Modified filling master batch with reinforcing and toughening effects and automatic production process of modified filling master batch

Abstract

The invention discloses a modified filling master batch with reinforcing and toughening effects and an automatic production process thereof, and belongs to the technical field of modified filling master batch production. The master batch is composed of polymer matrix resin, a dual-scale inorganic filler, a dynamic vulcanization toughening system, an interface modifier and a functional aid, the dual-scale filler is compounded by nano montmorillonite and micron wollastonite, and the toughening system comprises POE / SEBS and a liquid acrylate rubber compound. The production process comprises four main procedures of double-gradient interface construction, ultrasonic directional dispersion, dynamic vulcanization cooperative control and intelligent separation, a spiral arrangement ultrasonic vibrator array and an online dielectric spectrum monitoring technology are adopted, and a visual identification separation system and a three-stage waste heat recovery system are matched. Through combination of multi-scale filler synergistic enhancement and a dynamic vulcanization process, optimization of material performance is realized, an intelligent control system is adopted in a production process, and production efficiency and product consistency are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of modified filler masterbatch production, and particularly relates to a modified filler masterbatch with both reinforcing and toughening effects and its automated production process. Background Art

[0002] In the field of filler masterbatch, the traditional technology has long faced the core contradiction that it is difficult to synergistically improve the reinforcing and toughening properties. The existing technologies mostly adopt a single rigid filler (such as calcium carbonate, talcum powder) or an elastomer toughening agent modification system. The former can improve the rigidity of the material but easily leads to an increase in brittleness, while the latter can improve toughness but significantly sacrifices strength and heat resistance. At the process level, the conventional mechanical blending method is prone to stress concentration defects due to uneven filler dispersion and weak interfacial bonding force; while the static vulcanization process is difficult to precisely balance fluidity, strength and toughness due to uncontrollable crosslinking density. In addition, traditional interfacial modifiers rely on petroleum-based coupling agents, which have high environmental loads and poor compatibility with bio-based materials. The existing production processes generally lack intelligent control means, and the filler dispersion, vulcanization process and particle sorting rely on manual experience, resulting in poor product consistency, high energy consumption, and insufficient control of volatile organic compound (VOC) emissions, and it is difficult to meet the urgent needs of high-performance, green and intelligent manufacturing in high-end fields. The above technical bottlenecks have severely restricted the application expansion of filler masterbatch in harsh working conditions such as automobiles and electronics. Summary of the Invention

[0003] The main purpose of the present invention is to provide a modified filler masterbatch with both reinforcing and toughening effects and its automated production process, which can effectively solve the problems mentioned in the background art.

[0004] To achieve the above purpose, the technical solution adopted by the present invention is as follows: A modified filler masterbatch with both reinforcing and toughening effects is composed of the following raw materials in parts by weight: Polymer matrix resin: 100 parts; Double-scale inorganic filler: 15 - 25 parts, which is a compound of nanosheet montmorillonite and micron-sized modified wollastonite in a mass ratio of 2:1; Dynamic vulcanization toughening system: 8 - 15 parts, including a composite elastomer of POE / SEBS (70:30) and liquid acrylate rubber (LACM); Interfacial modifier: 3 - 5 parts, including a compound of castor oil-based polyurethane prepolymer (CO-PU) and maleic anhydride grafted polylactic acid (MAH-g-PLA); Functional additive: 1.5 - 3 parts, including hyperbranched polyester (HBP), bio-based erucamide and zinc oxide / stearic acid activation system.

[0005] Define the synergistic combination of dual-scale fillers and dynamic vulcanization system, enhance rigidity through nanosheets, disperse stress with micron-sized particles, and combine elastomeric sea-island structures to absorb impact energy, breaking through the technical bottleneck of the traditional filling system that "toughness must sacrifice strength".

[0006] Preferably, the particle size of the nanosheet montmorillonite is 50 - 100 nm, and it is surface-treated with silane coupling agent KH550; the particle size of the micron-sized modified wollastonite is 3 - 5 μm, and the coating rate of bio-based erucic acid amide grafted on the surface is 85% - 92%. KH550 chemically bonds to strengthen the interface combination of montmorillonite, and erucic acid amide physically coats to improve the dispersibility of wollastonite. The dual-gradient treatment solves the compatibility problem of multi-scale fillers.

[0007] An automated production process for preparing the above-mentioned modified filling masterbatch includes the following steps: S1. Dual-gradient interface construction: Put nanometer montmorillonite and micron wollastonite into a high-speed mixer according to a mass ratio of 2:1, and synchronously spray silane coupling agent KH550 and bio-based erucic acid amide (3:1) for surface treatment. Mix at a rotation speed of 1200 - 1500 rpm for 5 - 8 minutes, and control the material temperature to rise to 65 ± 3 °C; S2. Ultrasonic directional dispersion: The treated fillers enter the second zone of the twin-screw extruder. Turn on the 20 kHz ultrasonic oscillator array arranged in a spiral, apply an ultrasonic field with a power density of 3 - 3.5 W / cm², and adjust the amplitude (25 - 35 μm) in real-time through a viscosity sensor feedback, maintaining the residence time of the material for 45 - 60 seconds; S3. Dynamic vulcanization co-control: Inject liquid acrylate rubber (LACM) into the third zone of the extruder, trigger the vulcanization reaction of the zinc oxide / stearic acid activation system at 175 ± 2 °C, and simultaneously apply a shear rate of 120 - 150 S⁻¹. Collect dielectric constant data every 10 seconds through an on-line dielectric spectrometer, and dynamically adjust the injection rate of the vulcanizing agent to keep the crosslinking density stable at 15% - 20%; S4. Gradient devolatilization and intelligent sorting: The melt enters the vacuum devolatilization zone and cools down in two stages under a vacuum of -0.095 MPa: the first stage is from 160 °C to 145 °C in 30 seconds, and the second stage is from 145 °C to 140 °C in 15 seconds. After water-cooled die-face pelletization, use a convolutional neural network (CNN) vision recognition system to sort particles with a particle size of 2 - 3 mm, and automatically return the over-standard particles to the premixing process.

[0008] Break the agglomeration of fillers through ultrasonic directional dispersion, combine dynamic vulcanization to precisely control the crosslinking network, and simultaneously achieve the orderly distribution of fillers and the regulation of the toughening phase morphology, overcoming the defects of uneven dispersion and out-of-control vulcanization in the traditional blending process.

[0009] Preferably, the axial pitch of the ultrasonic oscillator array in S2 is 0.8 - 1.2 times the diameter of the screw, and when the melt viscosity > 1500 Pa·s is detected, it automatically switches to the pulse mode (working for 2 seconds / intermittent for 0.5 seconds). It maintains effective dispersion under high-viscosity working conditions and avoids local overheating and energy consumption waste caused by traditional continuous ultrasound.

[0010] Preferably, in S3, the LSTM neural network is used to process the dielectric spectroscopy data, and the input parameters of the prediction model include: Real-time dielectric constant ε' (sampling frequency 10 Hz); Loss factor tanδ value; Melt pressure fluctuation value (within ±0.15 MPa); Output the PID control parameters of the vulcanizing agent, and the response delay < 0.5 seconds.

[0011] Introduce the LSTM neural network to process multi-source sensing data, realize the dynamic prediction and closed-loop control of the vulcanization process, and improve the process stability and response speed compared with manual experience adjustment.

[0012] Preferably, the vision recognition system in S4 sets double judgment criteria: ① Geometric features: particle size 2 - 3 mm and aspect ratio < 1.5 ② Surface quality: specular reflectivity > 85% and no visible pores Particles that simultaneously meet ① and ② are marked as qualified products, and the sorting accuracy rate ≥ 98%.

[0013] Eliminate the inflow of surface defective products caused by traditional single-particle-size screening, and ensure the consistency of product performance.

[0014] Preferably, in the S4 vacuum devolatilization stage, the volatile gas at 145 - 160 °C is introduced into the waste heat recovery device, and the heat energy is used through a three-stage heat exchanger for: Preheat the mixer in S1 to 50 - 55 °C; Maintain the constant temperature of the ultrasonic oscillator array in S2 (65 ± 2 °C); Supply the plant hot water system (40 - 45 °C); The comprehensive heat energy utilization rate ≥ 72%, build a three-stage waste heat utilization system, convert process waste heat into effective energy such as pretreatment and constant temperature control, and break through the pain points of high production energy consumption and large heat loss in traditional production.

[0015] A production system for implementing the above automatic production process, including: A twin-screw extruder equipped with a helically arranged ultrasonic oscillator array (axial pitch is 0.8 - 1.2 times the screw diameter); A dynamic vulcanization reaction cavity integrated with on-line dielectric spectroscopy monitoring (sampling frequency 10 seconds / time); A fifth-order temperature control system with a fuzzy PID algorithm (temperature control accuracy: ±0.5°C); A die-face hot cutting granulation unit with a particle size adaptive sorting function.

[0016] Synergize the ultrasonic energy field with the material flow direction, improving the energy utilization rate by more than 40% compared to the traditional parallel arrangement.

[0017] Preferably, the adaptive sorting function is realized by a high-speed CCD camera (frame rate: 500fps) and a convolutional neural network (CNN) algorithm, and the sorting speed is ≥2000 grains / minute. The high-speed CCD and the CNN algorithm can achieve millisecond-level defect recognition, replacing manual visual inspection and solving the industry problems of low traditional sorting efficiency and high missed inspection rate.

[0018] Compared with the prior art, the present invention has the following beneficial effects: The present invention innovatively adopts a "core-shell-bridge" composite structure design to optimize the material properties through the synergistic effect of inorganic / organic multiphases. Combining the dynamic vulcanization process and the ultrasonic directional dispersion technology, a nano / micro double-scale reinforcement system and an elastic toughening network are constructed to break through the performance bottleneck of traditional filling materials; a bio-based interface modifier is introduced to improve the compatibility, an intelligent algorithm is integrated to real-time control the vulcanization process and particle sorting, and a waste heat recovery system is equipped to realize the cascade utilization of heat energy, forming a full-process technology system with the characteristics of structural innovation, process synergy, intelligent control and green energy conservation, effectively solving the contradiction between reinforcement and toughening performance, and significantly improving the comprehensive performance and production efficiency of products. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is a schematic diagram of the automated production process flow of the present invention; Figure 2 It is a schematic diagram of the S1 process in the automated production process of the present invention; Figure 3 It is a schematic diagram of the S2 process in the automated production process of the present invention; Figure 4 It is a schematic diagram of the S3 process in the automated production process of the present invention; Figure 5 It is a schematic diagram of the S4 process in the automated production process of the present invention; Figure 6 For Figure 1 The schematic diagram of the waste heat recovery process in DETAILED DESCRIPTION OF THE INVENTION

[0020] As Figures 1-6 shown, a modified filling masterbatch with both reinforcement and toughening effects and its automated production process flow are described below with reference to a detailed embodiment.

[0021] I. Raw material preparation and pretreatment 1. Polymer matrix resin: Select homopolypropylene (PP) with a melt index of 15 g / 10 min, grade T30S. Before use, dry it in an oven at 80 °C for 4 hours, and control the moisture content to ≤0.03%.

[0022] 2. Double-scale inorganic filler: Nano-montmorillonite: Select sodium-based montmorillonite with an interlayer spacing of 1.2 nm.

[0023] Pretreatment: Ultrasonically treat montmorillonite with 3 wt% silane coupling agent KH550 in an ethanol aqueous solution (ethanol: water = 95:5) for 30 minutes (power 300 W). After treatment, dry it in a vacuum at 120 °C to constant weight. Micro wollastonite: Select acicular wollastonite with an average aspect ratio of 8:1.

[0024] Pretreatment: Treat it with 1.5 wt% bio-based erucamide in a high-speed mixer at 60 °C for 15 minutes.

[0025] 3. Dynamic vulcanization system: The POE / SEBS blend (70:30) is pre-mixed in a Banbury mixer at 160 °C for 5 minutes. The liquid acrylate rubber (LACM) needs to be preheated at 50 °C before use to reduce its viscosity.

[0026] 4. Interface modifier: Synthesis of castor oil-based polyurethane prepolymer (CO-PU): Castor oil reacts with TDI in a ratio of NCO / OH = 2.1. The reaction temperature is 80 °C and the time is 3 hours. Maleic anhydride grafted polylactic acid (MAH-g-PLA): The grafting rate is 1.8% and the melt index is 12 g / 10 min.

[0027] II. Production process flow (I) Construction of double-gradient interface (S1) 1. Equipment configuration: Select SHL-100 type high-speed mixer; equipped with variable frequency speed regulation (0-2000 rpm) and infrared temperature measurement system. 2. Process parameters: ① Feeding order: First add the pretreated micro wollastonite; slowly add nano-montmorillonite; synchronously spray the modifier mixture (KH550: erucamide = 3:1).

[0028] ② Mixing parameters: Rotating speed: 1450 ± 50 rpm; time: 6.5 minutes; end temperature: 65 ± 2 °C.

[0029] ③Quality control points: Sampling and testing the filler coating rate (XPS analysis); ensuring no visible agglomerated particles.

[0030] (2) Ultrasonic directional dispersion (S2) 1. Equipment configuration: TSE-50 co-rotating twin-screw extruder; Specifically designed ultrasonic module: 20 kHz ultrasonic vibrator, arranged in a spiral pattern; axial spacing 45 mm (screw diameter 50 mm); maximum power 5 kW.

[0031] 2. Process parameters: Temperature setting: Zone I: 160 °C (material preheating); Zone II: 170 - 175 °C (ultrasonic dispersion zone); Ultrasonic parameters: Initial power density: 3.2 W / cm²; amplitude adjustment range: 25 - 35 μm; automatically adjusted according to the feedback of the on-line viscometer.

[0032] Melt quality control: Sampling every 30 minutes for SEM observation to ensure uniform filler dispersion (aggregate size ≤ 200 nm).

[0033] (3) Dynamic vulcanization collaborative control (S3) 1. Equipment modification: The third zone of the extruder is modified into a dynamic vulcanization reaction chamber Equipped with: precision liquid injection system (measurement accuracy ±0.5%); on-line dielectric spectrometer (measurement frequency 10 Hz - 1 MHz); melt pressure sensor (range 0 - 20 MPa).

[0034] 2. Process control: LACM injection: Injection port location: the 8th section of the screw; injection rate: 50 g / min ± 5% Vulcanization control: Activation temperature: 175 ± 1 °C; shear rate control: adjusted by screw speed (corresponding to 120 - 150 S-1).

[0035] Input parameters of the LSTM model: real-time dielectric constant (ε'); loss factor (tanδ); pressure fluctuation value.

[0036] Output parameters: correction amount of vulcanizing agent injection rate; fine-tuning value of screw speed.

[0037] 3. Quality control: Sampling every 15 minutes to test the crosslinking density (equilibrium swelling method) to ensure that the crosslinking density is stable in the range of 16% - 18%.

[0038] (IV)Gradient devolatilization and intelligent sorting (S4) Devolatilization system: Three-stage vacuum devolatilization design: First stage: -0.08 MPa, 160 → 150 °C; Second stage: -0.095 MPa, 150 → 145 °C; Third stage: -0.098 MPa, 145 → 140 °C; Residence time control: total time 45 ± 5 s.

[0039] Pelletizing and sorting system: Die face hot cutting pelletizer: die head temperature: 138 ± 2 °C; cutter speed: 800 rpm.

[0040] Vision sorting system: Basler ace 2 camera (500 fps); Light source: ring-shaped LED, adjustable brightness; Image processing: Resolution: 0.05 mm / pixel; Detection algorithm: Geometric feature detection (particle size, aspect ratio); Surface defect detection (porosity, depression); Sorting execution: Compressed air nozzle array; Sorting accuracy: ±0.1 mm; Waste heat recovery system: Heat exchanger configuration: First stage: plate heat exchanger (recovery temperature 145 - 160 °C); Second stage: shell-and-tube heat exchanger (recovery temperature 120 - 145 °C); Third stage: finned tube heat exchanger (recovery temperature 80 - 120 °C); Thermal energy distribution: 40% for raw material pretreatment; 30% for equipment constant temperature; 30% for plant heating.

[0041] III. Production system integration 1. Control system architecture: PLC main control: Siemens S7-1500; Sub-system communication: PROFINET real-time network; Data sampling period: 100 ms; Human-machine interface: WinCC host computer system; Real-time display: process parameter curves, quality inspection data, equipment status monitoring; 2. Key sensor configuration: Melt pressure: piezoelectric sensor (accuracy ±0.1%); Temperature measurement: armored thermocouple (accuracy ±0.5°C); Viscosity detection: on-line capillary rheometer (sampling period 10s); Safety protection system: Overpressure alarm (>18MPa); temperature gradient monitoring (temperature difference alarm for each interval); emergency stop interlock.

[0042] IV. Quality inspection plan 1. Process inspection: Sampling inspection every 30 minutes: Melt flow rate (ASTM D1238), filler dispersion (image analysis method), volatile content (thermogravimetric analysis).

[0043] 2. Finished product inspection: Physical properties: density (GB / T 1033), particle size distribution (screening method); Mechanical properties: tensile properties (GB / T 1040), impact strength (GB / T 1843); Thermal properties: heat distortion temperature (GB / T 1634), melt index (GB / T 3682).

[0044] V. Key points for process optimization 1. Optimization of filler dispersion: Matching relationship between ultrasonic parameters and screw speed: Speed (rpm) -- ultrasonic power (kW) 200 -- 3.0; 250 -- 3.5; 300 -- 4.0.

[0045] 2. Optimization of vulcanization control: Corresponding relationship between dielectric parameters and crosslinking density: ε' = 2.6 → crosslinking density 15%; ε' = 2.4 → crosslinking density 18%; ε' = 2.2 → crosslinking density 20%. 3. Energy consumption control: Power distribution for each section: Mixing: 15%; extrusion: 50%; granulation: 20%; auxiliary: 15%.

[0046] VI. Abnormal handling plan 1. Filler agglomeration: Phenomenon: The melt pressure suddenly increases by more than 15%; Treatment: Immediately increase the ultrasonic power by 20%; reduce the feeding rate by 30%; continuously monitor the pressure change.

[0047] 2. Insufficient vulcanization: Phenomenon: The dielectric constant ε' > 2.8 lasts for 30 seconds; Treatment: Automatically increase the injection amount of vulcanizing agent by 10%; increase the temperature in Zone III by 2°C; extend the residence time by 5 seconds.

[0048] 3. Sorting failure: Phenomenon: The sorting accuracy rate < 95% for 30 consecutive seconds; Treatment: Automatically switch to the standby camera; adjust the light source brightness by +20%; trigger the manual re-inspection program.

[0049] This embodiment details the complete production process from raw material pretreatment to finished product sorting, including specific details such as equipment selection, process parameters, and quality control. It verifies the synergistic advantages of the "core-shell-bridge" structure design and intelligent process control. The waste heat recovery system and the mechanism for recycling over-standard particles further embody the concept of green manufacturing, providing a reliable technical model for industrial promotion. During actual production, relevant parameters can be adjusted within the scope of the claims according to equipment conditions and product requirements. Data records are set for all process control points, facilitating quality traceability and process optimization.

[0050] The above shows and describes the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments. What is described in the above embodiments and the specification only illustrates the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention will have various changes and improvements, and these changes and improvements all fall within the scope of the present invention claimed. The scope of protection claimed by the present invention is defined by the appended claims and their equivalents.

Claims

1. A modified filled masterbatch with both strengthening and toughening effects, characterized in that: It is composed of the following raw materials by weight: Polymer matrix resin: 100 parts; Dual-scale inorganic filler: 15-25 parts, made of nano-sheet montmorillonite and micron-scale modified wollastonite in a mass ratio of 2:1; Dynamic vulcanization toughening system: 8-15 parts, including composite elastomer of POE / SEBS and liquid acrylic rubber; Interface modifier: 3-5 parts, comprising a compound of castor oil-based polyurethane prepolymer and maleic anhydride grafted polylactic acid; Functional additives: 1.5-3 parts, including hyperbranched polyester, bio-based erucamide and zinc oxide / stearic acid activation system.

2. The modified filler masterbatch with both strengthening and toughening effects according to claim 1, characterized in that: The nano-sheet montmorillonite has a particle size of 50-100 nm and is surface treated with a silane coupling agent KH550; the micron-grade modified wollastonite has a particle size of 3-5 μm and a coverage rate of 85% to 92% of the surface-grafted bio-based erucic acid amide.

3. An automated production process for preparing the modified filling masterbatch as described in any one of claims 1-2, characterized in that: The following steps are involved: S1. Construction of double gradient interface: Nano-montmorillonite and micron wollastonite were put into a high-speed mixer at a mass ratio of 2:1, and silane coupling agent KH550 and bio-based erucic acid amide were sprayed at a mass ratio of 3:1 for surface treatment, mixed at a speed of 1200-1500 rpm for 5-8 minutes, and the material temperature was controlled to rise to 65±3°C; S2, ultrasonic directional dispersion: the treated filler enters the twin-screw extruder zone II, the spirally arranged 20kHz ultrasonic vibrator array is turned on, an ultrasonic field with a power density of 3-3.5W / cm² is applied, and the amplitude range is adjusted to 25-35μm through real-time feedback from the viscosity sensor, and the material residence time is maintained at 45-60 seconds; S3, Dynamic vulcanization coordinated control: Liquid acrylic rubber is injected into zone III of the extruder to trigger the vulcanization reaction of the zinc oxide / stearic acid activation system at 175±2℃, and a shear rate of 120-150S-1 is applied simultaneously. The dielectric constant data is collected every 10 seconds through an online dielectric spectrometer, and the injection rate of the vulcanizer is dynamically adjusted to stabilize the crosslinking density at 15% to 20%; S4, gradient devolatilization and intelligent sorting: the melt enters the vacuum devolatilization zone and is cooled in two stages under a vacuum degree of -0.095MPa: the first stage is 160℃→145℃ / 30 seconds, and the second stage is 145℃→140℃ / 15 seconds. After pelletizing on the water-cooled die surface, a convolutional neural network visual recognition system is used to sort particles with a size of 2-3mm, and particles exceeding the standard are automatically fed back to the premixing process.

4. The automated production process of a modified filler masterbatch with both reinforcement and toughening effects according to claim 3, characterized in that: The axial spacing of the ultrasonic vibrator array in S2 is 0.8-1.2 times of the screw diameter, and when the melt viscosity is detected to be greater than 1500 Pa·s, it automatically switches to the pulse mode, that is, working for 2 seconds / resting for 0.5 seconds.

5. The automated production process of a modified filled masterbatch with both reinforcement and toughening effects according to claim 3, characterized in that: In S3, LSTM neural network is used to process dielectric spectrum data, and the prediction model input parameters include: Real-time dielectric constant ε' (sampling frequency 10Hz); Loss factor tanδ value; Melt pressure fluctuation value; Output vulcanizing agent PID control parameters, response delay <0.5 seconds.

6. The automated production process of a modified filler masterbatch with both strengthening and toughening effects according to claim 3, characterized in that: The visual recognition system in S4 sets dual judgment criteria: ①Geometric characteristics: particle size 2-3mm and aspect ratio <1.5 ②Surface quality: Mirror reflectivity>85% and no visible pores Particles that meet both ① and ② are marked as qualified products.

7. An automated production process for a modified filled masterbatch with both reinforcement and toughening effects according to claim 3, characterized in that: In the S4 vacuum devolatilization stage, the volatile gas at 145 - 160 °C is introduced into the waste heat recovery device, and the thermal energy is used through a three-stage heat exchanger for: Preheating the mixer in S1 to 50 - 55 °C; Maintaining the constant temperature of the ultrasonic oscillator array in S2 at 65 ± 2 °C; Supplying the plant hot water system.

8. A production system for implementing the automated production process as described in claim 3, characterized in that: It includes: A twin-screw extruder equipped with an ultrasonically oscillator array arranged in a spiral, with an axial pitch of 0.8 - 1.2 times the screw diameter; A dynamic vulcanization reaction cavity integrated with on-line dielectric spectroscopy monitoring, with a sampling frequency of 10 seconds / time; A fifth-order temperature control system equipped with a fuzzy PID algorithm, with a temperature control accuracy of ±0.5 °C; A die-face hot cutting granulation unit with a particle size adaptive sorting function.

9. The production system according to claim 8, characterized in that: The adaptive sorting function is realized by a high-speed CCD camera and a convolutional neural network algorithm, and the sorting speed is ≥ 2000 particles / minute.

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