Method for evaluating and detecting the thermal runaway behavior of solid-state batteries

Abstract

The application discloses a kind of evaluation and detection method of solid-state battery thermal runaway behavior, belong to lithium battery thermal prediction technical field;Including constructing the phase diagram of different system composition, generate crystal structure file;Obtain the energy data of relevant phase in crystal structure file, calculate the reaction energy of each system direct reaction and the reaction energy of intermediate phase to solid-state electrolyte;According to the reaction energy of direct reaction, the size relationship A of the thermal stability of substance is obtained, according to the reaction energy of intermediate phase to solid-state electrolyte, the size relationship B of the thermal stability of substance is obtained, the size relationship F of the thermal stability of substance is inferred;For the substance with uncertain thermal stability size relationship, ARC is used for experimental characterization, radar chart is obtained, the area size of radar chart is compared, and the size relationship G of the thermal stability of substance is obtained;F and G are combined to obtain the final relationship K.The application has the advantages that: more detailed and more accurate thermal stability analysis is provided, and the research of thermal runaway mechanism is facilitated.

Description

Technical Field

[0001] This invention belongs to the field of thermal prediction technology for lithium batteries, and particularly relates to a method for evaluating and detecting the thermal runaway behavior of solid-state batteries. Background Technology

[0002] Compared with currently commercialized lithium-ion batteries, solid-state lithium batteries offer both higher safety and greater potential for energy density improvement, which can help achieve the goal of widespread adoption of new energy vehicles.

[0003] Sulfide solid electrolytes possess high ionic conductivity and deformability. The biggest difference between solid-state batteries and mainstream traditional lithium-ion batteries lies in the electrolyte. Solid-state batteries use a solid electrolyte, replacing the electrolyte and separator in traditional lithium-ion batteries. Traditional lithium-ion batteries mainly consist of positive and negative electrode materials, electrolyte, and separator. The positive and negative electrode materials determine the battery capacity, while the electrolyte and separator serve as the medium for transporting lithium ions.

[0004] However, solid electrolyte materials, a core component of solid-state batteries, still face bottlenecks. Even with sulfide solid electrolytes exhibiting extremely high thermal stability, thermal runaway and fire can still occur at 200°C after contact with a lithium anode (Chem. Mater. 2017, 29, 8611-8619). Due to a lack of in-depth research, the thermal runaway mechanism of all-solid-state lithium batteries based on inorganic electrolytes remains unclear, affecting the design of high-safety solid-state lithium batteries. Therefore, conducting research on the thermal runaway of solid-state lithium batteries and understanding their thermal runaway mechanism is of great significance for designing solid-state batteries with high thermal safety. Summary of the Invention

[0005] The purpose of this invention is to meet practical needs by providing a method for evaluating and detecting the thermal runaway behavior of solid-state batteries, which provides a more reasonable research means for predicting the thermal safety behavior of new systems a priori.

[0006] To achieve the above-mentioned objectives, the present invention aims to provide a method for evaluating and detecting the thermal runaway behavior of solid-state batteries, comprising the following steps:

[0007] S1. Construct composition phase diagrams for different systems and generate crystal structure files of the relevant phases in the composition phase diagrams; the process of constructing the composition phase diagrams is as follows:

[0008] Based on the materials of the solid electrolyte and the metal electrode, establish N systems, each system including one solid electrolyte material and one metal electrode material, with the metal electrode material being the same metal in each system. Query the structural data in the database to construct the composition phase diagram corresponding to each system; where N is a natural number and N≥2;

[0009] S2. Obtain the energy data of the relevant phases in the crystal structure file, calculate the reaction products based on the energy data, and then calculate the reaction energy of the direct reaction of each system and the reaction energy of the intermediate phases relative to the solid electrolyte.

[0010] S3. Based on the reaction energy of the direct reaction, we can obtain the magnitude relationship A of the thermal stability of the substance. Based on the reaction energy of the intermediate relative solid electrolyte, we can obtain the magnitude relationship B of the thermal stability of the substance. We can deduce the magnitude relationship F of the thermal stability of the substance that satisfies both A and B.

[0011] S4. For substances with uncertain thermal stability relationships, experimental characterization is performed using ARC to obtain radar charts. By comparing the area sizes of the radar charts, the thermal stability relationship G of the substances can be determined.

[0012] S5. Combine the magnitude relationships F and G of the thermal stability of the substance to obtain the final magnitude relationship K of the thermal stability of the substance.

[0013] In the above-mentioned method for evaluating and detecting the thermal runaway behavior of solid-state batteries, S1 and S2 include: using Pymatgen to construct composition phase diagrams for different systems, generating relevant phase crystal structure files of the composition phase diagrams, inputting the relevant phase crystal structure files into first-principles prediction software for calculation, and obtaining the energies of reactants and products for each system; according to a pseudo-binary model, inputting the energy data of reactants and products for each system into Pymatgen for calculation, and obtaining the reaction energy of the direct reaction and the reaction energy of the intermediate relative to the solid electrolyte.

[0014] In the above-mentioned method for evaluating and detecting the thermal runaway behavior of solid-state batteries, the solid electrolyte is a sulfide solid electrolyte and the metal electrode is lithium metal.

[0015] In the above-mentioned method for evaluating and detecting the thermal runaway behavior of solid-state batteries, when the reaction energy of the direct reaction is lower than a first threshold, the substance has a tendency to react spontaneously.

[0016] In the above-mentioned method for evaluating and detecting the thermal runaway behavior of solid-state batteries, in S3, the relationship between the thermal stability of the substances is expressed as "a>b", indicating that the thermal stability of substance a is higher than that of substance b.

[0017] In the above-mentioned method for assessing and detecting thermal runaway behavior of solid-state batteries, when determining the relationship between the thermal stability of two substances, the two substances are considered to have similar thermal stability when the difference in reaction energy between the two substances is less than a second threshold, and "a~b" indicates that the thermal stability of a and b is similar.

[0018] In the above-mentioned method for assessing and detecting the thermal runaway behavior of solid-state batteries, if there is a definite relationship in B regarding the uncertain thermal stability of substances in A, then the relationship in B is considered correct; if there is a definite relationship in A regarding the uncertain thermal stability of substances in B, then the relationship in A is considered correct; when there is no uncertain relationship in the thermal stability of substances in A and B, then the corresponding substance is identified as the substance with the uncertain thermal stability relationship described in S4.

[0019] In the above-mentioned method for evaluating and detecting the thermal runaway behavior of solid-state batteries, the index parameters of the radar chart include the initial temperature T1 of the material's self-heating reaction, the final trigger temperature T2 of thermal runaway, the reciprocal of the highest temperature of the material detected during the entire test process 1 / T3, the time period Δt from the self-heating reaction to thermal runaway, and the enthalpy of reaction 1 / ΔH; the larger the area of ​​the radar chart, the higher the thermal stability of the material.

[0020] The above-mentioned methods for assessing and detecting the thermal runaway behavior of solid-state batteries also include:

[0021] Step 1: Use an XRD instrument to conduct supplementary experiments to verify the initial and final phases of the reaction;

[0022] Step 2: Temperature slice non-in-situ characterization to supplement and improve interfacial thermal behavior.

[0023] In the above-mentioned scheme for evaluating and detecting the thermal runaway behavior of solid-state batteries, step 2 further includes: detection of self-decomposition and SEM characterization.

[0024] The beneficial effects of this application are:

[0025] Based on the above technical solution, first-principles calculations are used to obtain the reaction energies of the direct reaction between the solid electrolyte and the metal electrode, as well as the reaction energies of the intermediate phase reaction. Based on these two reaction energies, the inherently valid relationship between the thermal stability of the substances can be directly obtained without coupled calculations. Furthermore, by introducing thermodynamic calculations of the intermediate phase, this method predicts the kinetic process in the actual reaction to a certain extent, obtaining a theory that more closely reflects actual thermal runaway conditions without the need for complex kinetic calculations. Substances with uncertain thermal stability relationships are specifically characterized experimentally using ARC. Five thermal stability-related data points obtained for each substance are compiled into a radar chart. The size of the radar chart area determines the relationship between the thermal stability of the substances. The obtained relationships are then comprehensively ranked to obtain an accurate result for the thermal stability relationship. This result combines simulation calculations and experiments, comprehensively considering numerous factors. In addition, supplementary verification experiments are added to verify the correctness of the results, making the solution more reliable. In summary, this technical solution provides a more reasonable research method for a priori predicting the thermal safety behavior of new systems, and can quickly and effectively assess the ease with which thermal runaway behavior will occur. Attached Figure Description

[0026] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

[0027] Figure 1 This is a flowchart illustrating a method for evaluating and detecting the thermal runaway behavior of a solid-state battery, as provided in an embodiment of the present invention.

[0028] Figure 2 This diagram illustrates the relationship between the mole fractions of four sulfides and their direct reaction energies in a pseudo-binary model provided in this embodiment of the invention. The nodes represent the reaction energies of a specific electrolyte directly reacting with Li metal under the corresponding mole fraction conditions at that node; L3 / Li represents the reaction between Li3PS4 (hereinafter referred to as L3) and Li metal; L4 / Li represents the reaction between Li4SnS4 (hereinafter referred to as L4) and Li metal; L6 / Li represents the reaction between Li6PS5Cl (hereinafter referred to as L6) and Li metal; and L7 / Li represents the reaction between Li7P3S4 and Li6P5Cl. 11 The reaction of L7 (hereinafter referred to as L7) with Li metal is an exothermic reaction with a negative reaction energy.

[0029] Figure 3 This diagram illustrates the reaction energies of the intermediate phases produced by the reaction of four sulfide solid electrolytes with lithium metal. The four sulfides are L3, L4, L6, and L7 from left to right. The horizontal axis represents the decomposition products of the reaction between the sulfides and lithium metal, i.e., the intermediate phases. The vertical axis of the solid points corresponding to the intermediate phases represents the reaction energy of the corresponding intermediate phases with the sulfide electrolytes.

[0030] Figure 4 This is a schematic diagram of the ARC instrument. The sample is placed in the middle, and the thermocouple in contact with the sample will provide real-time feedback on the sample's temperature to determine whether the sample has self-heating properties. The furnace temperature is adjusted according to the sample temperature to ensure that the sample is in an adiabatic state.

[0031] Figure 5 This is a schematic diagram illustrating the specific operating procedure of the ARC instrument. It cycles through a heating-waiting-search process. First, the instrument heats the sample according to the set temperature and waits for a period of time to allow the sample to reach thermal equilibrium. Then, it enters search mode to determine whether the sample exhibits self-exothermic behavior at that temperature. If the sample does not exhibit self-exothermic behavior, the instrument proceeds to the next set temperature for the heating-waiting-search process. If the sample begins to exhibit self-exothermic behavior, the instrument enters follow mode, and the furnace body maintains the same temperature as the sample, placing the sample in an adiabatic environment. When the sample temperature T > 400℃, the instrument stops heating, and the sample and furnace body undergo natural cooling.

[0032] Figure 6 Figure d is a schematic diagram of the ARC detection results of L3 and metallic Li; (a) is a graph showing the relationship between the reaction time and temperature of L3 sample and metallic Li; (b) is a local graph showing the relationship between the reaction time and temperature of L3 sample and metallic Li; (c) is a graph showing the relationship between the self-heating rate and temperature of L3 sample; (d) is a schematic diagram of L3 radar image; Figure d is constructed based on the data obtained from Figure ac.

[0033] Figure 7 Figure d is a schematic diagram of the ARC detection results of L4 and metallic Li; (a) is a graph showing the relationship between the reaction time and temperature of L4 sample and metallic Li; (b) is a local graph showing the relationship between the reaction time and temperature of L4 sample and metallic Li; (c) is a graph showing the relationship between the self-heating rate and temperature of L4 sample; (d) is a schematic diagram of L4 radar image; Figure d is constructed based on the data obtained from Figure ac.

[0034] Figure 8 This is a schematic diagram of the heating process of four sulfide solid electrolyte samples in a glove box; each row represents a schematic diagram of the reaction phenomenon of a certain sulfide and metallic Li as the heating time increases. The sulfides from top to bottom are L6, L3, L7 and L4.

[0035] Figure 9This diagram illustrates the results of supplementing the experiment using an XRD instrument; the black curve represents the XRD diffraction pattern of the powder after the reaction, the pink curve represents the XRD diffraction pattern of the electrolyte itself, and the standard PDF cards for each substance are shown below; the diffraction peaks marked with "▽" are peaks from the plastic wrap used during sample preparation, and the diffraction peaks marked with "?" are peaks that have not yet been labeled; after the reactions of L3 and L7, the diffraction peaks of the electrolyte almost disappeared, and Li2S and Li3P were generated; residual electrolyte diffraction peaks can still be seen in L4, indicating that the reaction was incomplete, and Li2S, LiSn, Li5Sn2, Sn, and SnS2 were also generated; L6 could not react completely within the current experimental conditions, and there are still strong diffraction peaks of the electrolyte and metallic lithium, but Li2S decomposition products were also generated at the same time.

[0036] Figure 10 This is a schematic diagram of the self-decomposition experiment. The effect of self-decomposition of different sulfide solid electrolytes on the interfacial thermal stability was tested. In the WithLi group, the electrolyte sheet was heated together with a lithium metal sheet in contact, and the presence of sulfur precipitation in the environment was observed by detecting the XRD on another non-contact lithium foil (the precipitated sulfur will react with the non-contact lithium foil to form lithium sulfide). In the Without group, the electrolyte sheet was directly heated, and the presence of sulfur precipitation in the environment was observed by detecting the XRD on another non-contact lithium foil.

[0037] Figure 11 This diagram illustrates the experimental results of the effect of self-decomposition on interfacial thermal stability. The "withoutLi" group reflects the self-decomposition of the sulfide itself and the sulfur evolution reaction. The stronger the Li2S peak marked by ▼, the more intense the self-decomposition and sulfur evolution of the electrolyte. The difference in Li2S peak intensity between the "withLi" and "withoutLi" groups represents the degree to which the self-decomposition product (sulfur) participates in the interfacial reaction. The greater the difference in peak intensity, the higher the degree of participation of the self-decomposition product in the interfacial reaction. In the "withoutLi" group, lithium sulfide peaks were detected in L3, L6, and L7, indicating a certain degree of sulfur evolution. L7 showed the highest degree of self-decomposition. L4 showed a lower degree of self-decomposition, and the decomposition products had lower volatility, so it was not significant in this experiment. In the "withLi" group, the lithium sulfide peak of L7 almost disappeared, indicating that the self-decomposition products of L7 participated in the interfacial reaction and formed a Li2S intermediate phase at the interface between L7 and lithium metal. The difference in the lithium sulfide peak intensity between L3 and L6 was small, indicating that the degree of participation of the self-decomposition product sulfur in the interfacial reaction was low.

[0038] Figure 12 This is a schematic diagram of the SEM characterization experiment. The yellow part in the diagram represents lithium foil, and the gray part represents sulfide solid electrolyte particles.

[0039] Figure 13The digital photograph shows the decomposition interface of lithium foil and different sulfide SE particles after co-heating at a set temperature; SEM images were captured in the areas marked with circles of corresponding colors, with no special markings indicating the uniform morphology of the reaction surface; Figures a and a correspond to the reactions of L7, L4, L3, L6 and lithium foil, respectively; Figure a shows that a dense passivation layer was formed on the surface of L7. Detailed Implementation

[0040] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0041] First Embodiment

[0042] This invention provides a method for evaluating and detecting the thermal runaway behavior of solid-state batteries, which is also a method for analyzing the thermal stability of solid-state batteries. The thermal runaway behavior of batteries can be judged by determining the relationship between the thermal stability of materials. Materials with poor thermal stability are more prone to thermal runaway behavior; conversely, materials with good thermal stability are less prone to thermal runaway behavior.

[0043] like Figure 1 As shown, the specific steps include:

[0044] S1. Construct composition phase diagrams for different systems and generate crystal structure files of the relevant phases in the composition phase diagrams; the process of constructing the composition phase diagrams is as follows:

[0045] Based on the materials of the solid electrolyte and the metal electrode, N systems are established. Each system includes one solid electrolyte material and one metal electrode material. The metal electrode material of each system is the same metal. The structural data in the database is queried to construct the composition phase diagram corresponding to each system. Here, N is a natural number and N≥2.

[0046] Four typical sulfides (Li6PS5Cl, Li3PS4, Li4SnS4 and Li7P3S) 11 Taking solid electrolytes (SE) as an example (hereinafter referred to as L6, L3, L4 and L7 respectively), the metal electrode is lithium metal, and there are four systems, i.e. N=4.

[0047] A phase diagram, also known as an equilibrium phase diagram, is a geometric figure that describes the equilibrium relationships between phases. It's a comprehensive graphical representation of the state of a material's phases in relation to temperature and composition, reflecting the thermodynamic equilibrium state of the system. Specifically, it indicates the equilibrium state of the system under certain conditions, regardless of the time required to reach equilibrium. The purpose of a phase diagram is to determine the direction and extent of a process.

[0048] Specifically, compositional phase diagrams can be constructed using Pymatgen. Pymatgen is one of the most powerful Python packages for high-throughput materials calculations, handling everything from modeling to input and output file processing for various density functional theory (DFT) calculation software. Using the Pymatgen package to construct compositional phase diagrams allows for the evaluation of the phase equilibrium relationship between a given SE or metallic electrode phase and composition C.

[0049] Phase equilibrium relationships are determined by constructing the energies of all relevant phases in the composition phase diagram. The phase equilibrium at composition C corresponding to the minimum energy value Eeq(C) is determined by comparing the energies of all relevant phases in their composition space.

[0050] In addition, structural data for each component can be obtained by querying the Materials Project. The Materials Project is an open materials science database and computational materials science platform initiated by Lawrence Berkeley National Laboratory. Through the Materials Project, researchers can quickly obtain high-quality materials data and computational tools.

[0051] In summary, chemical and thermodynamic data of each component in the above four systems were obtained from the materials project. Pymatgen was used to construct composition phase diagrams for different systems and generate crystal structure files of the relevant phases in the composition phase diagrams.

[0052] It should be noted that this invention does not specifically limit the database and the software, programs, languages, etc. required for constructing the composition phase diagram, but aims to achieve the purpose of the method described in this invention.

[0053] S2. Obtain the energy data of the relevant phases in the crystal structure file, calculate the reaction products based on the energy data, and then calculate the reaction energy of the direct reaction of each system and the reaction energy of the intermediate phase relative to the solid electrolyte.

[0054] There are many methods for calculating reaction energy using existing technologies, such as obtaining energy data of relevant phases in the crystal structure file using CASTEP software, or obtaining reaction energy by directly constructing an interface model; or calculating reaction energy by simplifying the ratio of SE and metal electrode, etc. This invention does not limit the specific method; the following method is a preferred method after weighing computational power and accuracy, and is more suitable for calculating reaction energy data involved in determining the magnitude of stability.

[0055] The relevant phase crystal structure file is input into first-principles prediction software for calculation to obtain the reaction products and the energies of reactants and products in each system. Based on the pseudo-binary model, the energy data of reactants and products in each system are input into Pymatgen for calculation to obtain the reaction energy of the direct reaction and the reaction energy of the intermediate phase relative to the solid electrolyte.

[0056] VASP is a software package developed by the Hafner group at the University of Vienna for electronic structure calculations and quantum mechanical-molecular dynamics simulations. It can solve the Kohn-Sham equation within the framework of density functional theory (DFT, which is a specific method of first-principles calculations) and the Roothaan equation under the Hartree-Fock (HF) approximation. It has excellent computational performance for periodic systems, metals, and other systems. Therefore, VASP is used here for relevant calculations on first principles.

[0057] The relevant phase crystal structure files involved in constructing the composition phase diagram are input into the VASP software package. Based on the specific settings of this package, the generalized gradient approximation (GGA) PBE is selected as the exchange-related functional, and the projected fused plane wave (PAW) pseudopotential is used to simplify the calculation of the inner-shell electronic structure in the atoms. The VASP software package is then used to optimize the crystal structure, obtaining the energies of the relevant phases in the composition phase diagram, such as the energies of reactants and products.

[0058] The energies of the reactants and products in each system are input into Pymatgen for calculation. The thermodynamic stability of the interface between the SE and the metal electrode for a given battery can be approximately solved using a pseudo-binary model. By treating the interface as a pseudo-binary model of SE and metal electrode, the two substances contained in the interface can be considered as a single entity, with the interface composition C... interface This can be expressed as the following formula:

[0059] C interface (C SE C electrode，x )=x·C SE +(1-x)·C electrode ,

[0060] Among them, C SE and C electrode These are the compositions of SE and the metal electrode material, respectively (normalized to one atom per molecular formula), where x is the mole fraction of sulfide SE, varying from 0 to 1.

[0061] The energy of the pseudo-binary interface is set as a linear combination of the SE and the metal electrode energy:

[0062] E interface(SE,electrode,x)=x·E(SE)+(1-x)·E(electrode),

[0063] Among them, E interface (SE, electrode, x) represents the total energy of the pseudo-binary interface, E(SE) represents the SE energy, and E(electrode) represents the metal electrode energy.

[0064] The decomposition energy ΔE of a certain material D It can be obtained through the following equation

[0065] ΔE D (phase) = E eq (C)-E(phase),

[0066] Among them, E eq (C) represents the minimum energy of the correlated phase in the space it occupies, ΔE D Let E(phase) represent the phase decomposition energy, and E(phase) represent the phase energy. By analogy, the decomposition energy of the pseudo-binary model can be expressed as:

[0067] ΔE D (SE, electron, x) = E eq (C interface (C SE C electrode，x ))-E interface (SE, electron, x)

[0068] Where, ΔE D (SE, electron, x) represents the decomposition energy of the pseudo-binary interface, E eq (C interface (C SE C electrode )) represents the total energy of the reaction products.

[0069] The reaction energy ΔE of the pseudo-binary interface D，mutuai (SE, electrode, x) is defined as the reaction energy between the phase equilibrium of SE and the metal electrode material.

[0070] ΔE D，mutual (SE, electron, x) = ΔE D (SE, electron, x) - x·ΔE D (SE)-(1-x)·ΔE D (electrode)

[0071] Where, x·ΔE D(SE) represents the reaction energy of electrolyte self-decomposition, (1-x)·ΔE D (electrode) represents the electrode self-reaction energy.

[0072] As x changes, there exists x = x m Make △E D,mutual If it is the minimum value, then

[0073] ΔE D，min，mutual (SE, electron) = min x∈(0，1) [ΔE D，mutual (SE, electron, x)).

[0074] It should be noted that the determined x m Corresponding to the most exothermic decomposition reaction, this path is selected as the most likely reaction path in reality; however, the actual interface layer may differ from the most favorable thermodynamic phase equilibrium and may have cross-interface element distribution and material composition.

[0075] The reaction products are obtained according to the determined reaction pathway. The total reaction energy is obtained by subtracting the total energy of the reactants from the total energy of the products.

[0076] Similarly, in the calculation of the intermediate phase, all possible intermediate phases and electrolyte materials obtained in all reaction pathways of a certain system are taken as reactants, and the aforementioned calculation method is applied to calculate the reaction energy of the intermediate phase. Specifically, the "electrode" or "SE" in the formula is replaced with the corresponding intermediate substance, and the reaction energy of each intermediate phase relative to "SE" is calculated separately. The path with the minimum reaction energy is selected as the most likely path for the intermediate phase. The reaction energy of the intermediate phase is obtained by subtracting the total energy of the intermediate phase reactants from the total energy of the intermediate phase reaction products.

[0077] Based on the above, when applied to four typical sulfides—L6, L3, L4, and L7—the following results were obtained: Figure 2 The reaction energies of each sulfide shown for direct reaction are as follows: Figure 3 The reaction energy of each intermediate phase is shown.

[0078] It should be noted that the calculation process of the aforementioned software VASP and Pymatgen involves calculation modules such as the thermodynamic stability calculation between different materials and the calculation of the thermodynamic influence of related self-decomposition / interface decomposition products on the system.

[0079] S3. Based on the reaction energy of the direct reaction, we can obtain the magnitude relationship A of the thermal stability of the substance. Based on the reaction energy of the intermediate relative solid electrolyte, we can obtain the magnitude relationship B of the thermal stability of the substance. We can deduce the magnitude relationship F of the thermal stability of the substance that satisfies both A and B.

[0080] The most probable reaction path for each system, i.e., the situation corresponding to x = xm, is reflected in... Figure 2 The middle represents the point corresponding to the lowest reaction energy when different sulfides and Li metal react at different mole fractions. Figure 2 It can be seen that the reaction energy at this point for each system is lower than the first threshold of -0.1 eV / atom. The value of the first threshold is based on a large number of experimental summaries and experience, which indicates that both sulfides and lithium metal have a tendency to react spontaneously.

[0081] A lower reaction energy in a direct reaction indicates poorer thermal stability; however, a higher reaction energy in a direct reaction does not necessarily guarantee high thermal stability.

[0082] Compare the reaction energies of the reaction pathways in each system that most closely resemble the actual reaction. Figure 2 As shown, the reaction energy corresponding to L4 is the largest, at -0.526 eV / atom; the reaction energy corresponding to L6 is the second largest, at -0.549 eV / atom; the reaction energy corresponding to L3 is the third largest, at -0.72 eV / atom; and the reaction energy corresponding to L7 is the smallest, at -0.781 eV / atom. Ranking the substances' thermal stability from largest to smallest, and using "a>b" to indicate that substance a's thermal stability is higher than substance b's, we can obtain the following relationship of thermal stability: L4~L6>L3>L7. Here, "~" indicates that the thermal stability of reactions L4 and L6 is similar. When determining the relationship of thermal stability between two substances, considering that the high-temperature environment involved in the experiment would cause two reactions with similar reaction energies to exhibit similar phenomena, and taking into account the errors in first-principles calculations and the errors between simplified and actual models, a second threshold was set. When the difference in reaction energies between two substances is less than the second threshold of 0.035 eV / atom, the two substances are considered to have similar thermal stability. The specific setting of the second threshold value is based on the calculation errors of the simulation and experimental experience. The graph clearly shows that L7 is the smallest, followed by L3, while L4 and L6 are similar and the largest.

[0083] Because the aforementioned substances and lithium metal both have a tendency to react spontaneously, all factors that affect the intensity of the reaction will have a significant impact on the final overall thermal stability. Among them, one of the more critical factors affecting the reaction process is the intermediate phase.

[0084] The intermediate phase with the worst thermal stability often limits the thermal stability of the entire system, therefore... Figure 3Taking the reaction pathway with the lowest reaction energy of the intermediate phase in each system as a reference, as shown in Table 1, the magnitude relationship B of the thermal stability of substances can be obtained: L6>L3~L7>L7~L4; among them, the intervals between the latter three are all less than 0.035 eV, but the difference between L3 and L4 is greater than 0.035 eV. It is considered that the thermal stability of the intermediate phase reaction of L3 is significantly higher than that of L4, and L7 and L3, L7 and L4 have similar stabilities.

[0085] Table 1 Table of the lowest reaction energy of the intermediate phase

[0086] SE Intermediate phase (the least stable path) <![CDATA[E mutual (eV / atom.)]]> L6 <![CDATA[Li3P]]> -0.203 L3 <![CDATA[Li3P]]> -0.271 L7 <![CDATA[Li3P]]> -0.305 L4 <![CDATA[Li7Sn2]]> -0.331

[0087] Therefore, the determination of the magnitude relationship of stability is transformed into a simple problem of comparing the magnitudes of algebra.

[0088] From the two simplified relational expressions L4~L6>L3>L7 and L6>L3~L7>L7~L4, obviously, L6>L3 and L6>L7 can be obtained.

[0089] In the latter expression, L7 does not have a definite magnitude relationship with L3 and L4, but in the former expression, it can be determined that L4>L7 and L3>L7. Therefore, L7 is the smallest term, and L6>L3>L7 can be obtained; similarly, L6 and L4 do not have a definite magnitude relationship in the former expression, but in the latter expression, L6>L4, so L6>L4>L7 can be obtained; in addition, the relationship between L3 and L4 in the former expression is L4>L3, and the relationship in the latter expression is L4<L3, and their positional relationship cannot be determined from this.

[0090] In summary, the magnitude relationship F of the thermal stability of the substance pairs with respect to the lithium metal interface, which is deduced to be necessarily true for both results, is L6>L3>L7 and L6>L4>L7, and the relationship between L3 and L4 needs to be further confirmed.

[0091] S4. Substances with uncertain thermal stability magnitude relationships are experimentally characterized by an Accelerating Rate Calorimeter (ARC) to obtain a radar chart, and the area sizes of the radar charts are compared to obtain the magnitude relationship G of the thermal stability of the substances.

[0092] Based on the above content, additional experiments are conducted to further determine the relationship between L3 and L4.

[0093] Such as Figure 4 and 5As shown, the ARC instrument uses a Heated-Wait-Search (HWS) mode. Samples L3 and L4 are placed in the instrument for initial heating. The instrument is set to wait for the sample to reach thermal equilibrium every 5 degrees Celsius, and then monitor the temperature change at that temperature to check for self-exothermic reactions. If the sample is determined to be self-exothermic, the instrument enters tracking mode, ensuring that the internal ambient temperature remains consistent with the sample, guaranteeing that the sample is in an adiabatic state and does not exchange heat with the environment. Finally, the time-temperature-heating rate data for L3 and L4 are obtained.

[0094] Five parameters were selected from the acquired data as the basis for comprehensive evaluation: {T1, T2, T3, Δt, ΔH}. T1 is the initial temperature of the sample's self-heating reaction, defined as the temperature at which the heating rate exceeds 0.02℃ / min; after a period of time (Δt), the sample enters the thermal runaway stage, and the heating rate will increase significantly by several orders of magnitude; T2 is the final trigger temperature for thermal runaway in quantitatively assessing thermal safety, set here to 1℃ / min; T3 is the highest temperature of the sample detected during the entire test. If the sample mass is large, T3 will exceed the thermocouple range; therefore, the reciprocal is used to mitigate this error when evaluating thermal stability; ΔH is calculated using ΔH = C. p The reaction enthalpy calculated as (T3-T1)(J / kg), where C p It is the specific heat capacity of the sample.

[0095] Among them, T1 and T2 are the most intuitive reflections of thermal stability, while T3, Δt and ΔH further supplement the entire process from autothermal reaction to thermal runaway from a kinetic perspective, making the data more reasonable.

[0096] It should be noted that since thermal runaway usually occurs instantaneously, the calculated ΔH does not represent the total thermodynamic heat release of the reaction, but it is still valuable for thermal safety assessment.

[0097] Higher T1, T2, and longer Δt indicate better thermal stability, while lower T3 and ΔH indicate better thermal safety. Using a radar chart with {T1, T2, Δt, 1 / T3, 1 / ΔH} as indicators of thermal safety characteristics provides a better visualization of the thermal perspective of the sulfide SE / Li system. The size of the radar chart area roughly indicates the system's thermal stability; a larger area represents higher thermal stability.

[0098] It should be noted that since Δt is more involved in the dynamic process, the weight of this parameter should be appropriately reduced, and more consideration should be given to the decisive influence of T1 on thermal stability. When the area difference is not significant, the weight of T1 should be considered to a limited extent.

[0099] like Figure 6 and Figure 7As shown, the radar image area of ​​L3 is larger than that of L4, indicating that the stability of L3 is higher than that of L4, i.e., G: L3>L4.

[0100] S5. Combine the magnitude relationships F and G of the thermal stability of the substance to obtain the final magnitude relationship K of the thermal stability of the substance.

[0101] Combining L3>L4 with the equations L6>L3>L7 and L6>L4>L7 obtained in S3, we get K: L6>L3>L4>L7, which represents the final thermal stability. From this relationship, we can see that among the four substances, L6 has the highest thermal stability, followed by L3, then L4, and L7 has the lowest. Correspondingly, L7 is most prone to thermal runaway, followed by L4, then L3, and L6 is least prone to thermal runaway.

[0102] Second Embodiment

[0103] Steps S1-S5 are detailed in the first embodiment and will not be repeated here. Supplementary experiments are conducted to verify the results, as shown in the following steps:

[0104] Step 1: Use an XRD instrument to conduct supplementary experiments to verify the initial and final phases of the reaction.

[0105] like Figure 8 As shown, four sulfide SE samples were heated in a glove box for a sufficient holding time. The resulting powders were then analyzed by XRD to obtain the reaction products of various sulfides SE and metallic lithium.

[0106] like Figure 9 As shown, analysis revealed that the products of L7 and L3 are both Li2S and Li3P, respectively. The predicted reaction pathways are Li3PS4 + 8Li → Li3P + 4Li2S and Li7P3S, respectively. 11 +24Li→3Li3P+11Li2S. No obvious phenomena are observed visually in the L6 reaction, but XRD detected the formation of an impurity phase, suggesting the pathway is Li6PS5Cl+8Li→Li3P+5Li2S+LiCl. The products of L4 are relatively complex, including LiSn, Li5Sn2, Li2S, SnS2, Sn, and residual L4, therefore the reaction pathway of L4 cannot be uniquely determined. However, the experimental results are consistent with the conclusions in Table 1.

[0107] Step 2: Temperature slice non-in-situ characterization to supplement and improve interfacial thermal behavior.

[0108] 1) Detection of self-decomposition: Self-decomposition of samples is often accompanied by the generation of volatile products (e.g., oxides decompose to release oxygen, sulfides decompose to release sulfur). These volatile products diffuse in the environment and can react with metallic lithium at high temperatures. Therefore, by introducing a lithium foil that does not directly contact the sample, volatile self-decomposition products in the environment can be detected, thus indirectly observing the self-decomposition phenomenon in the sample. Figure 10 As shown, lithium foil was attached to a stainless steel plate and placed next to samples containing different sulfide solid SE particles. The sample was ensured not to come into contact with the lithium foil, serving as a contactless lithium foil for detecting autodegradation products in the environment. The sample and the stainless steel plate with the attached lithium foil were placed in a handcrafted stainless steel container to reduce the diffusion of volatile autodegradation products, resulting in a higher concentration of these products in the environment, and then heated on a heating plate at a set temperature.

[0109] like Figure 11 As shown, the strength of Li2S in the withoutLi group represents the strength of the self-decomposition of the sample itself, and the change (the degree of weakening) of the lithium sulfide strength in the withLi group compared with the withoutLi group indicates the degree to which the self-decomposition products of the sample participate in the reaction in the whole system.

[0110] As can be seen, L7 exhibits strong self-decomposition, with S as the main decomposition product. Furthermore, the S released during self-decomposition can rapidly react with the contacting lithium foil to form Li2S, a product exhibiting strong stability against lithium.

[0111] This step preliminarily verifies the conclusion on the thermal stability of solids from the perspective of the inherent material decomposition itself, namely that L7 has the worst thermal stability.

[0112] 2) SEM characterization: such as Figure 12 As shown, four different sulfide (SE) particles were placed on a lithium foil and heated for a total of 30 minutes at a set temperature. After heating, the samples were separated, and SEM characterization was performed on the lithium foil surface. The samples were either simple electrolyte sheets or electrolyte sheets with lithium foil attached.

[0113] like Figure 13 As shown, the changes at the interface during the heating reaction were observed. A relatively dense passivation layer formed on the surface of L7, which, based on the previous experimental results, may be due to the strong reaction between the self-decomposition products and metallic lithium. The growth of the intermediate layer at the interface of L3 and L6 was not as dense and rapid as that of L7.

[0114] Furthermore, it should be noted that L4 reacted very rapidly in the experiment, reaching its target effect within minutes. Figure 13 The results shown indicate that L4 has faster reaction kinetics.

[0115] Supplementary experiments further verified the results obtained in the first embodiment, namely L6>L3>L4>L7.

[0116] Based on the above technical solution, the magnitude relationship of thermal stability of some substances is obtained through first-principles simulation calculations; for substances with uncertain relationships, an accurate magnitude relationship of thermal stability can be obtained through ARC experiments; supplementary experiments can further verify the correctness of the conclusions, making the entire technical content fast and reliable.

[0117] The above description is only a preferred embodiment of the present invention. It should be noted that, for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for evaluating and detecting the thermal runaway behavior of a solid-state battery, wherein the solid-state battery comprises a solid electrolyte and a metal electrode; characterized in that, The method includes: S1. Construct composition phase diagrams for different systems and generate crystal structure files of the relevant phases in the composition phase diagrams; the process of constructing the composition phase diagrams is as follows: Based on the materials of the solid electrolyte and the metal electrode, establish N systems, each system including one solid electrolyte material and one metal electrode material, with the metal electrode material being the same metal in each system. Query the structural data in the database to construct the composition phase diagram corresponding to each system; where N is a natural number and N≥2; S2. Obtain the energy data of the relevant phases in the crystal structure file, calculate the reaction products based on the energy data, and then calculate the reaction energy of the direct reaction of each system and the reaction energy of the intermediate phases relative to the solid electrolyte. S3. Based on the reaction energy of the direct reaction, we can obtain the magnitude relationship A of the thermal stability of the substance. Based on the reaction energy of the intermediate relative solid electrolyte, we can obtain the magnitude relationship B of the thermal stability of the substance. We can deduce the magnitude relationship F of the thermal stability of the substance that satisfies both A and B. S4. For substances with uncertain thermal stability relationships, experimental characterization is performed using ARC to obtain radar charts. By comparing the area sizes of the radar charts, the thermal stability relationship G of the substances can be determined. S5. Combine the magnitude relationships F and G of the thermal stability of the substance to obtain the final magnitude relationship K of the thermal stability of the substance.

2. The method for evaluating and detecting the thermal runaway behavior of solid-state batteries according to claim 1, characterized in that, S1 and S2 include: using Pymatgen to construct composition phase diagrams for different systems, generating relevant phase crystal structure files for the composition phase diagrams, inputting the relevant phase crystal structure files into first-principles prediction software for calculation, and obtaining the energies of reactants and products for each system; and inputting the energy data of reactants and products for each system into Pymatgen for calculation based on a pseudo-binary model to obtain the reaction energy of the direct reaction and the reaction energy of the intermediate relative to the solid electrolyte.

3. The method for evaluating and detecting the thermal runaway behavior of solid-state batteries according to claim 1, characterized in that, The solid electrolyte is a sulfide solid electrolyte, and the metal electrode is lithium metal.

4. The method for evaluating and detecting the thermal runaway behavior of solid-state batteries according to claim 1, characterized in that, When the reaction energy of the direct reaction is below the first threshold, the substance has a tendency to react spontaneously.

5. The method for evaluating and detecting the thermal runaway behavior of solid-state batteries according to claim 1, characterized in that, In S3, regarding the relationship between the thermal stability of the substances, "a>b" indicates that the thermal stability of substance a is higher than that of substance b.

6. The method for evaluating and detecting the thermal runaway behavior of solid-state batteries according to claim 1, characterized in that, The magnitude relationships of thermal stability of substances A and B mentioned in S3 include: when determining the magnitude relationship of thermal stability between two substances, if the difference in reaction energy between the two substances is less than the second threshold, the thermal stability of the two substances is considered to be similar, and "a~b" indicates that the thermal stability of substance a and substance b is similar.

7. The method for evaluating and detecting the thermal runaway behavior of solid-state batteries according to claim 1, characterized in that, The reasoning in S3 that the thermal stability relationship F of substances satisfying both A and B includes: if there is a definite relationship in B for the uncertain thermal stability relationship in A, then the relationship in B is considered correct; if there is a definite relationship in A for the uncertain thermal stability relationship in B, then the relationship in A is considered correct; when there is no uncertain relationship in the thermal stability relationship between A and B, then the corresponding substance is identified as the substance with the uncertain thermal stability relationship described in S4.

8. The method for evaluating and detecting the thermal runaway behavior of solid-state batteries according to claim 1, characterized in that, The radar chart's parameters include the initial temperature T1 of the material's autothermal reaction, the final trigger temperature T2 for thermal runaway, the reciprocal of the highest temperature detected during the entire test (1 / T3), the time interval Δt from the autothermal reaction to thermal runaway, and the enthalpy of the reaction (1 / ΔH). The larger the area of ​​the radar image, the higher the thermal stability of the material.

9. The method for evaluating and detecting the thermal runaway behavior of solid-state batteries according to claim 1, characterized in that, Also includes: Step 1: Use an XRD instrument to conduct supplementary experiments to verify the initial and final phases of the reaction; Step 2: Temperature slice non-in-situ characterization to supplement and improve interfacial thermal behavior.

10. The method for evaluating and detecting the thermal runaway behavior of solid-state batteries according to claim 9, characterized in that, Step 2 also includes: self-decomposition-related detection and SEM characterization.

Images