Sample component analysis method, electronic device, storage medium and program product

Abstract

The embodiment of the invention discloses a sample component analysis method, electronic equipment, a storage medium and a program product, and relates to the technical field of sample component analysis. The method comprises the following steps: acquiring a target sample, determining a target test condition, and analyzing the target sample based on the target test condition to obtain a first analysis result of the target sample; based on the first analysis result, determining at least two reference samples associated with the target sample and a blank sample; measuring the reference samples and the blank samples to obtain measurement data, and determining a quantitative analysis model based on the measurement data; and in response to a component analysis instruction of a to-be-detected sample, determining target components of the to-be-detected sample based on the quantitative analysis model. According to the scheme provided by the embodiment of the invention, the components of the sample and the content of each component can be quickly and accurately determined.

Description

Technical Field

[0001] This invention relates to the field of sample composition analysis technology, and in particular to a method for analyzing sample composition, electronic equipment, storage medium, and program product. Background Technology

[0002] Sample composition analysis has been widely applied across various industries, driving their development. In the chemical industry, component analysis of raw materials and products ensures the stability of the production process and the consistency of product quality. In the food industry, component analysis ensures food safety and compliance, preventing excessive levels of harmful substances or false advertising. In drug development, component analysis is crucial for determining the purity, stability, and active ingredients of drugs, directly impacting their safety and efficacy. Furthermore, compound composition analysis plays an indispensable role in environmental monitoring, agriculture, and geological exploration.

[0003] How to quickly and accurately determine the composition of a sample and the content of each component is a key research issue in the industry. Summary of the Invention

[0004] This invention provides a method, electronic device, storage medium, and program product for analyzing sample components, so as to quickly and accurately determine the components of a sample and the content of each component.

[0005] According to one aspect of the present invention, a method for analyzing sample components is provided, the method comprising:

[0006] Obtain a target sample, determine target test conditions, and analyze the target sample based on the target test conditions to obtain a first analysis result of the target sample;

[0007] Based on the first analysis results, at least two reference samples and a blank sample are identified as being associated with the target sample;

[0008] The reference samples and the blank samples are measured to obtain measurement data, and a quantitative analysis model is determined based on the measurement data.

[0009] In response to the component analysis command of the sample to be tested, the target components of the sample to be tested are determined based on the quantitative analysis model.

[0010] In an optional implementation of this embodiment, obtaining the target sample and determining the target test conditions includes:

[0011] A target sample of a set weight is obtained using a target weighing device, a target experimental instrument is determined, and target test conditions are determined based on the target experimental instrument.

[0012] The target test conditions include at least one of the following: temperature, humidity, pressure, holding time, depressurization time, sampling time, scanning range, voltage, current, and power.

[0013] In an optional implementation of this embodiment, the step of analyzing the target sample based on the target test conditions to obtain a first analytical result of the target sample includes:

[0014] The target sample is loaded into the test area of ​​the target instrument, and a non-standard semi-quantitative analysis is performed on the target sample to obtain the composition of the target sample and the concentration of each component.

[0015] In an optional implementation of this embodiment, determining at least two reference samples and a blank sample associated with the target sample based on the first analysis result includes:

[0016] Based on the content of each element in the first analysis results, at least two concentration gradient reference samples are determined; wherein each gradient covers the actual concentration range of the target element in the target sample, and includes at least one value lower than the actual concentration and one value higher than the actual concentration;

[0017] Each of the aforementioned reference samples and blank samples was prepared based on the aforementioned concentration gradients;

[0018] The blank sample contains 0 of each element.

[0019] In an optional implementation of this embodiment, the measurement of each of the reference samples and the blank sample to obtain measurement data includes:

[0020] Each of the reference samples and the blank sample is placed into the test area of ​​the target instrument, and each of the reference samples and the blank sample is measured to obtain the radiation intensity data of each of the reference samples and the blank sample.

[0021] In an optional implementation of this embodiment, determining the quantitative analysis model based on the measurement data includes:

[0022] A calibration curve is established based on the concentration of each element and the radiation intensity data corresponding to each element concentration;

[0023] The quantitative analysis model is determined based on the calibration curve.

[0024] In an optional implementation of this embodiment, determining the target components of the sample based on the quantitative analysis model in response to the component analysis command of the sample to be tested includes:

[0025] The sample to be tested is loaded into the test area of ​​the target instrument, the sample is measured, and the measurement results are input into the quantitative analysis model to obtain the composition of the sample and the concentration of each component.

[0026] According to another aspect of the present invention, an analytical apparatus for sample composition is provided, the apparatus comprising:

[0027] An acquisition module is used to acquire a target sample, determine target testing conditions, and analyze the target sample based on the target testing conditions to obtain a first analysis result of the target sample.

[0028] The sample determination module is used to determine, based on the first analysis result, at least two reference samples and a blank sample associated with the target sample;

[0029] The quantitative analysis model determination module is used to measure each of the reference samples and the blank samples, obtain each measurement data, and determine the quantitative analysis model based on each of the measurement data;

[0030] The component analysis module is used to determine the target components of the sample in response to the component analysis command of the sample to be tested, based on the quantitative analysis model.

[0031] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0032] At least one processor; and

[0033] A memory communicatively connected to the at least one processor; wherein,

[0034] The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to perform the sample component analysis method according to any embodiment of the present invention.

[0035] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement the sample component analysis method according to any embodiment of the present invention.

[0036] According to another aspect of the present invention, a computer program product is provided, comprising a computer program that, when executed by a processor, implements the method for analyzing sample components as described in any embodiment of the present invention.

[0037] The technical solution of this invention involves acquiring a target sample, determining target testing conditions, and analyzing the target sample based on the target testing conditions to obtain a first analytical result of the target sample; based on the first analytical result, identifying at least two reference samples and a blank sample associated with the target sample; measuring each of the reference samples and the blank sample to obtain measurement data, and determining a quantitative analysis model based on each measurement data; and responding to a component analysis command for the sample to be tested, determining the target components of the sample to be tested based on the quantitative analysis model, thereby quickly and accurately determining the components of the sample and the content of each component.

[0038] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0039] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0040] Figure 1 This is a flowchart of a sample component analysis method provided in Embodiment 1 of the present invention;

[0041] Figure 2 This is a flowchart of a sample component analysis method provided in Embodiment 2 of the present invention;

[0042] Figure 3 This is a schematic diagram of the structure of a sample component analysis device provided in Embodiment 3 of the present invention;

[0043] Figure 4 This is a schematic diagram of the structure of an electronic device for implementing the sample component analysis method of the present invention. Detailed Implementation

[0044] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0045] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0046] Example 1

[0047] Figure 1 This is a flowchart of a sample component analysis method according to Embodiment 1 of the present invention. This embodiment is applicable to the analysis of the components of a sample to be tested. The method can be executed by a sample component analysis device, which can be implemented in hardware and / or software. The sample component analysis device can be configured in an electronic device such as a computer, server, or tablet computer. Figure 1 As shown, the method includes:

[0048] Step 110: Obtain the target sample, determine the target test conditions, and analyze the target sample based on the target test conditions to obtain the first analysis result of the target sample.

[0049] The target sample can be a solid or a liquid solvent, and this embodiment does not limit it; at the same time, the target sample involved in this embodiment can be a mixture of multiple samples, and this embodiment does not limit it either.

[0050] In this embodiment, the target test conditions include at least one of the following: temperature, humidity, pressure, holding time, depressurization time, sampling time, scanning range, voltage, current, and power.

[0051] Optionally, in this embodiment, obtaining the target sample and determining the target test conditions may include: obtaining a target sample of a set weight through a target weighing device, determining the target experimental instrument, and determining the target test conditions based on the target experimental instrument.

[0052] In an optional implementation of this embodiment, after obtaining the target sample, the test conditions can be further determined based on the morphology of the target sample or the laboratory conditions; in this embodiment, these are referred to as target test conditions. In one example of this embodiment, approximately 1g of sample can be weighed and placed in a PE cup in a laboratory at 25°C and 55% humidity. The hydraulic press parameters are adjusted to a target pressure of 220kN; a holding time of 5s; a pressing time of 3s; a sampling time of 6s; and a sample depth of 8s, forming a disc shape, which is then placed into a mold with a 20mm diameter window. Further, the mold can be placed in the instrument's test area, and the instrument parameters can be set and calibrated. The test condition parameters can be: target material: Rh, voltage 50kV, current 60mA, power 4kW, optical path atmosphere: vacuum, sample spin on, detector calibration, and PHA (Pulse Height Analyzer) adjusted to the range of 100-300.

[0053] Furthermore, the target sample can be analyzed based on the target test conditions to obtain the first analytical result of the target sample.

[0054] In a specific implementation, analyzing the target sample based on the target test conditions to obtain the first analysis result of the target sample may include: loading the target sample into the test area of ​​the target instrument, performing non-standard semi-quantitative analysis on the target sample, and obtaining the composition of the target sample and the concentration of each of the components.

[0055] In one optional implementation of this embodiment, a mold containing the target sample (such as a 20mm diameter PE cup) can be stably placed into a sample tray; further, the sample chamber can be closed, the vacuum pump can be started, and the vacuum can be evacuated to ≤10Pa; further, the system can be waited for to prompt, and then proceed to the next step; non-standard semi-quantitative analysis can be performed in the target software (e.g., known sample component analysis software). For example, the target sample can be analyzed by the basic parameter method to obtain the components of the target sample and the concentration of each component.

[0056] For example, the first analytical result can be the elements: Pb, Ti, Zr, Nb, Fe; with concentrations of 70.69%, 5.281%, 11.022%, 2.751%, and 0.43%, respectively.

[0057] Step 120: Based on the first analysis result, determine at least two reference samples and a blank sample associated with the target sample.

[0058] Optionally, in this embodiment, after determining that the first analysis result has been obtained, at least two reference samples and a blank sample associated with the target sample can be further identified; for example, five reference samples and one blank sample can be prepared.

[0059] In this embodiment, determining at least two reference samples and a blank sample associated with the target sample based on the first analysis result may include: determining at least two reference samples with concentration gradients based on the content of each element in the first analysis result; wherein each gradient covers the actual concentration range of the target element in the target sample, and includes at least one value lower than the actual concentration and one value higher than the actual concentration; preparing each of the reference samples and blank samples based on each concentration gradient; wherein the content of each element in the blank sample is 0.

[0060] In one optional implementation of this embodiment, after analyzing the target sample to obtain the first analytical result, at least two reference samples with concentration gradients can be determined based on the content of each element in the first analytical result. Specifically, a reference sample can be made based on principles such as matrix matching, composition similarity, concentration gradient coverage, and adjusting values ​​to avoid the same values ​​above and below.

[0061] The matrix matching principle mainly refers to the fact that the prepared reference sample and the target sample should be as consistent as possible in terms of main chemical composition and physical structure. For example, if the matrix of the reference sample and the target sample is different, such as one being rich in silica and the other being free of silica, then even if the element concentrations are the same, the measured intensities will be different, which will lead to quantitative errors.

[0062] The principle of compositional similarity mainly means that the prepared reference sample and the target sample should not only match in terms of main components, but also in terms of minor components and impurity elements. It is understandable that even if the content is very low (less than 1%), it may significantly affect the measurement results of certain elements (such as the interference of Fe on Mn).

[0063] Concentration gradient coverage mainly refers to the fact that the concentration of the element to be tested in the reference sample should form at least three gradients and completely cover the actual concentration range of the element in the sample to be tested. In this embodiment, each gradient covers the actual concentration range of the target element in the target sample, which includes at least one value lower than the actual concentration and one value higher than the actual concentration.

[0064] Adjusting values ​​to avoid simultaneous increases and decreases means that when multiple analytes are present at the same time, the concentrations of all elements should not increase or decrease simultaneously in the same standard sample, as this would prevent the decoupling of the mutual influence between the elements.

[0065] Traditional methods rely on experience or trial and error in standard sample preparation, which can easily lead to incomplete concentration range coverage or matrix mismatch. This embodiment utilizes non-standard semi-quantitative pre-analysis to quickly determine the sample matrix composition and the content range of the analyte, guiding the design of standard sample preparation schemes. Compared to previous design processes, this approach is more flexible and effectively saves cost and time.

[0066] Furthermore, reference samples can be prepared based on each gradient concentration, as well as blank samples with a content of 0 for each element.

[0067] Step 130: Measure each of the reference samples and the blank samples to obtain measurement data, and determine a quantitative analysis model based on the measurement data.

[0068] Optionally, in this embodiment, after preparing each reference sample and the blank sample, each of the reference samples and the blank sample can be further measured to obtain measurement data. Furthermore, a quantitative analysis model can be determined based on the measurement data. The quantitative analysis model can be used to perform quantitative analysis on the sample to be tested to obtain the components of the sample to be tested and the content of each component.

[0069] Optionally, measuring each of the reference samples and the blank sample to obtain measurement data may include: loading each of the reference samples and the blank sample into the test area of ​​the target instrument, measuring each of the reference samples and the blank sample, and obtaining radiation intensity data for each of the reference samples and the blank sample.

[0070] In an optional implementation of this embodiment, each of the reference samples and the blank sample can be tested under the same target test conditions as the target sample. For example, in a laboratory at 25°C and 55% humidity, approximately 1g of sample is weighed and placed in a PE cup. The hydraulic press parameters are adjusted to a target pressure of 220kN; a holding time of 5s; a pressing time of 3s; a sampling time of 6s; and a sample depth of 8s, forming a disc shape, which is then placed into a mold with a 20mm diameter window. Further, the mold can be placed in the instrument's test area, and the instrument parameters can be set and calibrated. The test conditions can be: target material: Rh; voltage: 50kV; current: 60mA; power: 4kW; optical path atmosphere: vacuum; sample spin on; detector calibration; and PHA (Pulse Height Analyzer) adjusted to the range of 100-300. Further, tests can be performed on each of the reference samples and the blank sample respectively to obtain X-ray intensity data for each of the reference samples and the blank sample.

[0071] Optionally, determining the quantitative analysis model based on the measurement data may include: establishing a calibration curve based on the concentration of each element and the radiation intensity data corresponding to the concentration of each element; and determining the quantitative analysis model based on the calibration curve.

[0072] In an optional implementation of this embodiment, after obtaining the radiation intensity data of each reference sample and the blank sample, a calibration curve can be further established based on the concentration of each element and the radiation intensity data corresponding to each element concentration. Furthermore, the calibration curve can be determined as a quantitative analysis model.

[0073] Step 140: In response to the component analysis command of the sample to be tested, determine the target components of the sample to be tested based on the quantitative analysis model.

[0074] The sample to be tested can be a sample similar to the target sample (e.g., the components and the content of each component are similar) or a sample dissimilar to the target sample (e.g., the components and the content of each component are different). This embodiment does not limit the sample to a specific type.

[0075] Optionally, in this embodiment, after receiving the instruction to perform component analysis on the sample to be tested, the target components of the sample to be tested can be directly determined based on the quantitative analysis model. This can quickly obtain the target components of the sample to be tested, which will help with the subsequent analysis and application of the sample to be tested.

[0076] The technical solution of this embodiment involves acquiring a target sample, determining target testing conditions, and analyzing the target sample based on the target testing conditions to obtain a first analytical result of the target sample; based on the first analytical result, identifying at least two reference samples and a blank sample associated with the target sample; measuring each of the reference samples and the blank sample to obtain measurement data, and determining a quantitative analysis model based on each measurement data; and responding to a component analysis command for the sample to be tested, determining the target components of the sample to be tested based on the quantitative analysis model, thereby quickly and accurately determining the components of the sample and the content of each component.

[0077] Example 2

[0078] Figure 2 This is a flowchart of a sample component analysis method according to Embodiment 2 of the present invention. This embodiment is a further refinement of the above technical solution, and the technical solution in this embodiment can be combined with various optional solutions in one or more of the above embodiments. Figure 2 As shown, the method includes:

[0079] Step 210: Obtain the target sample, determine the target test conditions, and analyze the target sample based on the target test conditions to obtain the first analysis result of the target sample.

[0080] Step 220: Based on the first analysis result, determine at least two reference samples and a blank sample associated with the target sample.

[0081] Step 230: Measure each of the reference samples and the blank samples to obtain measurement data, and determine a quantitative analysis model based on the measurement data.

[0082] Step 240: Load the sample to be tested into the test area of ​​the target instrument, measure the sample to be tested, input the measurement results into the quantitative analysis model, and obtain the composition of the sample to be tested and the concentration of each component.

[0083] Optionally, in this embodiment, after receiving the component analysis instruction for the sample to be tested, the sample to be tested can be further placed into the test area of ​​the target instrument, and then the sample to be tested can be measured to obtain the radiation intensity data associated with the sample to be tested; further, the obtained radiation intensity data associated with the sample to be tested can be input into the quantitative analysis model to output the components of the sample to be tested and the concentration of each component.

[0084] The solution in this embodiment can quickly determine the composition and concentration of each component of an unknown sample based on a quantitative analysis model, thereby improving the efficiency and accuracy of sample composition analysis.

[0085] To better understand the sample component analysis method involved in this embodiment, a specific example is used below for illustration, which mainly includes the following:

[0086] Weigh approximately 1g ± 0.001g of the sample using a balance with a strength of 0.1g and record the reading.

[0087] In a laboratory at 25°C and 55% humidity, weigh approximately 1g of sample and place it in a PE cup. Adjust the hydraulic press parameters to: target pressure 220kN; holding time 5s; depressurization time 3s; sampling time 6s; sample depth 8s, forming a cake shape, and place it into a mold with a 20mm diameter window. Next, place the mold into the test area of ​​the target instrument, and set and calibrate the instrument parameters. The test conditions can be: target material Rh, voltage 50kV, current 60mA, power 4kW, optical path atmosphere vacuum, sample spin enabled, detector calibration, and PHA adjusted between 100-300. Begin sample testing with the following parameter settings: element test range OU, peak detection sensitivity: 1, smoothing points: 11.

[0088] After the test is completed, the target software is used to perform calculations, and qualitative results and semi-quantitative analysis are obtained based on the spectrum and the corresponding characteristic X-ray light intensity.

[0089] Furthermore, weigh the corresponding standard substances using a 0.1 g / L balance and record the readings for later calibration. The names and concentrations of each standard sample are shown in Table 1.

[0090] Table 1

[0091]

[0092]

[0093] Furthermore, after weighing, the sample can be mixed thoroughly using a mortar and pestle. Following steps 2, 3, 4, and 5, the sample is prepared using the tablet compression method, and the concentration of the standard is determined. The results are shown in Table 2.

[0094] Table 2

[0095] Standard product name 0 1 2 3 4 5 6 pb 0 84.81％ 73.92％ 66.35％ 62.26％ 59.34％ 56.53％ Ti 0 1.92％ 4.19％ 5.19％ 6.61％ 6.99％ 7.13％ zr 0 2.07％ 5.55％ 9.03％ 9.15％ 10.59％ 12.27％ nb 0 1.84％ 4.19％ 5.46％ 6.80％ 7.20％ 7.58％

[0096] Furthermore, you can open the target software, select - Quantitative Analysis Methods - Create New Analysis Method - Create Your Own Analysis Method - Enter the analysis method name - analysis type - diameter - optical path atmosphere, and the basic settings are now complete.

[0097] After completing the basic settings, perform component selection (determine the components, units, and analysis type) - establish a standard gradient - determine typical components - set measurement conditions - select the maximum and minimum values ​​for testing and optimize the measurement condition setting program (adjust the target, voltage, current, filter, field of view aperture, attenuator collimator, crystal, and detector according to the peak angle and pulse height) - standard sample determination - drift correction - calibrate the standard curve. This completes the standard curve (quantitative analysis model) setting.

[0098] The test results are shown in Table 3:

[0099] Table 3

[0100] Components Analytical value / % Pb 70.69 Ti 5.281 Zr 11.022 Nb 2.715

[0101] Traditional standards are often difficult to produce, so it takes years to build a database. Furthermore, unknown samples are complex and diverse, making it difficult to completely match the standards in the database. The solution in this embodiment can better characterize unknown samples through adaptive optimization.

[0102] The fundamental parameter method is based on the Sherman equation, adding fundamental parameters related to XRF (X-ray Fluorescence Spectroscopy), including fluorescence yield, characteristic line energy and relative intensity, spectrometer geometry, X-ray absorption spectra (edge ​​transitions, edge energies, and absorption coefficients), and primary radiation spectra (X-ray tube spectra), and then using the least squares method for iteration. Through the description of the fundamental parameter method, we can understand that the initial model suffers from drawbacks such as large errors due to complex matrices and slow model convergence.

[0103] The scheme in this embodiment utilizes gradient information to optimize the iteration direction and step size, avoiding the slow convergence speed or getting trapped in local optima problems of the basic parameter method. The existence of initial values ​​for gradient samples makes the parameters closer to their true values, accelerating convergence. With the optimization of the dynamic correction mechanism in this scheme, it can better adapt to the optimization model.

[0104] Traditional methods require multiple trials to determine the concentration range of the standard; the embodiments of the present invention can significantly reduce the preparation time of the standard by using non-standard semi-quantitative pre-analysis.

[0105] In this embodiment of the invention, by introducing a blank sample, background signals can be subtracted, avoiding repeated testing caused by background fluctuations in traditional methods. Simultaneously, the blank standard sample can also serve as a true value, increasing the overall accuracy of the test. This method is low-cost and easy to operate.

[0106] In a comparative experiment of this embodiment, approximately 7.000 g of mixed flux (anhydrous lithium tetraborate and lithium metaborate mixed flux) and 0.150–0.700 g of sample were weighed using a 0.1 g balance, and the readings were recorded. In a laboratory at 25°C and 65% humidity, the flux was added to a platinum crucible (30 ml), and then 8 drops of lithium bromide (150 mg / ml) solution were added. The platinum crucible was then placed in an electric melting furnace (Yusuo DY501), with the furnace parameters set as follows: oxygen… The oxidation temperature was 700℃, the oxidation time was 0–5 min, the melting temperature was 1050–1150℃, the melting time was 5 min, and the shaking temperature was 1050–1150℃, the shaking time was 6–9 min. After the electric melting furnace reached the specified temperature and melted completely, it was poured into a mold and cooled to form a glass sample. The prepared sample was sent to X-ray fluorescence analysis, and the multi-element content was determined by selecting the appropriate empirical coefficient method. The detection results are shown in Table 4 below.

[0107] Table 4

[0108]

[0109]

[0110] In another comparative experiment of this embodiment, approximately 1g ± 0.001g of sample was weighed using a balance with a strength of 0.1g and the reading was recorded. In a laboratory with a temperature of 25°C and a humidity of 55%, approximately 1g of sample was weighed and placed in a PE cup. Adjust the hydraulic press parameters as follows: target pressure: 220 kN; holding time: 5 s; pressing time: 3 s; sampling time: 6 s; sample depth: 8 s, forming a disc shape, and place it into a mold with a 20 mm diameter window. Place the mold in the target instrument's test area, and set and calibrate the instrument parameters. The selected test conditions are: target material: Rh, voltage: 30 kV, current: 100 mA, power: 4 kW, optical atmosphere: vacuum, sample spin on, detector calibration, and PHA adjusted to the range of 100-300. Start the sample test with the following parameter settings: element test range: OU, peak detection sensitivity: 1, smoothing points: 11, test time: 10 min. After the test, perform calculations and obtain qualitative and semi-quantitative analysis results based on the spectrum and corresponding characteristic X-ray light intensity. The test results are shown in Table 5 below.

[0111] Table 5

[0112] Components result O 16.9048 Si 0.0345 Cl 0.0541 Ti 5.037 Fe 0.0347 Zr 10.0809 Nb 2.8754 Hf 0.215 W 0.0603 Pb 64.7033

[0113] Compared with the comparative experiment, the first comparative experiment had the highest cost, the longest cycle, the smallest result error, and the highest proportional error; the second comparative experiment had the lowest cost, the shortest cycle, the largest result error, and the smallest proportional error. The scheme in this embodiment has moderate cost, short cycle, small result error, and small proportional error. In summary, the scheme in this embodiment has obvious advantages.

[0114] Example 3

[0115] Figure 3 This is a schematic diagram of the structure of a sample component analysis device provided according to Embodiment 3 of the present invention. Figure 3 As shown, the device includes: an acquisition module 310, a sample determination module 320, a quantitative analysis model determination module 330, and a component analysis module 340.

[0116] The acquisition module 310 is used to acquire a target sample, determine target test conditions, and analyze the target sample based on the target test conditions to obtain a first analysis result of the target sample.

[0117] The sample determination module 320 is used to determine, based on the first analysis result, at least two reference samples and a blank sample associated with the target sample;

[0118] The quantitative analysis model determination module 330 is used to measure each of the reference samples and the blank samples, obtain each measurement data, and determine the quantitative analysis model based on each of the measurement data;

[0119] The component analysis module 340 is used to determine the target components of the sample to be tested based on the quantitative analysis model in response to the component analysis command of the sample to be tested.

[0120] In this embodiment, the scheme involves: acquiring a target sample using an acquisition module, determining target testing conditions, and analyzing the target sample based on these conditions to obtain a first analytical result; using a sample determination module, identifying at least two reference samples and a blank sample associated with the target sample based on the first analytical result; using a quantitative analysis model determination module, measuring each reference sample and the blank sample to obtain measurement data, and determining a quantitative analysis model based on the measurement data; and using a component analysis module, responding to a component analysis command from the sample to be tested, determining the target components of the sample based on the quantitative analysis model. This allows for the rapid and accurate determination of the sample's components and the content of each component.

[0121] In an optional implementation of this embodiment, the acquisition module 310 is specifically used for:

[0122] A target sample of a set weight is obtained using a target weighing device, a target experimental instrument is determined, and target test conditions are determined based on the target experimental instrument.

[0123] The target test conditions include at least one of the following: temperature, humidity, pressure, holding time, depressurization time, sampling time, scanning range, voltage, current, and power.

[0124] In an optional implementation of this embodiment, the acquisition module 310 is further specifically used for:

[0125] The target sample is loaded into the test area of ​​the target instrument, and a non-standard semi-quantitative analysis is performed on the target sample to obtain the composition of the target sample and the concentration of each component.

[0126] In an optional implementation of this embodiment, the sample determination module 320 is specifically used for

[0127] Based on the content of each element in the first analysis results, at least two concentration gradient reference samples are determined; wherein each gradient covers the actual concentration range of the target element in the target sample, and includes at least one value lower than the actual concentration and one value higher than the actual concentration;

[0128] Each of the aforementioned reference samples and blank samples was prepared based on the aforementioned concentration gradients;

[0129] The blank sample contains 0 of each element.

[0130] In an optional implementation of this embodiment, the quantitative analysis model determination module 330 is specifically used for:

[0131] Each of the reference samples and the blank sample is placed into the test area of ​​the target instrument, and each of the reference samples and the blank sample is measured to obtain the radiation intensity data of each of the reference samples and the blank sample.

[0132] In an optional implementation of this embodiment, the quantitative analysis model determination module 330 is further specifically used for:

[0133] A calibration curve is established based on the concentration of each element and the radiation intensity data corresponding to each element concentration;

[0134] The quantitative analysis model is determined based on the calibration curve.

[0135] In an optional implementation of this embodiment, the component analysis module 340 is specifically used for:

[0136] The sample to be tested is loaded into the test area of ​​the target instrument, the sample is measured, and the measurement results are input into the quantitative analysis model to obtain the composition of the sample and the concentration of each component.

[0137] The sample component analysis device provided in the embodiments of the present invention can execute the sample component analysis method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects for executing the method.

[0138] Example 4

[0139] Figure 4 A schematic diagram of an electronic device 10 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0140] like Figure 4As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 may also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0141] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0142] Processor 11 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, central processing unit (CPU), graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as a method for analyzing sample components, which may include: acquiring a target sample, determining target test conditions, and analyzing the target sample based on the target test conditions to obtain a first analytical result of the target sample;

[0143] Based on the first analysis results, at least two reference samples and a blank sample are identified as being associated with the target sample;

[0144] The reference samples and the blank samples are measured to obtain measurement data, and a quantitative analysis model is determined based on the measurement data.

[0145] In response to the component analysis command of the sample to be tested, the target components of the sample to be tested are determined based on the quantitative analysis model.

[0146] In some embodiments, the method for analyzing sample components may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or mounted on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the method for analyzing sample components described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the method for analyzing sample components by any other suitable means (e.g., by means of firmware).

[0147] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0148] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0149] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0150] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0151] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0152] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through a communication network. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0153] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0154] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

[0155] This invention also provides a computer program product, including a computer program that, when executed by a processor, implements a database detection method as provided in any embodiment of this application.

[0156] In implementing the computer program product, computer program code for performing the operations of this invention can be written in one or more programming languages ​​or a combination thereof. Programming languages ​​include object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0157] It should be noted that in the embodiments of this application, certain software, components, models and other existing solutions in the industry may be mentioned. These should be regarded as exemplary and are only intended to illustrate the feasibility of implementing the technical solution of this application. However, it does not mean that the applicant has used or necessarily used the solution.

[0158] Note that the above description is merely a preferred embodiment of the present invention and the technical principles employed. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions can be made without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments, and may include many other equivalent embodiments without departing from the concept of the present invention, the scope of which is determined by the scope of the appended claims.

Claims

1. A method for analyzing sample components, characterized in that, include: Obtain a target sample, determine target test conditions, and analyze the target sample based on the target test conditions to obtain a first analysis result of the target sample; Based on the first analysis results, at least two reference samples and a blank sample are identified as being associated with the target sample; The reference samples and the blank samples are measured to obtain measurement data, and a quantitative analysis model is determined based on the measurement data. In response to the component analysis command of the sample to be tested, the target components of the sample to be tested are determined based on the quantitative analysis model.

2. The method for analyzing sample components according to claim 1, characterized in that, The process of obtaining the target sample and determining the target test conditions includes: A target sample of a set weight is obtained using a target weighing device, a target experimental instrument is determined, and target test conditions are determined based on the target experimental instrument. The target test conditions include at least one of the following: temperature, humidity, pressure, holding time, depressurization time, sampling time, scanning range, voltage, current, and power.

3. The method for analyzing sample components according to claim 1, characterized in that, The step of analyzing the target sample based on the target test conditions to obtain a first analytical result of the target sample includes: The target sample is loaded into the test area of ​​the target instrument, and a non-standard semi-quantitative analysis is performed on the target sample to obtain the composition of the target sample and the concentration of each component.

4. The method for analyzing sample components according to claim 3, characterized in that, The step of determining at least two reference samples and a blank sample associated with the target sample based on the first analysis result includes: Based on the content of each element in the first analysis results, at least two concentration gradient reference samples are determined; wherein each gradient covers the actual concentration range of the target element in the target sample, and includes at least one value lower than the actual concentration and one value higher than the actual concentration; Each of the aforementioned reference samples and blank samples was prepared based on the aforementioned concentration gradients; The blank sample contains 0 of each element.

5. The method for analyzing sample components according to claim 1, characterized in that, The measurement of each of the reference samples and the blank sample to obtain various measurement data includes: Each of the reference samples and the blank sample is placed into the test area of ​​the target instrument, and each of the reference samples and the blank sample is measured to obtain the radiation intensity data of each of the reference samples and the blank sample.

6. The method for analyzing sample components according to claim 5, characterized in that, The determination of the quantitative analysis model based on the measurement data includes: A calibration curve is established based on the concentration of each element and the radiation intensity data corresponding to each element concentration; The quantitative analysis model is determined based on the calibration curve.

7. The method for analyzing sample components according to claim 1, characterized in that, The step of responding to a component analysis command for the sample to be tested, and determining the target components of the sample to be tested based on the quantitative analysis model, includes: The sample to be tested is loaded into the test area of ​​the target instrument, the sample is measured, and the measurement results are input into the quantitative analysis model to obtain the composition of the sample and the concentration of each component.

8. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor to enable the at least one processor to perform the analytical method for the sample components according to any one of claims 1-7.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that, when executed by a processor, implement the method for analyzing the sample components according to any one of claims 1-7.

10. A computer program product comprising a computer program that, when executed by a processor, implements a method for analyzing sample components according to any one of claims 1-7.

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