Molecular and Microstructural Engineering Strategies for High-Performance Polypropylene Insulation Materials

Abstract

This study develops a high-performance polypropylene (PP) substrate platform by optimizing micro/macrostructures and introduces an efficient catalyst. Key findings include: (1) microstructural analysis identifies ash content impurities (>20 ppm) as triggers for partial discharge-induced insulation failure. PP molecular weights (10⁵–10⁶) with narrower distributions enhance mechanical strength, while functional groups (-CH₂/-CH₃) show no structural variations across samples. (2) Macroscopically, mixed α-β crystal interfaces increase insulation failure risks, necessitating single-crystalline structures. Higher temperatures reduce dielectric constants but increase losses, requiring environmental consideration. Crystallinity positively correlates with DC breakdown strength (443.31 kV/mm at 54.13% crystallinity). (3) Among three endo-donor catalysts, the internal electron donor 3-based catalyst achieved optimal die-test activity (47.7 kg PP/g cat·h). With 20 mL triethylamine, the catalyst reduced PP ash content by 42.1%, narrowed molecular weight distribution by 31.6%, and increased crystallinity by 8.74%. These results establish microstructure–property relationships for PP capacitors and provide technical guidelines for performance enhancement. The work addresses current limitations in PP evaluation methods and offers a practical strategy for manufacturing high-insulation PP materials through structural control and catalytic optimization.

1. Introduction

Polypropylene (PP), a low-cost thermoplastic with strong mechanical properties and chemical stability, is widely utilized in packaging, automotive, electronics, and medical devices [1,2,3]. However, under UV irradiation, high temperatures, or high-frequency conditions, PP suffers from molecular chain breakage, reducing mechanical strength, insulation, and electrical performance. Therefore, it is important to deeply analyze the microstructure and macroscopic properties of polypropylene [4,5,6,7].

In terms of microstructure testing of polypropylene base materials, the State Key Laboratory of Advanced Power Transmission Technology studied the crystallization properties of polypropylene using Differential Scanning Calorimetry (DSC) and found that resins with a high gauged index, a wide molecular weight distribution and a low distribution of iso-gauge defects had better crystallization properties [8]. The University of the Basque Country team showed that polypropylene ash mainly originates from the main catalyst, co-catalysts, and electron donors [9]. In terms of macroscopic property testing, the Tsinghua University team found that all bi-oriented polypropylene (BOPP) films prepared by stretching maintained a stable alpha crystalline structure through X-ray diffraction (XRD) and DSC testing [10]. The Exxon Research & Engineering team found that co-crystallization enhances the connections between spherical crystals and improves the mechanical properties of the material [11]. In terms of preparation, the Tianjin University team used p-phthalaldehyde and octafluoro-para-xylene dimer as additives to prepare three composite films, which significantly improved insulating properties [12]. Professor Claudio De Rosa of the University of Lisbon, Portugal, obtained polypropylene materials with both mechanical and insulating properties by adjusting the parameters of the crystallization process [13]. However, most of the existing studies are limited to the effect of a single characteristic parameter on the insulating properties, lack systematic research on the micro- and macro-structure of polypropylene, and fail to put forward an efficient method of preparing high-performance polypropylene base materials [14,15,16,17,18,19].

In this study, a platform for the preparation of high-performance polypropylene films based on micro/macro structural modulation was developed to address the problem that polypropylene is susceptible to insulation failure during long-term operation in power systems. The microstructure, physicochemical properties, and electrical performance of polypropylene were systematically investigated from the micro to macro levels by multi-scale characterization methods, and the evolution of its performance was revealed, revealing the mechanism of polypropylene insulation failure. In addition, a high-efficiency catalyst has been developed to prepare high-performance polypropylene base materials.

2. Platform and Principle

2.1. Polypropylene Base Material Performance Testing Principles and Platforms

2.1.1. Principles of Microstructure Characterization Methods

(1)

Ash content

The ash content testing process is shown in Figure 1. The specific steps are as follows: (1) In a well-ventilated environment, melt 5 g of the sample in a pre-weighed crucible. (2) Heat the sample under open conditions using an electric heating jacket, an electric furnace, or an alcohol blowtorch, with the temperature of the heating jacket being controlled at 330–340 °C to allow for a slow decomposition until the crucible is completely burned out of the liquid (pre-ashing). (3) Transfer the crucible to a high-temperature furnace to completely char the sample. (4) Further elevation in the electric furnace to ensure that the sample is completely burned. (5) Remove the crucible, put it in a desiccator, and cool it to room temperature, then weigh the crucible and the ash to calculate the ash content.

The equation for calculating the ash content is shown in Equation (1).

$$\theta ={\displaystyle \frac{10000m_1}{m_2}}\times 100\%$$

(1)

where θ is the ash content, m₁ is the mass of residue after combustion, and m₂ is the mass of the original specimen.

(2)

Molecular weight distribution

Based on the high-temperature Gel Permeation Chromatography (GPC) method for testing the molecular weight of polypropylene, the testing process is shown in Figure 2, which is as follows: (1) dissolve the polymer in a high-temperature solvent, so that it can be subjected to molecular sieving in the dissolved state. (2) The dissolved polymer specimen is passed through a chromatographic column, which is filled with a gel material of specific particle size, and the size of the particles determines the speed of the polymer molecules through the column. (3) The dissolved molecular weight information is determined by analyzing the dissolved solution at different time points.

For molecular weight test results, which are mostly based on averaging methods, there are two main forms: number-averaged molecular weight (Mn) and weight-averaged molecular weight (Mw). Mn is the sum of the fractions occupied by each molecule of different molecular weight and its corresponding molecular weight product, while Mw is the sum of the weight fractions occupied by each molecule of different molecular weight and its corresponding molecular weight product. On the basis of the above two molecular weights, the molecular weight distribution index MWD is investigated and is calculated as shown in Equation (2) to characterize the degree of dispersion of molecular weight distribution [20].

$$\mathrm{MWD}={\displaystyle \frac{\mathrm{Mw}}{\mathrm{Mn}}}$$

(2)

where Mn is the number average molecular weight and Mw is the weight average molecular weight.

The molecular weight and molecular weight distribution of polypropylene in this paper were tested by an Agilent PL-GPC 220 manufactured by Agilent Technologies, Santa Clara, CA, USA. high-temperature gel permeation chromatograph equipped with an oscillometric, viscosity, and light scattering detector. The chromatographic column consisted of three PLgel Mixed-B (10 μm)-type columns connected in series. 1,2,4-Trichlorobenzene (TCB) was used as solvent and mobile phase, and 0.0125 wt% of 2,6-di-tert-butyl-4-methylphenol was added to the polymer samples to avoid oxidative degradation during the test. The polymer samples were dissolved at 160 °C for 5 h. The tests were performed at 150 °C at a flow rate of 1.0 mL/min.

(3)

Functional group structure

Functional group structure is tested based on Fourier Transform Infrared Spectroscopy (FT-IR). FT-IR obtains information on the molecular structure of a substance by measuring the degree of absorption of a specimen at different wavelengths of infrared radiation. Different chemical bonds in a molecule (e.g., C-H, C=O, N-H, etc.) absorb infrared radiation at specific wavelengths of infrared light, and these absorption features can reflect the molecular structure of the molecule. Therefore, by analyzing the absorption peaks in the infrared spectrum, the presence of different functional groups in a molecule can be identified. For example, the C-H bond usually has an absorption peak between 2800 and 3000 cm⁻¹.

The FT-IR instrument model used in this thesis is IRpresitage-21 (Shimadzu, Kyoto, Japan), and its relevant parameters are listed in

Table 1. Parameters of IRpresitage-21 infrared spectrometer.

Parameters	Clarification
Wavelength range	7800 cm−1–350 cm−1
Resolution	0.4–1.0
SNR	≥45,000:1

below.

2.1.2. Principles of Macrostructural Characterization Methods

(1)

Crystallization properties

Characterization of the crystalline properties of polypropylene substrates requires the use of X-ray diffraction (XRD). This method relies on the principle that X-rays from a single source travel different paths, creating an optical path difference. When this difference equals an integer multiple of the X-ray wavelength, scattered rays constructively interfere to form diffraction peaks. By analyzing these diffraction peaks, the crystalline structure of the material can be determined. The XRD test can effectively identify the crystal type of polypropylene, the relative content of each crystal type, and other parameters, and the Bragg’s equation that determines the position of the diffraction peaks is shown in Equation (3).

$$2\mathrm{d}\sin \theta =n\lambda$$

(3)

where n is the number of reflection stages, and 2θ is the angle between the incident ray and the diffraction line.

The XRD test was carried out using a D8 ADVANCE A25 from Bruker, Berlin, Germany. The test target was a Cu target at a wavelength of 1.54060 Å, the scanning angle was from 10° to 80°, and the scanning rate was set at 5°/min.

(2)

Dielectric property

The dielectric properties test mainly measures the response of a material under an alternating electric field to evaluate its performance parameters, such as relative dielectric constant and dielectric loss. During the test, by applying AC voltage or DC field strength at different frequencies, the capacitance and loss angle tangent of the material are measured, and the relative dielectric constant is further calculated.

The relative permittivity and dielectric loss of the polypropylene substrate were tested based on broadband dielectric temperature spectroscopy using a frequency domain dielectric spectroscopy modeled Novcontrol Concept 80 system manufactured by Novocontrol Technologies GmbH, Montabaur, Germany, and the performance parameters shown in

Table 2. System performance parameters.

Performance Indicators	Parameter Range
Frequency	3 μHz–20 MHz
Temperature	−160 °C–400 °C
Voltage	0–2000 V(DC)

.

(3)

Breakdown characteristics

Based on the Weibull distribution, the DC and AC breakdown voltages of the test samples were tested and combined with the thickness of the test breakdown point, and the breakdown field strengths of the samples were calculated and obtained. The Weibull distribution function is shown in Equation (4).

$$P_f=1-\exp {\left(-{\displaystyle \frac{E_b}{E_0}}\right)}^{\beta }$$

(4)

where P_f is the breakdown probability, E_b is the breakdown field strength measured in the experiment, β is the shape parameter, and E₀ is the breakdown field strength at P_f = 63.2%.

After making appropriate simplifications to Equation (4), Equation (5) is then used to calculate the breakdown probability for each measured breakdown field strength E_b in the experiment.

$$P_f={\displaystyle \frac{i-0.44}{N+0.25}}$$

(5)

where N is the number of times the same specimen was tested, and i is the number of tests in ascending order of E_b values.

2.2. Platform for the Preparation of Polypropylene-Based Materials

2.2.1. Preparation Principle

Polypropylene is prepared as follows: (1) propylene monomer is placed in a solvent, and an initiator (e.g., peroxide) is used to initiate free radical polymerization. (2) Under the action of a catalyst, the propylene monomer undergoes a coordination insertion reaction, gradually forming a long chain structure. (3) The polypropylene is processed and molded in a process that includes melt extrusion, stretching, injection molding, and shaping.

2.2.2. Preparation Platform

The preparation platform consists of three sub-platforms, namely, raw material treatment, compound modification, and processing and molding. The raw material processing platform consists of catalyst storage tanks and polymerization reactors, which are used to convert propylene monomer into polypropylene; the mixing and modification platform consists of granule mixing towers, blenders, filtration devices and drying and cooling equipment, which are used to add catalysts and prepare crude products; and the processing and molding platform consists of extruders, injection molding machines, and presses, which are used to prepare polypropylene finished products with specific shapes. The preparation platform is shown in Figure 3.

2.3. Experimental Samples and Pre-Treatment

In this paper, five common polypropylene films were customized as samples from different manufacturers. To ensure the validity of the results, randomly selected specimens from different batches of customized samples were tested according to the chronological order in which the samples were sent by each manufacturer, named as Sample 1, Sample 2, Sample 3, Sample 4, and Sample 5. Sample 3 was produced by a foreign company, C, and the rest of the samples were produced by the domestic companies A, B, D, and E. All five polypropylene film samples comply with IEC 60674-3-1:2021 [21].

In order to prevent the influence of moisture on the performance of polypropylene materials, the polypropylene samples were placed in an oven at 60 °C and dried for 24 h before the test. The moisture content of the samples was not higher than 1% after drying. The dried polypropylene samples were put into an ultrasonic cleaner, and ethanol was used for cleaning for 10 min.

3. Polypropylene Base Material Performance Testing

3.1. Microstructure Testing of Polypropylene Base Materials

3.1.1. Ash Content

A 5 g sample of polypropylene was burned completely in a crucible at 20 °C with good ventilation. After complete carbonization, the sample was kept for 24 h to ensure complete decomposition of the organic matter. The crucibles were then removed from the high-temperature furnace and cooled to room temperature in a desiccator. The ash content of the five samples is shown in Figure 4.

Figure 4 shows that Sample 3 has the lowest ash content of 12 ppm, while Sample 1 has the highest ash content of 19 ppm. The error bars in the graph indicate the error between five repetitions of the measurement. Inorganic nucleating agents directly increase the ash content, while organic nucleating agents leave less residue after burning. The amount of ash is closely related to the rigor of the dehydration, washing, and drying steps. Apparently, some manufacturers do not control their operations strictly and do not select the best materials during the production process, which leads to the differences in the results mentioned above.

3.1.2. Molecular Mass

The molecular weight data of the five samples obtained by testing using the high-temperature GPC method are shown in Figure 5.

As Figure 5 shows, Sample 4 has the smallest Mn, while Sample 3 has the smallest Mw and MWD. The MWD differences between the samples are minimal, remaining around 4.0.

3.1.3. Functional Group Structure

FT-IR was used to conduct infrared spectral scanning experiments on polypropylene samples. The IR spectra of five samples were obtained, as shown in Figure 6.

Based on the measurement results in Figure 4, it can be seen that the infrared spectrum of polypropylene shows six distinct peaks, with wave numbers mainly concentrated in 2800–3000 cm⁻¹ and 1300–1500 cm⁻¹. There is no significant difference in the infrared characterization of the five samples, and the absorption peaks presented are all characteristic peaks of PP.

3.2. Macro-Property Testing of Polypropylene Base Materials

3.2.1. Crystallization Properties

The polypropylene film was tested based on XRD, the scanning angle was set at 15° of 2θ, the scanning speed was 0.2°/s, the step size was 0.02°, and the specimen was scanned for 15 min. The results of the XRD test are shown in Figure 7.

From the measurement results in Figure 7, it can be seen that Samples 1, 2, and 5 only show an α-characteristic peak with a 2θ of about 14°. Samples 3 and 4, on the other hand, show strong diffraction peaks with a 2θ of about 16° and β characteristic crystals. The ash may contain inorganic additives, some of which may act as crystalline nucleating agents, which would affect the choice of crystal shape for polypropylene. It is possible that when annealing at high temperature, the inorganic substances in the ash act as heat carriers to promote the formation of the α crystal type.

3.2.2. Dielectric Properties

The dielectric properties of five samples were tested under an applied AC voltage of 50 V and temperatures of 30 °C, 50 °C, 70 °C, and 90 °C. The dielectric constant and dielectric loss of the samples as a function of frequency are shown in Figure 8 for Sample 1.

As illustrated in Figure 8, at the same voltage, the dielectric constant of the sample gradually decreases with increasing temperature, and the frequency corresponding to the peak of dielectric loss decreases. With the increase in frequency, the dielectric constant decreases gradually, and the dielectric loss tends to increase and then decrease.

The dielectric properties of five samples were tested at 30 °C under DC field strengths of 3 kV/mm, 6 kV/mm, and 9 kV/mm. Taking Sample 2 as an example, the variation of dielectric constant and dielectric loss with frequency is shown in Figure 9.

As the data in Figure 9 show, as the applied field strength increases, the relative permittivity and dielectric loss of the specimen rise. With increasing frequency, the dielectric constant gradually decreases, while the dielectric loss initially increases and then decreases.

3.2.3. Breakdown Characteristic

The DC and AC breakdown characteristics of the five samples were tested, respectively, at the initial voltage of 105 kV and the voltage boost rate of 1 kV/s. Moreover, the data were fitted to each point, and the probability density function and the failure distribution function of the two-parameter Weibull distribution are shown in Equations (6) and (7).

$$f(x|\alpha ,\beta )=\left\{\begin{array}{ll}{\displaystyle \frac{\beta }{\alpha }}{\left({\displaystyle \frac{x}{\alpha }}\right)}^{\beta -1}{e}^{-{\left(\frac{x}{\alpha }\right)}^{\beta }},x\ge 0\hfill & \hfill \\ 0,x<0\hfill & \hfill \end{array}\right.$$

(6)

$$F(x)=1-e^{-({\displaystyle \frac{x}{\alpha }})\beta }$$

(7)

where α is the shape parameter, and β is the molecular weight of the polymer.

To calculate the two-parameter Weibull distribution function, Equation (6) can be converted from logarithmic form to linear form, and the parameters can be determined by the least-squares method, which is described in the IEC standard and will not be repeated here. Combined with the test principle in Section 2.1.2, the Weibull parameters include the breakdown strength and the shape parameter (β). The shape parameters of the five samples at AC and DC voltages are calculated and shown in

Table 3. Shape parameters of each sample at AC and DC voltages.

Sample	AC	DC
1	6.33	7.34
2	11.45	6.84
3	12.43	5.15
4	7.64	6.8
5	10.14	6.77

.

According to the data in Table 3, the Weibull breakdown probability diagrams of the samples can be obtained, as shown in Figure 10.

As shown in Figure 10a, when the breakdown failure probability is 63.2%, the AC breakdown field strength of Sample 1 is the lowest, which is 140.8 kV/mm. Sample 3 has the highest AC breakdown field strength at 165.39 kV/mm. It can be observed from Figure 10b that the DC breakdown field strength of Sample 1 is the lowest, which is 316.62 kV/mm. Sample 3 has the largest DC breakdown field strength of 441.31 kV/mm.

4. Analysis and Discussion

4.1. Influence of Microstructure on the Insulating Properties of Polypropylene

Based on the data in Figure 4 in Section 3.1.1, the ash content of all samples is less than or equal to 20 ppm. Impurities in ash conforming to the standard material of high purity may lead to charge accumulation and uneven distribution of the electric field inside the material, thereby causing local electric field distortion and ultimately affecting the material’s breakdown performance. Therefore, in the subsequent production of polypropylene base material, the ash content should be controlled to not exceed 20 ppm.

According to the data in Figure 5 in Section 3.1.2, it can be found that the molecular weight distribution index of all five samples is between 3 and 4.5. The smaller the molecular weight distribution index, the more uniform the molecular chain length, the closer the arrangement, the greater the electric field stress that can be withstood without micropores and cracks, so it has better insulation properties. Therefore, in the subsequent production of polypropylene base, the molecular weight distribution index should be reduced as much as possible.

In addition to analyzing the microscopic characteristics of the material based on the molecular weight distribution index of the specimen, it can also be analyzed based on the molecular weight change rate, which is calculated as shown in Equation (8), and the molecular weight distribution graph is plotted with the number of molecular weights as the horizontal coordinate and molecular weight change rate as the vertical coordinate as shown in Figure 11.

$$\rho ={\displaystyle \frac{d\omega }{d\log M}}$$

(8)

where ω is the number in the molecular weight distribution and M is the molecular weight of the polymer.

As shown in Figure 11, all curves exhibit peak molecular weights within a similar range (10⁵ to 10⁶), suggesting consistent primary distribution ranges across the tested materials. Notably, Sample 3 displays the highest dw/dlogM value at the primary peak, reflecting a more concentrated molecular weight distribution in this region. These findings highlight the importance of prioritizing higher molecular weights and narrower distribution ranges during polypropylene base material preparation to optimize performance.

According to the relevant content of Section 3.1.3, the positions and characteristics of each group of polypropylene in the infrared spectra of Sample 1, for example, are shown in

Table 4. Infrared spectral measurements of Sample 1.

Absorption Peak Wave Number/cm−1	Corresponding Wave Number Range/cm−1	Corresponding Vibration Mode
2950.24	3000~2700	Saturated C-H stretching vibration
2917.48	3000~2700	Saturated C-H stretching vibration
2868.07	3000~2700	Saturated C-H stretching vibration
2838.43	3000~2700	Saturated C-H stretching vibration
1454.02	1500~1350	Bending vibrations in saturated C-H surfaces
1375.09	1500~1350	Bending vibrations in saturated C-H surfaces

.

From Table 4, absorption peaks in the range of 3000~2700 cm⁻¹ correspond to saturated C-H stretching vibrations, while those in 1500~1350 cm⁻¹ correspond to saturated C-H in-plane bending vibrations. This indicates that the characteristic groups of PP are -CH₂ and -CH₃, along with the -CH group. The functional group structures of different samples showed no significant differences, allowing us to reduce excessive focus on functional groups in further processing of polypropylene base materials.

4.2. Influence of Macrostructure on the Insulating Properties of Polypropylene

According to the relevant data in Section 3.2.1, the XRD results of Sample 1 are shown in Figure 12.

According to Figure 12, Sample 1 exhibited α characteristic peaks at 2θ positions of 14°, 16.2°, 18.5°, and 21.2°, with the last three being small β diffraction peaks, nearly negligible. This phenomenon arises from thermodynamic imbalance during water-cooling, creating conditions for unstable β crystallization.

The crystallization types of the five polypropylene samples measured based on the XRD method are shown in

Table 5. XRD crystallization type test results.

Sample	Crystallization
1	α
2	α
3	α, β
4	α, β
5	α

.

The data in Table 5 show that Sample 1, Sample 2, and Sample 5 are α-crystalline, while Sample 3 and Sample 4 are α-crystalline coexisting with β-crystalline. Among them, α-crystallization is more stable due to higher structural regularity, while β-crystallization is a substable structure, usually caused by the addition of β-nucleating agents. The interface between α-crystallization and β-crystallization may become a charge migration channel, which increases the risk of insulation failure. Therefore, a single crystallization type should be controlled as much as possible when preparing polypropylene base materials.

According to the relevant data in Section 3.2.2, the variation of dielectric constant with temperature at 50 Hz for the five tests is shown in Figure 13.

As can be seen from Figure 13, the dielectric constants of all five polypropylene species are negatively correlated with temperature. The reason for this phenomenon is that for non-polar polymers, the relative dielectric constants satisfy the relationship shown in Equation (9) [22].

$${\displaystyle \frac{\epsilon -1}{\epsilon +2}}{\displaystyle \frac{M}{\rho }}={\displaystyle \frac{\alpha }{3{\epsilon }_0}}{N}_0=P_g$$

(9)

where N₀ is Avogadro’s constant, usually taken as 6.06 × 10²³ mol⁻¹, and P_g is the molecular polarization strength.

Since density is temperature dependent, and density decreases when temperature increases, then ε is indirectly temperature dependent, so the dielectric constant decreases slightly with increasing temperature.

Using Sample 1 as an example, the variation of dielectric loss with temperature at 50 Hz is shown in Figure 14.

As can be seen from Figure 14, the dielectric constants of the five polypropylene species are positively correlated with temperature. The reason for the above phenomenon is that the relationship between the dielectric loss of polypropylene and temperature satisfies the form shown in Equation (10).

$$\tan \delta (T)=\tan {\delta }_0\cdot e^{\frac{E_a}{kT}}$$

(10)

where tanδ(T) is the dielectric loss factor at temperature T, tanδ₀ is the dielectric loss factor at room temperature, E_a is the activation energy, and k is the Boltzmann constant.

The dielectric loss factor increases exponentially with temperature. However, at higher temperatures, polypropylene molecular chains move more freely, intermolecular interactions weaken, and the material’s response to the applied electric field diminishes, reducing polarization efficiency and slowing the dielectric loss growth rate. Thus, ambient temperature must be considered when preparing polypropylene base materials.

The AC and DC breakdown field strengths and shape parameters of five polypropylene samples were obtained according to the relevant contents of Section 3.2.3, as shown in

Table 6. Summary of AC and DC breakdown field strengths and shape parameters of polypropylene samples.

Sample	AC Breakdown Field Strength (kV/mm)	Shape Parameter	DC Breakdown Field Strength (kV/mm)	Shape Parameter
1	140.80	6.33	316.62	7.34
2	157.33	11.45	398.45	6.80
3	165.39	10.14	441.31	6.84
4	154.58	7.64	362.33	5.15
5	157.99	12.43	433.26	6.77

.

From the parameters in Table 6, it can be found that the AC and DC breakdown field strengths of Sample 3 are the highest, which is the same as the ash content test results in Section 4.1. The breakdown field strength of the same particle under DC is much higher than the AC breakdown field strength. Crystallinity refers to the proportion of ordered crystal regions in the total mass or volume of the polymer. Material crystallinity is calculated based on Equation (11).

$$X_c={\displaystyle \frac{I_c}{I_c+I_a}}\times 100\%$$

(11)

where I_c is the diffraction peak intensity in the crystalline region and I_a is the diffraction background intensity in the amorphous region.

The relationship between crystallinity and DC breakdown field strength of polypropylene was calculated and is shown in Figure 15.

As can be seen from Figure 15, the higher the crystallinity of polypropylene, the greater the DC breakdown field strength. The DC breakdown field strength of Sample 3 is the largest, which is 441.31 kV/mm, and its crystallinity is also the largest, which is 54.13%. When polyene materials are subjected to high DC voltage, the material will gradually be damaged, which will eventually lead to insulation deterioration and even breakdown. Therefore, when preparing polypropylene-based materials, the effect of crystallinity should be properly considered to improve the DC breakdown field strength of the material.

4.3. Preparation and Performance Testing of High-Performance Polypropylene Base Materials

4.3.1. Preparation Process

The preparation of polypropylene begins with the polymerization of propylene monomer, controlled by a catalyst, followed by separation, washing, and drying to obtain pure polypropylene particles, as shown in Figure 16. The steps are as follows: (1) prepare raw materials: propylene monomer, catalyst, and solvent. (2) Conduct liquid-phase polymerization, controlling the reaction rate with a catalyst. (3) Treat polymerization products: degas and distill to remove unreacted monomers, solvents, or by-products. (4) Separate and wash polypropylene: use solvent extraction or centrifugation to remove residual catalysts or solvents. (5) Dry and pulverize: dry the polypropylene to remove moisture, then pulverize it into pellets to form the polypropylene base.

4.3.2. Catalyst Selection

For the catalysts for the preparation of polypropylene, three different structural types of internal electron donors were analyzed and investigated in this section for the loaded preparation of polypropylene catalysts, and the physical properties of the catalysts and their polymerization model evaluations were obtained by experimental simulation calculations, as shown in

Table 7. Physical properties of catalysts prepared by different feeder electron systems and evaluation results of their polymerization in mold test.

Catalyst	Internal Electron Donor	Ti (wt%)	Polymerization Activity (kg PP/g cat·h)
1 (Cat 1)	1	3.1	26.7
2 (Cat 2)	2	5.5	19.4
3 (Cat 3)	3	5.5	47.7

.

It is clear from Table 7 that the model polymerization activity of Cat 3 prepared using internal electron donor 3 was 47.7 kg PP/g cat-h, which was higher than the catalytic activity of the other two catalysts prepared using endo-electron donor. Therefore, Cat 3 was chosen for the propylene molding polymerization test, and the effect of different Al/Ti ratios on the polymerization performance of the catalyst was investigated.

The catalyst die-test polymerization tests were carried out on a 10 L die-test polymerization kettle with Cat 3 as the main catalyst, triethylaluminum as the co-catalyst, and C-donor as the external electron donor, and the test results are shown in

Table 8. Effect of Al/Ti on catalyst and polymer properties in propylene polymerization.

Number	TEA (wt% = 10%)/mL	Al/Ti (mol/mol)	Activity (kg PP/g cat·h)	Polymer (MFR/g/10 min)
1	5	82.6	0	-
2	10	165.2	23.7	3.2
3	15	247.8	44.9	1.3
4	20	330.4	48.9	1.4

.

As shown in Table 8, the polymerization activity of the catalysts was improved when the amount of triethylaluminum (TEA) was changed under the condition that other polymerization conditions remained unchanged. When the amount of TEA was added at 5, 10, 15, and 20 mL, i.e., the ratio of triethylaluminum to the aluminum–titanium in the catalysts increased from 82.6 to 330.4, the polymerization activity of the catalysts was increased accordingly, and the activities were 44.9 and 48.9 kg PP/g cat·h, respectively, with the amount of TEA added at 15 and 20 mL. When the amount of TEA was added at 15 and 20 mL, the polymerization activity of the catalyst was 44.9 and 48.9 kg PP/g cat·h, respectively, and the polymerization activity of the catalyst was greatly improved compared with that when the amount of TEA was added at 10 mL.

Based on the results of the previous two experiments, and taking the catalytic activity as the key evaluation index, Cat 3 was finally determined as the main catalyst, and a catalyst system with internal electron donor 3 and a titanium concentration of 5.5% was used. On this basis, an efficient catalyst for the preparation of polypropylene substrate was produced by adding 20 mL of TEA as a co-catalyst.

4.3.3. Performance Testing of Polypropylene Substrates Optimized with Efficient Catalysts

The high-performance polypropylene base material, defined as Sample 6, was prepared by using Cat 3 prepared from internal electron donor 3, setting the addition amount of TEA to 20 mL. Its ash content, molecular weight distribution index, and crystallinity were obtained from relevant experimental tests according to the principles outlined in Section 2.1.1 and Section 2.2.2 and compared with the five samples described previously, with the results as shown in

Table 9. Test results of different specimens.

Sample	Ash Content (ppm)	MWD	Crystallinity (%)
1	19	4.81	51.54
2	15	4.03	52.97
3	12	3.32	54.28
4	17	4.43	52.73
5	13	3.94	53.47
6	11	3.29	56.15

and Figure 17, respectively.

In Figure 17a, ash content is positively correlated with molecular weight distribution index, while in Figure 17b, ash content is negatively correlated with crystallinity. According to the data in Table 9, the ash content of sample 6 was significantly reduced compared to the first five samples, with a maximum decrease of 42.1%. The MWD also decreased, with a maximum decrease of 31.6%. In addition, the crystallinity increased by 8.74%. These results provide strong evidence of the excellent performance of the polypropylene substrates prepared using this catalyst.

5. Conclusions

This paper discusses the failure of polypropylene insulation in long-term power system operation by establishing a microstructure and macro-property testing platform. The platform evaluates the ash content, molecular weight, functional groups, crystalline properties, and dielectric and breakdown characteristics of polypropylene at both the micro and macro levels, and analyzes the effects of these parameters on insulation failure. In addition, a high-performance polypropylene base preparation platform and an efficient catalyst were developed, and the properties of the prepared polypropylene bases were compared and verified. The main research results are as follows:

(1)

Microstructural testing of the polypropylene substrates showed that the ash content of the five groups of samples ranged from 12 to 20 ppm, and the ash content was negatively correlated with the insulating properties of the materials. The insulating properties were positively correlated with the molecular weight, and the narrower the molecular weight distribution, the better the performance, with the optimal sample having a molecular weight distribution index as low as 3.32. Infrared spectroscopy analysis showed that all the polypropylene samples had the same functional group structure, which mainly consisted of -CH, -CH2, and -CH3 groups, and no significant structural differences were found.

(2)

Macroscopic property tests showed that there were significant differences in molecular weight distribution and crystalline morphology among the samples. Samples 1, 2, and 6 were predominantly α-crystalline, while samples 3 and 4 contained a small amount of β-crystalline. Sample 3 has the lowest weight average molecular weight (333,450) but the highest crystallinity (54.13%), confirming the correlation between molecular structure and mechanical properties. The dielectric properties showed that the temperature increase at constant pressure resulted in a decrease in the dielectric constant and a frequency shift of the dielectric loss peak. Meanwhile, increasing the field strength at constant temperature enhances the dielectric parameter, while increasing frequency triggers a decrease in dielectric constant, and the trend of dielectric loss increasing and then decreasing. The crystallinity is positively correlated with the DC breakdown field strength, and the breakdown field strength of the No. 3 sample is up to 443.31 kV/mm.

(3)

Catalysts with different internal electron donors and titanium concentrations exhibited varying polymerization activities in high-performance polypropylene substrate preparation. The catalyst with endo-donor 3 and 5.5% titanium concentration achieved the highest activity of 47.7 kg PP/g cat·h. Optimization by adding 20 mL TEA and adjusting the Al/Ti ratio further increased activity to 51.9 kg PP/g cat·h. The resulting polypropylene showed significant improvements: ash content reduced by 42.1%, molecular weight distribution index dropped to 3.29, and crystallinity increased by 8.74%, demonstrating enhanced properties.