As artificial intelligence (AI) surges, it is not just algorithms that are being pushed to the brink, but the very materials that form the backbone of our computing infrastructure. Semiconductors and data centers, once mere tools, are now the stars of the show, demanding advanced materials that can handle higher temperatures, greater purity, and enhanced electrical performance.

Mike Finelli, Chief Technology and Innovation Officer at Syensqo, notes that the convergence of AI and materials science is transforming what is possible. ‘AI is now, from a material standpoint, really pushing semiconductors and the data centers to their physical limits,’ he says. This push towards the ‘top of the pyramid’ in materials performance is crucial for advancing AI while also making the tech more sustainable.

The future is not just about performance; it is about sustainability too. Syensqo is developing materials that meet stringent technical requirements while reducing environmental impact. The company is using AI to digitally synthesize millions of potential molecular combinations, predict their performance and sustainability characteristics, and narrow them to a smaller group for laboratory testing. This approach allows for a broader, deeper, and faster exploration of materials, giving scientists more time to solve complex engineering problems.

Finelli envisions a reinforcing cycle where AI helps develop materials that improve AI infrastructure, which in turn enables better AI to accelerate materials discovery. This feedback loop could create a cycle of innovation, expanding the realm of what future technologies can achieve. 'You end up in this accelerated materials, innovative cycle of materials innovation,' he says, 'that really excites me.'