Battery Quality Control and Quality Assurance

Challenges for current Li-ion battery technologies include limited lifetime and energy density. Quantitative analysis of microscopic cracks in cathode grains can help researchers better understand battery degradation and improve performance. However, it is difficult to accurately analyze these micro-cracks without being an image processing expert.

Using Thermo Scientific Avizo2D Image Processing Software, we worked with one customer to build a simple four-phase detection analysis of SEM cross-sections of a lithium nickel manganese cobalt oxide (NMC) cathode. In this analysis, we identified and color-coded grains (purple), cracks in the grain (red), matrix or background (also called porosity, gray), and binder interface (green). Avizo Software was able to quantify the differing proportions of each material at six different slices of the cathode. We also developed a simple workflow that the customer can apply to similar SEM acquisitions.

Micro-computed tomography (microCT) instruments non-destructively generate 3D reconstructions of samples by placing them on a rotating stage and illuminating them with a micro-spot X-ray source. The transmitted X-rays influenced by the material are captured by a detector, creating a 2D projection (the tomogram). A series of these projections, collected as the sample rotates, can be recombined into a digital 3D model and analyzed using Avizo3D Software.

Production quality control. Non-destructive analysis of a battery by microCT and Avizo Software can identify possible internal defects that may have occurred during manufacturing, such as soldering, leakage, delamination, and porosity. 

Failure analysis of aging and degradation. Incremental changes occur to a battery during multiple charging cycles, leading to degradation. MicroCT enables non-destructive investigation of the mechanisms behind this process. The number of cycles is one of most important factors for a rechargeable battery and is impacted by changes to foil, anode, and cathode morphology (length, radial distance, etc.), as well as core leakage.

To fully understand mechanisms of degradation, a sample must be examined at different scales, from the cell level (~18 mm) to the electrode level (~80 µm) to the particle level (~10 µm). But correlating imagery from different instruments operating at different scales can be challenging. After identifying a region of interest (ROI) at the macro scale, acquiring micro-scale data about it on a different instrument can be like finding a needle in a haystack.

In this correlative defect analysis of a pouch cell battery, an X-ray scan by an industrial CT instrument was used to identify an ROI containing a defect. Avizo Software was used to define the ROI with georeferencing information, allowing a laser PFIB instrument to expose the defect. EDS analysis was used to characterize the defect composition, mapping the cobalt, manganese, nickel, and carbon content.

One important focus of Li-ion battery research is understanding why performance degrades over time. Research indicates that the solid electrolyte interphase (SEI) layer formed on the surface of the electrode is key to performance. The SEI layer, which is formed by the deposition of organic and inorganic compounds during the first several charge/discharge cycles, stabilizes the electrode from further decomposition and promotes reversible capacity. Because the SEI layer is complex, many analytical techniques can contribute to understanding its formation and behavior.

The figure shows a micrograph of the anode cross‐section after extraction from a used battery in an argon-filled glove box with the copper current collector in the center and anode material coated on both surfaces. Superimposed is the color-coded Raman image created on a Thermo Scientific DXR3xi Raman Imaging Microscope from the spectral differences shown by the inset Raman spectra. The Raman image clearly shows that the coating on one side of the copper current collector is dominated by carbon black (labeled red) while the other side has a much greater density of the active graphite phase (labeled blue).

This example demonstrates the advantage of Raman imaging over traditional single-point measurements. The major differences in the two coatings could easily have been missed by single-point measurements, depending on where the points were measured.