Scientific innovation increasingly depends on collaboration, yet the organizational structure that fosters breakthrough ideas remains poorly understood. Existing metrics - such as team size or compositional diversity - capture readily observable characteristics but not the deeper architecture of collaboration. We introduce Structural Diversity (SD): the extent to which a team bridges multiple distinct knowledge communities within its prior collaboration network. Using a century-scale dataset of 260 million scientific publications (1900-2025) and combining causal inference with a quasi-natural experiment based on a U.S. National Science Foundation policy change in 2012, we show that SD is a powerful and robust predictor of disruptive innovation, outperforming traditional team novelty indicators such as team freshness and edge density. Moreover, SD positively interacts with team size and is able to mitigate the well-known "curse of scale" by transforming scale from a liability into a resource for creative synthesis. We find that one mechanism underlying this effect is Disciplinary Integration (DI): teams with higher SD can more effectively combine heterogeneous knowledge into novel configurations. Our findings position SD as both a new theoretical construct and an actionable design principle for organizing scientific collaboration. By linking the architecture of team assembly to the dynamics of creative discovery, our work offers a structural explanation for how collective intelligence can be systematically engineered to foster disruptive innovation.

翻译：科学创新日益依赖于合作，然而，催生突破性思想的组织架构仍鲜为人知。现有指标——如团队规模或组成多样性——捕捉的是易于观察的特征，而非合作的深层架构。我们引入结构多样性（SD）：即一个团队在其既往合作网络中连接多个不同知识社群的程度。利用涵盖一个世纪、包含2.6亿篇科学论文（1900-2025年）的数据集，并结合因果推断与基于美国国家科学基金会2012年政策变化的准自然实验，我们表明，SD是颠覆性创新强大且稳健的预测因子，其表现优于传统团队新颖性指标，如团队新鲜度和边密度。此外，SD与团队规模呈正向交互作用，并能够通过将规模从负担转化为创造性合成的资源，来缓解著名的“规模诅咒”。我们发现，这一效应背后的一个机制是学科整合（DI）：具有较高SD的团队能更有效地将异质性知识组合成新颖的构型。我们的研究结果将SD定位为一种新的理论构念和一种可行的组织科学合作的设计原则。通过将团队组建的架构与创造性发现的动态联系起来，我们的工作为如何系统性地构建集体智能以促进颠覆性创新提供了结构性解释。