Inductively coupled plasma mass spectrometer system for intelligent data processing and report generation

Abstract

The invention relates to the technical field of instruments and meters, in particular to an inductively coupled plasma mass spectrometer system for intelligent data processing and report generation. Comprising a sample introduction unit, a plasma excitation and ionization unit, a mass analyzer and detection unit, a vacuum system unit and an intelligent data processing and report generation unit. Efficient ionization is achieved through a bipolar radio frequency switching and AI optimized reaction gas plasma source, the AI optimization module monitors in real time and dynamically adjusts parameters so that the ionization efficiency can be stabilized at 92% + / -2%, and meanwhile a reaction gas control system can optimize plasma conditions to suppress interference ions. And the mass analyzer and the detection unit realize high-precision ion separation by utilizing AI interference correction and a QMS-TOF double analyzer mode, and an interference elimination module can automatically eliminate polyatomic ion interference, so that the ionization efficiency, the analysis precision and the accuracy are improved, the interference is effectively inhibited, and the analysis capability of the system on a complex sample is enhanced.

Description

Technical Field

[0001] The present invention relates to the technical field of instrumentation, and in particular to an inductively coupled plasma mass spectrometer system for intelligent data processing and report generation. Background Art

[0002] Inductively Coupled Plasma Mass Spectrometry (ICP-MS) is a highly sensitive analytical technique used to analyze elemental composition and isotope ratios. It combines an inductively coupled plasma (ICP) as an ion source and a mass spectrometer (MS) as a detector, enabling the precise determination of trace and even trace elements in samples.

[0003] Inductively coupled plasma is a high-temperature plasma torch generated by inductive coupling of a high-frequency electromagnetic field. When the carrier gas passes through a radio frequency coil, the gas is ionized and heated to form a plasma due to the action of the radio frequency energy. This high-temperature environment is sufficient to completely evaporate, atomize and ionize the sample entering it. However, in practical applications, it is not easy to achieve efficient and stable ionization. On the one hand, the complex physical and chemical processes of the plasma make the ionization efficiency easily affected by a variety of factors, such as the properties of the sample, the carrier gas flow rate, the radio frequency power, etc., making it difficult to maintain the ionization efficiency at a high level. On the other hand, the optimization of plasma conditions also faces many challenges. The presence of interfering ions will interfere with the determination of the target element, and traditional methods are not ideal in suppressing interfering ions.

[0004] The mass spectrometer is responsible for separating and detecting the ions from the ICP according to their mass-to-charge ratio (m / z). Ions of different mass numbers have different motion trajectories in an electric field or magnetic field, thus achieving separation. By detecting the signal intensities of these ions, the concentrations of each element in the sample can be quantitatively analyzed. However, in actual operation, traditional mass spectrometers have shortcomings in ion separation accuracy, especially the lack of effective means to eliminate the interference of polyatomic ions in complex samples, which can seriously affect the accuracy of the analysis results. At the same time, the signal acquisition dynamic range is narrow, and it is difficult to achieve comprehensive and accurate analysis for some complex samples with a large concentration range. As a result, traditional mass spectrometers have poor analytical precision and accuracy when analyzing complex samples, and cannot meet the needs of modern scientific research and industrial production for high-precision analysis of complex samples.

[0005] In the existing technology, the ionization efficiency is low and cannot be stably maintained at a high level. The plasma conditions are difficult to optimize and the interference ion suppression effect is poor. The ion separation accuracy is not high. There is a lack of effective means to eliminate the interference of polyatomic ions. The signal acquisition dynamic range is narrow, which makes it difficult to meet the needs of complex sample analysis. In addition, traditional mass spectrometers have poor analytical precision and accuracy when analyzing complex samples.

[0006] Based on this, the present invention provides an inductively coupled plasma mass spectrometer system with intelligent data processing and report generation to solve the above-mentioned technical problems. Summary of the Invention

[0007] The purpose of the present invention is to provide an inductively coupled plasma mass spectrometer system with intelligent data processing and report generation. The bipolar radio frequency switching and AI-optimized reaction gas plasma source of the present invention realize efficient ionization. The AI optimization module monitors in real time and dynamically adjusts parameters to stabilize the ionization efficiency at 92%±2%. At the same time, the reaction gas control system can optimize the plasma conditions to suppress interfering ions, and the mass analyzer and detection unit use AI interference correction and QMS-TOF dual analyzer mode to achieve high-precision ion separation. The interference elimination module can automatically eliminate polyatomic ion interference, and the detection module realizes ultra-wide dynamic range signal acquisition, thereby improving the ionization efficiency, analysis precision and accuracy, effectively suppressing interference and enhancing the system's analysis capability for complex samples.

[0008] To achieve the above object, the present invention provides the following technical solutions:

[0009] The present invention provides an inductively coupled plasma mass spectrometer system with intelligent data processing and report generation, comprising a sample introduction unit, a plasma excitation and ionization unit, a mass analyzer and detection unit, a vacuum system unit, and an intelligent data processing and report generation unit, wherein:

[0010] The sample introduction unit is responsible for converting liquid or solid samples into a form suitable for ICP-MS analysis;

[0011] The plasma excitation and ionization unit is used to achieve efficient ionization through bipolar radio frequency switching and AI-optimized reactive gas plasma source;

[0012] The mass analyzer and detection unit is used to achieve high-precision ion separation through AI interference correction and QMS-TOF dual analyzer mode;

[0013] The vacuum system unit is used to maintain a high vacuum environment by using intelligent control of the turbomolecular pump and remote monitoring of the Internet of Things;

[0014] The intelligent data processing and report generation unit is used for automatic data processing, result calculation and report generation.

[0015] The sample introduction unit includes a sample pretreatment module, an atomization module, and a transmission module, wherein:

[0016] The sample pretreatment module is used to dilute, filter, and digest liquid samples, and to crush, grind, and dissolve solid samples to convert them into liquid or gaseous forms;

[0017] The atomization module is used to convert the liquid sample into tiny aerosol particles using a nebulizer;

[0018] The transmission module is used to smoothly and efficiently transmit the generated aerosol or gaseous sample to the plasma excitation and ionization unit.

[0019] The plasma excitation and ionization unit includes a radio frequency power supply module, a reaction gas control system, and an AI optimization module, wherein:

[0020] The radio frequency power supply module is used to provide radio frequency energy with bipolar switching capability;

[0021] The reaction gas control system is used to control the flow rate of the reaction gases helium and hydrogen online to optimize the plasma conditions and suppress interfering ions;

[0022] The AI optimization module is used to monitor the plasma state in real time through artificial intelligence algorithms and automatically adjust parameters to achieve optimal ionization efficiency.

[0023] The AI optimization module is used to monitor the plasma state in real time through artificial intelligence algorithms and automatically adjust parameters to achieve optimal ionization efficiency. The specific operations are as follows:

[0024] A1: Real-time acquisition of plasma emission spectrum characteristic peak intensity, impedance phase angle and ion current intensity;

[0025] A2: Convert the original data into a multidimensional feature vector containing the electron temperature gradient and matrix effect index;

[0026] A3: Based on a pre-trained deep reinforcement learning model, it outputs RF power correction and reaction gas flow adjustment coefficients;

[0027] A4: Perform parameter adjustment with a delay of 50-200ms to stabilize the ionization efficiency at 92% ± 2%.

[0028] A3 uses a pre-trained deep reinforcement learning model to output the RF power correction coefficient ΔP RF and reaction gas flow adjustment coefficient ΔF gas , the specific formula is as follows:

[0029] The model is trained based on time series data and the reward function R is defined t for:

[0030]

[0031] Where, represents the ionization efficiency at time t; is the benchmark ionization efficiency; represents the detection intensity of the i-th element at time t; is the ideal detection intensity; w1, w2 are weight factors;

[0032] The output action space is: That is, the fine adjustment of the radio frequency power and the flow rate of helium and hydrogen;

[0033] The model uses the gradient descent method to update the parameter θ, and the loss function is defined as:

[0034]

[0035] Where Q is the target Q network; γ is the discount factor; D is the experience replay buffer; r t represents the immediate reward at time t; s t ,a t ,r t ,s t+1 is a four-tuple representing the state, action, reward, and next state sampled from the experience replay buffer D.

[0036] The mass analyzer and detection unit includes an analyzer module, an interference elimination module, and a detection module, wherein:

[0037] The analyzer module is used to provide on-demand switching of rapid screening and high-resolution accurate mass through QMS-TOF dual mode;

[0038] The interference elimination module is used for the collision reaction cell combined with the AI prediction model to automatically eliminate polyatomic ion interference;

[0039] The detection module is used for dual-channel detector with high-precision TDC to achieve 1×10 8 Dynamic range signal acquisition.

[0040] The collision reaction cell in the interference elimination module combines with the AI prediction model to automatically eliminate polyatomic ion interference. The specific operations are as follows:

[0041] B1: Real-time monitoring of the intensity ratio of characteristic peaks of polyatomic ions in the mass spectrum;

[0042] B2: Based on the pre-trained machine learning model, output the kinetic energy discrimination voltage and reaction gas mixing ratio of the collision reaction cell;

[0043] B3: Send the predicted parameters to the collision reaction pool actuator within <2ms;

[0044] B4: Confirm by secondary mass analysis that the interfering ion intensity is reduced to below the threshold.

[0045] The specific formulas for the kinetic energy discrimination voltage and the reaction gas mixing ratio in B2 are as follows:

[0046] The kinetic energy discrimination voltage V output by the model dis The calculation is as follows:

[0047] V dis =f1(I(m / z,t),N(t),P gas ,T cell )

[0048] Where I(m / z,t) is the signal intensity of the ion with mass-to-charge ratio m / z at time point t; N(t) is the background noise level; P gas is the pressure of the reaction gas; T cell is the temperature of the collision reaction cell; f1 is a function;

[0049] The reaction gas mixture ratio R output by the model mix The calculation is as follows:

[0050] R mix =f2(I(m / z,t),N(t),P gas ,T cell )

[0051] Wherein, the meanings of the variables are as above; f2 is a function.

[0052] The vacuum system unit includes a turbomolecular pump module, an intelligent monitoring module, and a remote operation and maintenance module, wherein:

[0053] The turbomolecular pump module is used to drive gas molecules toward the pump outlet through high-speed rotating turbine blades to achieve efficient gas extraction to maintain the high vacuum environment required for mass spectrometry analysis;

[0054] The intelligent monitoring module is used to monitor the pump status in real time through multiple sensors and reduce the failure rate using predictive maintenance algorithms;

[0055] The remote operation and maintenance module is used to transmit data to the cloud through the Internet of Things gateway, supporting engineers' remote diagnosis and parameter optimization.

[0056] The intelligent data processing and report generation unit includes a data acquisition module, a data processing module, a report generation module, a database management module, and a human-computer interaction module, wherein:

[0057] The data acquisition module is responsible for collecting raw data from each detector of the mass spectrometer, converting these data into digital signals, and transmitting them to the data processing module;

[0058] The data processing module is used to process the collected raw data using various data processing algorithms and models;

[0059] The report generation module is used to organize and format the analysis results obtained by the data processing module according to the report template and format requirements set by the user to generate a detailed analysis report;

[0060] The database management module is used to store and manage raw data, processed data, analysis reports, and various parameters and configuration information of the system;

[0061] The human-computer interaction module is used to provide users with an intuitive and friendly operation interface, through which users can input analysis tasks, set parameters, and view data and reports.

[0062] Compared with the prior art, the present invention has the following beneficial effects:

[0063] 1. The present invention achieves efficient ionization through bipolar RF switching and AI-optimized reactive gas plasma source. The AI optimization module monitors in real time and dynamically adjusts parameters to stabilize the ionization efficiency at 92%±2%. At the same time, the reactive gas control system can optimize plasma conditions to suppress interfering ions, and the mass analyzer and detection unit use AI interference correction and QMS-TOF dual analyzer mode to achieve high-precision ion separation. The interference elimination module can automatically eliminate polyatomic ion interference, and the detection module realizes ultra-wide dynamic range signal acquisition, thereby improving the ionization efficiency, analysis precision and accuracy, effectively suppressing interference and enhancing the system's analysis capability for complex samples.

[0064] 2. The present invention significantly improves analysis efficiency, data accuracy and user convenience through the full automation and intelligence of mass spectrometry data processing and report output, effectively reducing manual errors and time costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] Figure 1 Overall system diagram of the inductively coupled plasma mass spectrometer system for intelligent data processing and report generation in the present invention.

[0066] Figure 2 Interference elimination flow chart for the inductively coupled plasma mass spectrometer system for intelligent data processing and report generation according to the present invention.

[0067] Description of Figure Numbers:

[0068] 100. Sample introduction unit; 101. Sample pretreatment module; 102. Atomization module; 103. Transmission module; 200. Plasma excitation and ionization unit; 201. RF power supply module; 202. Reaction gas control system; 203. AI optimization module; 300. Mass analyzer and detection unit; 301. Analyzer module; 302. Interference elimination module; 303. Detection module; 400. Vacuum system unit; 401. Turbomolecular pump module; 402. Intelligent monitoring module; 403. Remote operation and maintenance module; 500. Intelligent data processing and report generation unit; 501. Data acquisition module; 502. Data processing module; 503. Report generation module; 504. Database management module; 505. Human-computer interaction module. DETAILED DESCRIPTION

[0069] The following will be combined with the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0070] Example:

[0071] like Figure 1-Figure 2 As shown, this embodiment provides an inductively coupled plasma mass spectrometer system with intelligent data processing and report generation, including a sample introduction unit 100, a plasma excitation and ionization unit 200, a mass analyzer and detection unit 300, a vacuum system unit 400, and an intelligent data processing and report generation unit 500, wherein: the sample introduction unit 100 is responsible for converting liquid or solid samples into a form suitable for ICP-MS analysis; the plasma excitation and ionization unit 200 is used to achieve efficient ionization through bipolar radio frequency switching and AI-optimized reaction gas plasma source; the mass analyzer and detection unit 300 is used to achieve high-precision ion separation through AI interference correction and QMS-TOF dual analyzer mode; the vacuum system unit 400 is used to maintain a high vacuum environment using intelligent control of the turbomolecular pump and Internet of Things remote monitoring; the intelligent data processing and report generation unit 500 is used for automated data processing, result calculation and report generation.

[0072] In this embodiment, it should be noted that: after the sample introduction unit 100 converts the sample into an analyzable form, the plasma excitation and ionization unit 200 realizes efficient ionization, and the mass analyzer and detection unit 300 completes high-precision ion separation and detection. The vacuum system unit 400 maintains the optimal analysis environment throughout the process, and finally the intelligent data processing and report generation unit 500 automatically completes data analysis and report output.

[0073] In the present invention, the sample introduction unit 100 includes a sample pretreatment module 101, an atomization module 102, and a transmission module 103, wherein: the sample pretreatment module 101 is used to dilute, filter, and digest liquid samples, and to crush, grind, and dissolve solid samples to convert solid samples into liquid or gaseous form; the atomization module 102 is used to use a nebulizer to convert liquid samples into tiny aerosol particles; and the transmission module 103 is used to smoothly and efficiently transmit the generated aerosol or gaseous samples to the plasma excitation and ionization unit 200.

[0074] In this embodiment, it should be noted that: the sample pretreatment module 101 completes the physical and chemical treatment of the sample, converts the liquid sample into an aerosol or maintains the gaseous sample form through the atomization module 102, and finally the transmission module 103 stably transports the processed sample to the plasma excitation and ionization unit 200.

[0075] In addition, it is important to note that the liquid sample processing process utilizes a gradient dilution technique with an adjustable dilution factor of 1-10,000x, equipped with a 0.22μm pore size inline filter, and a microwave digestion program supporting a 5-step temperature gradient from room temperature to 210°C. For solid sample processing, an integrated high-energy ball mill with an adjustable speed of 100-1500 rpm and a closed acid hydrolysis system supports a variety of digestion systems, including HNO3, HF, and H2O2. A concentric pneumatic nebulizer is used, consisting of a spray chamber, a nebulizer gas inlet, a sample solution inlet, and a droplet outlet. The nebulizer gas, typically argon, enters the nebulizer gas inlet at a high speed of 1-10 L / min, creating a negative pressure within the nebulizer. The sample solution is drawn into the sample solution inlet. The high-speed airflow breaks the liquid sample into tiny droplets with a diameter of 1-10μm. These droplets then enter the spray chamber, where a collision ball or flow disturbance device further breaks up larger droplets and achieves a more uniform aerosol distribution.

[0076] In the present invention, the plasma excitation and ionization unit 200 includes a radio frequency power supply module 201, a reaction gas control system 202, and an AI optimization module 203, wherein: the radio frequency power supply module 201 is used to provide radio frequency energy with bipolar switching capability; the reaction gas control system 202 is used to control the flow of helium and hydrogen reaction gases online to optimize plasma conditions and suppress interfering ions; the AI optimization module 203 is used to monitor the plasma state in real time through an artificial intelligence algorithm, and automatically adjust the parameters to achieve optimal ionization efficiency. The specific operations are as follows: A1: Real-time acquisition of the characteristic peak intensity, impedance phase angle and ion flow intensity of the plasma emission spectrum; A2: Converting the raw data into a multidimensional feature vector containing the electron temperature gradient and the matrix effect index; A3: Based on the pre-trained deep reinforcement learning model, outputting the radio frequency power correction and reaction gas flow adjustment coefficient; The specific formula is as follows: The model is trained based on time series data, and the reward function R is defined. t for:

[0077]

[0078] Where, represents the ionization efficiency at time t; is the benchmark ionization efficiency; represents the detection intensity of the i-th element at time t; is the ideal detection strength; w1, w2 are weight factors; the output action space is: That is, the fine-tuning of the RF power and the flow rates of helium and hydrogen. The model uses the gradient descent method to update the parameter θ, and the loss function is defined as:

[0079]

[0080] Where Q is the target Q network; γ is the discount factor; D is the experience replay buffer; r t represents the immediate reward at time t; s t ,a t ,r t ,s t+1 is a 4-tuple representing the state, action, reward, and next state sampled from the experience replay buffer D. A4: Perform parameter tuning with a delay of 50-200ms to stabilize the ionization efficiency at 92% ± 2%.

[0081] In this embodiment, it should be noted that: the RF power supply module 201 provides ionization energy, the reaction gas control system 202 accurately controls the plasma environment, and the AI optimization module 203 collects plasma state data in real time and dynamically optimizes the RF power and gas flow parameters based on the deep reinforcement learning model.

[0082] In addition, it should be noted that mass flow controllers are used to achieve high-precision control of gas flow. The flow adjustment ranges of helium and hydrogen are 0-10 mL / min and 0-5 mL / min, respectively, and the control accuracy can reach ±1% of the set value.

[0083] In the present invention, the mass analyzer and detection unit 300 includes an analyzer module 301, an interference elimination module 302, and a detection module 303, wherein: the analyzer module 301 is used to provide on-demand switching of rapid screening and high-resolution accurate mass numbers through the QMS-TOF dual mode; the interference elimination module 302 is used to automatically eliminate polyatomic ion interference by combining the collision reaction cell with the AI prediction model; the specific operations are as follows: B1: real-time monitoring of the polyatomic ion characteristic peak intensity ratio in the mass spectrum; B2: based on the pre-trained machine learning model, output the kinetic energy discrimination voltage and reaction gas mixing ratio of the collision reaction cell; the specific formula is as follows: the kinetic energy discrimination voltage V output by the model dis The calculation is as follows:

[0084] V dis =f1(I(m / z,t),N(t),P gas ,T cell )

[0085] Where I(m / z,t) is the signal intensity of the ion with mass-to-charge ratio m / z at time point t; N(t) is the background noise level; P gas is the pressure of the reaction gas; T cell is the temperature of the collision reaction cell; f1 is a function; the reaction gas mixing ratio R output by the model mix The calculation is as follows:

[0086] R mix =f2(I(m / z,t),N(t),P gas ,T cell )

[0087] Where, the meanings of the variables are as above; f2 is a function. B3: Send the predicted parameters to the collision reaction cell actuator within <2ms; B4: Confirm that the interfering ion intensity is reduced to below the threshold through secondary mass analysis. The detection module 303 uses a dual-channel detector with a high-precision TDC to achieve 1×10 8 Dynamic range signal acquisition.

[0088] In this embodiment, it should be noted that: the analyzer module 301 realizes flexible switching of the QMS-TOF dual mode, the interference elimination module 302 calculates and issues the optimal collision reaction cell parameters in real time based on the AI prediction model to eliminate polyatomic ion interference, and the detection module 303 uses dual-channel detection technology to achieve 1×10 8 Ultra-wide dynamic range signal acquisition.

[0089] It should be noted that the analyzer module 301 consists of a quadrupole mass spectrometer assembly, a time-of-flight mass spectrometer assembly, and a mode switching control circuit. The quadrupoles of the quadrupole mass spectrometer assembly are made of high-purity stainless steel, with an electrode length of 10-20 cm. High-precision power supplies provide stable DC and RF voltages, with voltage adjustment ranges of 0-1000 V and 0-2000 V, respectively, enabling effective screening of ions with a mass-to-charge ratio range of 5-1000 u. The time-of-flight mass spectrometer assembly includes an ion source, an accelerating field, a field-free flight tube, and a detector. The flight tube is 1-2 m long, and the accelerating field strength is adjustable between 1000 and 5000 V, enabling efficient ion acceleration and separation. The mode switching control circuit utilizes field-programmable gate array technology, enabling millisecond switching between QMS and TOF modes. It also optimizes the ion transport path during the switching process, ensuring efficient ion transmission and accurate analysis in different modes. The dual-channel detector consists of a high-sensitivity low-gain channel and a wide-dynamic-range high-gain channel. The low-gain channel uses a microchannel plate detector, which is suitable for detecting weak ion signals produced by trace elements. Its gain factor is 10 6 -10 8 , which can amplify single ion signals to a detectable level. The high-gain channel uses a Faraday cup detector, which is suitable for detecting strong ion signals generated by high-concentration elements and can withstand up to 10 -6 The high-precision TDC uses field programmable gate array technology and high-speed time measurement circuits with a time resolution of up to 100ps. It can accurately record the time when ions arrive at the detector, achieving high-precision acquisition and analysis of ion signals.

[0090] In the present invention, the vacuum system unit 400 includes a turbomolecular pump module 401, an intelligent monitoring module 402, and a remote operation and maintenance module 403, wherein: the turbomolecular pump module 401 is used to drive gas molecules to the pump outlet through high-speed rotating turbine blades to achieve efficient pumping to maintain the high vacuum environment required for mass spectrometry analysis; the intelligent monitoring module 402 is used to monitor the pump body status in real time through multiple sensors and use predictive maintenance algorithms to reduce the failure rate; the remote operation and maintenance module 403 is used to transmit data to the cloud through the Internet of Things gateway to support engineers' remote diagnosis and parameter optimization.

[0091] In this embodiment, it should be noted that: the turbomolecular pump module 401 establishes and maintains a high vacuum environment, the intelligent monitoring module 402 collects pump body operating status data in real time and implements predictive maintenance, and the remote operation and maintenance module 403 realizes cloud-based monitoring and remote control of equipment status.

[0092] In addition, it should be noted that the turbine blades adopt a multi-stage structure design, and the blades of each stage are arranged at a specific angle and spacing. When the blades rotate at high speed, the speed can reach 20,000-60,000 rpm, and they collide with the gas molecules many times, so that the gas molecules gain directional momentum and move toward the pump outlet step by step. Finally, they are discharged from the pump body, forming a high vacuum environment inside the mass spectrometer, and the vacuum degree can reach 10 -6 -10 -10 Pa. The multi-sensor includes temperature sensor, vibration sensor, speed sensor and vacuum sensor.

[0093] In the present invention, the intelligent data processing and report generation unit 500 includes a data acquisition module 501, a data processing module 502, a report generation module 503, a database management module 504, and a human-computer interaction module 505, wherein: the data acquisition module 501 is responsible for collecting raw data from various detectors of the mass spectrometer, converting these data into digital signals, and transmitting them to the data processing module 502; the data processing module 502 is used to use various data processing algorithms and models to process the collected raw data; the report generation module 503 is used to organize and format the analysis results obtained by the data processing module 502 according to the report template and format requirements set by the user, and generate a detailed analysis report; the database management module 504 is used to store and manage raw data, processed data, analysis reports, and various parameters and configuration information of the system; the human-computer interaction module 505 is used to provide users with an intuitive and friendly operation interface, through which users can input analysis tasks, set parameters, view data and reports.

[0094] In this embodiment, it should be noted that: the data acquisition module 501 acquires the original mass spectrometry data in real time, the data processing module 502 performs intelligent algorithm analysis and quality optimization, the report generation module 503 automatically generates a standardized analysis report, the database management module 504 realizes the storage and management of full-process data, and the human-computer interaction module 505 provides a visual operation interface.

[0095] In addition, it should be noted that the data processing module 502 processes the collected raw data, such as baseline correction, peak identification, integration, background subtraction, and interference correction, to improve data quality and accuracy. The data acquisition module 501 collects raw data including ion signal intensity, flight time, mass-to-charge ratio, and other information.

[0096] Throughout this specification, references to terms such as "one embodiment," "example," or "specific example" indicate that the specific features, structures, materials, or characteristics described in conjunction with that embodiment or example are included in at least one embodiment or example of the present invention. In this specification, schematic representations of these terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

[0097] The preferred embodiments of the present invention disclosed above are intended only to help illustrate the present invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the present invention to the specific embodiments described. Obviously, many modifications and variations are possible based on the content of this specification. These embodiments are selected and described in detail in this specification to better explain the principles and practical applications of the present invention, thereby enabling those skilled in the art to better understand and utilize the present invention. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. An inductively coupled plasma mass spectrometer system with intelligent data processing and report generation, characterized in that: The system comprises a sample introduction unit (100), a plasma excitation and ionization unit (200), a mass analyzer and detection unit (300), a vacuum system unit (400), and an intelligent data processing and report generation unit (500), wherein: The sample introduction unit (100) is responsible for converting liquid or solid samples into a form suitable for ICP-MS analysis; The plasma excitation and ionization unit (200) is used to achieve efficient ionization through bipolar radio frequency switching and AI-optimized reactive gas plasma source; The mass analyzer and detection unit (300) is used to achieve high-precision ion separation through AI interference correction and QMS-TOF dual analyzer mode; The vacuum system unit (400) is used to maintain a high vacuum environment by using an intelligently controlled turbomolecular pump and remote monitoring via the Internet of Things; The intelligent data processing and report generation unit (500) is used for automated data processing, result calculation and report generation.

2. The intelligent data processing and report generation inductively coupled plasma mass spectrometer system according to claim 1, characterized in that: The sample introduction unit (100) comprises a sample pre-processing module (101), an atomization module (102), and a transmission module (103), wherein: The sample pre-processing module (101) is used to dilute, filter and digest liquid samples, crush, grind and dissolve solid samples, and convert solid samples into liquid or gaseous forms; The atomization module (102) is used to convert the liquid sample into tiny aerosol particles using a nebulizer; The transmission module (103) is used to smoothly and efficiently transmit the generated aerosol or gaseous sample to the plasma excitation and ionization unit (200).

3. The intelligent data processing and report generation inductively coupled plasma mass spectrometer system according to claim 1, characterized in that: The plasma excitation and ionization unit (200) comprises a radio frequency power supply module (201), a reaction gas control system (202), and an AI optimization module (203), wherein: The radio frequency power supply module (201) is used to provide radio frequency energy with bipolar switching capability; The reaction gas control system (202) is used to control the flow rate of the reaction gases of helium and hydrogen online to optimize the plasma conditions and suppress interfering ions; The AI optimization module (203) is used to monitor the plasma state in real time through an artificial intelligence algorithm and automatically adjust parameters to achieve optimal ionization efficiency.

4. The intelligent data processing and report generation inductively coupled plasma mass spectrometer system according to claim 3, characterized in that: The AI optimization module (203) is used to monitor the plasma state in real time through an artificial intelligence algorithm and automatically adjust parameters to achieve optimal ionization efficiency. The specific operations are as follows: A1: Real-time acquisition of plasma emission spectrum characteristic peak intensity, impedance phase angle and ion current intensity; A2: Convert the original data into a multidimensional feature vector containing the electron temperature gradient and matrix effect index; A3: Based on a pre-trained deep reinforcement learning model, it outputs RF power correction and reaction gas flow adjustment coefficients; A4: Perform parameter adjustment with a delay of 50-200ms to stabilize the ionization efficiency at 92% ± 2%.

5. The intelligent data processing and report generation inductively coupled plasma mass spectrometer system according to claim 4, characterized in that: A3 uses a pre-trained deep reinforcement learning model to output the RF power correction coefficient ΔP RF and reaction gas flow adjustment coefficient ΔF gas , the specific formula is as follows: The model is trained based on time series data and the reward function R is defined t for: Where, represents the ionization efficiency at time t; is the benchmark ionization efficiency; represents the detection intensity of the i-th element at time t; is the ideal detection intensity; w1, w2 are weight factors; The output action space is: That is, the fine adjustment of the radio frequency power and the flow rate of helium and hydrogen; The model uses the gradient descent method to update the parameter θ, and the loss function is defined as: Where Q is the target Q network; γ is the discount factor; D is the experience replay buffer; r t represents the immediate reward at time t; s t ,a t ,r t ,s t+1 is a four-tuple representing the state, action, reward, and next state sampled from the experience replay buffer D.

6. The intelligent data processing and report generation inductively coupled plasma mass spectrometer system according to claim 1, characterized in that: The mass analyzer and detection unit (300) comprises an analyzer module (301), an interference elimination module (302), and a detection module (303), wherein: The analyzer module (301) is used to provide on-demand switching of rapid screening and high-resolution accurate mass number through QMS-TOF dual mode; The interference elimination module (302) is used to automatically eliminate polyatomic ion interference by combining the collision reaction cell with the AI prediction model; The detection module (303) is used for a dual-channel detector in conjunction with a high-precision TDC to achieve 1×10 8 Dynamic range signal acquisition.

7. The intelligent data processing and report generation inductively coupled plasma mass spectrometer system according to claim 6, characterized in that: The collision reaction cell in the interference elimination module (302) is combined with the AI prediction model to automatically eliminate polyatomic ion interference. The specific operation is as follows: B1: Real-time monitoring of the intensity ratio of characteristic peaks of polyatomic ions in the mass spectrum; B2: Based on the pre-trained machine learning model, output the kinetic energy discrimination voltage and reaction gas mixing ratio of the collision reaction cell; B3: Send the predicted parameters to the collision reaction pool actuator within <2ms; B4: Confirm by secondary mass analysis that the interfering ion intensity is reduced to below the threshold.

8. The intelligent data processing and report generation inductively coupled plasma mass spectrometer system according to claim 7, characterized in that: The specific formulas for the kinetic energy discrimination voltage and the reaction gas mixing ratio in B2 are as follows: The kinetic energy discrimination voltage V output by the model dis The calculation is as follows: V dis =f1(I(m / z,t),N(t),P gas ,T cell ) Where I(m / z,t) is the signal intensity of the ion with mass-to-charge ratio m / z at time point t; N(t) is the background noise level; P gas is the pressure of the reaction gas; T cell is the temperature of the collision reaction cell; f1 is a function; The reaction gas mixture ratio R output by the model mix The calculation is as follows: R mix =f2(I(m / z,t),N(t),P gas ,T cell ) Wherein, the meanings of the variables are as above; f2 is a function.

9. The intelligent data processing and report generation inductively coupled plasma mass spectrometer system according to claim 1, characterized in that: The vacuum system unit (400) includes a turbomolecular pump module (401), an intelligent monitoring module (402), and a remote operation and maintenance module (403), wherein: The turbomolecular pump module (401) is used to drive gas molecules toward the pump outlet through high-speed rotating turbine blades, thereby achieving efficient gas extraction to maintain the high vacuum environment required for mass spectrometry analysis; The intelligent monitoring module (402) is used to monitor the status of the pump body in real time through multiple sensors and reduce the failure rate using a predictive maintenance algorithm; The remote operation and maintenance module (403) is used to transmit data to the cloud via the Internet of Things gateway, supporting engineers in remote diagnosis and parameter optimization.

10. The intelligent data processing and report generation inductively coupled plasma mass spectrometer system according to claim 1, characterized in that: The intelligent data processing and report generation unit (500) includes a data acquisition module (501), a data processing module (502), a report generation module (503), a database management module (504), and a human-computer interaction module (505), wherein: The data acquisition module (501) is responsible for collecting raw data from various detectors of the mass spectrometer, converting the data into digital signals, and transmitting the digital signals to the data processing module (502); The data processing module (502) is used to process the collected raw data using various data processing algorithms and models; The report generation module (503) is used to organize and format the analysis results obtained by the data processing module (502) according to the report template and format requirements set by the user, and generate a detailed analysis report; The database management module (504) is used to store and manage original data, processed data, analysis reports, and various parameters and configuration information of the system; The human-computer interaction module (505) is used to provide users with an intuitive and friendly operation interface, through which users can input analysis tasks, set parameters, and view data and reports.

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