CN117629985A - Alloy impurity phase quantitative detection method - Google Patents
Alloy impurity phase quantitative detection method Download PDFInfo
- Publication number
- CN117629985A CN117629985A CN202311647222.8A CN202311647222A CN117629985A CN 117629985 A CN117629985 A CN 117629985A CN 202311647222 A CN202311647222 A CN 202311647222A CN 117629985 A CN117629985 A CN 117629985A
- Authority
- CN
- China
- Prior art keywords
- alloy
- concentration
- standard curve
- impurity
- calculating
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 239000012535 impurity Substances 0.000 title claims abstract description 51
- 229910045601 alloy Inorganic materials 0.000 title claims abstract description 27
- 239000000956 alloy Substances 0.000 title claims abstract description 27
- 238000001514 detection method Methods 0.000 title claims abstract description 13
- 238000000034 method Methods 0.000 claims abstract description 44
- 238000004364 calculation method Methods 0.000 claims abstract description 21
- 238000012545 processing Methods 0.000 claims abstract description 16
- 238000004422 calculation algorithm Methods 0.000 claims abstract description 13
- 238000011156 evaluation Methods 0.000 claims abstract description 13
- 230000035945 sensitivity Effects 0.000 claims abstract description 13
- 239000000243 solution Substances 0.000 claims abstract description 7
- 238000005259 measurement Methods 0.000 claims description 25
- VEXZGXHMUGYJMC-UHFFFAOYSA-N Hydrochloric acid Chemical compound Cl VEXZGXHMUGYJMC-UHFFFAOYSA-N 0.000 claims description 20
- 238000005554 pickling Methods 0.000 claims description 15
- 239000003153 chemical reaction reagent Substances 0.000 claims description 14
- 238000002835 absorbance Methods 0.000 claims description 12
- GRYLNZFGIOXLOG-UHFFFAOYSA-N Nitric acid Chemical compound O[N+]([O-])=O GRYLNZFGIOXLOG-UHFFFAOYSA-N 0.000 claims description 10
- 229910017604 nitric acid Inorganic materials 0.000 claims description 10
- 239000003795 chemical substances by application Substances 0.000 claims description 5
- 239000011259 mixed solution Substances 0.000 claims description 4
- 238000010438 heat treatment Methods 0.000 claims description 3
- PXHVJJICTQNCMI-UHFFFAOYSA-N Nickel Chemical compound [Ni] PXHVJJICTQNCMI-UHFFFAOYSA-N 0.000 abstract description 16
- RYGMFSIKBFXOCR-UHFFFAOYSA-N Copper Chemical compound [Cu] RYGMFSIKBFXOCR-UHFFFAOYSA-N 0.000 abstract description 11
- 229910052802 copper Inorganic materials 0.000 abstract description 11
- 239000010949 copper Substances 0.000 abstract description 11
- 238000004458 analytical method Methods 0.000 abstract description 10
- HCHKCACWOHOZIP-UHFFFAOYSA-N Zinc Chemical compound [Zn] HCHKCACWOHOZIP-UHFFFAOYSA-N 0.000 abstract description 8
- 229910052759 nickel Inorganic materials 0.000 abstract description 8
- 229910052725 zinc Inorganic materials 0.000 abstract description 8
- 239000011701 zinc Substances 0.000 abstract description 8
- 239000002253 acid Substances 0.000 abstract description 6
- 238000004090 dissolution Methods 0.000 abstract description 6
- 238000004401 flow injection analysis Methods 0.000 abstract description 6
- 238000005406 washing Methods 0.000 abstract description 6
- 238000005375 photometry Methods 0.000 abstract description 5
- 229910000838 Al alloy Inorganic materials 0.000 description 9
- 238000002360 preparation method Methods 0.000 description 6
- 238000002474 experimental method Methods 0.000 description 5
- 239000002245 particle Substances 0.000 description 5
- 238000011161 development Methods 0.000 description 4
- 239000002904 solvent Substances 0.000 description 4
- 238000007619 statistical method Methods 0.000 description 4
- JPVYNHNXODAKFH-UHFFFAOYSA-N Cu2+ Chemical compound [Cu+2] JPVYNHNXODAKFH-UHFFFAOYSA-N 0.000 description 3
- 238000007796 conventional method Methods 0.000 description 3
- 229910001431 copper ion Inorganic materials 0.000 description 3
- 239000003344 environmental pollutant Substances 0.000 description 3
- 239000000203 mixture Substances 0.000 description 3
- 231100000719 pollutant Toxicity 0.000 description 3
- 238000012544 monitoring process Methods 0.000 description 2
- 238000011481 absorbance measurement Methods 0.000 description 1
- 238000001479 atomic absorption spectroscopy Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000011109 contamination Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000002798 spectrophotometry method Methods 0.000 description 1
- 238000004611 spectroscopical analysis Methods 0.000 description 1
Abstract
The invention discloses a quantitative detection method for alloy impurity phases, which comprises grinding, acid washing and dissolution, and application of photometry combined with flow injection analysis, so that quick and high-flux determination of impurities such as copper, zinc, nickel and the like in an alloy is realized. The method has the advantages that multiple steps are completed through a single instrument, the use cost and the operation complexity of the instrument are reduced, and meanwhile, the accuracy and the reliability of the method are improved through sensitivity calculation, relative error evaluation and a data processing algorithm. The innovative method provides a solution with stronger feasibility and higher efficiency for alloy impurity analysis, and is expected to be widely applied in practical application.
Description
Technical Field
The invention relates to a quantitative detection method for alloy impurity phases.
Background
Conventional alloy impurity detection methods typically involve complex pretreatment steps and the use of multiple instruments, such as spark spectroscopy, atomic absorption spectroscopy, and the like. These methods suffer from the following drawbacks:
cumbersome pretreatment: the pretreatment process in the traditional method comprises the steps of grinding, acid washing, dissolving and the like, and the steps are time-consuming and labor-consuming, and are easy to introduce external pollution to influence accuracy.
The multi-instrument use: the combined use of various instruments adds complexity and cost to the analysis as well as increasing the technical difficulty of operation.
Limiting high throughput analysis: conventional methods generally require long analysis times, fail to meet the requirements for high throughput analysis, and limit the ability to monitor and react quickly in real time.
Technical limitations: in conventional methods, it is often limited by the sensitivity and stability of the instrument, which results in difficulties in accurate determination of low concentrations of impurities. Meanwhile, the control of experimental conditions and the establishment of a standard curve in the traditional method also face some technical difficulties.
Disclosure of Invention
The invention aims to provide a quantitative detection method for alloy impurity phases.
In order to achieve the above purpose, the invention is implemented according to the following technical scheme:
the invention comprises the following steps:
s1: grinding, pickling and dissolving an alloy sample containing impurities to be detected for later use; the grinding particle size was 200 mesh. The pickling is carried out by adopting a mixed solution of nitric acid and hydrochloric acid. The ratio of nitric acid to hydrochloric acid is 1:3, heating to 60-70 ℃ during pickling.
S2: preparing a corresponding reagent as a color reagent according to impurities to be detected; adding the solution in the step S1 into a color developing agent to form a color developing complex; measuring absorbance of the chromogenic complex using a spectrophotometer; according to a known standard curve, calculating the concentration of impurities to be detected in the sample;
s3: calculating the slope and intercept of a standard curve according to the sensitivity of the instrument and the measurement noise, determining the impurity concentration of the minimum reliable measurement according to the slope of the standard curve, comparing with the existing method, determining the relative error of the method, and evaluating the accuracy of the method; optimizing instrument parameters according to the result; the relative error is calculated using the following formula:
the accuracy of the evaluation method comprises reliability evaluation of the results, reliability and repeatability of the measurement results are evaluated by calculating relative error results, and for the data of multiple measurements, a control chart is drawn to monitor the stability of the method.
S4: comparing experimental results under different conditions, and calculating the average value and standard deviation of experimental data; and calculating the concentration of the impurity to be detected of the alloy sample by adopting a data processing algorithm on the detection data. For each experimental dataset under measurement conditions, the average value of the samples was calculatedAnd standard deviation s
Where n is the number of samples, x i Is the i-th data point.
The data processing algorithm carries out standard curve fitting and concentration calculation, and when the standard curve fitting is carried out, the fitting equation is as follows: y=mx=b
Wherein y is absorbance, x is concentration, m is slope, b is intercept, and the concentration of the impurity to be detected of the alloy sample is calculated according to a fitting equation.
The beneficial effects of the invention are as follows:
compared with the prior art, the method has the following technical effects:
simplifying the pretreatment steps:
according to the technical scheme, the sample pretreatment step is simplified by using the grinding step with the grinding granularity of 200 meshes, the acid washing of the nitric acid and hydrochloric acid mixed solution and the dissolution by selecting a proper solvent. This not only improves the efficiency of the experiment, but also reduces the possibility of external contamination.
A single instrument implements multiple steps:
the spectrophotometry is combined with flow injection analysis, and a plurality of steps of impurity detection including color development, absorbance measurement, standard curve fitting and the like are realized through a single instrument. This reduces the cost and complexity of instrument use while improving the reproducibility of the experiment.
Sensitivity and accuracy are improved:
the minimum reliably measured impurity concentration is determined by calculating the slope and intercept of the standard curve. The calculation of the relative error and the comparison with the traditional method further evaluate the accuracy of the method. By optimizing the instrument parameters, the sensitivity and accuracy of measurement are improved.
High throughput analysis and real-time monitoring:
by adopting flow injection analysis and combining a rapid and reliable photometry, the rapid and high-flux analysis of impurities to be detected in the alloy is realized. This makes the method suitable not only for laboratory environments, but also for applications where real-time monitoring is required.
Stability and reliability are improved:
the stability and the reliability of the method are evaluated through statistical analysis of experimental data, drawing of a control chart and calculation of relative errors. The repeatability and the credibility of the experimental result are ensured, and more reliable data support is provided for practical application.
By overcoming the defects of the traditional method, the technical scheme has higher efficiency, simpler and more convenient operation and better performance in the aspect of quantitative detection of alloy impurity phases.
Drawings
Fig. 1 is a flow chart of the present invention.
Detailed Description
The invention will be further described with reference to the accompanying drawings and specific embodiments, wherein the exemplary embodiments and descriptions of the invention are for purposes of illustration, but are not intended to be limiting.
As shown in fig. 1: the invention comprises the following steps:
s1: grinding, pickling and dissolving an alloy sample containing impurities to be detected for later use; the grinding particle size was 200 mesh. The pickling is carried out by adopting a mixed solution of nitric acid and hydrochloric acid. The ratio of nitric acid to hydrochloric acid is 1:3, heating to 60-70 ℃ during pickling.
S2: preparing a corresponding reagent as a color reagent according to impurities to be detected; adding the solution in the step S1 into a color developing agent to form a color developing complex; measuring absorbance of the chromogenic complex using a spectrophotometer; according to a known standard curve, calculating the concentration of impurities to be detected in the sample;
s3: calculating the slope and intercept of a standard curve according to the sensitivity of the instrument and the measurement noise, determining the impurity concentration of the minimum reliable measurement according to the slope of the standard curve, comparing with the existing method, determining the relative error of the method, and evaluating the accuracy of the method; optimizing instrument parameters according to the result; the relative error is calculated using the following formula:
the accuracy of the evaluation method comprises reliability evaluation of the results, reliability and repeatability of the measurement results are evaluated by calculating relative error results, and for the data of multiple measurements, a control chart is drawn to monitor the stability of the method.
S4: comparing experimental results under different conditions, and calculating the average value and standard deviation of experimental data; and calculating the concentration of the impurity to be detected of the alloy sample by adopting a data processing algorithm on the detection data. For each experimental dataset under measurement conditionsCalculating the average value of the samplesAnd standard deviation s
Where n is the number of samples, x i Is the i-th data point.
The data processing algorithm carries out standard curve fitting and concentration calculation, and when the standard curve fitting is carried out, the fitting equation is as follows: y=mx=b
Wherein y is absorbance, x is concentration, m is slope, b is intercept, and the concentration of the impurity to be detected of the alloy sample is calculated according to a fitting equation.
Embodiment one: determination of copper content
Sample preparation S1:
and (3) selecting an aluminum alloy sample containing copper impurities for mechanical grinding, and grinding the aluminum alloy sample into 200 meshes of particle fineness.
Acid washing and dissolution: the mixture of nitric acid and hydrochloric acid is used for pickling, and the ratio is 1:3. The pickling is carried out at the temperature of 65 ℃ to ensure that surface oxides and other pollutants are effectively removed. The sample is dissolved, and a proper solvent is selected to ensure complete dissolution of copper impurities.
Reagent preparation and color development S2:
BCA reagent was prepared as a color developer for copper ions.
Measurement of chromogenic Complex: the solution of step S1 is added to the BCA developer to form a color developing complex. The absorbance of the chromogenic complex was measured using a spectrophotometer.
Concentration calculation: the concentration of copper impurities in the sample was calculated spectrophotometrically using a known standard curve.
Sensitivity calculation and relative error evaluation S3:
sensitivity and relative error: the slope and intercept of the standard curve are calculated to determine the minimum reliably measured copper concentration. The accuracy of the method is evaluated using a relative error formula.
Optimizing instrument parameters: and optimizing instrument parameters according to the comparison result with the existing method.
Data statistics and processing S4:
statistical analysis of experimental data: and comparing experimental results under different conditions, and calculating the average value and standard deviation of experimental data.
Data processing algorithm: standard curve fitting and concentration calculation were performed using data processing algorithms. And calculating the concentration of copper impurities in the aluminum alloy sample according to the fitting equation.
Reliability evaluation of results: the relative error results are used to evaluate the reliability and repeatability of the measurement results. For data from multiple measurements, a control chart is drawn to monitor the stability of the method.
Standard curve equation: a=0.101 [ cu ] +0.017
Absorbance A of sample to be measured sample ＝0.325
Calculation of copper concentration from standard curve
The calculation results are as follows:
by simplifying the pretreatment steps and adopting the flow injection analysis combined photometry, the rapid and high-throughput analysis of the copper content is realized. Multiple steps are realized by a single instrument, so that the cost and the operation complexity are reduced, and the repeatability of the experiment is improved. By optimizing instrument parameters and evaluating relative errors, the accuracy and stability of the method are improved.
Embodiment two: determination of Zinc content
Sample preparation S1:
and (3) selecting an aluminum alloy sample containing zinc impurities for mechanical grinding, and grinding the aluminum alloy sample into 200 meshes of particle fineness.
Acid washing and dissolution: the mixture of nitric acid and hydrochloric acid is used for pickling, and the ratio is 1:3. The pickling is carried out at the temperature of 65 ℃ to ensure that surface oxides and other pollutants are effectively removed. The sample is dissolved, and proper solvent is selected to ensure that zinc impurities are completely dissolved.
Reagent preparation and color development S2:
a soft red reagent was prepared as a color developer for copper ions.
Measurement of chromogenic Complex: and (3) adding the solution obtained in the step (S1) into a soft red reagent color developing agent to form a color developing complex. The absorbance of the chromogenic complex was measured using a spectrophotometer.
Concentration calculation: the concentration of zinc impurities in the sample was calculated spectrophotometrically using a known standard curve.
Sensitivity calculation and relative error evaluation S3:
sensitivity and relative error: the slope and intercept of the standard curve are calculated to determine the minimum reliably measured zinc concentration. The accuracy of the method is evaluated using a relative error formula.
Optimizing instrument parameters: and optimizing instrument parameters according to the comparison result with the existing method.
Data statistics and processing S4:
statistical analysis of experimental data: and comparing experimental results under different conditions, and calculating the average value and standard deviation of experimental data.
Data processing algorithm: standard curve fitting and concentration calculation were performed using data processing algorithms. And calculating the concentration of zinc impurities in the aluminum alloy sample according to the fitting equation.
Reliability evaluation of results: the relative error results are used to evaluate the reliability and repeatability of the measurement results. For data from multiple measurements, a control chart is drawn to monitor the stability of the method.
Standard curve equation: a=0.202 [ zn ] +0.012
Absorbance A of sample to be measured sample ＝0.265
According to the standardCurve calculation of copper concentration
The calculation results are as follows:
by simplifying the pretreatment steps and adopting the flow injection analysis combined photometry, the rapid and high-flux analysis of the zinc content is realized. Multiple steps are realized by a single instrument, so that the cost and the operation complexity are reduced, and the repeatability of the experiment is improved. By optimizing instrument parameters and evaluating relative errors, the accuracy and stability of the method are improved.
Embodiment III: determination of Nickel content
Sample preparation S1:
and (3) selecting an aluminum alloy sample containing nickel impurities for mechanical grinding, and grinding the aluminum alloy sample into 200 meshes of particle fineness.
Acid washing and dissolution: the mixture of nitric acid and hydrochloric acid is used for pickling, and the ratio is 1:3. The pickling is carried out at the temperature of 65 ℃ to ensure that surface oxides and other pollutants are effectively removed. The sample is dissolved, and a proper solvent is selected to ensure that the nickel impurities are completely dissolved.
Reagent preparation and color development S2:
a soft red reagent was prepared as a color developer for copper ions.
Measurement of chromogenic Complex: and (3) adding the solution obtained in the step (S1) into a soft red reagent color developing agent to form a color developing complex. The absorbance of the chromogenic complex was measured using a spectrophotometer.
Concentration calculation: the concentration of nickel impurities in the sample was calculated spectrophotometrically using a known standard curve.
Sensitivity calculation and relative error evaluation S3:
sensitivity and relative error: the slope and intercept of the standard curve are calculated to determine the minimum reliably measured nickel concentration. The accuracy of the method is evaluated using a relative error formula.
Optimizing instrument parameters: and optimizing instrument parameters according to the comparison result with the existing method.
Data statistics and processing S4:
statistical analysis of experimental data: and comparing experimental results under different conditions, and calculating the average value and standard deviation of experimental data.
Data processing algorithm: standard curve fitting and concentration calculation were performed using data processing algorithms. And calculating the concentration of the nickel impurities in the aluminum alloy sample according to the fitting equation.
Reliability evaluation of results: the relative error results are used to evaluate the reliability and repeatability of the measurement results. For data from multiple measurements, a control chart is drawn to monitor the stability of the method.
Standard curve equation: a=0.046 [ n ] i ]+0.012
Absorbance A of sample to be measured sample ＝0.316
Calculation of copper concentration from standard curve
The calculation results are as follows:
by simplifying the pretreatment steps and adopting the flow injection analysis combined photometry, the rapid and high-throughput analysis of the nickel content is realized. Multiple steps are realized by a single instrument, so that the cost and the operation complexity are reduced, and the repeatability of the experiment is improved. By optimizing instrument parameters and evaluating relative errors, the accuracy and stability of the method are improved.
These three examples demonstrate the superiority of the newly proposed quantitative detection method of the alloy impurity phase over the conventional method. The novel method has greater feasibility and practicability in practical application by simplifying operation steps, reducing cost and improving experimental efficiency and accuracy.
The technical scheme of the invention is not limited to the specific embodiment, and all technical modifications made according to the technical scheme of the invention fall within the protection scope of the invention.
Claims (7)
1. The quantitative detection method of the alloy impurity phase is characterized by comprising the following steps of:
s1: grinding, pickling and dissolving an alloy sample containing impurities to be detected for later use;
s2: preparing a corresponding reagent as a color reagent according to impurities to be detected; adding the solution in the step S1 into a color developing agent to form a color developing complex; measuring absorbance of the chromogenic complex using a spectrophotometer; according to a known standard curve, calculating the concentration of impurities to be detected in the sample;
s3: calculating the slope and intercept of a standard curve according to the sensitivity of the instrument and the measurement noise, determining the impurity concentration of the minimum reliable measurement according to the slope of the standard curve, comparing with the existing method, determining the relative error of the method, and evaluating the accuracy of the method; optimizing instrument parameters according to the result;
s4: comparing experimental results under different conditions, and calculating the average value and standard deviation of experimental data; and calculating the concentration of the impurity to be detected of the alloy sample by adopting a data processing algorithm on the detection data.
2. The method for quantitatively detecting the impurity phase of an alloy according to claim 1, characterized by comprising the steps of: the grinding granularity in the step S1 is 200 meshes.
3. The method for quantitatively detecting the impurity phase of an alloy according to claim 1, characterized by comprising the steps of: and in the step S1, the pickling is performed by adopting a mixed solution of nitric acid and hydrochloric acid.
4. The method for quantitatively detecting the impurity phase of an alloy according to claim 3, wherein: the ratio of nitric acid to hydrochloric acid is 1:3, heating to 60-70 ℃ during pickling.
5. The method for quantitatively detecting the impurity phase of an alloy according to claim 1, characterized by comprising the steps of: in the step S3, the relative error is calculated using the following formula:
the accuracy of the evaluation method comprises reliability evaluation of the results, reliability and repeatability of the measurement results are evaluated by calculating relative error results, and for the data of multiple measurements, a control chart is drawn to monitor the stability of the method.
6. The method for quantitatively detecting the impurity phase of an alloy according to claim 1, characterized by comprising the steps of: in step S4, for each experimental data set under the measurement condition, an average value of the samples is calculatedAnd standard deviation s
Where n is the number of samples, x i Is the i-th data point.
7. The method for quantitatively detecting the impurity phase of an alloy according to claim 6, wherein: and (3) performing standard curve fitting and concentration calculation by a data processing algorithm in the step (S4), wherein when the standard curve fitting is performed, a fitting equation is as follows: y=mx=b
Wherein y is absorbance, x is concentration, m is slope, b is intercept, and the concentration of the impurity to be detected of the alloy sample is calculated according to a fitting equation.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311647222.8A CN117629985A (en) | 2023-12-04 | 2023-12-04 | Alloy impurity phase quantitative detection method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311647222.8A CN117629985A (en) | 2023-12-04 | 2023-12-04 | Alloy impurity phase quantitative detection method |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN117629985A true CN117629985A (en) | 2024-03-01 |
Family
ID=90019661
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311647222.8A Pending CN117629985A (en) | 2023-12-04 | 2023-12-04 | Alloy impurity phase quantitative detection method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117629985A (en) |
-
2023
- 2023-12-04 CN CN202311647222.8A patent/CN117629985A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN102033101A (en) | Method for measuring metal impurities in high-purity MgO film material by using inductively coupled plasma mass spectrometer | |
| CN103323412B (en) | Thiocyanate spectrophotometry method for detecting iron content of high-temperature alloy | |
| CN104237209A (en) | Method for synchronously detecting copper, bismuth, iron, lead, tellurium, selenium, antimony and palladium in electrolytic silver through ICP-AES (Inductively Coupled Plasma-Atomic Emission Spectrometry) | |
| CN110514643B (en) | Method for measuring trace elements in high-purity magnesium-based oxide by inductively coupled plasma emission spectrometry | |
| CN110940660A (en) | Method for determining silver, arsenic, tin, boron, copper and zirconium in nickel-based superalloy | |
| CN109632680B (en) | Method for detecting phosphorus in water body based on permutation entropy | |
| CN111443079A (en) | Method for simultaneously detecting contents of trace As, Pb, Cd, Zn, Cr, Co and V elements in ferric trichloride | |
| JP4434026B2 (en) | Isotope ratio analysis method using plasma ion source mass spectrometer | |
| Wengert | Photometric determination of zirconium in magnesium alloys | |
| CN109781684A (en) | A kind of detection method of Mercury in Marine Sediment and arsenic | |
| CN110220887B (en) | Method for measuring lead, zinc, tin and nickel in waste circuit board stripping material resin powder | |
| CN117629985A (en) | Alloy impurity phase quantitative detection method | |
| MacNEVIN et al. | (Ethylenedinitrilo) tetraacetic Acid Chelation of Platinum Group Metals. Spectrophotometric Determination of Iridium | |
| CN108956582A (en) | A kind of emission spectrometry method of high-copper Phosphorus From Wastewater content | |
| CN111474165A (en) | Method for testing concentration content of lithium hexafluorophosphate in lithium ion functional electrolyte by using ICP (inductively coupled plasma) | |
| CN112578071A (en) | Quantitative analysis method for inorganic acid salt in electrolytic stripping powder | |
| CN111141725A (en) | Quantitative detection method for lithium hexafluorophosphate in lithium ion battery electrolyte | |
| CN114354579B (en) | Method for simultaneously detecting silver and palladium elements in silver and palladium mixture | |
| van Staden et al. | Determination of zinc in pharmaceutical products by use of a sequential injection analysis system | |
| Wah Fong et al. | Multi-elements (aluminium, copper, magnesium, manganese, selenium and zinc) determination in serum by dynamic reaction cell-inductively coupled plasma-mass spectrometry | |
| Shen | Determination of silver in copper concentrate by atomic absorption spectrometry | |
| Goyal et al. | Direct Determination of Cadmium in Nuclear-Grade Beryllium by GFAAS | |
| CN116067939A (en) | Quantitative detection method of lithium hexafluorophosphate | |
| CN115356328A (en) | Method for rapidly determining content of multiple elements in high-temperature nickel-based alloy | |
| Maeda et al. | Determination of Microgram Quantities of Tungsten in Iron, Molybdenum, and Titanium by X-Ray Fluorescence Analysis |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |