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The use of characterisation methods is vital to both ensure the quality of Li-ion batteries and for the development of the next generation of batteries. Oxford Instruments provides a range of detectors and analytical systems which are designed with battery applications from research through to manufacturing in mind.
| Manufacturing & Quality Control | Research & Development | ||
| Quality (purity) verification of powder material | Mapping of element distribution in battery materials | ||
| Automated identification of contaminants | Characterisation of texture and grain size | ||
| Manufacturing processes | Understanding of crack propagation and failure mechanisms | ||
| Complete characterisation of powder products (composition,particle size, and cleanliness) | Analysis of light elements and beam sensitive materials | ||
The materials used in the production of Li-ion batteries must be of high purity in order for the final products to have the specified performance and lifetime. High purity also prevents dangerous failures caused by metallic particles penetrating isolating barriers. Quality control and monitoring of materials throughout the manufacturing process is crucial as even very small amounts of contaminants can have catastrophic consequences.
AZtecBattery provides a fully automated solution for identifying and characterising contaminants in powder materials. Understanding the sources of contamination is the first step towards eliminating them and ensuring the quality of the manufactured product.
*Automated particle detection, measurement and EDS analysis
4k BEX image of a SiC anode contaminated by a piece of cathode
Routine QA/QC of powders often doesn't allow for elaborate sample preparation, as high throughput is key in production lines. Our response to this problem is Unity, our Backscattered Electron and X-ray detector. Unity introduces a new analytical approach: Backscattered Electron and X-ray imaging (BEX), enabling more flexible workflows and fast data acquisition with no shadowing effects (particulated samples often suffer from geometry effects as they are densely packed and tend to aggregate), combined with the benefits of high resolution imaging.
BEX also enhances the use of AZtecLive implementing faster sample inspection and analysis.
The key to successfully addressing research challenges around optimising battery performance, enhancing capacity, maximising power delivery, and minimising degradation lies in improved understanding of the materials on the nanoscale. Variations in chemistry, grain size and texture are related to the performance and stability of the final battery; being able to characterise the material is vital for ensuring the quality of the final product.
Many of the battery materials are beam sensitive, making analysis in SEM challenging. The latest technology used in the Oxford Instruments Symmetry S3 (EBSD) and Ultim Max (EDS) detectors has improved the sensitivity significantly, thereby providing a solution for characterisation of beam sensitive materials.
As battery technology is pushed further to the edge: we require more reliable, durable, long lasting batteries. This portfolio is a collection of application notes detailing Oxford Instruments solutions and how they have been used to help improve battery performance.
Li-ion batteries have been a key enabling technology over the last decade and are vital to further developments of EVs (Electrical Vehicles). Controlling the cleanliness of the raw materials is critical for ensuring the safety of the batteries. Automated analysis makes it fast and easy to identify contaminants and where the contaminants are being introduced.
Discover how EBSD can be used to obtain grain size and texture information from NCM (nickel, cobalt, manganese) cathode material. By characterising and comparing samples of different cathode materials at different stages of the battery’s lifetime, it's possible to link the performance with the microstructure and improve understanding of how the materials can be optimised.
New and existing materials for lithium ion batteries are being studied extensively with the aim of increasing their storage capacity and lifetime. While the SEM is an important tool in the study of these materials, characterising the distribution of Li still remains one of the main challenges.
Lithium Ion batteries are found in most mobile electronic devices (e.g. laptop computers, phones etc). They are the dominant battery technology due to their superior energy to weight ratio and lack of memory effect. They are also the primary battery type used in the latest generation of electric and hybrid cars.
With researches facing significant challenges in improving the performance of Lithium ion batteries, our group of experts explore how material characterisation is key to balancing the essential battery qualities of energy density, power density, cost, safety, and lifetime.
Learn how to characterise Li-based phases for next generation battery development using Scanning Electron Microscopy (SEM) combined with Energy Dispersive Spectroscopy (EDS) and Electron Backscatter Diffraction (EBSD). In the webinar, learn how you can monitor materials quality throughout the production process and investigate failure mechanisms and develop solutions.
Find out how electron microscopy can be combined with light and scanning-probe microscopy analyses on the identical positions in order to investigate structure-property relationships in optoelectronic devices and how all parts of a Li-ion battery can be characterised.
We will be giving you the chance to see the correlation of EDS, EBSD, EM, and AFM data on a variety of materials and life science applications, including duplex steel, battery materials, and biomedical implants in this webinar.
In this webinar, you will learn about the development of EBSD detector technology and, in particular, about Oxford Instruments' new Symmetry S2 EBSD detector. The presenters will explain some of the important technological developments behind the exceptional performance of the CMOS-based Symmetry S2.
Low energy microanalysis requires improvement in hardware: windowless, improved sensitivity, improved energy resolution. It also requires improved software for deconvolution..
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