The extensive use of polypropylene (PP) in various industries has heightened interest in developing efficient methods for recycling and optimising its mixtures. This study focuses on formulating predictive models for the Melt Flow Rate (MFR) and shear viscosity of PP blends. The investigation involved characterising various grades, including virgin homopolymers, copolymers, and post-consumer recyclates, in accordance with ISO 1133 standards. The research examined both binary and ternary blends, utilising traditional mixing rules and symbolic regression to predict rheological properties. High accuracy was achieved with the Arrhenius and Cragoe models, attaining R2 values over 0.99. Symbolic regression further enhanced these models, offering significant improvements. To mitigate overfitting, empirical noise and variable swapping were introduced, increasing the models\' robustness and generalisability. The results demonstrated that the developed models could reliably predict MFR and shear viscosity, providing a valuable tool for improving the quality and consistency of PP mixtures. These advancements support the development of recycling technologies and sustainable practices in the polymer industry by optimising processing and enhancing the use of recycled materials.

The effect of contamination of polypropylene (PP) with selected polymers is studied to simulate the effect of mis-sorting in recycling streams. Polystyrene (PS), polyethylene terephthalate (PET), polycarbonate (PC), acrylonitrile butadiene styrene (ABS), and polylactic acid (PLA) were compounded with PP at different concentrations varying between 3 and 10%. Infrared spectroscopy proved the absence of chemical bonds between the constituents. Generally, melt flowability, except for the PP/PLA blend, and crystallinity were only slightly affected by the incorporation of the contaminating polymers. Samples of the polymer blends were injection moulded and further tested for their tensile and impact properties. Critical behaviour was induced by the introduction of a weld line as a result of the application of multiple gating points during injection moulding. Results generally show the applicability of PP mixtures within the investigated range of contamination, without much sacrifice in mechanical performance. However, in the case of ABS and PLA, more care should be taken when designing complex parts with weld lines, due to reduced toughness.

In the present work, short glass fiber is superficially modified with different concentrations of polyhedral oligomeric silsesquioxanes (Trisilanol-Isobutyl, TSI-POSS) for processing as a filler in a polypropylene matrix (PP). It is observed that increasing the amount of TSI-POSS increases the fracture point and tensile strength; the opposite is the case for the strength impact property. The behaviors of both dynamic mechanical and thermal analyses are also observed. The flame behavior, i.e., the burning rate, decreases with increasing TSI-POSS in the polymers.

A new two-step method for developing a nanocomposite of polypropylene (PP) decorated with photocatalytically active TiO2 nanoparticles (nTiO2) is proposed. This method involves the low-temperature plasma functionalization of polypropylene followed by the ultrasound-assisted anchoring of nTiO2. The nanoparticles, polymeric substrate, and resultant nanocomposite were thoroughly characterized using nanoparticle tracking analysis (NTA), microscopic observations (SEM, TEM, and EDX), spectroscopic investigations (XPS and FTIR), thermogravimetric analysis (TG/DTA), and water contact angle (WCA) measurements. The photocatalytic activity of the nanocomposites was evaluated through the degradation of methyl orange. The individual TiO2 nanoparticles ranged from 2 to 6 nm in size. The oxygen plasma treatment of PP generated surface functional groups (mainly -OH and -C=O), transforming the surface from hydrophobic to hydrophilic, which facilitated the efficient deposition of nTiO2. Optimized plasma treatment and sonochemical deposition parameters resulted in an active photocatalytic nTiO2/PP system, degrading 80% of the methyl orange under UVA irradiation in 200 min. The proposed approach is considered versatile for the functionalization of polymeric materials with photoactive nanoparticles and, in a broader perspective, can be utilized for the fabrication of self-cleaning surfaces.

Predicting the mechanical properties of polymer materials using machine learning is essential for the design of next-generation of polymers. However, the strong relationship between the higher-order structure of polymers and their mechanical properties hinders the mechanical property predictions based on their primary structures. To incorporate information on higher-order structures into the prediction model, X-ray diffraction (XRD) can be used. This study proposes a strategy to generate appropriate descriptors from the XRD analysis of the injection-molded polypropylene samples, which were prepared under almost the same injection molding conditions. To this end, first, Bayesian spectral deconvolution is used to automatically create high-dimensional descriptors. Second, informative descriptors are selected to achieve highly accurate predictions by implementing the black-box optimization method using Ising machine. This approach was applied to custom-built polymer datasets containing data on homo- polypropylene and derived composite polymers with the addition of elastomers. Results show that reasonable accuracy of predictions for seven mechanical properties can be achieved using only XRD.
This study proposes a strategy to generate appropriate descriptors, which realize highly accurate predictions of mechanical properties via machine learning from the XRD analysis of the molded polypropylene samples.

This article raises the topic of the critical examination of polypropylene, a key polymeric material, and its extensive application within the automotive industry, particularly focusing on the manufacturing of brake fluid reservoirs. This study aims to enhance the understanding of polypropylene\'s behavior under mechanical stresses through a series of laboratory destruction tests and numerical simulations, emphasizing the finite element method (FEM). A novel aspect of this research is the introduction of the PEAK parameter, a groundbreaking approach designed to assess the material\'s resilience against varying states of strain, known as triaxiality. This parameter facilitates the identification of critical areas prone to crack initiation, thereby enabling the optimization of component design with a minimized safety margin, which is crucial for cost-effective production. The methodology involves conducting burst tests to locate crack initiation sites, followed by FEM simulations to determine the PEAK threshold value for the Sabic 83MF10 polypropylene material. The study successfully validates the predictive capability of the PEAK parameter, demonstrating a high correlation between simulated results and actual laboratory tests. This validation underscores the potential of the PEAK parameter as a predictive tool for enhancing the reliability and safety of polypropylene automotive components. The research presented in this article contributes significantly to the field of material science and engineering by providing a deeper insight into the mechanical behavior of polypropylene and introducing an effective tool for predicting crack initiation in automotive components. The findings hold promise for advancing the design and manufacturing processes in the automotive industry, with potential applications extending to other sectors.

Microplastics have been detected in the atmosphere as well as in the ocean, and there is concern about their biological effects in the lungs. We conducted a short-term inhalation exposure and intratracheal instillation using rats to evaluate lung disorders related to microplastics. We conducted an inhalation exposure of polypropylene fine powder at a low concentration of 2 mg/m3 and a high concentration of 10 mg/m3 on 8-week-old male Fischer 344 rats for 6 h a day, 5 days a week for 4 weeks. We also conducted an intratracheal instillation of polypropylene at a low dose of 0.2 mg/rat and a high dose of 1.0 mg/rat on 12-week-old male Fischer 344 rats. Rats were dissected from 3 days to 6 months after both exposures, and bronchoalveolar lavage fluid (BALF) and lung tissue were collected to analyze lung inflammation and lung injury.
Both exposures to polypropylene induced a persistent influx of inflammatory cells and expression of CINC-1, CINC-2, and MPO in BALF from 1 month after exposure. Genetic analysis showed a significant increase in inflammation-related factors for up to 6 months. The low concentration in the inhalation exposure of polypropylene also induced mild lung inflammation.
These findings suggest that inhaled polypropylene, which is a microplastic, induces persistent lung inflammation and has the potential for lung disorder. Exposure to 2 mg/m3 induced inflammatory changes and was thought to be the Lowest Observed Adverse Effect Level (LOAEL) for acute effects of polypropylene. However, considering the concentration of microplastics in a real general environment, the risk of environmental hazards to humans may be low.

In this study, the impact of ethylene oxide, propylene oxide, 1,2-butene oxide, and 1,2-pentene oxide on the polymerization of propylene at an industrial level was investigated, focusing on their influence on the catalytic efficiency and the properties of polypropylene (PP) without additives. The results show that concentrations between 0 and 1.24 ppm of these epoxides negatively affect the reaction\'s productivity, the PP\'s mechanical properties, the polymer\'s fluidity index, and the PP\'s thermal properties. Fourier transform infrared spectroscopy (FTIR) revealed bands for the Ti-O bond and the Cl-Ti-O-CH2 bonds at 430 to 475 cm-1 and 957 to 1037 cm-1, respectively, indicating the interaction between the epoxides and the Ziegler-Natta catalyst. The thermal degradation of PP in the presence of these epoxides showed a similar trend, varying in magnitude depending on the concentration of the inhibitor. Sample M7, with 0.021 ppm propylene oxide, exhibited significant mass loss at both 540 °C and 600 °C, suggesting that even small concentrations of this epoxide can markedly increase the thermal degradation of PP. This pattern is repeated in samples with 1,2-butene oxide and 1,2-pentene oxide. These results highlight the need to strictly control the presence of impurities in PP production to optimize both the final product\'s quality and the polymerization process\'s efficiency.

The pUC-derived plasmid yield from E. coli using polypropylene tubes (PP) was compared among round and conical tubes. The yield from cells grown in a cheaper conical-PP with flat-bottom was 1.5-fold higher (p < 0.001) than other PP. The use of the conical-PP can save research budgets in the current inflationary environment.

Zinc stearate (Znst) was physically blended with the sodium 4-[(4 chlorobenzoyl) amino] benzoate (SCAB) to obtain the SCAB-Znst composite nucleating agent. Znst was used to improve the dispersion property of SCAB and exert a lubricating effect on the PP matrix. The scanning electron microscopy and the fracture surface morphology of the PP/SCAB composite illustrated that the addition of Znst greatly reduced the aggregation phenomenon of SCAB in the PP matrix. The result of the rotary rheometer indicated that Znst exhibits internal lubrication in PP. The DSC result illustrated that the crystallization properties of PP were improved. Compared with pure PP, the Tc of the PP/SCAB composite increased by 1.44 °C (PP/Znst), 13.48 °C (PP/SCAB), and 14.96 °C (PP/SCAB-Znst), respectively. The flexural strength of pure PP, PP/SCAB, and PP/SCAB-Znst were 35.8 MPa, 38.8 MPa, and 40.6 MPa, respectively. The tensile strength of the PP/SCAB and PP/SCAB-Znst reached the values of 39.8 MPa and 42.9 MPa, respectively, compared with pure PP (34.1 MPa). The results demonstrated that Znst can promote the dispersion of SCAB in the PP matrix while exerting a lubricating effect, which enabled the enhancement of the crystalline and mechanical properties of PP.