The most important materials in lithium-ion batteries are the “active” particles which store and release lithium ions during charging and discharging, as they store energy in these devices. To design batteries for any potential application, scientists must understand the dynamics of ions in active particles. However, conventional methods of studying lithium-ion dynamics cannot follow, at sub-micron resolution, the rapid changes occurring in batteries that charge in minutes. These are being developed for emerging applications such as fast charging vehicles and flying taxis. In a newspaper in Nature, good weather et al.1 report a technique which makes it possible to visualize such a rapid dynamic.
Lithium-ion batteries consist of two porous electrodes (positive and negative), made of active particles, carbon and a binding material. The carbon provides the necessary electronic conduction and the binder holds the other materials together like a glue. Batteries also contain an electrolyte, which provides a conduit through which ions can travel from one electrode to another.
Battery applications can be classified based on their runtime – for example, portable electronic devices require batteries that last 10 hours or more, and electric vehicles should be able to drive for 6-8 hours. To track the internal ionic dynamics of batteries for each of these operations, researchers must image the associated physical and chemical interactions at least ten times faster than run time. This is equivalent to selecting a camera shutter speed suitable for sports shooting: if the shutter speed is too slow, the camera produces blurry images. In the context of batteries, the physical aspects of interest are the geometry of the active particles and the structure of the porous electrodes, while the key chemical process is the evolution of ion concentrations in the active particles and the electrolyte.
Each battery imaging technique has its own characteristic image acquisition time – this determines which battery operations can be tracked accurately. Techniques previously available2–8 take a few minutes to acquire an image, and therefore can only capture processes that take place over several hours.
Happy time et al. customized an optical microscopy technique, previously used in biology9, to follow the movement of lithium ions in the active materials of batteries. In this approach, a laser beam is projected onto electrochemically operating battery particles while they store or release lithium ions, and the scattered light is analyzed. The local concentration of electrons in these particles changes as more lithium is stored, which in turn changes the diffusion pattern. Therefore, the time course of the scattering signals at each position on a particle correlates with the local change in lithium concentration (Fig. 1).
Notably, the image acquisition time for the technique of Merryweather and colleagues is less than 1 second, which allows the examination of processes much faster than was previously possible. However, having a short acquisition time is not the only requirement when studying battery operation. Imaging techniques also need to be able to study batteries during operation and have reasonable spatial resolution – less than a micron resolution is needed to track what’s going on in an active particle. The authors’ technique also meets this requirement. Additionally, the technique can map ion dynamics at the electrode scale, comparing the change in ionic concentration in active particles that are spatially separated in the electrode.
Almost all active materials that store lithium or other ions undergo electronic changes as the ion concentration changes, and therefore can be studied by this technique. The variation over time of ion concentration in active particles is poorly understood, as conventional techniques cannot directly follow changes in local concentration across a particle during rapid operation. By solving this problem, the method of Merryweather and colleagues will help researchers validate hypothetical mechanisms of ion transport in these materials (see Ref. 10, for example).
It should be noted that the spatial resolution of the authors’ imaging technique is limited by a fundamental limit defined by the wavelength of light used, which means that shorter wavelengths are required to resolve problems. smaller details. The resolution is around 300 nanometers in the current study. Another caveat is that scattering is the cumulative effect of light interacting with only the first atomic layers of the particle. This approach therefore only captures the ionic dynamics in the 2D plane associated with these atomic layers. On the other hand, 3D information can be obtained using slower methods, such as X-ray tomography.3,5.
It will be exciting to delve deeper into the authors’ findings for individual particles and to study porous electrodes under far-from-equilibrium conditions associated with fast charging. For example, it was assumed11 last year, that inhomogeneous porous electrode structures lead to non-uniform distribution of lithium in the electrodes when batteries are charged within minutes. The technique of Merryweather and his colleagues could serve as a test for such predictions.
This method could also be used to examine solid electrolytes, interesting but poorly understood battery materials. If the scattering of light from solid electrolytes changes with local ionic concentration as it does in active materials, then the technique could be used to map how the distribution of ions in these electrolytes changes when an electric current passes them. crosses. Optical scattering could also be useful for studying other systems involving the coupled transport of ions and electrons, such as catalyst layers in fuel cells and electrochemical gas sensors.
In the future, it should be possible to quantify the relationship between scattering response and lithium-ion concentration by conducting careful scattering experiments using active particles of uniform composition. This correlation could then be used to convert the scattering signals to local concentrations. However, the relationship will not necessarily be the same for different materials and could be difficult to identify in each case. Machine learning techniques could be used to streamline the determination of these relationships and automate the analysis of diffusion responses.12.
The authors’ imaging technique also opens up the prospect of simultaneously following the chemical and physical (geometric) changes that occur in the active particles during battery operation. The evolution over time of the diffusion in a particle would reveal local changes in the lithium concentration, and the difference between the diffusion of a particle and that of other materials in a battery (such as the binder or the electrolyte ) could be used to determine the shape of the particle and how it changes over time. Such experiments would revolutionize the study of active materials (like silicon) which expand and contract noticeably as the lithium concentration changes within them. Materials of this type store much more energy than the active materials currently in use, and their use could reduce the weight of the battery. This would be particularly useful in electric vehicles, as it would allow longer ranges.
The research of Merryweather and his colleagues offers previously inaccessible information on the materials of batteries operating in conditions far from equilibrium. Their method of directly observing the evolution of active particles during operation will complement existing approaches, in which internal modifications are deduced from destructive tests of batteries. It could therefore revolutionize the battery-design cycle.
The author declares no competing interests.