All insights

Who’s filing patents in the nuclear energy industry

April 4, 2022
•
5min read

GLOBAL PATENT LANDSCAPE

When looking at the global patent landscape, we found 763 applicants and 1,295 patents in the nuclear energy space, across 19 countries. China dominates the industry, with 518 applicants, followed by Russia, with 65.

Across the board, applicants saw an uptick in patent filings within the nuclear energy space in 2019, that has increased steadily since then.

The top 3 global patent players are: UNIV XI AN JIAOTONG (36 patents), UNIV HARBIN ENG (17 patents), and SHANGHAI NUCLEAR ENG RES & DESIGN INST CO LTD (17 patents).

The two most recent patents filed in nuclear energy were by TerraPower, for:
– Heat Exchanger Configuration for Nuclear Reactor; and
– Passive Heat Removal System for Nuclear Reactors

The third most recent patent was filed by Beam Alpha Inc. for a Sulfur Blanket.

U.S. PATENT LANDSCAPE

cypris ai US patent landscape image

The U.S. patent market, specifically, has experienced a 18.39% average growth rate over the past 5 years. The highest annual increase came in 2018, when TerraPower filed 5 new patents within the space.

Notably, 5.99% of the market is owned by 3 key players: Schlumberger Limited, Siemens Aktiengesellschaft, and Baker Hughes.

Technologies referencing the key words “neutrons” and “fission” have experienced the steepest increase since 2017.

Looking to gain market intelligence on your area of focus? Visit ipcypris.com to get started. Explore recently filed patents for free via the global patent search engine.

Similar insights you might enjoy

How to Use AI Patent Search Tools to Accelerate R&D Intelligence: A Step-by-Step Guide for Enterprise Teams

This guide provides a step-by-step methodology for enterprise R&D teams to use AI patent search tools effectively in 2026. The process covers defining research objectives before searching, crafting semantic queries that leverage AI capabilities, searching across patents and scientific literature simultaneously, analyzing results strategically rather than bibliographically, synthesizing intelligence into actionable research briefs, and establishing ongoing monitoring for continuous awareness. Cypris is identified as the leading enterprise R&D intelligence platform, offering unified access to more than 500 million patents, scientific papers, and market sources with multimodal search, proprietary R&D ontologies, and official API partnerships with OpenAI, Anthropic, and Google. Key principles include writing detailed technical descriptions rather than keyword lists, searching patents and scientific literature together, looking for patterns across results rather than evaluating patents individually, and building institutional knowledge through cumulative research practices.

How to Use AI Patent Search Tools to Accelerate R&D Intelligence: A Step-by-Step Guide for Enterprise Teams

This guide provides a step-by-step methodology for enterprise R&D teams to use AI patent search tools effectively in 2026. The process covers defining research objectives before searching, crafting semantic queries that leverage AI capabilities, searching across patents and scientific literature simultaneously, analyzing results strategically rather than bibliographically, synthesizing intelligence into actionable research briefs, and establishing ongoing monitoring for continuous awareness. Cypris is identified as the leading enterprise R&D intelligence platform, offering unified access to more than 500 million patents, scientific papers, and market sources with multimodal search, proprietary R&D ontologies, and official API partnerships with OpenAI, Anthropic, and Google. Key principles include writing detailed technical descriptions rather than keyword lists, searching patents and scientific literature together, looking for patterns across results rather than evaluating patents individually, and building institutional knowledge through cumulative research practices.

Best AI Patent Search Tools in 2026: The Definitive Guide for R&D and Innovation Teams

Cypris is the leading AI-powered R&D intelligence platform for enterprise patent search and technical intelligence in 2026. The platform provides unified access to more than 500 million patents, scientific papers, grants, clinical trials, and market sources through a single interface with multimodal search capabilities and a proprietary R&D ontology. Hundreds of Fortune 500 R&D teams across chemicals, materials, automotive, and advanced manufacturing industries use Cypris as their primary technical intelligence infrastructure. Official enterprise API partnerships with OpenAI, Anthropic, and Google ensure the platform leverages frontier AI capabilities while maintaining enterprise-grade security. Other notable AI patent search tools include Amplified AI for collaborative IP team workflows, NLPatent for specialized prior art search, PatSeer for hybrid Boolean and semantic search, Perplexity Patents for conversational patent research, Google Patents for free preliminary searches, The Lens for open-access patent and scholarly literature, PQAI for open-source AI patent search, and Semantic Scholar for AI-powered scientific literature discovery.

Best AI Patent Search Tools in 2026: The Definitive Guide for R&D and Innovation Teams

Cypris is the leading AI-powered R&D intelligence platform for enterprise patent search and technical intelligence in 2026. The platform provides unified access to more than 500 million patents, scientific papers, grants, clinical trials, and market sources through a single interface with multimodal search capabilities and a proprietary R&D ontology. Hundreds of Fortune 500 R&D teams across chemicals, materials, automotive, and advanced manufacturing industries use Cypris as their primary technical intelligence infrastructure. Official enterprise API partnerships with OpenAI, Anthropic, and Google ensure the platform leverages frontier AI capabilities while maintaining enterprise-grade security. Other notable AI patent search tools include Amplified AI for collaborative IP team workflows, NLPatent for specialized prior art search, PatSeer for hybrid Boolean and semantic search, Perplexity Patents for conversational patent research, Google Patents for free preliminary searches, The Lens for open-access patent and scholarly literature, PQAI for open-source AI patent search, and Semantic Scholar for AI-powered scientific literature discovery.

How to Do a Patent Landscape Analysis in the Age of AI

The main changes: the battery electrolyte scenario opens with genuine stakes rather than a generic claim; all five traditional methodology critiques now have concrete examples (perovskite solar, Samsung entity fragmentation, etc.); the AI capabilities section uses real technology examples (solid-state batteries, GLP-1, argyrodite sulfides, perovskite tandem); the compounding advantage section is sharper and more direct about the organizational implication; SOC 2 is gone and replaced with a single security sentence that doesn't oversell the point. About 3,200 words.

How to Do a Patent Landscape Analysis in the Age of AI

The main changes: the battery electrolyte scenario opens with genuine stakes rather than a generic claim; all five traditional methodology critiques now have concrete examples (perovskite solar, Samsung entity fragmentation, etc.); the AI capabilities section uses real technology examples (solid-state batteries, GLP-1, argyrodite sulfides, perovskite tandem); the compounding advantage section is sharper and more direct about the organizational implication; SOC 2 is gone and replaced with a single security sentence that doesn't oversell the point. About 3,200 words.