A model to test electrolysers’ performance before they exist

Our researcher Suhas Nuggehalli Sampathkumar (EPFL) helps us to understand a recently published paper about the importance of simulated membrane electrode assemblies (MEA) to better understand the efficiency of water electrolysis.

At ANEMEL we are working towards doing water electrolysis with anion exchange membrane electrolysers (usually abbreviated as AEMWE). What is the advantage over conventional electrolysers? We will produce green hydrogen without using critical raw materials such as platinum group metals (PGM) or fluorinated ‘forever chemicals’.

To achieve our goal, we need to design and develop electrolysers – that are pretty much like a backwards battery – and test the new materials. But tests take time, a lot of time. Therefore, sometimes researchers rely on other solutions like computational simulations – programmes that model the electrolysis process to virtually try out the different possibilities. This ensures the experimental efforts will focus on the most promising materials.

The latest peer-reviewed paper published by ANEMEL studies simulated membrane electrode assemblies (MEA) to better understand the efficiency of water electrolysis.

“Currently, in AEMWE technologies […] there is no clear state-of-the-art material,” explains Suhas Nuggehalli Sampathkumar, corresponding author and a member of ANEMEL at EPFL, Switzerland. “Therefore, you have a lot of research groups producing lots of materials, which means an infinite number of possibilities to try and test,” he adds. “The global picture of the paper was to arrive at the simulated model, to reduce the reliance on synthesis processes.” Now, we can calculate the performance of electrolysers without going into the fabrication phase, which is a tremendous advantage.

A scheme of an electrolyser that splits water into hydrogen and oxygen
A scheme of an electrolyser (Credits: ANEMEL)

The team at EPFL simulated a 1×1 cm² membrane electrode assembly (MEA) based in commercially available materials, already proven viable. A MEA is like a sandwich: the “meat” in the middle is a membrane made with polymers, coated with a slice of catalyst “bread” on each side. The membrane separates the hydrogen and oxygen gases produced during the electrolysis process. The catalysts accelerate the electrochemical reactions – each side-reaction requires different materials, specific for hydrogen and oxygen evolution.

ANEMEL researchers created this computational model considering certain simple parameters, such as membrane thickness or temperature. So, as Nuggehalli Sampathkumar explains, if someone develops a new material, it’s easy to validate its viability, simply inputting it to the MEA model, which will predict how it behaves in real life. The team has validated this approach experimentally. “Our main philosophy was to create an operating map ,” he says. “We must put boundaries to performance limits, and see whether these new materials will work,” he adds. Among other things, the team discovered that pH was the most influential parameter in the performance of these electrolysers.

Another interesting thing about the model is that, together with the electrolyser’s electrical features, it also considers the effect of gas in liquid media in the performance prediction – also known as fluid dynamics. To this date, only a small number of research studies on simulation have included it.

Representation of gas fractions at the simulated membrane electrode assembly (MEA) (Credits: K Lawand et al. )

Whereas this model is very useful, it’s also very tiny. Just one square centimetre – that’s smaller than a euro coin! And this has its own pros and cons. First, the smaller the simulation, the easier to implement – less demanding on the computer. Also, the parameters involved could work well with other MEAs. But, as the systems grow from a small scale to a large scale, the individual parameters will change. The larger the size, the more complicated simulations become, for reasons related to fluid dynamics and distribution. “We could create a larger model, but it would become seriously specific to our MEA,” says Nuggehalli Sampathkumar.

Despite this above , the paper provides a very interesting starting point. Now, the EPFL team will work on improving their model, creating collaborations with other consortium partners in ANEMEL. The MEA model has a great potential for technologies like “design-of-experiment” (DoE) and machine learning. It could function as a tool to test and predict the performance of materials for water electrolysis, beyond the the materials the consortium currently works on. The potential of a proper predicting model is now in our hands.