The distribution of patent impact in federal research: A citation analysis of LANL, SNL, and LLNL

The distribution of patent impact in federal research: A citation analysis of LANL, SNL, and LLNL

Journal article

1 volume.

This research note analyzes forward citations for patents granted to the three largest U.S. National Laboratories: Los Alamos (LANL), Sandia (SNL), and Lawrence Livermore (LLNL). Using USPTO data from 2005 to 2021, we examine the rarity of high-impact inventions within the federal research system. Grounded in March's (1991) exploration-exploitation framework, we define an Innovation Lottery model where mission-driven R&D is characterized by extreme uncertainty and stochastic breakthroughs. Our results reveal a consistent power-law distribution across all three labs, with scaling exponents (alpha) ranging from 1.88 to 3.02. Sandia (SNL) exhibits the most heavy-tailed distribution (alpha = 1.88), suggesting a robust alignment with dual-use commercial cycles, while LLNL's rapid decay (alpha = 3.02) reflects the friction of highly specialized Big Science. We find that up to 67.7% of patents receive only a single citation, representing the necessary search costs of discovery. Conversely, a tiny fraction of Black Swan outliers accounts for the vast majority of technological spillovers. Aligning with May 2025 GAO findings regarding patent quality, we argue that volume-based KPIs are fundamentally misleading. We propose reforming technology transfer through tiered CRADA structures and success-based royalty recapture to better optimize the head of the impact distribution.

Crossref

World Patent Information ; 85, June, 2026

World Patent Information

Oxford [England] : Elsevier Ltd., 2026.

eng

https://www.sciencedirect.com/science/article/abs/pii/S0172219023000108

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