Phase transition temperature measurement method for molten salt using electric conductivity

Abstract

To provide a phase transition temperature measurement method using electric conductivity.SOLUTION: A phase transition temperature measurement method using electric conductivity, includes the stages of: providing an electric conductivity change graph for a molten salt according to a temperature change; and performing at least one mathematical analysis stage of (i) a stage of primarily differentiating the electric conductivity change graph, (ii) a stage of secondary differentiating the electric conductivity change graph, and (iii) a stage of determining the number (n) of data and resolution (▵T) on the basis of the electric conductivity change graph to derive Tn according the following formula (1), and performing linear regression analysis for a linear section to detect an abnormal value by using a distance from a linear regression formula as a reference. Tn=Tmax-▵Txn ... Formula (1) (In the formula (1), n is the number of data, and ▵T is an interval of measurement temperatures, which means resolution).SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to a method for measuring a phase transition temperature using electrical conductivity, and to a method for quickly and accurately measuring the phase transition temperature of a solid solution without using expensive special equipment. [Background technology]

[0002] A substance changes phase at a specific temperature. The temperature at which a liquid substance solidifies is called the freezing temperature, and the temperature at which a solid substance melts is called the melting temperature. The temperature at which a liquid substance begins to solidify is called the liquidus temperature, and the temperature at which a solid substance begins to melt is called the solidus temperature.

[0003] If a substance is pure and free of impurities, the temperature does not change during the phase change, so the four phase change temperatures are the same. The same temperature is maintained without any change only while the solid changes into liquid and the liquid changes into solid. However, since all substances contain impurities, there is a possibility that there may be differences in the four phase change temperatures. However, even if the temperature changes, only the starting point remains constant, so the liquidus temperature is a value that does not change. For this reason, the international temperature standard regards the liquidus temperature of a specific substance as the most ideal reference point.

[0004] Molten salt reactors (MSRs) use liquid fuel in the form of molten salt mixtures and have attracted much attention due to their inherent safety properties. The molten salt mixture should be maintained in a liquid state within a desired temperature range and should have a relatively low melting point to allow for efficient heat transfer and fluid dynamics within the reactor. Understanding the phase transition behavior of various molten salt mixtures is crucial for the design and development of molten salt reactors, as the selection of a molten salt mixture with an appropriate melting point affects the safety, efficiency, and overall performance of the reactor.

[0005] In order to evaluate the safety and material corrosivity of fuel salts in such molten salt reactors, it is necessary to derive a phase equilibrium diagram of the fuel salt according to its composition, and the phase transition temperature values ​​experimentally measured in high-temperature molten salts can be very usefully used as reference data for the phase equilibrium diagram of fuel salts based on computational thermodynamics. In this regard, in the case of the DSC (differential scanning calorimetry) measurement method, which is a representative method for experimentally measuring phase transition temperatures, there are problems such as the need to use an expensive special reactor cell, and the need to install large equipment in a small glove box to analyze molten salts that are very sensitive to moisture and oxygen in the atmosphere.

[0006] Meanwhile, Korean Patent No. 10-1412594B1 (Patent Document 1) discloses a method for measuring the electrical conductivity of a solution, and therefore, if it is possible to determine the phase transition temperature based on electrical conductivity suitable for use in actual process sites, it is expected to be widely applicable in related fields. [Prior art documents] [Patent documents]

[0007] [Patent Document 1] Korean Patent No. 10-1412594 Summary of the Invention [Problem to be solved by the invention]

[0008] Therefore, one aspect of the present invention is to provide a method for measuring electrical conductivity and determining a phase transition temperature based on the electrical conductivity. [Means for solving the problem]

[0009] According to one aspect of the present invention, the method includes the steps of: preparing a graph showing a change in electrical conductivity of a molten salt according to a change in temperature; (i) a step of first differentiating the graph, (ii) a step of second differentiating the graph, and (iii) a step of determining the number of data (n) and the resolution (ΔT) based on the graph and calculating T by the following formula (1):n and performing a linear regression analysis on the linear section to detect an outlier based on a distance from the linear regression equation; A method for measuring a phase transition temperature using electrical conductivity is provided, comprising:

[0010] Tn=T max -△Txn...Equation (1) (In the above formula (1), n ​​is the number of data points, and △T is the interval between the measured temperatures, which means the resolution.) Effect of the Invention

[0011] The method for measuring phase transition temperature based on electrical conductivity of the present invention can easily and quickly calculate accurate phase transition temperature values ​​by measuring electrical conductivity of a target and determining phase transition temperature by adopting a series of mathematical algorithms based on the measured electrical conductivity. Therefore, it is expected that the phase transition temperature values ​​experimentally measured for high-temperature molten salts according to the present invention can be used as reference data for calculation-based thermodynamic phase equilibrium diagrams. [Brief description of the drawings]

[0012] [Figure 1] 1 shows a general algorithm flow chart for determining phase transition temperatures using electrical conductivity data. [Diagram 2] This shows the definitions of the items described in the algorithm flowchart in Figure 1. [Diagram 3] The electrical conductivity-temperature curve measured for a (0.56LiCl-0.44KCl)-NdCl3 (30 wt%) molten salt and (a) the first derivative and (b) the second derivative results for determining the phase transition temperature are shown. [Figure 4] 1 shows the electrical conductivity-temperature curve measured for a (0.56LiCl-0.44KCl)-NdCl3 (15 wt%) molten salt, and graphs of (a) the first derivative and (b) the second derivative results for determining the phase transition temperature. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0013] Hereinafter, preferred embodiments of the present invention will be described with reference to the accompanying drawings. However, the present invention can be modified in various other forms, and the scope of the present invention is not limited to the embodiments described below.

[0014] The phase transition behavior of a molten salt mixture is one of the fundamental properties that must be most critically understood in determining the operating temperatures that affect the safety, efficiency, and overall performance of a molten salt nuclear reactor, and the present invention provides a new method for measuring the phase transition temperatures using electrical conductivity data.

[0015] In the method for measuring a phase transition temperature using electrical conductivity according to the present invention, when electrical conductivity is measured, the substance is not particularly limited as long as the substance has electrical conductivity to be measured, and may be a solid solution or a molten salt having electrical conductivity. For example, the molten salt may be LiPF6, LiF, KF, NaF, RbF, CsF, CaF2, MgF2, SrF2, BaF2, AlF3, UF3, UF4, PuF3, ThF3, ZrF4, NdF3, CeF3, LaF3, LiCl, KCl, NaCl, RbCl, CsCl, CaCl2, MgCl2, SrCl2, BaCl2, AlCl3, UCl3, UCl4, PuCl3, ThCl3, ZrCl4, NdCl3, CeCl3, LaCl3, LiBr, KCBr, NaBr, RbBr, CsBr, CaBr2, MgBr2, SrBr2, The compound may include one or more selected from the group consisting of BaBr2, AlBr3, UBr3, UBr4, PuBr3, ThBr3, ZrBr4, NdBr3, CeBr3, LaBr3, LiI, KI, NaI, RbI, CsI, CaI2, MgI2, SrI2, BaI2, AlI3, UI3, UI4, PuI3, ThI3, ZrI4, NdI3, CeI3, LaI3, LiI, KI, NaI, LiNO3, KNO3, NaNO3, RbNO3 and CsNO3, and preferably one or more selected from the group consisting of LiCl-KCl, NaCl-KCl, NaCl-MgCl2, LiCl-NaCl-CaCl2-BaCl2, NaCl-KCl-BaCl2, CsI, UCl3, UCl4, NdCl3, CeCl3 and LaCl3.

[0016] More specifically, the method for measuring a phase transition temperature using electrical conductivity of the present invention includes the steps of preparing a graph showing the change in electrical conductivity of a molten salt with respect to a change in temperature, and performing at least one mathematical analysis step.

[0017] The mathematical analysis step applicable to the present invention includes (i) a step of first differentiating the graph of the change in the electrical conductivity of the molten salt, (ii) a step of second-differentiating the graph of the change in the electrical conductivity of the molten salt, and (iii) a step of determining the number of data (n) and a resolution (ΔT) based on the graph of the change in the electrical conductivity of the molten salt, and calculating T by the following equation (1): nderiving a linear regression equation, performing a linear regression analysis on the linear section, and detecting an outlier based on a distance from the linear regression equation.

[0018] Tn=T max -△Txn...Equation (1) (In the above formula (1), n ​​is the number of data points, and △T is the interval between the measured temperatures, which means the resolution.)

[0019] As a result of the above mathematical analysis step, the phase transition temperature can be determined to be the point where the value is highest when the first derivative is calculated, in the case of (i), the inflection point where the value is zero when the second derivative is calculated, and in the case of (iii), the temperature corresponding to the abnormal value.

[0020] The phase transition temperature to be measured in the present invention is not particularly limited as long as it is a temperature at which the phase of a substance changes. For example, the phase transition temperature may be the liquidus temperature (T L ) may also be used.

[0021] On the other hand, liquidus temperature (T L ) and solidus temperature (T S When the difference between the liquidus temperature (T) and the solidus temperature (T) is 25°C or less, i.e., the closer the interval is, the more difficult it may be to measure the liquidus temperature and the solidus temperature separately. In this case, by including the step of performing the mathematical analysis step (iii), a relatively accurate liquidus temperature (T) can be obtained. L ) can be determined.

[0022] The present invention is preceded by a step of preparing a graph showing the change in electrical conductivity of the molten salt depending on the temperature. At this time, the device or method for measuring the electrical conductivity is not limited, and the measurement can be performed using any known device or method.

[0023] On the other hand, when a graph of the change in electrical conductivity of the molten salt due to the change in temperature is prepared, the change in temperature can be either an increase or a decrease in temperature. For example, when measuring electrical conductivity while decreasing the temperature, the maximum temperature (T m ) and start the determination from the maximum temperature. In this case, the maximum temperature is not particularly limited and may be, for example, the maximum temperature that the high-temperature furnace can withstand. However, in consideration of the economical aspect of the process, the temperature may be cooled from the melting temperature of the molten salt to be analyzed or a temperature 50 to 500°C higher than the melting temperature to room temperature. Alternatively, starting with a salt in a solid phase, the electrical conductivity may be measured while increasing the temperature above the melting temperature. However, in consideration of the accuracy of the data, when a graph of the change in electrical conductivity of the molten salt with temperature change is created while increasing the temperature, it is preferable that the temperature increase rate proceeds slowly at 20°C / h or less. In consideration of the time required for the analysis and accuracy, it is preferable to start from the melting temperature of the molten salt or a temperature 50 to 500°C higher than the melting temperature and create a graph while cooling the temperature to room temperature.

[0024] In the above formula (1) of (iii), n is the number of data, and the range is not particularly limited, but in consideration of the reliability of the data, it is preferably 10 or more, and may be an integer of 100 or less, for example, 50 or less, or 30 or less. Meanwhile, ΔT is an interval of the measurement temperature and may mean the resolution, and is also not particularly limited and can be adjusted as necessary, but in consideration of the reliability of the data and the time required, it is preferably 2 to 10°C.

[0025] Meanwhile, the step (iii) of detecting an abnormal value based on the distance from the linear regression equation may detect an abnormal value when the absolute value of the distance constant indicating the distance from the linear regression equation is equal to or greater than the discrimination criterion value in Table 1. However, the discrimination criterion value may be adjusted as necessary.

[0026] For example, in the step of detecting an abnormal value based on the distance from the linear regression equation, at least one of the following equations A to E may be applied. That is, at least one of the above equations may be selected to detect the distance from the linear regression equation.

[0027]

number

[0028] More specifically, the algorithm proceeds based on the discrimination criteria values ​​disclosed in Table 1 below.

[0029] [Table 1]

[0030] For example, when all of formulas A to E are applied, if the absolute value of the distance constant is less than the discrimination criterion value in Table 1 when the selected formula is applied, the linear regression analysis is performed again, n is added as n+1, and the linear regression analysis is performed again, and 1 is further added to n, in this manner, the algorithm proceeds. In this case, it is not necessary to satisfy all of formulas A to E, and it is checked independently for each formula whether it is less than the discrimination criterion value. If the absolute value of the distance constant according to formulas A to E is equal to or greater than the discrimination criterion value, the point is determined to be an abnormal value, and the temperature of the point is determined to be the liquidus temperature (T L ) may be performed.

[0031] Meanwhile, the step of detecting an abnormal value based on the distance from the linear regression equation in (iii) is performed based on the liquidus temperature (T L ) is the solidus temperature (T S The step may end when the

[0032] For example, the present invention provides a method for obtaining a graph showing a change in electrical conductivity of a molten salt with increasing temperature by increasing the temperature of the molten salt, and a method for obtaining a solidus temperature (T S ), increasing the temperature to a temperature 50 to 500° C. higher than the melting temperature of the molten salt to melt the molten salt, cooling the molten salt to room temperature while plotting a graph of the change in electrical conductivity of the molten salt with decreasing temperature, and determining the number of data (n) and resolution (△T) based on the graph of the change in electrical conductivity of the molten salt with decreasing temperature, and calculating T by the above formula (1). n and performing a linear regression analysis on the linear section to detect an abnormal value based on a distance from the linear regression equation. The step of detecting an abnormal value includes performing a linear regression analysis again when the absolute value of the distance constant confirmed by at least one equation selected from equations A to E is less than a discrimination reference value, incrementing n as n+1, and determining that the absolute value of the distance constant is equal to or greater than the discrimination reference value as an abnormal value, and determining the temperature at that point as a liquidus temperature (T L and determining whether the

[0033] The present invention will be described in more detail with reference to the following specific examples. The following examples are merely illustrative for the purpose of aiding understanding of the present invention, and are not intended to limit the scope of the present invention. EXAMPLES

[0034] 1. Materials and Equipment A customized glass capillary cell (1.5 mm inner diameter, 3 cm capillary length) was used to perform the electrical conductivity measurements, with a Pt wire (1 mm diameter) used for electrical contact between the capillary cell and the highly conductive liquid. The electrical conductivity values ​​were obtained by performing step voltage measurements in microseconds using a potentiometer.

[0035] On the other hand, the cell constant is a coefficient used to convert the measured resistance (or the reciprocal of the resistance) into conductivity. A capillary cell is selected that has a cell constant in an appropriate range. Generally, for highly conductive liquids, a cell constant of 300 cm is used. -1 A cell with a value equal to or greater than this is recommended. The cell constant was determined by placing a KCl standard solution of known conductivity in the capillary cell in a thermostatic water bath at 291 K and using the following equation:

[0036] C = k × R

[0037] where C is the cell constant (cm -1 ), k is the electrical conductivity of the solution (Scm -1 ), and R is the resistance of the solution, which was determined from the slope of the current-voltage curve obtained from the microsecond step voltmeter.

[0038] 2. Method for determining the phase transition temperature of molten salt According to the present invention, the electrical conductivity of a molten salt mixture is measured at regular intervals while the temperature is decreased using the electrical conductivity measurement system described above in connection with the materials and equipment described in 1., and a series of mathematical algorithms are applied to the measured values ​​to objectively and accurately determine the phase transition temperature.

[0039] (1) Measurement of electrical conductivity To measure the electrical conductivity in the high-temperature molten salts, the molten salt mixture was placed in a quartz vessel and then placed in a high-temperature furnace inside a glove box (99.999% argon, moisture and oxygen are both <1 ppm). The temperature of the high-temperature furnace was controlled and monitored using a thermocouple, which was placed as close as possible to the edge of the capillary cell to measure the exact temperature. To measure the phase transition of the molten salt mixture, the electrical conductivity was measured at regular intervals while decreasing the temperature in the range of 300-650 °C.

[0040] (2) Determination of phase transition temperatures based on mathematical algorithms 1) Second order differential method The measured electrical conductivity-temperature curve is differentiated first and / or second, and the point where the first differential result is the highest and the value where the second differential result has an inflection point of zero can be determined as the phase transition temperature. This method can distinguish transition points that are difficult to determine by the intersection of a simple linear regression equation, and more accurate temperatures can be determined by appropriately adjusting the temperature interval corresponding to the resolution.

[0041] However, for example, the solidus temperature (T S ) and liquidus temperature (T L In a molten salt system with two phase transition temperatures, T S and T L In the case where the temperature interval between is small, the calculation by differentiation may lead to inaccuracies depending on the case, so the phase transition temperature can be determined by the following mathematical algorithm-based phase transition temperature determination method or by further carrying out such a method.

[0042] 2) Analysis algorithms using linear regression and statistical data analysis The phase transition temperatures can be determined in a systematic manner, as shown in the algorithmic flow chart of FIG. 1, by determining values ​​according to various statistical criteria in the formulas A, B, C, D, and E.

[0043] In this case, the following descriptions in the above algorithm are defined as follows: T0=T max : The maximum temperature at which the conductivity measurement begins T n = minimum temperature in the linear section T max = maximum temperature T L =liquidus temperature △T=resolution n = minimum number of data R 2 = Coefficient of determination Z = distance constant |Z| = absolute value of the distance constant Z det = Criterion value

[0044] Furthermore, the above formulas A, B, C, D, and E are exemplary statistical formulas that can evaluate how far the data values ​​are from the linear regression formula, as follows:

[0045]

number

[0046] In this case, the definitions of the items described in each formula are as follows:

[0047] n: number of data k: The number of independent terms in the regression model (for example, in the case of a linear model, y=ax+b, so a, b, and so on, making two)

number

[0048] 3. Experimental example: Determination of phase transition temperature The LiCl-KCl molten salt is the object of measurement, which is a chloride-based molten salt used in the thermochemical reprocessing of spent nuclear fuel. Various physical properties of the molten salt have been investigated by several researchers, for example, the melting temperature depending on the KCl (or LiCl) composition has been measured in various studies using thermal analysis methods.

[0049] To verify the validity of the electrical conductivity-based method for determining the phase transition temperature, electrical conductivity-temperature curves were obtained from LiCl-KCl-based molten salt mixtures and the solidus temperature (T S : solidus temperature) and liquidus temperature (T L The liquidus temperature (L: liquidus temperature) was determined.

[0050] As a result, all measured temperature values ​​were compared with previously reported reliable results.

[0051] Figure 3 shows the electrical conductivity vs. temperature curve (a) measured for LiCl-KCl-NdCl3 (30wt%) molten salt and the graph (b) of the first and second derivatives to determine the phase transition temperature, and Figure 4 shows the electrical conductivity vs. temperature curve (a) measured for LiCl-KCl-NdCl3 (15wt%) molten salt and the graph (b) of the first and second derivatives to determine the phase transition temperature. Here, wt% is the percentage of the mass of NdCl3 relative to the mass of the total solution, using LiCl-KCl eutectic mixture as the solvent.

[0052] In the experimental example 1 (type I) in Figure 3, S and T L If the interval between the T and the T curve is sufficiently large, the exact transition temperature can be determined based on the first and / or second derivative of the curve. S are 353℃ (first derivative), 352℃ (second derivative), and T L were confirmed to be 420°C (first derivative) and 417°C (second derivative), which are consistent with the values ​​presented in the literature (T S : 355℃ and T L It was confirmed that the temperature was very similar to that of the conventional annealing furnace (424°C).

[0053] On the other hand, as in the case of Experimental Example 2 (Type II) in FIG. 4, T S and T L When the interval between is narrower than 25°C, T L Therefore, it may be difficult to clearly determine the inflection point corresponding to the statistical evaluation criteria presented in this invention. L、cal The values ​​were calculated as shown in Table 1 and compared in Table 2.

[0054] Table 2 shows the results obtained from the statistical equations (A-E) that evaluate how far the data values ​​deviate from the linear regression equation. In Table 2 below, column 1 shows n, columns 2 and 3 show T (absolute temperature, the degree Celsius plus 273) and x values ​​(1 / T, the reciprocal of absolute temperature), and column 4 shows y values ​​(lnk). Column 5 shows the predicted values ​​from the linear regression equation.

number

[0055]

Table 2

[0056] For the conductivity-temperature curve measured with the (0.56LiCl - 0.44KCl)-NdCl3(15wt%) salt, the T obtained from the analysis algorithm using linear regression and statistical data analysis L values are summarized in Table 3 below.

[0057]

Table 3

[0058] As a result, as can be confirmed from Table 3 above, in the case of the conductivity-temperature curve in Figure 4, the % difference value calculated from the values reported in the literature shows a difference of around 10%, and it was confirmed in the order of C < E < D < A < B.

[0059] Furthermore, in order to confirm the objectivity and compatibility of the evaluation methods for formulas A to E, for the conductivity-temperature curves with different result values using 0.70LiCl - 0.30KCl salts with different compositions, the T obtained from the analysis algorithm using linear regression and statistical data analysis L values are summarized in Table 4 below.

[0060]

Table 4

[0061] As a result, as can be confirmed from Table 4 above, the % difference values compared with the literature values showed differences in the order of C, E < D < A < B. Commonly, it was confirmed that the C and E methods have less difference from the literature values, and the A and B methods show relatively large differences.

[0062] Thus, the method of aggregating values ​​according to various statistical criteria according to the present invention can be expected to provide a level of control over objectivity, rationality, and sensitivity to achieve a desired level of uncertainty.

[0063] That is, the phase transition temperature measurement system based on electrical conductivity measurement according to the present invention is very promising as a new methodology for measuring the phase transition temperatures of various multi-component molten salt systems, and the measurement system is much simpler and faster than conventional thermal analysis techniques, while such an analysis algorithm enables consistent measurement of transition temperatures under any conditions and environments.

[0064] Although the embodiments of the present invention have been described in detail above, the scope of the present invention is not limited thereto, and it will be obvious to those having ordinary skill in the art that various modifications and variations are possible without departing from the technical idea of ​​the present invention described in the claims.

Claims

1. preparing a graph showing the change in electrical conductivity of the molten salt depending on the change in temperature; (i) taking a first derivative of the graph; (ii) taking a second derivative of the graph; and (iii) Based on the graph, the number of data (n) and the resolution (ΔT) are determined and calculated by the following formula (1): ｎ and performing at least one mathematical analysis step of deriving a linear regression equation based on a distance from the linear regression equation and detecting an abnormal value based on the distance from the linear regression equation. T ｎ =T ｍａｘ -△Txn .. .. .. .. .. Formula (1) (In the above formula (1), n ​​is the number of data, and ΔT is the interval between the measured temperatures, which means the resolution.)

2. 2. The method for measuring a phase transition temperature using electrical conductivity according to claim 1, wherein the phase transition temperature is determined to be a point where the value is highest when the first derivative is calculated, a point where the value is zero when the second derivative is calculated, or a temperature corresponding to the abnormal value when the second derivative is calculated.

3. liquidus temperature (T Ｌ ) and solidus temperature (T Ｓ 2. The method of claim 1, further comprising the step of performing the mathematical analysis step (iii) if the difference between the measured temperature and the measured value is 25° C. or less.

4. 2. The method for measuring a phase transition temperature using electrical conductivity according to claim 1, wherein the temperature change is a change in temperature by cooling the molten salt to room temperature from a melting temperature of the molten salt to be analyzed or a temperature 50 to 500° C. higher than the melting temperature, or a change in temperature by raising the temperature of a solid molten salt to a temperature equal to or higher than the melting temperature.

5. The molten salt is LiCl-KCl, NaCl-KCl, CsCl-KCl, LiCl-NaCl-CaCl ２ -BaCl ２ , NaCl-KCl-BaCl ２ , CaF ２ , NdCl ３ , CeCl ３ and LaCl ３ The method for measuring a phase transition temperature using electrical conductivity according to claim 1, comprising at least one component selected from the group consisting of:

6. The phase transition temperature is the liquidus temperature (T Ｌ 2. The method for measuring a phase transition temperature using electrical conductivity according to claim 1 .

7. 2. The method for measuring a phase transition temperature using electrical conductivity according to claim 1, wherein in the formula (1) of (iii), n is an integer of 10 or more and 100 or less, and ΔT is 2 to 10° C.

8. When applying one or more of the following formulas A to E, if the absolute value of the distance constant is less than the discrimination criterion value, perform the linear regression analysis again and add n as n+1. If the absolute value of the distance constant is equal to or greater than the discrimination criterion value, determine it as an abnormal value and define the temperature at that point as the liquidus temperature (T Ｌ 2. The method for measuring a phase transition temperature using electrical conductivity according to claim 1, further comprising the step of determining whether the phase transition temperature is greater than or equal to the electrical conductivity. [0010] (The definitions of the items in each formula are as follows: n: number of data k: Number of independent terms in the regression model [0025]

9. In the step (iii) of detecting an abnormal value based on the distance from the linear regression equation, when the absolute value of the distance constant indicating the distance from the linear regression equation is equal to or greater than each of the following discrimination criteria in the derivation formulas A to E of each distance constant, the abnormal value is detected. In this case, the discrimination criteria are: Formula A: 2 Formula B: The smaller of 6 / n and 0.99 Formula C:2 Formula D: 1 Formula E: When n is less than 30, it is 1. When n is 30 or more, it is 2 / n ０．５ The method for measuring a phase transition temperature using electrical conductivity according to claim 8 .

10. The step of detecting an abnormal value based on the distance from the linear regression equation in (iii) is performed using a liquidus temperature (T Ｌ ) is the solidus temperature (Solidus Temperature, T Ｓ 9. The method for measuring a phase transition temperature using electrical conductivity according to claim 8, wherein the step ends when the electric conductivity becomes equal to the electric conductivity.

11. A graph showing a change in electrical conductivity of the molten salt with increasing temperature is obtained while increasing the temperature of the solid molten salt; The graph of the change in electrical conductivity of the molten salt with increasing temperature is first- or second-differentiated to obtain the solidus temperature (T Ｓ ) determining increasing the temperature to a temperature 50 to 500° C. higher than the melting temperature of the molten salt to melt the molten salt; A graph showing the change in electrical conductivity of the molten salt with decreasing temperature is obtained while the temperature is being cooled to room temperature; The number of data (n) and the resolution (ΔT) are determined based on the graph of the change in electrical conductivity of the molten salt due to the temperature drop, and T is calculated according to the formula (1). ｎ and detecting an outlier based on a distance from the linear regression equation by performing a linear regression analysis on the linear section; The step of detecting the abnormal value may include: when applying one or more of the following formulas A to E, if the absolute value of the distance constant is less than a discrimination reference value, performing a linear regression analysis again, adding n as n+1, and if the absolute value of the distance constant is equal to or greater than the discrimination reference value, determining that the abnormal value is an abnormal value, and calculating the temperature at that point as a liquidus temperature (T Ｌ 2. The method for measuring a phase transition temperature using electrical conductivity according to claim 1, comprising the step of determining: [0030] (In this case, the definitions of the items described in each formula are as follows: n: number of data k: Number of independent terms in the regression model [0045] In this case, the discrimination criteria in the derivation formulas A to E of the distance constants are as follows: Formula A: 2 Formula B: The smaller of 6 / n and 0.99 Formula C:2 Formula D: 1 Formula E: When n is less than 30, it is 1. When n is 30 or more, it is 2 / n ０．５ ).

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