties of the product.

To achieve suitable conditions for the production of paving blocks and obtain products with good, stable properties, careful selection of production parameters is necessary. A traditional method for optimizing production parameters is the one-variable-at-a-time approach. In this method, each experiment is designed to include one variable change while other parameters are kept constant, and experiments are repeated with different variable changes each time. However, this method is costly and time-consuming and does not achieve truly optimal values. Therefore, using statistical tools such as the response surface method with the Box-Behnken design can help alleviate and address many optimization challenges. The Box-Behnken experimental design allows for the simultaneous evaluation of the combined effects of different parameters such as mixing temperature, mixing time, compression force, etc., at various levels on the compressive strength, flexural strength, and surface abrasion resistance of paving blocks.

This study is novel in that it specifically explores the optimal production conditions for paving blocks made from the combination of recycled thermoplastic waste and municipal incineration ash, a relatively unexplored area. Previous studies have often focused on the use of either recycled plastic or incineration ash independently, rather than in combination. The results from these studies show varying degrees of success in improving material properties but do not comprehensively address the combined effects of these two types of waste. By identifying optimal parameters using the Box-Behnken design, this study makes a significant contribution to the field of sustainable building materials, providing a feasible solution for waste management and material innovation.

EXPERIMENT Raw materials and chemicals - Incineration ash from the household waste treatment of APT - Seraphin Hai Duong Environmental Joint Stock Company. - Recycled thermoplastic waste from the household waste treatment of APT - Seraphin Hai Duong Environmental Joint Stock Company, with chemical composition including polyethylene (PE - 97.82%); polypropylene (PP - 2.18%). - Thermal stabilizer commercial product (from China), Mold stabilizer (from China), and Mold release agent (from China). Methods of fabrication and analysis of the physical properties of the tiles The tiles were manufactured using hot-melt extrusion on a twin-screw extruder with a ratio of recycled thermoplastic waste/ waste incineration ash/ additives = 60/40/3. The technical parameters for tile fabrication were adjusted according to Table 2.

The produced tile samples were determined and analyzed for various indicators such as: surface mass loss abrasion resistance according to TCVN 6065:1995, flexural strength according to standard TCVN 6355:2009. Additionally, assessments were made on edge length deviation, edge straightness, surface flatness, cracks, surface layer cracks, and edge surface crack according to standard TCVN 7744:2013. Heavy metal content was determined according to JIS 5741:2016 standard. Statistical analysis of experimental results Variance analysis, regression analysis, model determination, response surface analysis, and optimization were all performed on the experimental data obtained. ANOVA (Analysis of Variance) is an objective decision-making tool based on statistics, evaluated by regression coefficients, F-values, P-values, and correlation coefficient R.

Methods for Analyzing the Composition of Harmful Substances The method for analyzing leachate solutions in QCVN 07: 2009/BTNMT aims to determine the potential release of hazardous components from waste under natural conditions. Waste samples are prepared and leached, with liquid waste (solid content < 0.5%) filtered through a glass fiber filter and used directly for analysis. For solid or sludge waste (solid content ≥ 0.5%), the solid fraction is separated, mechanically treated, and leached using an acidic solution prepared from CH3COOH and water, with a 20:1 ratio to the solid waste mass, over 18 ± 2 hours. The leachate solution is then analyzed to determine the concentration of hazardous components, using methods ASTM D5233-92 or EPA 1311 (TCLP).

The analysis results are calculated using the formula Ctb = (Vl * Cl + Vnc * Cnc) / (Vl + Vnc) to determine the average leachate concentration of the hazardous components. RESULTS AND DISCUSSION Experimental results Analysis of the components of some harmful substances and the structural morphology of waste incineration ash In practice, there have been studies utilizing this type of ash in agriculture for soil improvement, in industrial materials, and for environmental restoration in some limestone quarrying mines. However, the consumption rate is still low due to the perception that this ash is hazardous waste containing toxins or radiation. Therefore, this work conducted an analysis of the components of harmful substances in the ash samples from the waste incineration facility before applying in tile manufacturing.

The components of some harmful substances in the incineration ash from the waste disposal facility were presented in Table 1. Table 1. Components of some harmful substances in the incineration ash from the waste disposal facility. Hazardous component Content (mg/l) QCVN07:2009/BTNMT Soaking extraction concentration (mg/L) Sample 1 Sample 2 Sample 3 Lead (Pb) < 0,005 < 0,005 < 0,005 15 Cadmium (Cd) < 0,005 < 0,005 < 0,005 0,5 Mercury (Hg) < 0,003 < 0,003 < 0,003 0,2 Selenium (Se) 0,048 0,054 0,047 1 Arsenic (As) 0,007 0,032 0,024 2 Chromium (VI) < 0,15 < 0,15 < 0,15 5 The results in Table 6 showed that the concentrations of hazardous substances in the incinerated waste ash were extremely low and meet the standards of QCVN07:2009/BTNMT.

This indicated that this source of ash can be fully utilized in the production of tiles and some other construction materials without causing harm to the environment. SEM images of the incinerated waste ash were presented in Figure 1 (A). As observed, the particles of household waste incinerator ash were irregular, fragmented, and porous. SEM images of the incinerated waste ash show that the particles are irregular, fragmented, and porous. The irregular shape and porosity help increase surface area, improving adhesion in composite materials. However, fragmentation and uneven particle size can create weak points, reducing the homogeneity and mechanical strength of the final product. The particle size distribution indicates the presence of both small and large particles, creating a wide size range.

This uneven size distribution can affect the dispersion and integration of ash in composite materials, leading to inconsistent mechanical properties. High porosity can enhance the thermal and acoustic insulation properties of the material but may also reduce mechanical strength if the pores are too large or unevenly distributed. Incinerated waste ash shows advantages in insulation properties but requires optimization to improve mechanical strength. Figure 1. (A) SEM images and (B) particle size distribution of the waste incineration ash. Analysis of the influence of technological parameters on the mechanical properties of tiles Effects of Mixing Temperature, Time, and Compression Force on the Compressive Strength of Paving Blocks Made from Recycled Thermoplastics and Incineration Ash The paving blocks were manufactured using a hot-melt mixing method in a twin-screw extruder with a waste thermoplastic/ incineration ash/additive ratio of 60/40/3.

The technical parameters for producing the paving blocks were adjusted as follows: Table 2. Effect of Mixing Temperature on Compressive Strength. Mixing Temperature (°C) Mixing Time (minutes) Compression Force (tons) Compressive Strength (MPa) 120 20 150 11.17 150 20 150 12.4 180 20 150 14.26 210 20 150 16.21 240 20 150 15.79 The results show that the compressive strength gradually increases as the mixing temperature rises from 120°C to 210°C, reaching a maximum value of 16.21 MPa at 210°C. However, when the mixing temperature continues to increase to 240°C, the compressive strength slightly decreases to 15.79 MPa. This indicates that excessively high mixing temperatures can reduce the compressive strength of the product.

Table 3. Effect of Mixing Time on Compressive Strength Mixing Temperature (°C) Mixing Time (minutes) Compression Force (tons) Compressive Strength (MPa) 210 10 150 14.08 210 15 150 16.94 210 20 150 16.18 210 25 150 15.48 210 30 150 15.57 The results indicate that the compressive strength reaches its highest value of 16.94 MPa when the mixing time is 15 minutes. When the mixing time exceeds 15 minutes, the compressive strength tends to decrease. This suggests that the optimal mixing time to achieve the highest compressive strength is 15 minutes. A B Table 4. Effect of Compression Force on Compressive Strength. Mixing Temperature (°C) Mixing Time (minutes) Compression Force (tons) Compressive Strength (MPa) 210 15 120 16.87 210 15 135 18.19 210 15 150 16.99 210 15 165 15.37 210 15 180 13.78 The results show that the compressive strength reaches its highest value of 18.19 MPa when the compression force is 135 tons.

When the compression force exceeds 135 tons, the compressive strength decreases. This indicates that the optimal compression force to achieve the highest compressive strength is 135 tons. Based on the results from the three tables above, the optimal conditions to achieve the highest compressive strength for paving blocks made from waste plastics and incineration ash are: • Mixing Temperature: 210°C • Mixing Time: 15 minutes • Compression Force: 135 tons These conditions yield the highest compressive strength of 18.19 MPa. Additional experiments should be conducted to test other properties of the product, such as flexural strength and abrasion resistance, to ensure that the product meets the necessary quality standards for practical applications.

Experimental Design The Box-Behnken design is a Response Surface Methodology (RSM) approach used in experimental design. In this study, technological parameters including mixing temperature (A, °C), mixing time (B, minutes), and compression force (C, tons) were investigated. Through the use of mathematical and statistical methods, the RSM approach explores the factors that may influence various variables. The different technological conditions of the experiment were presented in Table 5. The Design Expert software was used as a statistical analysis tool. Table 5. Technical parameters used in the experiment. Technical parameters Variation range (Δ) Technological conditions -1 0 1 Mixing temperature, oC, (A) 10 200 210 220 Mixing time, minutes (B) 5 10 15 20 Pressure, tons (C) 15 120 135 150 To investigate the influence of technological parameters on the material fabrication process, 15 different experiments were conducted (Table 6) and evaluated using various methods.

Table 6. Experimental results obtained under different technological conditions N.O Mixing temperature, oC (A) Mixing time, minutes (B) Pressure, tons (C) Compressive strength (MPa) Flexural strength (MPa) Surface abrasion resistance (g/cm2) 1 200 15 150 17.25(±0.087) 9.78(±0.032) 0.011(±0.0004) 2 210 15 135 18.25(±0.087) 10.1(±0.032) 0.02(±0.0004) 3 200 15 120 15.05(±0.087) 9.25(±0.032) 0.017(±0.0004) 4 210 20 120 16.73(±0.087) 9.17(±0.032) 0.009(±0.0004) 5 200 10 135 16.52(±0.087) 9.61(±0.032) 0.018(±0.0004) 6 200 20 135 17.41(±0.087) 9.92(±0.032) 0.012(±0.0004) 7 210 15 135 18.25(±0.087) 10.1(±0.032) 0.02(±0.0004) 8 210 20 150 17.54(±0.087) 9.82(±0.032) 0.007(±0.0004) Research Article 9 210 15 135 18.25(±0.087) 10.1(±0.032) 0.02(±0.0004) 10 220 20 135 18.06(±0.087) 9.85(±0.032) 0.013(±0.0004) 11 210 10 150 17.33(±0.087) 9.5(±0.032) 0.012(±0.0004) 12 220 10 135 17.92(±0.087) 9.98(±0.032) 0.019(±0.0004) 13 210 10 120 16.04(±0.087) 9.2(±0.032) 0.016(±0.0004) 14 220 15 150 17.19(±0.087) 9.9(±0.032) 0.015(±0.0004) 15 220 15 120 17.07(±0.087) 9.47(±0.032) 0.014(±0.0004) Analysis of the influence of technological parameters on the mechanical properties of tiles Data from 15 experiments were analyzed to evaluate the influence of technological factors such as mixing temperature, mixing time, and pressure on the properties of tiles.

The ANOVA results for compressive strength, flexural strength, and surface abrasion resistance were conducted with a confidence level of 95% and a significance level of 5%, as presented in Table 7. Table 7. Analysis of variance results for compressive strength, flexural strength, and surface abrasion resistance. Source Compressive strength Flexural strength Surface abrasion resistance F-value p-value F-value p-value F-value p-value Model 687.53 < 0.0001 489.08 < 0.0001 541.07 < 0.0001 A-Mixing temperature 1095.37 < 0.0001 148.41 < 0.0001 22.50 0.0051 B- Mixing time 253.74 < 0.0001 80.04 0.0003 1440.00 < 0.0001 C-Pressure 1330.82 < 0.0001 1321.78 < 0.0001 302.50 < 0.0001 AB 76.63 0.0003 140.29 < 0.0001 0.0000 1.0000 AC 589.43 < 0.0001 7.25 0.0432 245.00 < 0.0001 BC 31.39 0.0025 88.77 0.0002 20.00 0.0066 A² 546.71 < 0.0001 18.21 0.0080 28.85 0.0030 B² 127.02 < 0.0001 512.12 < 0.0001 1108.85 < 0.0001 C² 2385.16 < 0.0001 2252.32 < 0.0001 1939.62 < 0.0001 R² 0.9992 0.9977 91.0262 0.9989 0.9968 62.3115 0.9990 0.9971 70.5193 Adjusted R² Adeq Precision The model analysis in Table 7 demonstrated that this model was fully consistent with the experiments, as evidenced by the model’s Fisher statistics (Fisher) values of 687.53 for compressive strength, 489.08 for flexural strength, and 541.07 for surface abrasion resistance.

The reliability of the model was evaluated with a 95% confidence interval. Process parameters with P values less than 0.05 indicate their significance to the mechanical properties in the design space. For compressive strength, the variables A (mixing temperature), B (mixing time), C (pressure), AB, BC, AC, A², B², and C² were all significant model terms with p < 0.05. Similarly, for flexural strength, the variables A, B, C, AB, BC, AC, A², B², and C² were significant, demonstrating their critical role in the manufacturing process of tiles made from recycled plastic and waste incineration ash. For surface abrasion resistance, the variables A, B, C, BC, AC, A², B², and C² were found to be significant, indicating their influence on the surface durability of the tiles.

These results underscore the importance of optimizing these parameters to achieve the desired mechanical properties in the final product. The LoF (Lack of Fit) was used to assess data variation in the model. The LoF values for compressive strength, flexural strength, and surface abrasion resistance models are 0.0031, 0.0006, and 0.00000008, respectively, indicating that the model reflects data variation well. After removing non-significant variables (p > 0.05) and applying regression analysis, the objective function of the model was determined, represented by the quadratic regression equation as follows: Compressive strength = 18,25 + 0,50125A + 0,24125B + 0,5525C – 0,1875AB – 0,52AC – 0,12BC – 0,52125A2 – 0,25125B2 – 1,08875C2 (1) Flexural strength = 10,10 + 0,08A + 0,05875B + 0,23875C - 0,11AB – 0,025AC + 0,0875*BC – 0,04125A2 – 0,21875B2 – 0,45875C2 (2) Surface abrasion resistance = 0,02 + 0,000375A – 0,003B – 0,001375C + 0,00175AC + 0,0005BC – 0,000625A2 – 0,003875B2 – 0,005125C2 (3) The positive and negative coefficients preceding the variables in the equation represent the positive and negative influences of different factors on all reactions.

From regression equations (1) and (2), all three factors A, B, C positively influence compressive strength and flexural strength. The extent of their influence decreases in the order of C > A > B, corresponding to their coefficients in equations (1) and (2). .Equation (3) showed that factor A (mixing temperature) had a positive influence on surface abrasion resistance, meaning that as the mixing temperature increases, the surface abrasion resistance improves. This implies that higher temperatures help in creating a more durable surface for the tiles. On the other hand, factors B (mixing time) and C (pressure) had negative influences on surface abrasion resistance. This means that as the mixing time and pressure increase, the surface abrasion resistance decreases.

Longer mixing times can lead to over-processing, causing the materials to become less cohesive and more prone to wear. Similarly, higher pressure can cause unwanted deformations or structural damage, reducing the material’s ability to resist abrasion. Thus, while an increase in mixing temperature can enhance surface durability, excessive mixing time and pressure can have detrimental effects, underscoring the importance of optimizing these parameters to achieve the best mechanical properties for the tiles. Analysis of diagnostic plots regarding predicted and actual responses Diagnostic plots of predicted values versus actual values are an important step in experimental design and data analysis. The purpose of these plots is to assess the goodness-of-fit of the model by comparing the predicted values from regression equations with the actual experimental data.

This helps identify any systematic biases or patterns that may indicate issues with the model. By visualizing the residuals (the differences between predicted and actual values), researchers can examine the normality, homoscedasticity, and independence of the residuals. These plots also help detect outliers or influential data points that may skew the results. Overall, diagnostic plots are essential for confirming the accuracy and reliability of the model, ensuring that the predictions align well with the observed data. The reaction plots generated by the model’s diagnostic plots were presented in Figures 2a – 2f. The residuals were randomly distributed along the mean line, indicating that the errors follow a normal distribution. This reflected a high degree of similarity between the model and the data [31].

Figures 2a, 2c, and 2e showed a good correlation between experimental and theoretical values, as the experimental points cluster along the diagonal and the distribution of experimental points was random within the range (-8, 8) in Figures 2b, 2d, and 2f. The model’s adequacy was also confirmed by the determination coefficients R². The determination coefficient for compressive strength model, flexural strength model, and surface abrasion resistance model was 0.992, 0.9989, and 0.9990, respectively. This confirmed a strong relationship between the models and experimental data. Figure 2. Normal probability plot of residuals for compressive strength (2a, 2b), flexural strength (2c, 2d), and surface abrasion resistance (2e, 2f). Analysis of the influence of technological parameters on the mechanical properties of tiles The influence of pairs of technological factors (AB, AC, BC) on the objective functions was depicted through 2D and 3D response surface plots of the tile manufacturing process (Figures 3a-3f).

The independent variables were plotted on the X and Y axes, while the response was plotted on the Z axis. The color of the contour lines describes the levels of response, with blue, light green, and dark red indicating areas of less effective, intermediate, and effective interaction, respectively [24, 25]. Analysis of the influence of technological parameters on compressive strength Figure 3 indicated the influence of the interaction between mixing temperature, mixing time, and compression force on the compressive strength of tiles using 2D and 3D surface response diagrams. Figures 3a, 3b illustrated the influence of mixing temperature and mixing time on the compressive strength of tiles. Initially, as the mixing temperature and time increase, the compressive strength of the tiles tended to increase.

However, if the mixing temperature was further increased to 220°C and the mixing time to 20 minutes, this value tended to decrease as the components of the recycled thermoplastic may degrade. In the interaction between temperature and compression force in Figures 3c, 3d, as the mixing temperature increases, the initial compression force also increases and then decreases. Because of the high temperature, the viscosity of the system was reduced. Therefore, it reduced the activity of the components in the system while the high compression force caused undesired deformation and structural damage to the tiles. The same trend was observed for the interaction between mixing time and compression force on the compressive strength of tiles (Figure 3 Research Article e, f).

As the mixing time increases, the components in the mixture distributed more evenly. However, prolonged mixing time causes agglomeration of ash and slag in the system, reducing the homogeneity of the system. For the value of the compressive strength objective function, the interaction between pairs of factors affected the value of the objective function in the order AC > AB > BC. Figure 3. Surface Response Diagrams 2D, 3D illustrates the influence of interaction between mixing temperature, mixing time, and compression force on the compressive strength of tiles. Analysis of the influence of technological parameters on flexural strength The influence of the interaction between mixing temperature, mixing time, and compression force on the flexural strength of tiles is depicted by 2D and 3D surface response diagrams as presented in the figure 4.

Figures 4a, 4b show a trend of flexural strength as the temperature increases from 200°C to 210°C with mixing time under 15 minutes. However, flexural strength begins to decrease when the temperature and mixing time exceed these values simultaneously. Flexural strength is influenced by temperature and mixing time, as depicted in Figures 4c, 4d, and flexural strength affected by mixing time and compression force is presented in Figures 4e, 4f. From the 2D, 3D surface response diagrams, it can be observed that the maximum compressive strength is achieved under tile manufacturing conditions at a mixing temperature of 210°C, mixing time of 15 minutes, and compression force of 135 tons. For the value of the flexural strength objective function, the influence of interaction between pairs of factors on the value of the objective function decreases in the order AB > BC > AC.

Figure 4. Surface Response Diagrams 2D, 3D illustrates the influence of interaction between mixing temperature, mixing time, and compression force on the flexural strength of tiles. Analysis of the influence of technological parameters on surface wear resistance The influence of the interaction between mixing temperature, mixing time, and compression force on the surface abrasion resistance of tiles is represented by 2D and 3D surface response diagrams as presented in the figure 5. Plots in Figure 5a and 5b showed that initially, the surface abrasion resistance increased as the mixing temperature and time increase. However, this property decreased if the mixing time exceeds 15 minutes and the mixing temperature exceeds 210°C.

The effects of the pairs of factors, temperature, mixing time, and mixing time with pressure, were presented in Figure 5c, 5d; and Figure 5e, 5f, respectively. For the surface abrasion resistance objective function, the influence of the interaction between pairs of factors on the objective function decreased in the order of AC > BC, and the AC factor pair did not affect this objective function. Figure 5. 2D and 3D response surface plots illustrates the influence of the interaction between mixing temperature, mixing time, and pressure on the surface abrasion resistance of tiles. Optimization of the tile manufacturing process and verification After conducting ANOVA analysis, some technical solutions were presented in Table 9.

The optimal values of independent variables were determined by solving the quadratic equation using the objective function method presented in Figure 6. The chosen level of the objective function was level 2. The results of confirmation tests for the optimal tile manufacturing conditions were presented in Table 8. Figure 6. Optimal conditions and predicted physical properties of tiles. Table 8. Confirmation test results with optimal tile manufacturing parameters. Compressive strength (MPa) Flexural strength (MPa) Surface Abrasion resistance (J/cm2) Error (%) Prediction Experimental values Prediction Experimental values Prediction Experimental values Compressive strength Flexural strength Surface Abrasion resistance 18.250 18.530 10.10 10.15 0.020 0.0207 1.53 1.48 3.50 Through confirmation experiments, the error between prediction and experimental values was < 5%.

Therefore, the model can be effectively used to predict the mechanical properties of tiles. Tiles manufactured from recycled plastic and incinerator bottom ash have the highest compressive strength reaching 18.248 MPa [32], equivalent to the compressive strength of M150- grade tiles according to TCVN-1451:1998. The results of this study, along with technological advancements, not only allow the incorporation of recycled plastic combined with incinerator bottom ash into building material production [33] but also offer a beneficial and effective method to minimize its environmental impact compared to landfilling or incineration methods [34, 35]. Analysis of heavy metal content in tiles according to Vietnamese standards (QCVN 07) The composition of heavy metals in the studied samples was presented in Table 9.

Table 9. Heavy metal content in tiles Content name Unit Sample 2 JIS A 5741:2016 C1 C2 Lead (Pb) mg/L < 0,00001 < 0,00001 ≤ 0,01 Cadmium (Cd) < 0,00001 < 0,00007 ≤ 0,01 Mercury (Hg) < 0,000261 < 0,00018 ≤ 0,0005 Selenium (Se) < 0,000032 < 0,00001 ≤ 0,01 Arsenic (As) < 0,00201 < 0,00098 ≤ 0,01 Chromium (Cr) < 0,00016 < 0,00234 ≤ 0,05 Note: C1 : Concentration in blank sample; C2 : Concentration from test sample in leach solution From Table 8, the heavy metals in both the initial tile samples and in the leach solution meet the standards and did not pose a health risk. Therefore, using the manufacturing process outlined from the ash, slag of the waste incineration plant and recycled thermoplastic can produce various other building materials such as interlocking tiles for public facilities like waste treatment plants, walls in parks, floor tiles, etc.

Conclusion Theinfluenceofinputparameterssuchasmixingtemperature,mixingtime,andcompressionforceonthecompressivestrength, flexural strength, and surface abrasion resistance of tiles made from recycled thermoplastic and municipal incineration waste slag was analyzed. Variance analysis showed that the model is a statistically good predictor for these properties. Regression equations have been developed for compressive strength (1), flexural strength (2), and surface abrasion resistance (3) of the tiles. The model can effectively predict the mechanical properties of tiles manufactured from recycled thermoplastic and incinerated municipal waste slag. The optimal input parameters for manufacturing these tiles are a mixing temperature of 210°C, mixing time of 15 minutes, and compression force of 135 tons, resulting in compressive strength of 18.25 MPa, flexural strength of 10.10 MPa, and surface abrasion resistance of 0.02 J/cm2.

The produced tiles meet the M150 grade according to TCVN-1451:1998 and comply with the physical properties, dimensions, and defects specified in TCVN 7744-2013 (exterior terrazzo tiles). These findings demonstrate the effectiveness of optimizing the manufacturing parameters to produce high-quality paving bricks from recycled materials. The use of waste plastics and incineration ash not only provides a sustainable solution for waste management but also results in strong, durable construction materials. These bricks are suitable for various applications, including sidewalks, pathways, and other infrastructure projects requiring high load-bearing capacity and durability. This study highlights the potential for innovative recycling methods to contribute to environmental sustainability and material innovation in the construction industry.

Data availability The data used to support the findings of this study are included within the article. Declaration of competing interest: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

REFERENCES

1. Agyeman, S., Obeng-Ahenkora, N. K., Assiamah, S., & Twumasi, G, 2019. Exploiting recycled plastic waste as an alternative binder for paving blocks production. Case Studies in Construction Materials, 11, e00246.

2. Jambeck, J., Hardesty, B. D., Brooks, A. L., Friend, T., Teleki, K., Fabres, J., Beaudoin, Y., Bamba, A., Francis, J., Ribbink, A. J., Baleta, T., Bouwman, H., Knox, J., & Wilcox, C, 2018. Challenges and emerging solutions to the landbased plastic waste issue in Africa. Marine Policy, 96, 256–263.

3. Ferronato,N.,&Torretta,V,2019.Wastemismanagement in developing countries: A review of global issues. International Journal of Environmental Research and Public Health, 16(6), 1060.

4. Harvey, F, 2019. Animals and birds under increasing threat from plastic waste. Retrieved May 5, 2020, from The Guardian.

5. Dinesh, S., Parishee, M. K., Sriram, J., & Bashith, M. M, 2018. Effective use of waste plastic as manufacturing of paver block. International Journal of Advanced Research in Basic Engineering Sciences and Technology, 4, 231– 235.

6. Mageshwaran, A., Vino, S., Satish Kumar, C., Vijayakumar, M., & Praveen Kumar, T, 2018. Effective utilization of waste plastic with sand in addition with nylon grids in paver stones. International Journal of Current Engineering and Scientific Research, 5, 14–17.

7. Junod, T.L, 1976. Gaseous Emissions and Toxic Hazards Associated with Plastics in Fire Situations—A Literature Review. NASA-TN-D-8338; NASA: Washington, DC, USA.

8. Fraternali, F.; Ciancia, V.; Chechile, R.; Rizzano, G.; Feo, L.; Incarnato, L, 2011. Experimental study of the thermomechanical properties of recycled PET fiber-reinforced concrete. Compos. Struct., 93, 2368–2374.

9. Jambeck, J.R.; Geyer, R.; Wilcox, C.; Siegler, T.R.; Perryman, M.; Andrady, A.; Narayan, R.; Law, K.L, 2015. Plastic waste inputs from land into the ocean. Science 2015, 347, 768–771.

10. Alqahtani, F.K.; Ghataora, G.; Khan, M.I.; Dirar, S, 2017. Novel lightweight concrete containing manufactured plastic aggregate. Constr. Build. Mater. 2017, 148, 386– 397.

11. Mattsson, K.; Hansson, L.A.; Cedervall, T, 2015. Nanoplastics in the aquatic environment. Environ. Sci. Process. Impacts 2015, 17, 1712–1721.

12. Bolden, J., Abu-Lebdeh, T., & Fini, E, 2013. Utilization of recycled and waste materials in various construction applications. American Journal of Environmental Science, 9(1), 14–24.

13. Cao Tiến Phú, Hoàng Lê Anh, Nguyễn Thị Kim, Lê Văn Quang và Huỳnh Trọng Phước, 2022. Nghiên cứu một số tính chất của tro xỉ đốt chất thải rắn sinh hoạt ở Việt Nam và tiềm năng sử dụng làm vật liệu xây dựng, Tạp chí Vật liệu & Xây dựng Tập 12, Tr.5-11.

14. Huỳnh Trọng Phước, Nguyễn Trường Long, Lâm Trí Khang, Lê Thành Phiêu và Lê Văn Quang, 2021. Nghiên cứu chế tạo gạch bê tông tự chèn cho công trình bảo vệ bờ sử dụng phế thải tro-xỉ lò đốt rác, Tạp chí Vật liệu xây dựng, Tr.24-28.

15. United Nation Environment Programme, 2020. Building blocks for a greener Nairobi, https://www.unep.org/ youngchampions/news/story/ building-blocks-greenernairobi.

16. UNICEF, 2019. UNICEF breaks ground on Africa’s first-ofits-kind recycled plastic brick factory in Coote d’Ivoire. https://www.unicef.org/press-releases/unicef-breaksground-africas-first-its-kind-recycled-plastic-brickfactory-c%C3%B4te.

17. M.K. Mondal, B.P. Bose, P. Bansal, 2019. Recycling waste thermoplastic for energy efficient construction materials: An experimental investigation, Journal of Environmental Management 240 119–125.

18. Ilyas Ennahal, Walid Maherzi, Mahfoud Benzerzour, Yannick Mamindy, Nor Edine Abriak, 2020. Performance of Lightweight Aggregates Comprised of Sediments and Thermoplastic Waste, Waste and Biomass Valorization. Research Article

19. Bolden, J., Abu-Lebdeh, T., & Fini, E, 2013. Utilization of recycled and waste materials in various construction applications. American Journal of Environmental Science, 9(1), 14–24.

20. Ferreira, L., de Brito, J., & Saikia, N, 2012. Influence of curing conditions on the mechanical performance of concrete containing recycled plastic aggregate. Construction and Building Materials, 36, 196–204.

21. Gawande, A., Zamare, G., Renge, V. C., Tayde, S., & Bharsakale, G, 2012. An overview on waste plastic utilization in asphalting of roads. Journal of Engineering Research and Studies, 3(2), 1–5.

22. Manju, R., Sathya, S., & Sheema, K, 2017. Use of plastic waste in bituminous pavement. International Journal of ChemTech Research, 10(8), 804–811.

23. Mansour, A. M. H., & Ali, S. A, 2015. Reusing waste plastic bottles as an alternative sustainable building material. Energy for Sustainable Development, 24, 79–85.

24. Yaro, N.S.A., Napiah, M.B., Sutanto, M.H., Usman, A., Saeed, S.M, 2021. Modeling and optimization of mixing parameters using response surface methodology and characterization of palm oil clinker fine modified bitumen. Constr. Build. Mater. 298, 123849.

25. Usman, A., Sutanto, M.H., Napiah, M., Zoorob, S.E., Al- Sabaeei, A.M, 2021. Optimization of irradiated waste polyethylene terephthalate modified asphalt pavement using response surface methodology. Geomech. Eng. 26 (6), 513–527

26. L. Wu, K. L. Yick, S. P. Ng, and J. Yip, 2012. Application of the BoxBehnken design to the optimization of process parameters in foam cup molding. Expert System Application, vol. 39, no. 9, pp 8059–8065.

27. B. S. Kumar and S. Balachandar, 2014. A Study on the Influence of Hot Press Forming Process Parameters on Flexural Property of Glass/PP Based Thermoplastic Composites Using Box-Behnken Experimental Design. ISRN Material Science, vol. 3, no 4, pp 1–6.

28. G. B. Kiran, K. N. S. Suman, N. M. Rao and R. U. M. Rao, 2011. A study on the influence of hot press forming process parameters on mechanical properties of green composites using Taguchi experimental design. Int. J. Eng. Sci. Technol. vol. 3, no. 4, pp 253–263.

29. Izdihar Tharazi , Abu Bakar Sulong , Farrahshaida Mohd Salleh , Abdul Hakim Abdullah, Nur Farhani Ismail, 2020. Application of Response Surface Methodology for Parameters Optimization in Hot Pressing Kenaf Reinforced Biocomposites. Journal of MechanicalEngineering Vol 17(3), 131-144.

30. Haliza Jaya, Nik NorimaN zulkepli, mohd Firdaus omar, shayfull zamree abd rahim, Marcin nabiałek, kinga Jeż, mohd mustafa al bakri abdullah, 2022. OptimizatiOn Of injectiOn mOulding prOcess via design Of experiment (dOe) methOd based On rice husk (rh) reinfOrced lOw density pOlyethylene (ldpe) cOmpOsite prOperties. Arch. Metall. Mater. 67, 2, 719-727.

31. Yaro, N.S.A., et al, 2022. Mixture design-based performance optimization via response surface methodology and moisture durability study for palm oil clinker fine modified bitumen asphalt mixtures. Int. J. Pavement Res. Technol. 1–28

32. Velmurugan, V., Gokul Raj, R., & Harinisree, A, 2019. Rebuilding of plastic waste to pavement bricks. International Journal for Research in Applied Science and Engineering Technology, 7(4), 927– 931.

33. Hameed, A. M., & Ahmed, B. A. F, 2019. Employment the plastic waste to produce the light weight concrete. Energy Procedia, 157, 30–38.

34. Awasthi, A. K., Shivashankar, M., & Majumder, S, 2017. Plastic solid waste utilization technologies: A Review. In IOP conference series: Materials science and engineering (Vol. 263, No. 2, p. 022024). IOP Publishing.

35. Schmaltz, E., Melvin, E. C., Diana, Z., Gunady, E. F., Rittschof, D., Somarelli, J. A., Virdin, J., & Dunphy-Daly, M. M, 2020. Plastic pollution solutions: emerging technologies to prevent and collectmarineplastic pollution. Environment International, 144, 106067. Research Article