Aluminum-plastic interface in-situ morphology and spectrum combined analysis system and analysis method in hydrothermal environment

Abstract

The invention discloses an aluminum-plastic interface in-situ morphology and spectrum combined analysis under a hydrothermal environment, which comprises a sample holder, an in-situ heating table is arranged on the sample holder, a hydrothermal reactor for placing a sample is arranged in the in-situ heating table, observation windows are arranged on the upper side and the lower side of the in-situ heating table, and the in-situ heating table is connected with the hydrothermal reactor. An inverted microscope is arranged below an observation window on the lower side of the in-situ heating table, a camera is arranged at an observation port of the inverted microscope, and a Fourier infrared ATR spectrometer and a Raman spectrometer are arranged above the observation window on the upper side of the in-situ heating table; the camera, the Fourier infrared ATR spectrometer and the Raman spectrometer are respectively connected with the server, and the server is sequentially connected with the machine learning module and the visual report module. The aluminum-plastic interface in-situ morphology and spectrum combined analysis system under the hydrothermal environment has the problems of insufficient real-time monitoring and incomplete data analysis in the current research.

Description

Technical Field

[0001] The present invention belongs to the field of composite material interface science and characterization technology, and particularly relates to an in-situ morphology and spectral analysis system for an aluminum-plastic interface under a hydrothermal environment, and also relates to an in-situ morphology and spectral analysis method for an aluminum-plastic interface under a hydrothermal environment. Background Art

[0002] With the widespread application of composite materials in packaging, construction, electronics, and other fields, the use of paper-plastic-aluminum composites has increased annually, but the problem of waste disposal has also become increasingly prominent. Paper-plastic-aluminum composites are composed of multiple layers of paper, plastics (such as polyethylene (PE) and polypropylene (PP), and aluminum foil), with each layer tightly bonded together by adhesives or heat pressing. This complex structure makes it difficult to efficiently separate and recycle discarded paper-plastic-aluminum composites, resulting in resource waste and environmental pollution. Currently, the disposal of paper-plastic-aluminum waste mainly relies on landfill or incineration, but these methods not only waste resources but also cause secondary pollution to the environment. Therefore, the development of an efficient and environmentally friendly paper-plastic-aluminum waste separation technology is of great significance.

[0003] Hydrothermal liquefaction technology is a waste treatment method using high-temperature, high-pressure water. It effectively decomposes organic matter to recover high-quality bio-oil and metal components. Due to its unique chemical composition, hydrothermal liquefaction of paper-plastic-aluminum composite packaging waste offers the following advantages: First, the co-liquefaction of biomass and plastic creates a synergistic interaction. The reactive intermediates produced by biomass liquefaction can promote the breakage of C—C bonds in plastic polymers, reducing their thermal stability. The hydrogen generated by hydrogen-rich polyolefin chains stabilizes free radicals generated by biomass thermal degradation, preventing them from repolymerizing into solid biochar. Furthermore, through reactions such as hydrodehydration and decarboxylation, the concentration of oxygen-containing groups such as aldehydes, carbonyls, and carboxylic acids is reduced. Second, aluminum undergoes an Al-H₂O reaction under hydrothermal conditions to produce H₂ (2Al + 4H₂O → 2AlOOH + 3H₂ at 280–480°C), enabling in-situ hydrodeoxygenation and upgrading of the bio-oil.

[0004] However, the aluminum-plastic interface is tightly bonded, and its interfacial separation characteristics and reaction behavior in a hydrothermal environment directly affect the migration of H2O molecules to the aluminum foil interface, thereby affecting the chemical reaction rate on the aluminum foil surface. Interfacial separation involves complex physical and chemical changes, such as physical changes such as interfacial debonding, bulging, and crack formation, as well as molecular structural changes such as chemical bond breaking and new bond formation. Traditional research methods mainly rely on offline analysis, which makes it difficult to monitor dynamic changes in real time. In addition, existing methods generally rely on a single characterization technique, unable to simultaneously obtain multi-source data at the physical and chemical levels. In addition, data processing efficiency is low, making it difficult to meet the needs of efficient separation and recovery. Summary of the Invention

[0005] The first purpose of the present invention is to provide an in-situ morphology and spectral analysis system for the aluminum-plastic interface under a hydrothermal environment to solve the problems of insufficient real-time monitoring and incomplete data analysis in current research.

[0006] In order to achieve the above-mentioned purpose, the technical solution adopted by the present invention is an in-situ morphology and spectral combined analysis system of the aluminum-plastic interface under a hydrothermal environment, comprising a sample rack, an in-situ heating platform provided on the sample rack, a hydrothermal reactor for placing samples provided in the in-situ heating platform, observation windows provided on the upper and lower sides of the in-situ heating platform, an inverted microscope arranged below the observation window on the lower side of the in-situ heating platform, a camera arranged at the observation port of the inverted microscope, a Fourier transform infrared (ATR) spectrometer and a Raman spectrometer arranged above the observation window on the upper side of the in-situ heating platform; the camera, the Fourier transform infrared (ATR) spectrometer and the Raman spectrometer are respectively connected to a server, and the server is connected to a machine learning module and a visualization report module in turn.

[0007] The technical solution of the present invention also has the following characteristics: As a preferred technical solution of the present invention, the hydrothermal reactor is a capillary quartz tube, and the end of the capillary quartz tube is sealed by an oxygen welding gun.

[0008] As a preferred technical solution of the present invention, a quartz tube reactor cavity is provided inside the in-situ heating platform, and resistance heating wires and semiconductor cooling sheets are provided around the quartz tube reactor cavity.

[0009] As a preferred technical solution of the present invention, the camera is arranged on a tripod.

[0010] As a preferred technical solution of the present invention, the camera is a CMOS camera.

[0011] As a preferred technical solution of the present invention, the machine learning module uses a three-dimensional convolutional neural network to analyze morphological images, automatically identify interface changes, and uses a graph neural network to process Raman spectral data to track the dynamic changes of multiple chemical bonds.

[0012] The second purpose of the present invention is to provide an in-situ morphology and spectral analysis method for the aluminum-plastic interface under a hydrothermal environment to solve the problems of insufficient real-time monitoring and incomplete data analysis in current research.

[0013] In order to achieve the above object, the technical solution adopted by the present invention is a method for analyzing the in-situ morphology of the aluminum-plastic interface under a hydrothermal environment by combining spectroscopy and the like, comprising: Step 1, placing the sample into a hydrothermal reactor; Step 2: Initialize and set up the inverted microscope, in-situ heating stage, Fourier transform infrared (ATR) spectrometer, and Raman spectrometer; Step 3, using an in-situ heating stage to simulate a hydrothermal environment; Step 4, collecting raw data using an inverted microscope, a Fourier transform infrared (ATR) spectrometer, and a Raman spectrometer; Step 5: Call the machine learning module to perform joint analysis and fusion processing on the acquired multimodal data such as morphology and spectrum, and realize the visualization and output of the data based on the visualization report module.

[0014] The beneficial effects of the present invention are as follows: the present invention is an in-situ morphology and spectral analysis system for the aluminum-plastic interface under a hydrothermal environment, which successfully captures key processes such as the initiation of debonding and bulging growth at the aluminum-plastic interface, and discovers the directional expansion phenomenon of interface cracks; it successfully realizes real-time monitoring of Al-O bonds and C-H bonds, quantitative analysis of interface reaction kinetics, and two-dimensional chemical composition mapping, and has significant advantages such as good high-temperature stability, high signal acquisition efficiency, and support for in-situ chemical dynamic imaging, which solves the problems of insufficient real-time monitoring and incomplete data analysis in existing aluminum-plastic separation research, and provides a scientific basis and technical support for the separation mechanism of the aluminum-plastic interface under a hydrothermal environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a structural schematic diagram of an in-situ morphology and spectrum analysis system for an aluminum-plastic interface under a hydrothermal environment of the present invention.

[0016] In the figure: 1. Tripod, 2. Camera, 3. Inverted microscope, 4. Sample holder, 5. In-situ heating stage, 6. Observation window, 7. Hydrothermal reactor, 8. Fourier transform infrared (ATR) spectrometer, 9. Raman spectrometer, 10. Server, 11. Machine learning module, 12. Visual reporting module. DETAILED DESCRIPTION

[0017] The technical solution of the present invention will be further described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0018] Example 1 like Figure 1 As shown, the present invention provides an in-situ morphology and spectroscopy analysis system for an aluminum-plastic interface under a hydrothermal environment, comprising a sample rack 4, an in-situ heating platform 5 provided on the sample rack 4, a hydrothermal reactor 7 for placing a sample provided in the in-situ heating platform 5, observation windows 6 provided on the upper and lower sides of the in-situ heating platform 5, an inverted microscope 3 arranged below the observation window 6 on the lower side of the in-situ heating platform 5, a camera 2 arranged at the observation port of the inverted microscope 3, a Fourier transform infrared (ATR) spectrometer 8 and a Raman spectrometer 9 arranged above the observation window 6 on the upper side of the in-situ heating platform 5; the camera 2, the Fourier transform infrared (ATR) spectrometer 8 and the Raman spectrometer 9 are respectively connected to a server 10, and the server 10 is connected in turn to a machine learning module 11 and a visualization report module 12.

[0019] The hydrothermal reactor 7 adopts a capillary quartz tube structure, and the tube end is sealed with a portable oxygen welding gun; the in-situ heating stage is provided with a quartz tube reactor cavity, surrounded by resistance heating wires and semiconductor refrigeration plates for rapid heating and cooling, and observation windows 6 are opened on the surface and bottom; the inverted optical microscope 4 integrates a high-precision hot and cold stage and a high-speed CMOS camera 2 for observing the dynamic morphology and rheological properties of the sample during the continuous heating process; the Raman spectrometer 9 and the Fourier ATR infrared spectrometer 8 adopt a confocal optical design for detecting the real-time change law of the functional groups of organic matter in the hydrothermal process, and the two test results complement and verify each other; the server 10 is used for real-time processing of multi-source data; the machine learning module 11 is used to automatically identify image changes, track the dynamic changes of multiple chemical bonds, establish cross-modal associations, and improve prediction accuracy; the visualization report module 12 is used to generate experimental reports that support three-dimensional reconstruction and dynamic annotation.

[0020] The capillary quartz tube wall thickness is calculated based on the inner diameter and operating pressure. The reaction volume is controlled by adjusting the reaction tube length, and the reaction pressure is characterized by the water density parameter. The in-situ heating platform 5 is compatible with hydrothermal reactors 7 of various specifications. Observation windows 6 opened on the surface and bottom of the in-situ heating platform 5 are larger than the diameter of the quartz tube reactor and are more than 1 / 3 the length of the quartz tube reactor, supporting real-time optical and spectral monitoring. The bottom-mounted observation window is for use with an inverted optical microscope 3, and the top observation window is for a Raman spectrometer 9 and a Fourier transform ATR infrared spectrometer 8. The in-situ heating platform 5 has a temperature control range of -50°C to 500°C, with a temperature control accuracy of ±0.1°C. It integrates a PT100 thermocouple temperature sensor and a PID controller.

[0021] The optical microscope uses an inverted microscope3, which allows ample space on the stage for sample placement. The observation window at the bottom of the in-situ hot and cold stage allows for observation of the sample's morphological changes during heating. The microscope integrates a high-precision hot and cold stage with a high-speed CMOS camera, achieving a spatial resolution of 0.5μm and supporting 100fps image acquisition. A precision mechanical platform ensures observation stability. The in-situ heating stage 5 features a multimodal collaborative detection architecture with a modular three-station design encompassing microscopic observation, ATR detection, and Raman detection. It is equipped with a high-precision linear motor drive system and a fast switching mechanism (ATR lever lift time < 0.3 seconds). The Fourier Transform Infrared Spectrometer 8 utilizes a diamond / ZnSe composite crystal detection window, ensuring optical stability in high-temperature and high-pressure environments. Features such as real-time background compensation, dynamic pressure adjustment, and intelligent scanning parameter optimization ensure high measurement accuracy. It boasts a maximum temporal resolution of 0.5 seconds and supports simultaneous topographic and spectral data fusion. Server 9 uses the Xeon Platinum 8380 processor and NVIDIA A100 graphics card architecture, and has the ability to process optical images, spectral data and environmental parameters in real time, ensuring strict synchronization of experimental processes.

[0022] Machine Learning Module 11 uses a three-dimensional convolutional neural network (3D-CNN) to analyze topographic images and automatically identify interface changes. It also uses a graph neural network (GNN) to process Raman spectral data and track the dynamic changes of multiple chemical bonds. It also integrates the Transformer model to establish cross-modal associations and improve prediction accuracy.

[0023] The Visual Report Generation Module 12 uses the WebGL 2.0 interactive visualization engine, supporting 3D reconstruction, timeline control, and dynamic annotation. It automatically generates experimental reports, supports PDF / HTML export, and is compatible with VR immersive data exploration.

[0024] Example 2 Different from Example 1, in the in-situ morphology and spectral analysis system of the aluminum-plastic interface under a hydrothermal environment of Example 2 of the present invention, the hydrothermal reactor is preferably a capillary quartz tube, and the end of the capillary quartz tube is sealed by an oxygen welding gun to ensure that it has good sealing properties.

[0025] Example 3 Different from Example 2, in Example 3 of the present invention, a system for in-situ morphology and spectral analysis of aluminum-plastic interface under a hydrothermal environment is provided, a quartz tube reactor cavity is provided inside the in-situ heating platform, and resistance heating wires and semiconductor refrigeration sheets are provided around the quartz tube reactor cavity to facilitate heating.

[0026] Example 4 Different from Example 3, in Example 4 of the present invention, in an in-situ morphology and spectrum analysis system for aluminum-plastic interface under a hydrothermal environment, the camera is a CMOS camera, which is set on a tripod and can adjust the angle adaptively.

[0027] Example 5 Different from Example 4, in Example 5 of the present invention, an in-situ morphology and spectral analysis system for an aluminum-plastic interface under a hydrothermal environment, a machine learning module uses a three-dimensional convolutional neural network to analyze morphology images, automatically identify interface changes, and uses a graph neural network to process Raman spectral data, track the dynamic changes of multiple chemical bonds, and accurately identify the morphology of the image.

[0028] Example 6 The present invention provides an in-situ morphology and spectroscopy analysis method for an aluminum-plastic interface under a hydrothermal environment, which is specifically implemented according to the following steps: Step 1, placing the sample into the hydrothermal reactor 3; First, an aluminum-plastic composite or other metal-plastic composite material is cut into a size suitable for a capillary quartz tube and placed in a specially designed quartz capillary reactor. Hydrothermal reactor 3 is constructed of optical-grade quartz to ensure light transmittance on the observation surface. Deionized water is injected via a vacuum injection system to maintain a constant liquid-to-solid ratio, providing standardized initial conditions for subsequent experiments. The capillary quartz tube ports are sealed using oxygen welding.

[0029] Step 2, setting parameters for the inverted microscope, in-situ heating stage, Fourier transform infrared (ATR) spectrometer, and Raman spectrometer; During the system's initialization, due to sample stage space limitations and optical path conflicts, topography, ATR-FTIR, and Raman spectroscopy could not be performed simultaneously at the same location. Therefore, an intelligent sample stage scheduling strategy was implemented to achieve efficient switching between multimodal measurements and maintain time-correlation errors within 1%.

[0030] First, the system requires preheating and basic alignment. The in-situ heating stage 5 must be preheated to a base temperature of 50°C to minimize the impact of temperature drift on subsequent detection. Furthermore, the sample stage 4 utilizes high-precision three-dimensional motorized control (positioning accuracy ±1μm) to ensure fast and precise switching between different detection modes. Regarding optical path coordination, the microscope optical path requires preliminary calibration, and a 20× long working distance objective lens is used to ensure clarity in morphological observations. Furthermore, the ATR-FTIR detection unit's lever mechanism and the microscope objective lens utilize an alternating lift design to avoid structural interference. The Raman probe integrates a fast-switching mirror and shares part of the optical path with the microscope to improve optical component utilization and reduce switching time.

[0031] During the inspection process, the system executes the measurement tasks of each module according to a strict timing protocol. First, the sample stage moves to the microscope observation position, where a 1-second video capture (30 fps) is performed to record morphological changes. This then enters the rapid switching phase, where the ATR pressure bar rises and the sample stage translates 2mm to the Fourier transform infrared (ATR) spectrometer 8 detection position. The crystal pressure bar lowers and contacts the sample, and the ATR-FTIR spectrum is acquired, completing 32 scans (approximately 30 seconds). The sample stage then translates again to the Raman detection position, where the Raman probe extends and aligns with the sample, acquiring a spectrum within a 5-second integration time. After the entire inspection cycle is complete, the sample stage automatically returns to the morphological observation position for the next round of measurements. The switching time for the entire process is controlled within 40 seconds, enabling fast and efficient multimodal inspection.

[0032] Through precise mechanical coordination, intelligent timing control, and error compensation strategies, this system achieves efficient acquisition of multimodal data while ensuring optimal working conditions for each detection method, providing a precise and reliable experimental platform for in-depth research on the separation and reaction behavior of aluminum-plastic interfaces under hydrothermal environments.

[0033] Step 3, using an in-situ heating stage to simulate a hydrothermal environment; The hydrothermal environment simulation process utilizes a programmed control strategy. The target temperature (adjustable from 50°C to 350°C) is reached at a heating rate of 5°C / min. An environmental parameter acquisition system records key parameters such as temperature and pressure in real time at a 10Hz frequency, providing environmental background data for subsequent analysis.

[0034] Step 4, collecting raw data using an inverted microscope, a Fourier transform infrared (ATR) spectrometer, and a Raman spectrometer; Multimodal collaborative observation is implemented during the in-situ data acquisition phase. Topography observations utilize differential interference spectroscopy (DIS) mode, coupled with an autofocus system to achieve ±0.5μm focus stability. A temperature-time-topography data triplet is simultaneously constructed. Raman spectroscopy is performed at pre-set monitoring points, with spectral data quality ensured through dynamic adjustment of laser power (5-50mW) and real-time thermal radiation background subtraction. ATR-FTIR detection utilizes a diamond crystal window, maintaining a constant contact force of 20±2N via a pressure feedback system. Infrared spectra are acquired in real time from 4000-650cm⁻¹, with a temperature compensation algorithm mitigating thermal drift. A precise timing controller coordinates the acquisition sequence of the three detection modules, automatically switching between ATR and Raman detection between topography observations to ensure time correlation errors of less than 1 second between modal data. A specially developed real-time quality assessment module provides instant feedback on data credibility indicators, automatically triggering repeated acquisitions when the signal-to-noise ratio falls below a set threshold.

[0035] Step 5: Analyze the morphological and spectral data using a machine learning module; The intelligent analysis and processing module utilizes an advanced algorithm system. The image processing stage uses a U-Net network to accurately segment interface feature areas, calculate key parameters such as the debonding area ratio, and generate dynamic thermal maps to visually demonstrate morphological evolution. Spectral analysis uses Gaussian fitting to resolve overlapping peaks and establish a chemical bond strength-temperature curve, achieving a characteristic peak displacement accuracy of ±0.2 cm⁻¹.

[0036] Step 6: Use the visual reporting module to perform multimodal data integration; Interactive visualization tools are used to present experimental data and analysis results. Feature point matching algorithms are often used to achieve spatial registration of morphological and spectral data (with an error of <5 μm), constructing a unified spatiotemporal coordinate system. This allows for the establishment of a correlation matrix between morphological parameters and chemical composition, calculation of interfacial reaction kinetics, and ultimately, the generation of a physicochemical model that reveals the mechanisms of interfacial evolution.

[0037] Step 7: Use the visualization report module to complete visualization and output.

[0038] Adjust hydrothermal reaction parameters based on experimental data to optimize the aluminum-plastic separation process. The visual reporting module provides comprehensive analytical support. The dynamic display interface utilizes three-view synchronization technology, supporting timeline zooming and cross-sectional analysis. The intelligent reporting system automatically extracts key parameters and generates reports in multiple formats (PDF / HTML / JSON) that include experimental conditions, analysis results, and prediction models, meeting the needs of diverse application scenarios.

[0039] In addition, to ensure long-term stability of the system, a 2°C / min gradient temperature reduction is performed after the experiment, the optical system is calibrated regularly, and a comprehensive experimental data archiving and indexing system is established to achieve traceability and repeatability of research data.

[0040] Therefore, compared with the prior art, the present invention has the following advantages: (1) In-situ morphology and Raman characterization: The physical structure changes of the aluminum-plastic interface are observed in real time through in-situ morphology characterization technology (such as optical microscopy and electron microscopy), and the molecular structure changes are monitored using in-situ Raman characterization technology to achieve a comprehensive analysis at the physical and molecular levels.

[0041] (2) Hydrothermal environment simulation: Design a dedicated hydrothermal reaction pool to precisely control temperature, pressure, and humidity to simulate the actual hydrothermal environment and provide real conditions for aluminum-plastic separation research.

[0042] (3) Machine learning and visualization technology: Use high-performance computers to process multi-source data in parallel, establish a predictive model of interface separation and reaction behavior through machine learning algorithms (such as convolutional neural networks and support vector machines), and combine visualization technology to generate interactive reports to improve data analysis efficiency and result presentation.

[0043] (4) Efficient separation and recycling: By real-time monitoring and analysis of the dynamic changes of the aluminum-plastic interface, the hydrothermal liquefaction process parameters are optimized to achieve efficient separation and recycling of aluminum-plastic composite materials, providing technical support for resource recycling.

[0044] Application Examples The experimental principle of the in-situ morphology and spectroscopy analysis system for aluminum-plastic interface under hydrothermal environment is as follows: 1. Experimental materials and preparation.

[0045] Commercially available Tetra Pak packaging waste (a paper-plastic-aluminum composite material) was used as the experimental sample. Its composition was: outer layer polyethylene (PE, 50 μm thick) / cardboard (200 μm) / aluminum foil (7 μm) / inner layer polyethylene (50 μm). After removing the paper fibers from the sample, it was cut into approximately 1 mm x 1 mm specimens and ultrasonically cleaned in ultrapure water for 10 minutes to remove surface contaminants.

[0046] 2. System initialization configuration.

[0047] (1) Hydrothermal reactor: Use a quartz capillary with an inner diameter of 1.5 mm and a wall thickness of 0.3 mm. Calculate and confirm the pressure bearing capacity (20 MPa safety margin) according to the formula δ = (P·D) / (2S) (2) In-situ heating table: Set the coordinates of the three workstations: microscopic observation position (X=0, Y=0), ATR detection position (X=2mm, Y=0), and Raman detection position (X=4mm, Y=0) Temperature program: room temperature → 280℃ (5℃ / min) → insulation stage (3) Detection parameters: Optical microscope: 50× objective, DIC mode, acquisition rate 30 fps Raman spectroscopy: 785 nm laser, power 15 mW, integration time 10 s ATR-FTIR: resolution 4 cm⁻¹, 64 scans 3. Experimental process records (1) Temperature range 50-150℃: Morphology observation: The polyethylene layer was found to be expanding (expansion rate 0.8% / ℃) Raman spectroscopy: The intensity of the CH stretching vibration peak (2880 cm⁻¹) decreased by 12% ATR-FTIR: The characteristic peak of ester group (1740cm⁻¹) was detected (2) Temperature range 150-220℃: Morphological changes: Initial debonding occurs at the aluminum-plastic interface (debonding area ratio 18%) Chemical changes: Raman detection of an increase in the intensity of the Al-O bond (780 cm⁻¹) Synchronous detection: morphology-spectrum time correlation error 0.8 seconds (3) Critical temperature 280℃: Bumping phenomenon was observed (height suddenly increased by 120μm) H2 generation was detected (Raman characteristic peak 4155cm⁻¹) ATR shows the formation of AlOOH characteristic peak (1020cm⁻¹) 4. Data Analysis Results Based on the machine learning output, 3D-CNN identified three typical failure modes. GNN predicted the interfacial reaction activation energy Ea = 45.2 ± 2.1 kJ / mol, and the Transformer model had an accuracy rate of 92.7%. Based on the analysis results, the model is proposed: (1) Optimal separation temperature window: 265-275°C (2) Pressure control threshold: 4.2±0.3MPa (3) Optimized residence time: 8-12 minutes 5. Verification Experiment The experiment was repeated three times and showed that: Aluminum foil recycling rate increased to 98.5% (traditional method 89%) Plastic degradation efficiency increased by 40% Energy consumption is reduced by 25%.

[0048] Clearly, this method accurately captures the critical conditions for aluminum-plastic interface separation, providing reliable parameters for industrial recycling processes. The synergistic mechanism of "localized aluminum foil ablation and plastic interface penetration," discovered through in situ observations, offers new insights for subsequent material modification.

Claims

1. A system for analyzing the in-situ morphology and spectroscopy of the aluminum-plastic interface under hydrothermal conditions, characterized by: The system includes a sample rack, an in-situ heating stage is provided on the sample rack, a hydrothermal reactor for placing samples is provided in the in-situ heating stage, observation windows are provided on the upper and lower sides of the in-situ heating stage, an inverted microscope is arranged below the observation window on the lower side of the in-situ heating stage, a camera is arranged at the observation port of the inverted microscope, and a Fourier transform infrared (ATR) spectrometer and a Raman spectrometer are arranged above the observation window on the upper side of the in-situ heating stage; the camera, Fourier transform infrared (ATR) spectrometer and Raman spectrometer are respectively connected to a server, and the server is connected to a machine learning module and a visual reporting module in turn.

2. The in-situ morphology and spectroscopy analysis system for aluminum-plastic interface under hydrothermal environment according to claim 1, characterized in that: The hydrothermal reactor is a capillary quartz tube, and the end of the capillary quartz tube is sealed by an oxygen welding gun.

3. The in-situ morphology and spectroscopy analysis system for aluminum-plastic interface under hydrothermal environment according to claim 1, characterized in that: A quartz tube reactor cavity is provided inside the in-situ heating platform, and resistance heating wires and semiconductor cooling sheets are provided around the quartz tube reactor cavity.

4. The in-situ morphology and spectroscopy analysis system for aluminum-plastic interface under hydrothermal environment according to claim 1, characterized in that: The camera is arranged on a tripod.

5. The in-situ morphology and spectroscopy analysis system for aluminum-plastic interface under hydrothermal environment according to claim 1, characterized in that: The camera is a CMOS camera.

6. The in-situ morphology and spectroscopy analysis system for aluminum-plastic interface under hydrothermal environment according to claim 1, characterized in that: The machine learning module uses a three-dimensional convolutional neural network to analyze topographic images, automatically identify interface changes, and uses a graph neural network to process Raman spectral data and track the dynamic changes of multiple chemical bonds.

7. A method for analyzing the in-situ morphology and spectroscopy of the aluminum-plastic interface under a hydrothermal environment, characterized in that: include: Step 1, placing the sample into a hydrothermal reactor; Step 2: Initialize and set up the inverted microscope, in-situ heating stage, Fourier transform infrared (ATR) spectrometer, and Raman spectrometer; Step 3, using an in-situ heating stage to simulate a hydrothermal environment; Step 4, collecting raw data using an inverted microscope, a Fourier transform infrared (ATR) spectrometer, and a Raman spectrometer; Step 5: Call the machine learning module to perform joint analysis and fusion processing on the acquired multimodal data such as morphology and spectrum, and realize the visualization and output of the data based on the visualization report module.

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