Building the materials foundation for AI

构建人工智能的材料基石

The AI boom is becoming a materials challenge. As AI pushes computing into new territory, the materials behind that infrastructure are becoming just as crucial as the algorithms running on it. Semiconductors and data centers are approaching physical limits around performance, thermal management, electrical efficiency, and reliability, creating new demands for materials that can do more at once. 人工智能的繁荣正演变为一场材料挑战。随着人工智能将计算推向新的领域，支撑这些基础设施的材料变得与运行其上的算法同样重要。半导体和数据中心在性能、热管理、电气效率和可靠性方面正接近物理极限，这为能够同时实现多种功能的材料创造了新的需求。

At the same time, AI is giving materials scientists new ways to search the enormous universe of possible molecules and accelerate the development of solutions. For Mike Finelli, chief technology and innovation officer and chief North America officer at Syensqo, that convergence is transforming what advanced materials can enable. “AI is now, from a material standpoint, really pushing semiconductors and the data centers to their physical limits,” he says. 与此同时，人工智能为材料科学家提供了探索庞大分子宇宙的新方法，并加速了解决方案的开发。对于 Syensqo 首席技术与创新官兼北美区总裁 Mike Finelli 而言，这种融合正在改变先进材料所能实现的目标。他说：“从材料的角度来看，人工智能现在确实正在将半导体和数据中心推向其物理极限。”

As requirements accumulate, including high temperature, purity, electrical performance, chemical resistance, plasma resistance, and long-term stability, materials move toward what Finelli calls the “top of the pyramid.” Beyond supporting AI innovation, he contends that advanced materials are “actually increasingly defining what’s going to be possible.” 随着高温、纯度、电气性能、耐化学性、耐等离子体性和长期稳定性等要求的不断累积，材料正向 Finelli 所称的“金字塔顶端”迈进。他认为，先进材料不仅在支持人工智能创新，而且“实际上正日益定义着未来可能实现的目标”。

That challenge is playing out across the infrastructure powering the AI surge. Syensqo is developing materials for high-voltage data center architectures, advanced sealing materials for semiconductor manufacturing, and thermal-management solutions including fluids for direct immersion cooling. Some of those innovations can also cross industry boundaries. Materials developed for electric vehicles, for example, can help address the higher voltage and energy-density demands that are emerging in data centers. 这一挑战正在支撑人工智能浪潮的基础设施中上演。Syensqo 正在为高压数据中心架构开发材料、为半导体制造开发先进密封材料，以及包括直接浸没式冷却液在内的热管理解决方案。其中一些创新还可以跨越行业界限。例如，为电动汽车开发的材料可以帮助解决数据中心中出现的高电压和高能量密度需求。

The definition of performance is also changing. More customers are expecting materials to meet technical requirements while reducing environmental impact. “Our goal is to remove the trade-off between performance and sustainability,” Finelli says. That means considering sustainability at the beginning of the research process instead of treating it as an additional requirement once a material has been developed. 性能的定义也在发生变化。越来越多的客户期望材料在满足技术要求的同时，还能减少对环境的影响。Finelli 表示：“我们的目标是消除性能与可持续性之间的权衡。”这意味着在研究过程的初期就要考虑可持续性，而不是在材料开发完成后将其视为一项额外要求。

AI is changing how those materials are discovered, too. Syensqo is using AI agents to digitally synthesize millions of potential molecular combinations, predict their performance and sustainability characteristics, and narrow them to a much smaller group for laboratory testing. The result, Finelli says, is the ability to go “broader, deeper, and faster” while giving scientists more time to solve complex engineering problems. 人工智能也在改变这些材料的发现方式。Syensqo 正在利用人工智能代理数字化合成数百万种潜在的分子组合，预测其性能和可持续性特征，并将它们缩小到更小的范围进行实验室测试。Finelli 说，其结果是能够实现“更广、更深、更快”的研发，同时让科学家有更多时间去解决复杂的工程问题。

Looking to the future, Finelli sees the possibility of a reinforcing cycle: AI helps develop materials that improve AI infrastructure, which in turn enables better AI to accelerate materials discovery. That feedback loop could create a cycle of innovation and expand what future technologies can achieve. “You end up in this accelerated materials, innovative cycle of materials innovation,” says Finelli. “That really excites me, and it gives us the opportunity to continue enabling technologies that will shape the future.” 展望未来，Finelli 看到了一个良性循环的可能性：人工智能有助于开发改善人工智能基础设施的材料，而这反过来又使更强大的人工智能能够加速材料的发现。这种反馈循环可以创造一个创新周期，并扩展未来技术所能达到的高度。Finelli 说：“最终你会进入这种加速材料研发、材料创新的循环中。这让我感到非常兴奋，它让我们有机会继续赋能那些将塑造未来的技术。”