Innovators in Energy Research Lead the Way Towards Sustainability

Microscopy Solutions for Energy Materials Research

Innovators in Energy Research Lead the Way Towards Sustainability

Microscopy Solutions for Energy Materials Research

Imagine the impact if we would find new ways for more sustainable energy technologies. Research and development of efficient devices such as batteries, solar cells, and fuel cells is crucial here, however, making this transition presents challenges.

Discover how innovators use advanced microscopy to reveal the connections between device, material microstructures and ultimate performance in these next generation technologies and point the way towards new breakthroughs in Energy Materials research.

In this interview, Prof. Joachim Mayer, RWTH Aachen, talks about materials as technology enablers and what we can expect to see in energy consumption and storage over the coming years.

Imagine the impact if we would find new ways for more sustainable energy technologies. Research and development of efficient devices such as batteries, solar cells, and fuel cells is crucial here, however, making this transition presents challenges.

Discover how innovators use advanced microscopy to reveal the connections between device and material microstructures and ultimate performance in these next generation technologies and point the way towards new breakthroughs in Energy Materials research.

In this interview, Prof. Joachim Mayer, RWTH Aachen, talks about materials as technology enablers and what we can expect to see in energy consumption and storage over the coming years.

Prof. Silke Christiansen

Fraunhofer Institute for Ceramic Technologies and Systems IKTS

Prof. Dr. Silke Christiansen

Our goal is to optimize energy materials properties from the macro to the atomic scale. We established a comprehensive workflow using electrons, ions, X-rays, light and probes in 2D and 3D. All is connected so data can be analyzed using software powered by machine learning to help us create a digital twin and intelligently drive materials optimization.

Silke Christiansen I Fraunhofer Institute for Ceramic Technologies and Systems IKTS, Forchheim, DE.

Energy systems like solar cells, fuel cells, and batteries contain many materials with varying properties, scales, and arrangements. Our goal is to control and optimize material and interface properties from macro to atomic scale with device manufacturers who optimize and control device performance. In our lab we established a comprehensive energy materials workflow which includes sample preparation, inert transfer, cryogenic environments, and full microscopic, spectroscopic, and bulk characterization using electrons, ions, x-rays, light, and probes in 2D and 3D. All this is connected so data can be analyzed correlatively and quantitatively using statistical tools and image recognition software powered by machine learning to help us create a digital twin and intelligently drive materials and device optimization.

Multi-modal characterization of a solid-oxide fuel cell (SOFC) stack with unwanted cracks
The image here shows multi-modal characterization of a solid-oxide fuel cell (SOFC) stack with unwanted cracks. SOFC electrolytes should be pore-free while the electrodes need porosity so gas can reach the catalyst. Fuel cells supplied electricity on the 1960s Apollo missions but even today improvements are needed. As SOFCs operate in severe conditions at elevated temperatures, microcracking due to thermal expansion can lead to early failure. Correlative microscopy offers a way out here because several analytical methods can be applied together in one work step.

For further reading: Wolz, BC, Jaremenko, C, Vollnhals, F, Kling, L, Wrege, J, Christiansen, S. X-ray microscopy and automatic detection of defects in through silicon vias in three-dimensional integrated circuits. Engineering Reports e12520, (2022): https://doi.org/10.1002/eng2.12520,


Prof. Paul Shearing

University College London (UCL)

Prof. Paul Shearing

In The Electrochemical Innovation Lab at UCL, we help drive towards a Net Zero carbon future by studying electrochemical power systems including batteries, fuel cells, and super-capacitors in order to improve performance, durability, and safety, and lower cost.

Prof. Paul Shearing I Royal Academy of Engineering Chair in Emerging Battery Technologies, Department of Chemical Engineering at University College London (UCL), UK.

Microscopy techniques are central to our research – we have spent the past decade building a library of data on materials, electrodes, and electrochemical devices with our microscopes running around the clock. This is a real exemplar of a multi-scale challenge and provides exciting opportunities for correlative microscopy. With increasingly sophisticated tools for in situ and operando microscopy, we believe that we can condense the time it takes from discovering exciting new materials, to their deployment in the real world.

Imaging and modelling of advanced Li-ion batteries
The image here is from a recent paper on imaging and modelling of advanced Li-ion batteries. Using high resolution X-ray, ion-beam, and electron microscopy techniques, we gain insight into the huge complexity of these devices. There is a critical relationship between material morphology and device performance – for example in the trade-off between energy and power density in batteries. With an improved understanding of the fundamental relationship between device performance and microstructure, we are increasingly equipped to tackle these complex challenges.

Image courtesy of: Lu, X., Bertei, A., Finegan, D.P. et al. 3D microstructure design of lithium-ion battery electrodes assisted by X-ray nano-computed tomography and modelling. Nat Commun 11, 2079 (2020). Provided by Springer Nature. https://doi.org/10.1038/s41467-020-15811-x, licensed under CC BY 4.0: https://creativecommons.org/licenses/by/4.0/


Dr. Roland Brunner

Materials Center Leoben

P.D. Roland Brunner

In my group we focus on image-based material characterization and analysis in energy storage and microelectronics. To do this we develop and apply advanced imaging and analysis workflows leveraging artificial intelligence to characterize the structural and chemical properties across the cell- and microstructure-levels from mm to nm in 2D as well as 3D.

P.D. Roland Brunner I Materials Center Leoben, AT

In batteries, for instance, the electrochemical properties and morphology of the materials directly impact performance. Therefore, a deep understanding of structure-property relationships across length scales is key to improving the devices and materials within. Silicon-based anode materials hold promise for next-generation Li-ion batteries due to the high theoretical capacity, but challenges remain around capacity fade and cell life expectancy. Proper material engineering is essential here and an accurate representation of the complex multi-phase microstructures helps guide materials synthesis and processing efforts.

To do this we develop and apply advanced imaging and analysis workflows leveraging artificial intelligence to characterize the structural and chemical properties across cell- and microstructure-levels from mm to nm in 2D as well as 3D.

ZEISS Atlas 5 connected software environment showing the 3D XRM (ZEISS Xradia 610) and FIB-SEM data (ZEISS Crossbeam 550)
The image above shows a silicon-based anode material imaged using one such workflow correlating X-ray microscopy and focused ion-beam scanning electron microscopy in a connected software environment. Green Areas indicate the correlated volume of interests (VOIs) and arrows indicate the workflow steps. To understand the morphology of Si-based anodes we need high contrast nm-scale resolution and a field of view at the µm-scale. Correlative imaging approaches like this unveil the underlying structural and chemical evolution in 3D and are highly beneficial for battery research.

Image courtesy of: Vorauer, T., Kumar, P., Berhaut, C.L. et al. Multi-scale quantification and modeling of aged nanostructured silicon-based composite anodes. Commun Chem 3, 141 (2020). Provided by Springer Nature. https://doi.org/10.1038/s42004-020-00386-x, licensed under CC BY 4.0: https://creativecommons.org/licenses/by/4.0/


Learn More on How Microscopy Can Be Applied in Energy Materials Research

In this 42-page WILEY ebook, get an overview of:

  • Microscopy techniques & their benefits for energy materials research
  • Microscopy-enabled accomplishments in energy materials research (11 short versions of selected peer-reviewed articles from various WILEY journals)
  • Current challenges & future developments in microscopy applications for energy materials (Interview with Professor Paul Shearing from the University College London)
WILEY Energy Materials Research Ebook

Download the Wiley Ebook Here

Unable to load form.

Recommended Microscopy Solutions


ZEISS Xradia 620 Versa

3D X-ray Microscopy for Faster Sub-Micron Imaging of Intact Samples

Unlock new degrees of versatility for your scientific and industrial research with the most advanced 3D X-ray microscope models in the ZEISS Xradia Versa family. Building on industry-best resolution and contrast, ZEISS Xradia 610 & 620 Versa expand the boundaries of your non-destructive sub-micron scale imaging.

Learn more about ZEISS Xradia 620 Versa

ZEISS Xradia Ultra Family

Nanoscale X-ray Imaging

Synchrotron X-ray nanotomography enables non-destructive 3D imaging at the nanoscale but you have to apply for very limited beamtime. What if you didn’t have to wait for synchrotron time anymore? Imagine if you had synchrotron capabilities in your own lab. With the ZEISS Xradia Ultra family, you have 3D non-destructive X-ray microscopes (XRM) at hand that deliver nano-scaled resolution with synchrotron-like quality.

Learn more about the ZEISS Xradia Ultra Family

ZEISS GeminiSEM

Field Emission Scanning Electron Microscope

ZEISS GeminiSEM stands for effortless imaging with sub-nanometer resolution. Use it for your most demanding projects in materials and life science. Innovations in electron optics and a new chamber design let you benefit from better image quality, usability and flexibility. Combine excellence in imaging and analytics. Take sub-nanometer images below 1 kV without an immersion lens. Discover three unique designs of the Gemini electron optics. Explore, how the GeminiSEM family answers all your imaging and analytical needs.

Learn more about ZEISS GeminiSEM

ZEISS Crossbeam

Your FIB-SEM for High Throughput 3D Analysis and Sample Preparation

Combine imaging and analytical performance of a high resolution field emission scanning electron microscope (FE-SEM) with the processing ability of a next-generation focused ion beam (FIB). You may be working in a multi-user facility, or an academic or industrial lab. Take advantage of ZEISS Crossbeam’s modular platform concept and upgrade your system with growing needs, e.g. with the LaserFIB for massive material ablation. During milling, imaging or when performing 3D analytics Crossbeam will speed up your FIB applications.

Learn more about ZEISS Crossbeam

ZEISS Atlas 5

Master Your Multi-scale Challenge

Create comprehensive multi-scale, multi-modal images with a sample-centric correlative environment using Atlas 5. This solution extends the capacity of your ZEISS SEM, FE-SEM (field emission scanning electron microscope) or FIB-SEM (focused ion beam). Efficiently navigate and correlate images from any source, e.g. light- and X-ray microscopes. Take full advantage of high throughput and automated large area imaging. Unique workflows help you to gain a comprehensive understanding of your sample. Its modular structure lets you tailor Atlas 5 for your everyday needs in materials research.

Learn more about ZEISS Atlas 5

ZEISS Advanced Reconstruction Toolbox

Better image quality, higher throughput

ZEISS Advanced Reconstruction Toolbox (ART) introduces Artificial Intelligence (AI)-driven reconstruction technologies on your ZEISS Xradia 3D X-ray microscope (XRM) or microCT. A deep understanding of both X-ray physics and applications enable you to solve some of the hardest imaging challenges in new and innovative ways. Discover how speed of data acquisition and reconstruction as well as image quality are enhanced without sacrificing resolution by using OptiRecon, two variants of DeepRecon and PhaseEvolve, the unique modules of ART.

ZEISS Advanced Reconstruction Toolbox

ZEISS ZEN Intellesis

Use the Power of Deep Learning to Easily Segment Your Images

ZEN Intellesis uses established machine-learning techniques powered by Python, such as pixel classification and deep learning to easily create robust and reproducible segmentation results, even for non-experts. You can now train the software once and then ZEN Intellesis can segment a batch of hundreds of images automatically. You save time and minimize user bias.

Learn more about ZEISS ZEN Intellesis