Application of Nondestructive Testing Technology in Device‐Scale for Lithium‐Ion Batteries

Lithium‐ion batteries (LIBs), due to their high energy density and long cycling life have been widely applied in a variety of industries, including electric vehicles, small‐ and medium‐sized electronic devices, and intelligent medical care. Nevertheless, the security and real‐time state of LIBs is difficult to obtain accurately, improving the battery's service life and ensuring battery safety have become the focus of research. Nondestructive testing (NDT) technology has developed quickly to reach this purpose, requiring a thorough investigation of how batteries’ internal structures have evolved. The principles, contributing factors, and applications of various widely used NDT techniques are summarized and discussed in this review. These inspection techniques can be used to evaluate the battery condition, observe the internal structure of the battery, analyze the failure phenomenon and electrochemical performance of the battery operation, etc. Finally, a summary and outlook are given regarding the characteristics and prospects of NDT methods. This overview will show new light on the application of NDT technology for LIBs and will promote the development of next‐generation LIBs with high security.


Introduction
The rapid development of our society inevitably overexploits finite fossil energy, causing a series of environmental problems and energy crises.It is urgent to explore new clean energy to meet the demand for low carbon emission, environmentally friendly, and sustainable development.To correspond with the requirements of individuals for green and clean energy, the development of energy sources like solar, wind, and tide has been accelerated.The most popular method for converting these intermittent energies into electricity so that it can be utilized is currently through batteries, which are devices that implement the conversion between electric energy and chemical energy. [1]As a result, lead-acid batteries, zinc-manganese batteries, nickel-cadmium batteries, nickel-metal hydride batteries, and lithium-ion batteries (LIBs) appeared in our social production and lifetime. [2]Among them, due to several advantages such as high energy density, light weight, recyclability, and environmental friendliness, LIBs have the widest range of applications, including electric vehicles, small-and medium-sized electronic devices, and intelligent medical care. [3]owever, the increase in energy density and safety performance of LIBs has currently been the focus of research to fulfill more demands in modern life. [4]o improve the capacity and efficiency, a deep understanding of the principle of LIB operation is necessary.LIBs depend on lithium ions to be de-embedded back and forth between the two electrodes.Lithium ions are embedded in the negative electrode from the positive, leaving the negative electrode in a lithium-rich state when charging.It is the opposite, as the lithium ions are de-embedded from the negative and combined with the positive electrode when discharging.The transport of lithium ions is the key to LIB's performance, therefore, increasing the number of lithium ions, improving the transfer rate, and expanding the electrode embedding holes are some options choices to reach the goal. [5]To ensure the safety of LIBs, it is unavoidable to understand and analyze the phenomena and causes of battery failure. [6]The commonly found failure phenomena include poor electrolyte wetting, [7] cell expansion, [8] gas production inside the cell, [9] lithium dendrites generation, [10] solid electrolyte cracking, [11] etc. [12] The causes of each phenomenon are different and some of them are unavoidable, but only by analyzing and correcting them as much as possible can we guarantee the safety of the battery. [13]s mentioned above, whether to improve the performance or to ensure the safety of the battery, we all need to start with the internal structure of the battery changes.Performance is determined by structure, therefore, the battery detection methods are crucial, and many testing technologies have emerged recently. [14]ome of them have been applied for many years and have expanded their functions through development and innovation, such as X-ray computed tomography (X-ray CT) [15] and neutron scanning imaging. [16]Some are already mature in other fields and broadened the application areas by making some transformations, such as ultrasonic inspection [17] and magnetic resonance imaging (MRI). [18]Others have been developed specifically for this area, such as magnetic field scanning imaging and some special testing technologies.The classification of these technologies varies according to different criteria and here we simply divide these techniques into imaging detection and data analysis. [19]Imaging technology can be further divided into in situ imaging and ex situ imaging depending on the necessity of damaging test batteries.In situ imaging allows for direct detection without the need to disassemble the battery, while ex situ imaging requires battery disassembly.Besides, in situ imaging and data analysis can both be referred to as nondestructive testing (NDT) techniques since they do not damage the LIB under test. [20]he interior of the battery is a relatively airtight system that will stop running once it is broken.As a result, the practical application of ex situ detection techniques is quite limited.They are commonly used for postfailure analysis of the battery because of the need to disassemble the battery.On the contrary, in situ technology can detect the internal conditions of the working batteries in real-time and give feedback in time, which can help to have a more comprehensive understanding of the structural changes and defects that occur during operation, providing the possibility for further performance improvement and safety assurance of battery. [21]Consequently, the NDT technique is more feasible and helpful for realistic production applications.
However, there are only a small number of review articles on NDT techniques, and most of them focus on nondestructive without limiting the scope of the inspection, which leads to the fact that some of the NDT techniques in the articles are only applicable to the electrode rather than the entire battery.Therefore, in this article, we mainly discuss several currently used NDT techniques for LIBs.For each NDT method, the imaging/analysis signal is distinctly different.According to the way the signal acquires information, we simply divide it into transmissive signal, resonance signal, and data, as shown in Figure 1.We will introduce the commonly used NDT techniques of these three signals in turn, including the principles and influencing factors.Besides, the applications of these technologies will also be presented and demonstrated.

Transmissive Signal Imaging
The signal attenuates when passing through the test sample, resulting in variations in strength.Transmissive signal imaging utilizes these variations to form the contrast of the images.Transmissive signal imaging is a commonly used NDT technique that directly reflects the structure and changes inside the sample.The following sections will describe three types of transmissive signal imaging techniques in accordance with the wavelength (Figure 2).In general, a shorter wavelength of the signal has more energy and stronger transmission.However, there are discrepancies between different signals.Each technology has different characteristics and varies in application.

X-Ray CT
X-ray CT is a computer-aided technique for constructing 2D/3D images of an item using X-ray scanning.As shown in Figure 3a, an X-ray CT instrument mainly consists of four parts: an X-ray tube, detector, rotation stage, and testing cell.Although the transmissive signal strength is relatively strong, they still weaken as they are scattered or absorbed when passing through the cell. [22]Several factors affect the quality of the CT images.Higher resolution can be achieved by increasing the atomic number of the target material, the emission current voltage, the exposure time, and the number of projections. [23]owever, it is equally important to take into account both the cost and the time.Studies of how this technology can enhance battery performance and safety are described in the following paragraphs.
Performance is determined by structure.LIBs depend on lithium ions to be inserted/extracted back and forth between the two electrodes.The performance of LIBs is directly affected by the transport channels of Li þ ions, which are controlled by the microstructure of the battery.Therefore, the observation of the microstructure of LIBs is constructive to explore the further improvement of the battery performance. [24]Shearing et al. used X-ray CT and double scan superposition (DSS) techniques to obtain the microstructural characterization of the cell by computational modeling. [25]The carbon bonded regions (CBD) and the LiNi 1/3 Mn 1/3 Co 1/3 O 2 (NMC) cell differed in attenuation of X-rays on the scanning images, where high-attenuation NMC showed white and low-attenuation CBD and micropores showed gray.Besides, DSS can further separate microporosity and CBD during secondary processing of CT images, and the results obtained are similar to SEM, as shown in Figure 3b.3D CT scans can also be built with computer modeling, and different information can be obtained by changing the scale, including the distinction between NMC, CBD, and pores, the effective diffusion flux of lithium ions, and the orientation of NMC particles (Figure 3c).Through these techniques, we can visualize various microstructure information of the battery directly and further investigate the effects of each factor to improve the cell performance.
With the development and application of LIBs, lithium-sulfur (Li-S) batteries with high energy density and low cost have attracted attention, but the shuttle effect of intermediate-phase polysulfides greatly affects performance. [26]To limit the adverse effects of sulfide dissolution, the evolution of sulfur conversion in battery operation should be explored first.Shearing et al. first utilized X-ray micro-CT to observe the volume changes of sulfur particles and CBD phases under different depths of discharge (DoD) and depth of charge (DoC). [27]DoD is the proportion of discharged electrical energy relative to the total capacity which represents the percentage of effective energy that has been discharged from the battery.Similarly, DoC refers to the proportion of discharged electrical energy relative to the total capacity which represents the percentage of the battery's capacity that has been filled with charge.As shown in Figure 3d, sulfur was preferentially dissolved from the edge of the electrode to the center as DoD increased, while it was generated from the inside to the outside as DoC increased, and the CBD cracks may affect the distribution of sulfur.Besides, Shearing et al. also analyzed the dissolution and size distribution of sulfur. [27]Further study of cell aging can be carried out with these results.
LIBs are mainly composed of the cathode, anode, membrane, and electrolyte.Compared to liquid electrolytes, solid-state electrolytes (SSEs) have the potential to increase the energy density of the batteries. [28]However, the performance of the solid-state batteries (SSBs) can be impacted by interfacial transitions between the SSE and the electrode and interfacial phase cleavage during cycling. [29]Thus, observing the structural changes of SSBs during battery operation is meaningful for further investigations.Tippens et al. used X-ray CT and scanning electron microscope (SEM) techniques to scan the self-prepared Li 1þx Al x Ge 2Àx (PO 4 ) 3 (LAGP) cells before and after cycling. [30]The CT images of LAGP particles in Figure 4a revealed cracks at the top and bottom, while the SEM images in Figure 4a revealed a deepening of the top  Wavelength and transmitting depth of different transmissive signals. [19]hase contrast and an interfacial transition after cycling.We defined the damaged area as the valuation of the suppressed transport crack in the SSE.As shown in Figure 4b, there was no obvious crack in the SSE and no obvious change in the battery impedance in the early period, the main change in the cell is interfacial transition.However, when the charge transfer number reached 2.2 mAh, the SSE cracked and the battery impedance increased significantly.Besides, the battery impedance increased continuously with the expansion of the crack.It can be inferred that the battery failure is caused by a mechanical fracture and is not related to the interface transition from the relationship between battery impedance and SSE cracking.The cells were subjected to constant current cycling and constant potential cycling, and the CT scans were recorded.The cracks appeared and extended from the edge to the interior in the LAGP particles as cycling time increased, where were initially without cracks (Figure 4c).The LAGP particles contained only a few holes before cycling, however, radial cracks and circumferential cracks appeared, forming an interwoven mesh structure concentrated inside the particles after cycling (Figure 4c).These conclusions are critical for engineering lithium/SSE interfaces to minimize stress build-up, which may block the transport of lithium ions and influence performance. .Reproduced with permission. [25]Copyright 2020, Springer Nature.d) CT images of Li-S batteries.Volume maps of sulfur particles at different DoD (left) and DoC (middle).Volume maps of CBD phase, sulfur particles at 25.6% DoD and 100% DoC (right from top to bottom).Reproduced with permission. [27]Copyright 2018, American Chemical Society.Underneath: 3D scanning images of LAGP particle cracks at various cycle times.The green arrow numbers represent the amount of charge transfer, and the blue arrow numbers represent the volume increase of the cracks observed from the whole particle.Reproduced with permission. [30]Copyright 2019, American Chemical Society.d) Structural characteristics of the active materials in the negative cross-section Gðx, y N1 , zÞ φ k N (red) and the positive cross-section Gðx, y P1 , zÞ φ k P (blue).Reproduced with permission. [32]Copyright 2018, Royal Society of Chemistry.
No matter the Li-S battery or SSB mentioned earlier, they are both exploring increasing the capacity of the battery.It was found that the actual battery capacity depends on the number of cycles, temperature, discharge current, DoD, and other operational circumstances as well as battery structure parameters. [31]With the support of NDT techniques, we can not only explore the internal structure but also directly obtain the capacity.Battery capacity refers to the ability to store electrical energy.And larger capacity means longer working time under the same discharge situation, which makes it one of the key indicators of the battery's performance.Therefore, calibration of the battery capacity is necessary.However, since current methods like electrical measurement are cumbersome, the combination of NDT techniques and formula derivation provides an innovative idea.Hou et al. derived the relationship between the actual battery capacity and the working conditions and structural parameters of the battery based on Faraday's law. [32]S(φ k ) is the structural parameter, while T k is the temperature and n k s the number of cycles in Equation (1).
With the support of X-ray CT technology, the structural characteristics of the active material in both anode and cathode cross sections of the battery can be observed and recorded.The actual capacity of the battery can then be calculated using the gathered data and the equation.From Figure 4d, it can be found that the loss of strong active materials in the anode cross-section image is more than that in the cathode cross-section image when the battery capacity decays.It provided a new way to detect battery capacity without damage.
Battery security has always been an unavoidable focus in battery use, however, there are still many issues that need to be resolved in practical applications.The structure of the electrode may change during the charging and discharging process because of the de-embedding of lithium ions back and forth between the two electrodes and the formation of solid electrolyte interface (SEI) film, especially if the electrode is prone to swelling under low-temperature conditions. [33]This irreversible deformation is likely to cause safety problems for batteries.Therefore, the observation of battery expansion signs in time is necessary. [34]uo et al. used series-connected cells for cycling tests at low temperatures of about 0 °C. [35]The cells polarized severely at low temperatures, exhibiting faster decrease in capacity and irregular cycling at the fourth, tenth, and eleventh rotations.In addition, the battery pack after low-temperature cycling expanded significantly compared to before, as shown in Figure 5a.X-ray CT scan of the battery pack before and after the cycle (Figure 5b) revealed that the two cells had a neat structure and obvious interval before the experiment.After the low-temperature cycle, the internal deformation of the battery such as bending and swelling occurred, and overlap occurred between the cells. [36]Similarly, Blazek et al. revealed inhomogeneous swelling of the jelly-roll electrode windings inside commercial 18 650 batteries through helical trajectory X-ray micro-CT. [37]Various components of the cell can be clearly distinguished from the high-resolution CT image, as shown in Figure 5c.We can quantitatively compare the thickness in each axial direction from different vertical height sections before and after cell aging with specific data.As shown in Figure 5d, direction G5 was affected by the positive tab resulting in a decrease in the thickness of both fresh and aged cells after z = 9 mm, and also direction G1 was affected by the negative tab causing a slight drop in the thickness of the cells at z = 26 mm.The results analyzed showed that most of the thickness increase occurred at the top and bottom of the aged cell, and there was an axial inhomogeneous expansion compared to the fresh cell.Besides, it is also difficult to avoid the safety problem of heat generation in the battery caused by the current.Heenan et al. monitored the internal temperature of 18 650 column batteries in operation using X-ray diffraction (XRD)-CT and multichannel collimator. [38]The outcomes guided the thermal management of batteries and the safe use of aging ones.Although imaging technology cannot inherently prevent the battery from expanding or heat generation, it can alert the battery to potential safety issues before they occur avoiding further damage.
In summary, X-ray CT is commonly employed in conjunction with other techniques or analytical methods as mentioned previously, and can be subdivided into several types, as shown in Table 1.Each type varies in terms of suitable batteries, advantages, limitations, and applications.The difference between X-ray CT and X-ray micro-CT is the resolution of the images, while both of them can detect essentially all batteries with ease and are widely used.Although X-ray has the widest range of transmitting depth discussed in this article, the image is still limited by sample thickness and suffers from light elements insensitivity and sample radiation exposure.X-ray CT and X-ray micro-CT have a wide range of applications, not only for obtaining a variety of information such as ingredient, structure, distribution, etc. but also for observing phenomena such as electrolyte cracking and cell expansion.In comparison, helical trajectory X-ray micro-CT and XRD-CT are more targeted and mostly applied to column batteries, providing extensive information and detailed images.Reaching these goals resulted in timeconsuming and high costs, along with the support of various software technologies.Helical trajectory X-ray micro-CT can be used to detect slight expansion in all directions of the electrodes inside cylindrical batteries, while XRD-CT can be used to monitor the internal temperature of operating batteries.With these, we can choose the appropriate X-ray CT technique according to the batteries, inspection conditions, and purpose.

Neutron Scanning Imaging
Although neutron scanning imaging is similar to X-ray imaging, the interaction of neutrons with materials is different from that of X-rays and the two can be used in combination.Neutrons are extremely sensitive to light elements and are strongly absorbed by light elements while passing through an object, but their interaction with metallic elements is modest. [39]Therefore, it can create a lined image by analyzing the amount and intensity of transmitted neutrons. [40]As shown in Figure 6a, a neutron scanning imaging instrument mainly consists of five parts: neutron tube, pinhole, charge-coupled devices detector, rotation stage, and testing cell.The spatial resolution is the key to limiting The first two images are before cycling and the others are after cycling under 0 °C.Reproduced with permission. [35]Copyright 2019, Elsevier.c) Micro-CT image of the LIB at y-z cross-section.d) The thickness of 16 layers of electrodes in each axial direction from different vertical height sections before and after cell aging.Different axial directions are shown in the right upper image.Reproduced with permission. [37]Copyright 2022, Elsevier.the development of neutron scanning imaging technology, but the high penetration depth of neutrons makes it easier to investigate thick samples. [41]he transport of lithium is critical in LIBs and directly affects the performance of the battery.Therefore, the investigation of lithium distribution in the battery can reveal the diffusion movement of lithium during discharge and charge, which can indicate the direction for improving the performance of the battery.Direct observation of lithium distribution through normal detection techniques is difficult as the transport takes place inside the battery, but can be achieved with the help of neutron sensitivity to lithium elements.Bilheux et al. explored the lithium distribution within coin cells using neutron computed tomography. [42]As shown in Figure 6b, lithium distribution was nonuniform in different cross-sections of the cells discharged at different rates, especially at the top and the center of the electrode.And a faster rate had led to a relatively more nonuniform distribution.However, the distribution of lithium in different cross-sections of the cells charged at different rates was relatively more homogeneous (Figure 6c).It can be concluded that both the choice of charging and discharging test conditions and the location inside the battery have effects on the distribution of lithium ions.Therefore, both the battery testing and the design should fully consider the working conditions of the battery, such as the potential decrease of the battery in the discharge process may be caused by the uneven distribution of Li þ ions.
Battery performance can also be significantly impacted by the production process in addition to the internal structure.Electrolyte infiltration is one of the crucial parts of the production process of LIBs. [43]The electrolyte commonly used in LIBs is an SoC samples in bulk and in A, B, and C cross-sections.DC for discharge first and charge then while the number for the inverse of the rate.The colors represent the different neutron attenuation.Reproduced with permission. [42]Copyright 2018, Elsevier.organic solvent, which contains many hydrogen groups. [44]dditionally, the neutron signal is severely attenuated when passing through the electrolyte, which will show darker on the image and form a certain degree of lining with other battery components.Thus, Reinhart et al. utilized neutron imaging to investigate the electrolyte infiltration process in the pouch cell, and the whole infiltration process in the cell can be observed clearly. [45]s shown in Figure 7a, the electrolyte was initially concentrated at the bottom of the cell due to gravity, and gradually the electrolyte flowed upward in a U-shape as time went by.Besides, it was found that more electrolytes existed in the folds of the cell.Therefore, the pouch cell was sealed and exhausted after the infiltration process, which not only eliminated the bubbles and folds but also distributed the electrolyte uniformly.In addition, Reinhart et al. proposed a data processing method to eliminate image errors and explored the electrolyte infiltration pathway. [45]gure 7. a) Neutron images of the electrolyte infiltration process in the pouch cell at different times.Reproduced with permission. [45]Copyright 2016, Elsevier.b) Neutron images of the electrolyte infiltration process in the column cell under vacuum (left) and atmospheric (right) pressure at different times.Reproduced with permission. [46]Copyright 2018, Elsevier.c) Left: cell voltage-time (black) and gas volume-time (red) curves at C/10 and C/2.Right: cell neutron transmission images (green dots in the left diagram) at different cycle times.(LFP/LTO cell, LFP/graphite cell, LNMO/LTO cell, LNMO/graphite cell in order).Reproduced with permission. [49]Copyright 2015, Springer Nature.
However, Gilles et al. utilized neutron imaging to investigate the electrolyte infiltration process of the column cell. [46]The obtained image data were normalized and underwent further processing to make the infiltrated electrode more apparent in the image.We can conclude that vacuum injection infiltration is much faster than atmospheric pressure from Figure 7b, which shows that the cell is completely infiltrated at 47 min under vacuum conditions, while the center of the cell is still not infiltrated at that time under atmospheric pressure.Gilles et al. also investigated the infiltration rate of electrolytes in different directions and concluded that the electrolyte infiltration rate from the four sides to the center of the electrode is basically the same. [46]The judgment from neutron imaging can effectively improve infiltration production efficiency and cell performance.
Another important part of the production process of LIBs is chemical degassing, where there should be no gas inside the battery in theory.However, in practice, the performance is often disturbed by gas formation inside the battery. [47]The following are a few of the potential causes of gas formation.When the cell is overcharged, it may generate the lithium dendrite at the cathode and destroy the SEI film, making part of the electrolyte oxidized to generate gas.When the cell is overdischarged, it may produce precipitation at the cathode and turn the electrolyte organic solvent into gas.Besides, the electrolyte interface may have side reactions to generate gas. [48]A quick and accurate method to judge the presence of gas in the battery is required.Janek et al. proposed a method to calculate the gas volume and use neutron imaging to probe the gas production during the cycling of different pouch batteries. [49]The four groups were LiFePO 4 /Li 4 Ti 5 O 12 (LFP/LTO), LiFePO 4 /graphite, LiNi 0.5 Mn 1.5 O 4 /Li 4 Ti 5 O 12 (LNMO/LTO), and LiNi 0.5 Mn 1.5 O 4 / graphite cells.As shown in Figure 7c, the LFP/LTO cell did not generate any gas during cycling, because its working voltage was far behind the decompose voltage of the electrolyte. [50]While the LFP/graphite cell started to generate gas from the first cycle, the subsequent formation of SEI film prevents further decomposition of electrolytes. [51]The comparison showed that gas generation generally occurs at the cathode rather than the anode.As shown in Figure 7c, the LNMO/LTO cell continuously generated gas during the whole process of cycling. [52]Although the gas production pattern of the LNMO/graphite cell was similar to that of the LFP/graphite cell, the volume of gas generated from the LNMO/graphite cell was significantly larger than that of the other groups.It was inferred that the presence of dissolved metal ions at the anode caused the SEI film to be destroyed and resulted in a large amount of gas formation.Although the technique does not prevent the generation of gas, the analysis of the images provides the right selection of suitable materials to increase the cell lifetime.
As mentioned above, the expansion phenomenon cannot be ignored in the battery security problem, [53] and neutron imaging is another available option to monitor battery expansion.Gorsich et al. tracked the movement in the position of the aluminum current collector during the charging and discharging process of the pouch battery by neutron imaging to investigate the expansion phenomenon. [54]Lithium dendrite is another factor that seriously threatens battery safety except for battery expansion, which is a dendritic deposition product that may be formed in the negative electrode of lithium metal in battery usage. [55]e formation and growth of lithium dendrite will cause damage more than cell volume changes, as it is easy to form dead lithium which will affect the electrochemical performance and even cause battery short circuits (Figure 8a). [56]To avoid these situations, monitoring the growth of lithium dendrites and improving measures are necessary.Song et al. used neutron imaging and tomography to analyze the growth process of lithium dendrites in the battery. [57]The neutron imaging underwent various processing steps and was normalized, and the dark area in Figure 8b represented lithium for the large absorption of neutrons.The deposition of lithium at the cathode increased steadily as charging time increased.Tomography images (Figure 8c) showed the lithium deposition process more concretely, the lithium dendrites were clearly started from the edge of the diaphragm during charging and vanished during discharging.Song et al. also proposed a possible electrochemical mechanism to explain the occurrence of voltage drop and recovery of the battery after a short circuit. [57]This can help us to better understand the formation of lithium dendrites and to minimize this phenomenon.
In summary, neutron imaging is a transmission signal imaging technique that is similar to X-ray imaging not only in imaging modality and instrument composition but also in the integration of usage with other techniques.However, neutron imaging and X-ray imaging differ in properties and applications (Table 2).X-ray has shorter wavelengths and is sensitive to electron density, while neutron is sensitive to nuclear density and light elements.Consequently, X-ray imaging has more energy, deeper penetration, and higher image resolution.Neutron imaging can be applied to directly observe the hydrogen-containing electrolyte infiltration, the lithium distribution, and the growth of lithium dendrites.In addition, neutron imaging can also distinguish between isotopes for more precise investigations.Comparison of these two imaging techniques facilitates a deeper understanding and selection and provides insights for future NDT integration.

Ultrasonic Inspection
Ultrasound is a mechanical vibration wave with a frequency higher than 20 kHz that propagates across a uniform medium with qualities similar to other signals.Additionally, when the ultrasonic frequency rises, the rate of signal degradation accelerates. [58]The reflectance and transmittance of ultrasonic signals at the contact vary because the acoustic impedance of different media shifts.The acoustic impedance of solids and liquids is significantly greater than that of gases.Therefore, the ultrasonic signal will be substantially reflected at the gas-liquid or gas-solid interface, which is extremely sensitive to gases. [59]As shown in Figure 9a, an ultrasound imaging instrument mainly consists of three parts: an emitting probe, a receiving probe, and a testing cell.Depending on the receiving signal, the ultrasonic NDT techniques commonly used today can be divided into reflective and transmissive methods. [60]lectrolyte infiltration is one of the production processes of LIBs that can adjust to improve performance as mentioned previously.Diffusion between electrode sheets and penetration from electrode surface to electrode particle gap are two steps that make up the whole wetting process. [61]The former is short and the latter is long, and it is challenging to accurately determine the wetting time and wetting status without testing. [62]Ultrasound imaging is utilized to visualize this process which propagates differently in different media. [63]In a dry electrode, a solid electrode particle is the only propagation medium, whereas, in a wet electrode, an electrolyte can be another way (Figure 9b). [64]As a result, the ultrasonic signals obtained in the two situations are significantly different. [65]Dahn et al. performed an ultrasonic characterization of the battery with excess electrolyte, the green signal indicated that the electrolyte was well wetted, while the blue signal indicated that the electrolyte was not completely wetted. [64]In the beginning, the electrolyte fully surrounded the electrode.As time increased, the middle area of the electrode was gradually infiltrated.Deng et al. investigated the electrolyte injection volume and resting time of commercial batteries. [64]By comparing the testing findings as shown in Figure 9c, it can be determined that this battery requires just 0.8 mL of electrolyte Figure 8. a) Representative risks from lithium dendrites in batteries.Reproduced with permission. [113]Copyright 2020, Elsevier.b) Normalized neutron transmission images during charging.The colors represent the different neutron absorption coefficients.c) Tomographic 3D images of Li distribution during charging and discharging.Reproduced with permission. [57]Copyright 2019, American Chemical Society.filling and only 24 h of resting time, which can help to reduce the cost in the actual production process and ensure the normal use of the battery.Contrary to infiltration, the phenomenon of "reinfiltration" refers to a process where the electrolyte is initially well-infiltrated but gradually deteriorates throughout the battery's aging cycle. [64]attery aging is frequently accompanied by irreversible volume changes, while irreversible volume changes will hasten battery aging. [66]The battery may experience particle cracking, volume expansion, SEI film thickening, and other issues that increase the electrolyte infiltrating area, resulting in poor infiltrating of the initially wetted electrode and the phenomenon of reinfiltration. [67]This phenomenon is relevant to the aging of the battery, while battery aging is relevant to the DoD of the battery. [68]Dahn et al. investigated the capacity of batteries with different DoD after 23 000 h of aging cycles. [64]The battery with 100% DoD .Reproduced with permission. [64]Copyright 2020, Elsevier.
had just 71% of its initial capacity, and the ultrasound image revealed a wide range of signal loss, demonstrating that the electrolyte was seriously insufficient.In contrast, the 25% DoD battery had only an 8% capacity reduction, and the ultrasound image revealed only partial electrolyte infiltration at the corners of the battery (Figure 9d).These results clearly demonstrate the re-infiltration phenomena, which is the reason for the battery discharge capacity decreasing with increasing DoD at the same cycle time.
The battery management system (BMS) is an effective tool to ensure safe use of batteries.The state of charge (SoC), also known as the remaining battery power, which refers to the ratio of the remaining power to the rated capacity under the same conditions at a certain discharge rate, is an important parameter in BMS. [69]It is the threshold value for battery charging and discharging, and the battery charging and discharging conditions can be effectively protected by adjusting the SoC accordingly.In general, if the remaining power is too low, the current should be limited when charging and the power should be automatically disconnected when charging. [70]Since SoC is an electrochemical parameter and ultrasound is a mechanical vibration wave that reflects the outcome of particle vibration propagation, there is no direct correlation between the two. [71]However, several works examining the connection between SoC and ultrasonic signal variance discovered a linear link between SoC and the time-of-flight (ToF) results of ultrasonic signals (Figure 10a). [72]In addition, a hysteresis phenomenon in which the eigenvalues of the ultrasonic signal for the charging process are generally higher than those for the discharge process is observed during the experiments (Figure 10b). [73]The difference in acoustic impedance between the anode and cathode and the difference in stresses generated during the charging and discharging processes may both contribute to this phenomenon. [63,74]72a] As shown in Figure 10c, the peak height and ToF of the fast wave were constant with the change of SoC, while the peak height of the slow wave was proportional to SoC and ToF was inversely proportional to SoC.It was obvious that the slow wave was suitable for analyzing SoC.Another important parameter in BMS, the state of health (SoH) is defined as the ratio of the capacity of a cyclically aged battery to its initial capacity and is one of the most crucial factors for assessing the health of LIBs. [75]In most cases, a new battery is required to prevent accidents when SoH falls to 80%. [76]77b] As shown in Figure 10d, it was found that the SoH has a linear relationship with both two signals.Besides, Chang et al. proposed a new transition equation to estimate the state function and combined it with the extended Kalman filter to build a new model to estimate the battery SoH which found that better in line with the actual values compared to the voltage measurements. [78]Both SoC and SoH investigations are crucial to BMS and beneficial for battery security.
In summary, ultrasound imaging can be subdivided into three types based on the imaging signal, each of which has advantages, limitations, and applications (Table 3).Reflective ultrasound differs from transmissive ultrasound in the collection of signals for imaging, while other properties are consistent.Both are sensitive to gas and liquid which can be utilized to observe electrolyte infiltration and reinfiltration phenomena.However, the ultrasonic signal is weak in penetration, making it difficult to detect thick and complex-shaped cells, while failing to directly reflect the electrochemical properties of the sample as a mechanical vibration wave.And ToF connects the ultrasound signal with the electrochemical properties of the cell, which can be used to detect SoC and SoH.However, ToF is a characteristic that can only be received from ultrasound signals.

Resonance Signal Imaging
Unlike transmissive signal imaging, changes in conditions alter some signals of the sample.Imaging through these signals is the principle of resonance signal imaging.Different detection techniques require distinct changes in conditions.As shown in Figure 11, some require coordination between the applied signals and the change in conditions, while others require only changes in conditions.Two techniques that use magnetic field variations of resonance signals for imaging are described in the following sections.Although the imaging signals are similar, they vary in conditions leading to different characteristics and applications.

MRI
MRI and nuclear magnetic resonance (NMR) are similar in principle, which are techniques that collect electromagnetic waves released from the sample in an applied magnetic field and radiofrequency pulses, allowing for the generation of images of the interior structure. [79]MRI can further spatially resolve a wealth of molecular information available from NMR, it can noninvasively visualize the internal information.Although frequently used in the medical field, MRI has also been used for the analysis of battery materials in recent years. [80]As shown in Figure 12a, an ultrasound imaging instrument mainly consists of three parts: main coil, radio frequency (RF) coil, and cylindrical sample which is made for testing coin cells.And the graph can be performed from one-, [81] two-, [82] and three-dimensions [83] depending on the imaging signals and methods.Proton spin-lattice relaxation time T 1 and sample magnetization rate are the direct influence factors. [84]In addition, the sample edge is susceptible to signal distortion from external factors, and sample orientation can also result in quantitative errors and image distortion. [83]SBs have the potential to overcome the low capacity of the LIBs, but with an efficiency issue mainly caused by the interfacial resistance.The interfacial resistance is related to the structural match and SEI between the electrode and the SSE, which affects the lithium ions transport leading to higher resistance. [85]In addition, the diffusive polarization of lithium within the SSE may lead to short circuits. [86]Therefore, figuring out the distribution of lithium ions on SSBs facilitates better design to improve efficiency.Hu et al. employed MRI to investigate the lithium distribution of solid electrolytes and PEO-coated electrolytes during battery operation. [87]Figure 12b showed that the lithium was primarily concentrated in the middle part, and there were cracks and lithium deficiency in all cross-sections after cycling, mainly in the upper and bottom.Compared to the unmodified one, the PEO-coated electrolyte also had lithium deficiency but with higher and more stable Li þ density during the whole process (Figure 12c), which can conclude that the PEO-coated cell had better cycling stability.Besides, the XPS results showing the PEO coating was beneficial for lithium ions separation from the SSE was also consistent with the conclusion.These image results demonstrate that effect modification can improve the efficiency of SSBs and MRI is a useful tool for performance improvement explanations.Dendrites especially lithium dendrites frequently form during battery charging causing a safety problem with the usage.Unlike other detection techniques mentioned earlier, MRI can simultaneously quantify and provide spatial information on these microscopic lithium structures. [88]Although the thickness of RF penetration is extremely thin (skin depth), the microscopic porous structure is not an obstacle to signal propagation, and information on the newly formed microstructure can be obtained by comparing the signal intensity difference between the before and after images. [89]Grey et al. investigated the relationship between lithium dendrites and lithium concentration in electrolytes with MRI. [90]As shown in Figure 12d, two signals were applied for imaging, the 1D lithium ion projection signal of the electrolyte for concentration analysis and the chemical shift (CS) signal for lithium dendrite imaging.The lithium concentration decreased and the range of the CS signal expanded significantly at the cathode as charging proceeded.The study revealed that limited mass transport is the dominant mechanism governing dendrite undercharging current greater than the  7 Li 3D MRI images of Li 10 GeP 2 S 12 SSE at the top, middle, and bottom sections before (above) and after (underneath) cycling.c) 7 Li 3D MRI images of PEO-coated Li 10 GeP 2 S 12 SSE at the top, middle, and bottom sections before (above) and after (underneath) cycling.Reproduced with permission. [87]Copyright 2018, American Chemical Society.d) MRI images of 7 Li electrolyte concentration profile (top) and the 7Li CS (bottom) for the cell charged at 0.76 mA cm À2 .Reproduced with permission. [90]Copyright 2015, American Chemical Society.e) Magnetic field maps of the pouch cell during discharge and charge at 0.5 C. The values on each map represent the capacity lost/gained in the process and the color shades represent the strength of the magnetic field.Reproduced with permission. [95]Copyright 2018, Springer Nature.critical.Besides, Jerschow et al. compared the microstructural changes especially dendrites of the battery both before and after charging in 3D images directly by using MRI and chemical-shift imaging methods. [91]These explorations of lithium dendrites are useful for controlling the growth and safeguarding the battery.
SoC is an important factor to evaluate batteries and it is related to the internal electrochemical property as mentioned earlier.By using a magnetic field signal instead of an RF signal, a connection can be built between the image and the internal reaction of the battery. [92]As the lithiation of the material changes its magnetization, the magnetic field signal will also change during constant current charge and discharge. [93]The magnetic field variation can be measured not only to analyze the change in material magnetization rate but also to evaluate the battery SoC by comparing the change. [94]Jerschow et al. used NMR to gather the magnetic field signal of the battery during constant-current charging and discharging, which was imaged by echo time mapping. [95]The signal gradually decreased during discharge, while the opposite occurred for the charging process, as shown in Figure 12e.The SoC of the battery can be obtained by correlating the capacity lost with the magnetic field variation during the whole process, and the magnetization rate of the battery material can also be calculated by equation during lithiation.Furthermore, certain battery defects, such as electrode folding or missing, can be identified by the changes in the image. [95]n summary, MRI/NMR is performed by exciting sample atoms with the help of an applied magnetic field and radiofrequency pulses, which can be subdivided into two types depending on the collected signals (Table 4).For the magnetic field signal, current change is the main reason for the signal, which can be used to detect the lithium distribution and the battery SoC.However, the detection accuracy of magnetic field signals is limited because current variations are affected by multiple factors in combination.For the CS signal, mainly for the detection of specific elements, which are often utilized in batteries to monitor the formation and growth of lithium dendrites.However, the application is also limited to the specific element detected.Detection of the electrical properties of the battery can take into account the magnetic field signal, while the analysis of the variation in specific elements can take into account the corresponding CS signal.

Magnetic Field Scanning Imaging
Based on the fundamental Bio-Shaver rule, magnetic field scanning imaging gauges the electrochemical performance of batteries by detecting the change in magnetic field strength during battery usage.Combining the obtained magnetic field signal with the detected location can provide the tracking function for battery packs or large-volume batteries.As shown in Figure 13a, a magnetic field scanning imaging instrument mainly consists of three parts: three-axis pulleys, a magnetic probe, a shield, and a testing cell.The magnetic field intensity of the detection signal can be influenced by various factors, among which current and material magnetization rates are the direct ones, and the measurement height and cell spacing between each other are indirect.In general, lower measurement height and wider cell spacing can show more obvious magnetic field characteristics. [96]he battery converts chemical energy into current output, making current one of the most significant performances of the battery.And normal LIB current should remain relatively stable.Abnormal current changes in the battery will not only cause damage to the appliance but also represent a possible internal battery failure.The commonly used current detection methods, either coulomb counting or incremental capacity-differential voltage (IC-DV) analysis, both have defects in accuracy and cost. [97]Wu et al. used computational transformation analysis to relate magnetic field strength to the current variation of the battery, and the area of the detected battery was divided and then analyzed by the principal component approach. [98]With this method, batteries with different current variation trends were located at different positions, while batteries with the same current variation trend but different magnitudes could also be distinguished from their locations.
Conductivity is proportional to the current in a simple circuit normally which is used to describe the ability of electrons to flow through a substance. [99]Magnetic field scanning images can indicate not only cell current, but also further detect the conductivity with a constant magnetization rate.Kimura et al. produced a visual representation of the relationship between the conductivity inside the cell and the magnetic field generated during working by the instrument and equations. [100]A simple illustration of the whole process is shown in Figure 13b.We can get the magnetic field strengths H x (x,y,0) and H y (x,y,0) in the x and y directions of the cell by setting the boundary for the Fourier transform equation of the magnetic field.Additional magnetic field strength ΔH can be calculated from Equation (2), where h T is the electrode distance, h is the electrode thickness, σ(x,y) is the electrode conductivity distribution, φ(x,y) is the electrode surface potential distribution on two-dimensional planar, and σ 0 is the electrode conductivity.The magnetic field signals obtained from the cycling cell were converted into the conductivity distribution according to Equation (3).As shown in Figure 13c, the center of the cell saw the most change in conductivity distribution during cycling, and the abnormal conductivity region expanded with the number of cycles.
Actual commercial batteries are often connected in series with parallel battery packs to improve power and capacity. [101]owever, it will produce an unbalanced current if the capacity of the batteries in parallel battery packs is not consistent, which will heat the batteries and accelerate aging, causing some security issues. [102]Rapid location of defective cells in battery packs is of practical importance in the inspection.Li et al. proposed a model to evaluate the capacity consistency of battery packs using magnetic field scanning and a method to quickly locate the inconsistent capacity of multiparallel battery packs. [103]n summary, magnetic field scanning is similar to MRI/NMR, both of which directly reflect the electrical properties of the battery sample.Although both are imaged through magnetic field signals, the principle of imaging differs from each other.As shown in Table 5, MRI/NMR relies on applied magnetic field and radiofrequency pulses to trigger atomic leaps, while magnetic field scanning relies on current or magnetization rate variations to trigger magnetic field changes.Therefore, their applications are different.For MRI/NMR as mentioned earlier, it is also possible to utilize CS signal imaging for specific element investigations.For magnetic field scanning, without the necessity of external signals, allowing a wide area and rapid detection.
In comparison, MRI/NMR is now more mature in other fields such as medicine, while magnetic field scanning is more suitable for massive production.

Data Analysis
Except for the previous transmissive signal imaging and resonance signal imaging, data analysis is another approach  [100] Copyright 2021, IOP Publishing Ltd.for performing NDT on LIBs. [104]Although data analysis generally does not require additional testing instruments, the usage restrictions and range are relatively limited.Besides, data analysis is based on multiple and reliable data.But in some particular situations, data analysis can provide us with more effective and additional options.Hong et al. combined formula derivation and electrical resistance tomography (ERT) to investigate the relationship among the resistivity, the local cell temperature, and the SoC. [105]As shown in Figure 14a, both sides (A and B) of the cell had 12 electrodes connected to ERT for the experiment.The cell resistivity change with temperature was basically the same in all blocks of both A and B sides (Figure 14b), which can be roughly divided into three parts: dormant region (-20 to 0 °C), exponential region (0-50 °C), and exhausted region (50-80 °C).The variations of resistivity were not significant in the dormant region and the exhausted region affected by the low and high temperatures, while resistance and temperature exhibited a nearly positive linear connection in the exponential region.Therefore, Equation ( 4) calculating the temperature in the exponential region could be derived from the data, where T 0 is the critical temperature, ρ is the resistivity, A j and B j are the resistivity values in level j at 0 and 50 °C, α is the growth factor of resistivity.In addition, Figure 14c showed that the resistivity decreased with increasing SoC at different temperatures, but the variation was more obvious at low temperatures (0 °C) with SoC above 70%. .Reproduced with permission. [107]Copyright 2020, Elsevier.
To broaden the application and cut the cost, thermodynamics has been proposed as an alternative tool for battery material analysis which relies only on simple battery current, voltage, and temperature measurements. [106]Lee et al. used a nondestructive thermodynamic method to analyze the entropy evolution attributed to the electrodes in the cell, offering the possibility to monitor the aging of the electrodes. [107]The cell entropy spectrum was measured by an electro-thermodynamic method of A and B cells with different positive electrodes under constant current cyclic aging.As shown in Figure 14d, where R 2 in the first four plots represented the correlation between simulated and actual data, and R 2 in the last two plots represented the number of mutual relationships between A-type and B-type cells, a larger R 2 value indicated a stronger correlation.It can be inferred that the battery entropy of low SoC is dominated by the negative electrode of the battery, and the battery entropy of high SoC is dominated by the positive electrode of the battery.
Capacity fade is an important issue to discuss, but because the factors causing the problem are numerous and difficult to distinguish, there are few feasible approaches.Data analysis is an accurate and effective method of capacity degradation.Pan et al. utilized open circuit voltage analysis to diagnose the battery aging mechanism by quantifying the loss of active materials and lithium inventory. [108]As shown in Figure 15a, battery aging is presented as capacity fade, which is mainly caused by the loss of available lithium-ion inventory (LLI), the loss of active negative electrode material (LAM NE ), and the loss of active positive electrode material (LAM PE ).In addition, the electrodes will be in lithiated or delithiated states during the charging or discharging process as a result LAM NE can be classified into LAM liNE and LAM deNE , the same as LAM PE .As shown in Figure 15b, the terminal voltage (Q-V ) curve and the incremental capacity (IC) curve came out with the same result the battery capacity gradually decreases after 650 cycles.Further exploration of the capacity variations of the entire cell and the components of the cell revealed that the capacity of the negative electrode, the positive electrode, and the lithium inventory all declined with cycling.Among them, the variation of Q PE and Q Li was more significant and matched the trend of the whole battery capacity, which indicated that LAM PE and LLI had a major impact on capacity degradation.As mentioned above, exploration of LAM PE and LAM NE in different states separately from Figure 15c found that LAM liPE and LAM dePE , LAM liNE and LAM deNE had the same trend and were consistent with Q PE and Q NE , suggesting that both states of LAM had the same contribution to the plummeting stage of Q. dV/dQ curve is another approach to analyze from a quantitative perspective. [109]Ando et al. utilized dV/dQ curve analysis of NCM and lithium-manganese oxide (LMO) cells to figure out the effect of each cell component on the capacity under different conditions. [110]It was necessary to distinguish the effects of each cell component in the mixture.The dV/dQ curves of the simulated components were generally in agreement with the actual measurements, with the cathode Ca 1 peak for the LMO phase transition and the Ca 2 peak for the LMO transformation to NCM (Figure 15d).The anode An 1 and An 2 peaks represented different structures of graphite (Figure 15d). [111]The cells were tested under different conditions and the contribution of each component to the capacity decay was obtained separately according to the equation. [111]Figure 15e shows that the cathode degradation relied on the SoC while the anode degradation happened regardless of the test conditions.It also demonstrated that the SEI grew faster with increasing temperature and the formation of SEI was the primary cause of capacity decay at 100% to 70% of battery SoC. [112]

Conclusion and Outlook
NDT techniques have important practical applications for exploring the internal structure of LIBs and evaluating the working conditions of LIBs, which can effectively help practitioners in the development of LIBs to further improve battery performance.Besides, NDT techniques can also monitor the internal reactions of the working batteries in real time, which can help comprehensively understand the formation of defects to ensure battery security.Although the development and application of NDT have become more and more extensive in recent years, there is still more room for progress in terms of accuracy, integration, and simplification, which are some of the directions for the future development of NDT techniques.These three directions do not conflict with each other but rather can be combined to achieve better progress.
Different NDT techniques have corresponding applicability and restrictions which need to be carefully considered and selected from samples and circumstances before usage.As shown in Table 6, X-ray CT has a high-resolution image and is suitable for observing the internal structure of the batteries, but the interactions between X-ray and light elements are weak which means a blind detection area.However, neutron scanning imaging is sensitive to light elements and suitable for analyzing lithium dendrites and distribution, but with a high cost and a low resolution.Ultrasonic inspection is effective for determining the status of batteries and screening gases, but it is challenging to identify complicated irregular materials.MRI and NMR are useful to detect lithium which can help to understand the formation of dendrites, but the application in this field is not mature yet.Magnetic field scanning imaging is relevant to the electrical properties of the batteries, but the conversion software requires high and the usage range is small.Other inspection methods as supplements for some specific cases are restricted.Each NDT technique has advantages and limitations, and the accuracy of signal selection, the integration of detection functions, and the simplification of detection equipment are the requirements for the development of future NDT (Figure 16): 1) Accuracy involves the precise selection of inspection signals and decisions after full consideration of the test conditions and detection goals.The precise choice of the application scope fundamentally determines the results and should be given significant attention.For example, ultrasonic technology should be chosen for exploring the gas production phenomenon in batteries, X-ray and neutron imaging technologies should be chosen for observing the internal structure of thick samples, MRI and NMR technologies should be chosen for detecting the growth of lithium dendrites, and magnetic field scanning imaging technology should be chosen for analyzing the capacity difference of battery packs.Besides, the test conditions and final goals should also be emphasized in the process.For example, both neutron and ultrasound can be used to monitor electrolyte infiltration, but neutron imaging is more appropriate for complex cell structures.Neutron scanning, ultrasound, and MRI can all detect hydrogen, but only neutron detection can distinguish hydrogen and obtain exact conclusions in the presence of deuterium and tritium isotopes.Accuracy is the prerequisite and foundation of integration and simplification, and only when accuracy is guaranteed can integration and simplification be meaningful.At the same time, integration and simplification can also improve accuracy further; 2) each NDT method has certain limitations in function, and the integration of multiple techniques is very meaningful for practical applications.For example, X-ray and neutron have different sensitivities for elements of different molecular weights, and the integration of these two techniques can complement their respective shortcomings to horizontal extend detection range.Meanwhile, the integration of nondestructive techniques can also accomplish the longitudinal extension of the inspection, leading to more accurate and complete results.For example, magnetic field scanning imaging can quickly and precisely locate defects in a battery pack, while X-ray or neutron imaging can further observe the internal structure and variations of defects, and the combination of Reproduced with permission. [108]Copyright 2020, Elsevier.d) Voltage-capacity curve and dV/dQ curve of each component of the cell before the experiment.e) Contribution of each cell component to capacity decay under different SoC and temperature.(Cathode degradation in red, SEI formation in blue, anode degradation in green).Reproduced with permission. [110]Copyright 2018, Elsevier.
them can make the entire investigation process more convenient and accurate.The result of the integration can both improve accuracy and achieve simplification.Accuracy is the basis and goal of the integration, while simplification is an inevitable consequence of the integration; and 3) though NDT techniques have made some progress recently, the application in actual production is still lacking because of caused by the cost and volume of testing equipment.Therefore, simplifying the equipment in these two aspects is the way to achieve large-scale application.For example, the broad detection area of magnetic field scanning imaging is ideal for actual manufacturing inspection, which can simplify the instrument movement bracket to adapt the production line, resulting in a significant decrease in production costs and a considerable increase in efficiency.Besides, the simplified process fits at the same time as the integration process described previously.For example, instruments that combine X-ray and neutron imaging technologies not only apply both but effectively reduce the amount and the volume of needed instruments.Simplification is achieved with accuracy and integration guaranteed, and simplification has a beneficial effect on both.
In conclusion, NDT is a promising and growing technology for lithium battery research, development, and testing.The future of NDT technology will combine multiple methods to gather the necessary information in a piece of simple equipment.Therefore, this equipment will be both comprehensive and accurate.And with this, the security of LIBs will be obtained in real-time and the development of the secondary batteries field will usher in another breakthrough.

Figure 1 .
Figure 1.Introduction of different NDT signals to achieve battery performance and security.

Figure 3 .
Figure 3. a) X-ray CT device brief drawing.b) X-ray nano-CT image of different components (anode, separator, and cathode from left to right) and the slice of the cathode after DDS (red dotted rectangle) and SEM image of the same cathode.c) NMC 3D model CT characterization in different scales (colors represent different electrode materials, color shades represent the effective diffusion flux of lithium ions, and colors represent the orientation of NMC particles in order).Reproduced with permission.[25]Copyright 2020, Springer Nature.d) CT images of Li-S batteries.Volume maps of sulfur particles at different DoD (left) and DoC (middle).Volume maps of CBD phase, sulfur particles at 25.6% DoD and 100% DoC (right from top to bottom).Reproduced with permission.[27]Copyright 2018, American Chemical Society.

Figure 4 .
Figure 4. a) 2D cross-sectional CT images before and after cycling and SEM images after cycling of LAGP particles.b) Battery impedance and damage area versus charge transfer number.c) Above 2D cross-sectional CT images of LAGP particles at various cycle times.Underneath: 3D scanning images of LAGP particle cracks at various cycle times.The green arrow numbers represent the amount of charge transfer, and the blue arrow numbers represent the volume increase of the cracks observed from the whole particle.Reproduced with permission.[30]Copyright 2019, American Chemical Society.d) Structural characteristics of the active materials in the negative cross-section Gðx, y N1 , zÞ φ k N (red) and the positive cross-section Gðx, y P1 , zÞ φ k P (blue).Reproduced with permission.[32]Copyright 2018, Royal Society of Chemistry.

Figure 5 .
Figure 5. a) Pictures of connected batteries before and after the test.b) CT images of the same battery pack.The first two images are before cycling and the others are after cycling under 0 °C.Reproduced with permission.[35]Copyright 2019, Elsevier.c) Micro-CT image of the LIB at y-z cross-section.d) The thickness of 16 layers of electrodes in each axial direction from different vertical height sections before and after cell aging.Different axial directions are shown in the right upper image.Reproduced with permission.[37]Copyright 2022, Elsevier.

Figure 6 .
Figure 6.a) Neutron scanning device brief drawing.b) Neutron imaging of D10 (left) and D5 (right) samples with 0% SoC in bulk and in the A, B, and C cross-sections.D for discharge and the number for the inverse of the rate.c) Neutron imaging of DC10 (left) with 100% SoC and DC5 (right) with 85%SoC samples in bulk and in A, B, and C cross-sections.DC for discharge first and charge then while the number for the inverse of the rate.The colors represent the different neutron attenuation.Reproduced with permission.[42]Copyright 2018, Elsevier.

Figure 9 .
Figure 9. a) Ultrasound device brief drawing.b) Different propagation of ultrasonic waves in dry electrodes and electrolytes.c) Ultrasound imaging of electrolytes with different injection volumes and resting times.d) Capacity-time diagram and ultrasound images of batteries with different DoD at C/3 and 40 °C.Colors represent signal strength (left) and information change during operation (right).Reproduced with permission.[64]Copyright 2020, Elsevier.

Figure 10 .
Figure 10.a) Graphs of signal height versus delay time as battery SoC changed.The blue dashed line connected the fast wave height whereas the red solid line connected the slow wave height.b) Image of slow compressional wave signal height with SoC under different conditions.2C rate charging is shown as a black box and 4C rate discharging is shown as a red circle.The R 2 value indicates the degree of fitting.c) Fast wave (right) and slow wave (left) peak height and ToF signals with SoC images.The R 2 value indicates the degree of fitting.Reproduced with permission.[72a]Copyright 2017, Elsevier.d) Images of ToF and SA signals with SoH.The color represents the number of cycles.Reproduced with permission.[77b]Copyright 2018, Elsevier.
The above three transmission signal imaging techniques are different from each other, and the selection of different techniques and signals is necessary for effective detection according to different targets.

Figure 12 .
Figure 12. a) MRI device brief drawing.b)7 Li 3D MRI images of Li 10 GeP 2 S 12 SSE at the top, middle, and bottom sections before (above) and after (underneath) cycling.c)7 Li 3D MRI images of PEO-coated Li 10 GeP 2 S 12 SSE at the top, middle, and bottom sections before (above) and after (underneath) cycling.Reproduced with permission.[87]Copyright 2018, American Chemical Society.d) MRI images of7 Li electrolyte concentration profile (top) and the

Figure 13 .
Figure 13.a) Magnetic field scanning device brief drawing.b) Simple illustration of the testing process.c) Magnetic field intensity images and conductivity distribution images of the cell before the cycle test (green), after 100 cycle test (blue), and after 200 cycle test (red).Magnetic field intensity images are obtained by image superimposition and conductivity distribution images are obtained by the formula.Reproduced with permission.[100]Copyright 2021, IOP Publishing Ltd.

Figure 14 .
Figure 14.a) Model diagram of the ERT experimental setup.b) Resistivity versus temperature curves of different blocks in side A (above) and side B (underneath).The numbers represent different blocks.c) Resistivity versus SoC curves under different temperatures of block 1.Reproduced with permission.[105]Copyright 2015, MDPI.d) R 2 -SoC and |s|-SoC function diagrams of cell A and cell B. (A 1 cell, A 2 cell, B 1 cell, B 2 cell, A 1 and B 1 cells, A 2 , and B 2 cells in order).Reproduced with permission.[107]Copyright 2020, Elsevier.

Figure 15 .
Figure 15.a) Capacity degradation factors of LIB.b) Q-V curve, IC curve, entire cell capacity Q cell , positive electrode capacity Q PE , negative electrode capacity Q NE , and lithium inventory capacity Q Li in order under cycle.c) Loss of active positive/negative electrode material at different states under cycle.Reproduced with permission.[108]Copyright 2020, Elsevier.d) Voltage-capacity curve and dV/dQ curve of each component of the cell before the experiment.e) Contribution of each cell component to capacity decay under different SoC and temperature.(Cathode degradation in red, SEI formation in blue, anode degradation in green).Reproduced with permission.[110]Copyright 2018, Elsevier.

Table 1 .
Comparison of different types of X-ray CT.

Table 2 .
Comparison of neutron signal and X-ray signal.

Table 3 .
Comparison of different signals of ultrasound imaging.

Table 4 .
Comparison of different signals of MRI/NMR.

Table 5 .
Comparison of MRI/NMR and magnetic field scanning.

Table 6 .
Comparison of NDT techniques.