53 E-Mobility Engineering | July/August 2026 Thermal interface materials | Product focus is focusing on silicone-based twocomponent materials that offer very good robustness against swelling and vibration. Another approach centres on a highly adhesive silicone based on standard gap filler liquid technology, resulting in a TIM that is slightly less strong than a dedicated structural adhesive but strong enough for many structural applications if the system is mechanically robust overall. Interdependent properties High thermal conductivity is also difficult to achieve in a material that must have all the benefits of a traditional structural adhesive. The challenge in balancing thermal conductivity against adhesion, dielectric strength, mechanical compliance, durability and manufacturability is especially acute because these properties are deeply interdependent. Improving one often works against another, which is why it is critical for design engineers and scientists to discuss trade-offs and priorities early in the development cycle. In dealing with this kind of complexity, computational methods such as machine learning are increasingly valuable in material discovery. Such digital tools not only help optimise design and development cycles for leading material creators, but also give customers access to ‘data cubes’ to make use of digital twins in simulating their future battery systems. Use of AI is already helping with the creation of predictive formulations, effectively eliminating the need for real physical trial-and-error iterative formulations. However, AI needs to be fed with sufficient data and experience for it to work effectively. The challenge with formulating new TIMs is that datasheet values alone don’t provide sufficient information. Among the many additional factors to be considered are surface quality and structure, thermal contact resistance, compression behaviour, and interaction within the complete system. As more data become available, however, it should become much easier to predict TIM performance and tailor it for a given application. The goal is not necessarily for AI to generate the formulation of a material directly, rather it would be more practical for it to define and optimise the requirements. Once the desired performance parameters are clearly described, the TIM manufacturer can then use AI models as tools to support material R&D. That said, the industry is still a long way from a world in which an engineer can enter a set of requirements and become an important trend for specific applications, with each layer optimised for its individual function. Another perspective is that the next generation of composites should be centred on novel polymer networks designed to create stronger, more efficient interfaces with both fillers and substrates. Although it is tempting to focus on one or two headline properties, high-performance materials must satisfy a much broader and often competing set of requirements. The real challenge lies in achieving that balance in a way that delivers reliable performance while enabling robust, high-throughput manufacturing. In cell-to-pack battery designs, the TIM has to serve as a thermal bridge, a structural adhesive and an electrical insulator at the same time. This requirement is pushing development priorities further in the direction of TCAs. Here, the challenge is to find the optimum balance between bonding strength and elasticity when used to join various surfaces and the materials used in next-gen batteries. The change in TIM development occasioned by cell-to-pack architectures is moving away from maximising thermal conductivity to balancing thermal, mechanical and dielectric reliability over the battery’s service life. The material has to wet large surfaces, compensate for tolerances, bond or support the cells, survive vibration and ageing, and still maintain electrical insulation under compression, humidity and thermal cycling. The property most difficult to achieve without trade-offs is usually mechanical/ structural performance. Once a TIM becomes more adhesive or load-bearing, it tends to become stiffer, harder to rework, more stress-inducing and sometimes less tolerant to cell swelling. Increasing filler content improves thermal conductivity, but can hurt elongation, processability and dielectric robustness. Choosing the right polymer can make a significant difference, and one company Requirements for TIMs increasingly include durability of 15 years or more on bumpy roads and in humid, salty environments, followed by reliable debonding (Image: Parker)
RkJQdWJsaXNoZXIy MjI2Mzk4