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Join Us for the Next Battery2030+ Webinar: Can Computational Modelling Reveal What Experiments Can’t?
Join us online on 26 March 2026 at 15:00 CET for the next session of the Battery2030+ webinar series, exploring how computational modelling can help interpret experimental data and uncover hidden mechanisms in battery materials.
Our project, together with OPERA and ULTRABAT, is introducing this initiative under the framework of Battery2030+. The series, titled “Time and Length-Scale Operando Bridging Techniques to Study Battery Interfaces,” is designed to familiarise scientists with experimental methods that make it possible to study interfacial processes in real time.
Bridging Experiments and Modelling in Battery Research
A combination of complementary experimental techniques allows researchers to build a detailed picture of chemical structures and processes in the bulk, at surfaces, and across interfaces of energy materials. However, interpreting experimental data is often not straightforward. Multiple explanations can appear equally plausible, making it challenging to identify the true underlying mechanisms.
This is where computational modelling plays a crucial role.
Approaches such as Density Functional Theory (DFT) and molecular dynamics simulations provide powerful tools to support and refine experimental interpretations. They enable researchers to calculate structural, electronic, and transport properties, offering insights that are difficult—or sometimes impossible—to obtain experimentally.
By combining modelling with experimental techniques, scientists can better understand key processes such as ion transport, interfacial reactions, and material degradation in lithium-ion batteries and beyond.
What Can Modelling Reveal?
Computational modelling can help address several critical questions in battery research, including:
- Can oxygen diffusion mechanisms in SOFC materials be clarified by combining EXAFS with molecular dynamics simulations?
- Can DFT accurately predict XAS spectra for materials such as LiFeSO₄F, Li₂FeSiO₄, and NMC?
- Can modelling explain interfacial phenomena such as CEI-driven self-charge in polyanion cathodes?
- Can atomistic simulations predict the cycling behaviour of anode materials?
- Can DFT provide insight into degradation pathways in NMC and guide new experimental measurements?
These examples highlight how modelling not only complements experiments but also helps guide future research directions.
Webinar Format
Each webinar combines two complementary parts:
1️⃣ A short tutorial introducing one or more experimental techniques, followed by a brief break.
2️⃣ A research talk demonstrating how these techniques are applied in current studies.
This format supports both knowledge transfer and lively discussion among researchers from different disciplines.
Upcoming Webinar: Applications of Non-linear Spectroscopy in Battery Science
The upcoming session will feature:
Maria Alfredsson (University of Kent)
Topic: Can computational modelling reveal what experiments can’t?
In this webinar, the speaker will explore how computational modelling supports the study of energy materials, with a focus on lithium-ion batteries. The presentation will highlight how modelling can complement experimental observations, resolve ambiguities, and provide predictive insight into material behaviour.
The talk will cover key examples where modelling helps explain structural, electronic, and transport properties, offering a deeper understanding of processes that govern battery performance, stability, and degradation.
Building Collaboration Through Knowledge
This webinar series represents a joint effort by OPINCHARGE, OPERA, and ULTRABAT to bring together Europe’s battery research community around advanced characterisation methods, strengthen collaboration, and accelerate innovation in interface science