Discover three white paper that illustrate how microscopy and machine learning techniques enable state-of-the-art analysis of energy materials.

From the quantitative microstructural analysis of lithium-ion batteries to a 4D study of volumetric changes in a coin cell battery to investigating platinum nanoparticles in perovskite catalysts - scroll down and explore the use cases.

Quantitative Microstructural Analysis of State-of-the-art Lithium-ion Battery Cathodes
- Using ZEISS ZEN Intellesis

White Paper
2021

  • Motivation: Compare segmentation methods for quantitative analysis of lithium-ion batteries (LIB)
  • Technique: SEM imaging and machine learning (ML) based analysis of LIB cathode constituents
  • Detailed Description: Explaining the fundamental functionality of the ML-based approach
  • Outcome: Comparing classic thresholding to an ML-based approach the latter proved to be faster, more accurate as well as more reliable. ML was less prone to over or underestimation of segmented phases and therefore suited for repeatable and reliable quantitative microstructural analysis.

Investigating Sweet Spot Imaging of Perovskite Catalysts Bearing Exsolved Active Nanoparticles
White Paper
2022

  • Motivation: Improve catalytic chemical reactions using Pt nanoparticles in perovskite, accurately determine the catalytic ability of Pt nanoparticles
  • Technique: SEM imaging, finding optimal conditions for imaging of samples at high resolution
  • Detailed Description: Sweet spot imaging, high-resolution imaging at low keV, using Gemini electron optics with Inlens SE and ESB technology
  • Outcome: Observing nanoparticle decoration and better understanding the structure and morphology of nanoparticles. The paper provides more information on the subsurface and morphologically distinct regions of interest

4D Study of Silicon Anode Volumetric Changes in a Coin Cell Battery using X-ray Microscopy
White Paper
2019

  • Motivation: Study the microstructure of a coin cell battery to find pathways to increased capacity
  • Technique: Non-destructive, high-resolution X-ray microscopy (XRM), rendering of 3D volumes, volumetric analysis
  • Detailed Description: Micrometer-scaled analysis of novel anode material utilizing techniques like Resolution at a Distance (RaaD); volume rendering of regions of interest; displacement mappings after charge
  • Outcome: Detailed analysis of the microstructure, a method beyond electrochemistry, enabled the evaluation of volumetric changes in a silicon anode. The experiment showed the effectiveness of high resolution (XRM) to obtain meaningful and insightful volumetric information for the evaluation of new materials in batteries.
Learn how microscopy and machine learning techniques enable state-of-the-art analysis of energy materials in this collection of White Papers
Quantitative Microstructural Analysis of State-of-the-art Lithium-ion Battery Cathodes Using ZEISS ZEN Intellesis
Investigating Sweet Spot Imaging of Perovskite Catalysts Bearing Exsolved Active Nanoparticles
4D Study of Silicon Anode Volumetric Changes in a Coin Cell Battery using X-ray Microscopy