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Silicon anodes have become the leading route to higher-energy lithium-ion batteries, and their patent landscape is distinctive because the field is organized around competing solutions to a single physical problem. Silicon's specific capacity is on the order of 4,200 milliamp-hours per gram, more than ten times the roughly 372 milliamp-hours per gram of graphite, which is why replacing some or all of the graphite with silicon raises energy density.¹,² At the same time, silicon expands by up to about 300 percent when it takes up lithium and shrinks again when it releases it, which pulverizes the material, breaks electrical contact, and repeatedly reforms the passivating solid-electrolyte interphase layer, degrading the cell.¹,³,⁴ The industry's approaches to managing that swelling define the landscape, and each is a distinct region of patenting: silicon oxide, or SiOx, whose in-situ lithium-silicate formation buffers expansion and improves cycle life at the cost of some initial capacity;⁵ silicon-carbon composites, in which silicon is confined within a porous carbon scaffold that accommodates expansion, the route that dominates today's commercial scale-up;⁶,⁷ silicon-graphite blends that ease drop-in adoption by adding modest silicon to conventional anodes;⁸ silicon nanowires and nanostructures, whose small dimensions tolerate strain; and engineered silicon films made by vapor deposition. Cutting across these are the surface coatings and binders that stabilize the passivating layer,³ the electrolytes tuned for silicon, and the manufacturing processes that produce the material at cost.
The landscape is advancing quickly and is concentrated, which raises the stakes across every layer. Silicon anodes have a decisive practical advantage over more distant next-generation chemistries: they drop into existing lithium-ion cell designs and manufacturing lines, using the same electrolytes, separators, and equipment, so they can raise energy density without a wholesale factory change.⁸ Governments have funded domestic silicon-anode manufacturing, and material makers and cell makers have moved from samples toward volume, with micro-silicon designs and nano-engineered composites converging as alternative routes to practical scale.⁶,⁹ Because the core approaches are heavily engineered, the composite, nanowire, film, and architecture estates create real freedom-to-operate considerations for new entrants. This shows in the record: across the Cypris corpus of more than 500 million patents and scientific papers, the silicon-anode set holds on the order of 21,740 families and grew from about 1,008 in 2020 to roughly 3,000 in 2024, with the most active assignees dominated by the CATL group, which sums to on the order of 1,716 families across variant strings, followed by LG Energy Solution, Samsung SDI, Gotion, and SVOLT, and China leading on geography by a wide margin ahead of South Korea, the United States, Germany, and Japan; 2025 and 2026 counts are partial because of the publication lag, and the route split in the top hits is dominated by silicon-carbon composite chemistries.
The strategic question is which approach and layer to back, and the white space sits where performance and cost are hardest to reconcile. Increasing the silicon content while controlling swelling and preserving cycle life is the central problem, and the composite, nanowire, film, SiOx, and architecture approaches each have open ground.¹,²,⁵,⁶ Durable surface coatings and a stable passivating layer, electrolytes formulated for silicon, and low-cost, scalable manufacturing are decisive and comparatively open layers, because they determine whether a high-silicon anode survives enough cycles at an acceptable cost, and improving the first-cycle coulombic efficiency, which is a persistent limitation of high-silicon designs, is a distinct and actively worked target.¹⁰ Full-cell integration and recycling adapted to silicon are further distinct layers. Reading the landscape by approach, layer, and owner, and tracking both the patents and the underlying materials research, is what separates a crowded region from an open one.
Where the silicon-anode white space is
Swelling management at high silicon content. Approaches that raise the silicon fraction while controlling expansion and preserving cycle life, across composites, nanowires, films, SiOx, and architectures, are the central problem and a high-value layer.¹,⁵,⁶
Durable coatings and stable interphase. Surface coatings and binders that stabilize the passivating layer as silicon expands and contracts are a decisive, actively worked layer.³
Silicon-tuned electrolytes. Electrolytes and additives formulated for silicon's volume change and surface chemistry are a distinct layer affecting lifetime and safety.
Low-cost, scalable manufacturing. Vapor-deposition, dry-process, and micro-silicon methods that produce silicon anode material at competitive cost are where deployment is decided.⁶
First-cycle coulombic efficiency. Raising initial coulombic efficiency, a persistent limitation of high-silicon anodes, is a distinct, actively worked target.¹⁰
How AI-powered landscape and white space analysis helps
Resolving a landscape organized around competing solutions to one problem, across several material and process layers, requires more than keyword search. AI-powered analysis addresses this with semantic search that clusters activity by approach, material, and layer across varied terminology, attribution that normalizes material-maker, cell-maker, and manufacturer filers to canonical entities including their many variant strings, and continuous monitoring that keeps pace with a fast-scaling field. Because silicon-anode advances appear in materials literature before they are patented, reading both patents and literature gives the earliest signal of where durable, low-cost anodes are emerging.
Where Cypris fits
Cypris runs patent landscape and white space analysis for fast-scaling materials fields such as silicon anodes across a corpus of more than 500 million patents and scientific papers, organized through a proprietary R&D ontology. The ontology clusters activity by approach, silicon-carbon composite, nanowire, film, SiOx, and cell architecture, and by layer, silicon material, coatings and interphase, electrolyte, and manufacturing, and normalizes material-maker, cell-maker, and manufacturer filers to canonical entities across their variant strings, so a team can resolve which approaches and layers are crowded and which remain open as white space, and can track new entrants as the field scales. Semantic search across patents and scientific literature connects filings to the underlying materials research, which is where silicon-anode advances appear first. Cypris Q, the platform's agentic layer, lets teams run landscape and white space analysis conversationally and chain the clustering, attribution, and gap analysis, and Agentic Monitoring tracks a defined approach over time and flags new patents and papers as they publish. Cypris provides enterprise API partnerships with OpenAI, Anthropic, and Google, and is built with enterprise-grade security. Cypris serves hundreds of enterprise customers across pharmaceuticals, chemicals, advanced materials, energy, and other regulated industries.
FAQ
What is the silicon anode patent landscape? The silicon anode patent landscape is the set of patents covering higher-energy lithium-ion anodes that use silicon in place of some or all of the graphite. It divides across competing approaches, silicon-carbon composites, silicon oxide, silicon-graphite blends, nanowires, films, and stiff cell architectures, plus coatings, electrolytes, and manufacturing. Each approach is a distinct region of patenting.
How much more lithium can silicon store than graphite? Silicon's specific capacity is on the order of 4,200 milliamp-hours per gram, compared with roughly 372 milliamp-hours per gram for graphite, so silicon can hold more than ten times as much lithium by weight. That difference is why replacing some or all of the graphite with silicon raises energy density. The trade-off is that silicon swells and cracks on charging.
Why do silicon anodes swell, and why does it matter? Silicon anodes swell because silicon expands by up to about 300 percent when it absorbs lithium and shrinks when it releases it, which cracks the material, breaks electrical contact, and repeatedly reforms the passivating surface layer, degrading the cell. Managing that swelling is the central engineering problem. The competing approaches are all ways to control or accommodate it.
What approaches does the landscape cover? The landscape covers silicon oxide, which buffers expansion in-situ; silicon-carbon composites, in which silicon sits in a porous carbon scaffold; silicon-graphite blends, which ease drop-in adoption; silicon nanowires and nanostructures; and engineered silicon films. Each manages expansion differently and carries its own IP. Freedom-to-operate and white space analysis must treat them separately.
Why are silicon anodes advancing faster than some other next-generation batteries? Silicon anodes are advancing quickly because they drop into existing lithium-ion cell designs and manufacturing lines, using the same electrolytes, separators, and equipment, so they raise energy density without a wholesale factory change. This drop-in advantage lowers the barrier to adoption compared with chemistries that require new manufacturing. It is a major reason the field is scaling.
Where is the white space in silicon anodes? The white space includes swelling management at high silicon content, durable coatings and a stable interphase, silicon-tuned electrolytes, low-cost scalable manufacturing, and first-cycle coulombic efficiency. The central problem is raising silicon content while preserving cycle life. The most open, high-value opportunities are in coatings, electrolytes, and manufacturing.
What software helps analyze the silicon anode patent landscape? Software for the silicon-anode landscape should cluster activity by approach and material layer, resolve material-maker, cell-maker, and manufacturer filers to canonical owners across variant strings, search patents and scientific literature semantically, and monitor a fast-scaling field continuously. Cypris does this across more than 500 million patents and scientific papers using a proprietary R&D ontology, semantic search, Cypris Q, and Agentic Monitoring.
Which teams use silicon anode patent landscape analysis? Silicon anode patent landscape analysis is used by R&D, innovation, IP, and strategy teams at battery, materials, automotive, and electronics companies, and their suppliers, as well as investors assessing the sector. It informs which approach to back, where to file, and where competitors are concentrated. Cypris serves hundreds of enterprise customers across advanced materials, energy, chemicals, and other regulated industries.
Endnotes
- Deng, X., Nanda, J., Li, W., et al. (2024). A comprehensive review of silicon anodes for high-energy lithium-ion batteries. Next Energy, 3. https://doi.org/10.1016/j.nxener.2024.100176
- Lu, T., Wei, Y., et al. (2024). Recent advances in interface engineering of silicon anodes. Energy Storage Materials, 66. https://doi.org/10.1016/j.ensm.2024.103243
- Cao, C., Abate, I. I., Persson, K. A., Toney, M. F., et al. (2019). Solid electrolyte interphase on native oxide-terminated silicon anodes. Joule, 3(3). https://doi.org/10.1016/j.joule.2018.12.013
- Ali, S., et al. (2024). Innovative solutions for high-performance silicon anodes for real-world applications. Nano-Micro Letters, 16. https://doi.org/10.1007/s40820-024-01388-3
- Liu, Z., Zhou, L., Mai, L., et al. (2018). Silicon oxides: a promising family of anode materials for lithium-ion batteries. Chemical Society Reviews, 47. https://doi.org/10.1039/c8cs00441b
- Liu, X., Wang, D., Sun, Y., & Jin, H. (2024). Advances and future prospects of micro-silicon anodes. Advanced Functional Materials, 34. https://doi.org/10.1002/adfm.202403032
- Shen, X., Feng, X., et al. (2022). Interfacial design of silicon/carbon anodes for rechargeable batteries: a review. Journal of Energy Chemistry, 76. https://doi.org/10.1016/j.jechem.2022.09.020
- Li, P., Kim, H., Myung, S.-T., & Sun, Y.-K. (2020). Diverting exploration of silicon anode into practical way: silicon-graphite composite. Energy Storage Materials, 35. https://doi.org/10.1016/j.ensm.2020.11.028
- Kazzazi, A., Bresser, D., et al. (2020). The success story of graphite as anode material, including silicon (oxide) composites. Sustainable Energy & Fuels, 4. https://doi.org/10.1039/d0se00175a
- Wu, F., Jiang, Z., Sun, Y., & Jin, H. (2021). A review on boosting initial coulombic efficiency of silicon anodes. Small, 17. https://doi.org/10.1002/smll.202102894
Long-duration energy storage has become essential to a grid built on wind and solar, and its patent landscape is distinctive because LDES is not a single technology but a set of competing approaches, each with its own chemistry or physics. Lithium-ion batteries dominate short-duration storage of a few hours but become uneconomical when the need is to store energy for tens of hours or several days, which is what bridging multi-day lulls in renewable generation requires. LDES fills that gap, and the approaches divide into distinct regions of patenting: metal-air batteries, especially iron-air designs that store energy by reversibly rusting iron and breathe oxygen from the air;¹ flow batteries, whose defining feature is that they decouple power from energy by storing charge in liquid electrolytes, so power scales with the stack and energy scales with the tank, across iron, vanadium, and organic chemistries;²,³,⁴,⁵ compressed-air storage; gravity-based storage; and thermal storage. Cutting across the approaches are the electrochemistry and electrodes, the electrolyte and the management of unwanted side reactions such as hydrogen formation, the stack and system design, and, for mechanical and thermal approaches, the engineering of the storage medium. Because a viable system depends on several of these layers, freedom-to-operate and white space analysis must span the approaches and the layers together.
The landscape is being pulled forward by public programs and by first commercial projects. In the United States, the Department of Energy's Long Duration Storage Shot has set a target to reduce the cost of grid-scale storage for systems that deliver ten or more hours of duration by 90 percent by the end of the decade, and technology-agnostic funding has followed for iron-air, iron and other flow, and mechanical and thermal routes.⁶ The approaches sit at different stages: iron-air designs have attracted major investment and government support and moved into first commercial pilots and grid connections;¹ iron flow and other flow chemistries are being deployed with proprietary solutions to long-standing electrolyte-degradation and side-reaction problems;⁷ vanadium flow remains the most mature flow chemistry;⁸,⁹ and organic flow chemistries offer a route to lower-cost, earth-abundant electrolytes with lifetime and stability as the central challenge.¹⁰,¹¹ Because applications publish about eighteen months after filing, the most recent electrochemistry and system filings are under-represented, so the current frontier is more active than granted-patent counts suggest.
The strategic question is which approach and layer to back, and the white space sits where cost, durability, and efficiency are hardest to reconcile. Across the Cypris corpus of more than 500 million patents and scientific papers, families explicitly tagged long-duration energy storage number on the order of 133, with a narrower LDES plus flow and metal-air cut returning about 76 families, and Form Energy recurring across the metal-air and oxyanion hits; because the LDES tag is recent, the underlying redox-flow patent base is far larger than this tagged slice, and per-chemistry queries are needed to size each route. For iron-air and metal-air batteries, raising round-trip efficiency and cycle life and managing the air-breathing electrode and side reactions are the central problems.¹ For flow batteries, electrolyte stability and cost and the suppression of hydrogen-forming side reactions are decisive, and organic and iron chemistries that use earth-abundant materials are a comparatively open, high-value area.²,³,⁴,¹⁰,¹¹ System integration that makes any of these dispatchable and affordable at grid scale, and the mechanical and thermal designs behind compressed-air, gravity, and thermal storage, are further distinct layers. Reading the landscape by approach, layer, and owner, and tracking both the patents and the underlying electrochemistry research, is what separates a crowded region from an open one.
Where the LDES white space is
Iron-air and metal-air electrochemistry.Raising round-trip efficiency and cycle life and managing the air-breathing electrode and side reactions are the central problems for the leading low-cost route.¹
Flow-battery electrolytes. Stable, low-cost electrolytes, especially earth-abundant iron and organic chemistries, and suppression of hydrogen-forming side reactions are a comparatively open, high-value layer.²,⁴,¹⁰,¹¹
Side-reaction and degradation management. Technologies that suppress hydrogen formation and electrolyte degradation improve efficiency and lifetime across the battery routes.⁵,¹⁰
System integration and dispatchability.Designs that make long-duration systems affordable, dispatchable, and grid-integrated are where deployment economics are decided.⁶
Mechanical and thermal storage.Compressed-air, gravity, and thermal designs are distinct regions of engineering IP with their own scaling challenges.
How AI-powered landscape and white space analysis helps
Resolving a landscape that spans several storage approaches, each with its own chemistry or physics, requires more than keyword search. AI-powered analysis addresses this with semantic search that clusters activity by approach, layer, and chemistry across varied terminology, attribution that normalizes developer and academic filers to canonical entities, and continuous monitoring that keeps pace with a policy-driven surge. Because LDES advances appear in electrochemistry and engineering literature before they are patented, reading both patents and literature gives the earliest signal of where durable, low-cost systems are emerging.
Where Cypris fits
Cypris runs patent landscape and white space analysis for multi-approach energy fields such as long-duration energy storage across a corpus of more than 500 million patents and scientific papers, organized through a proprietary R&D ontology. The ontology clusters activity by approach, metal-air, flow, compressed-air, gravity, and thermal, and by layer, electrochemistry and electrodes, electrolyte, stack and system, and mechanical and thermal design, and normalizes developer and academic filers to canonical entities, so a team can resolve which approaches and layers are crowded and which remain open as white space, and can track new entrants as the field scales. Semantic search across patents and scientific literature connects filings to the underlying electrochemistry and engineering research, which is where LDES advances appear first. Cypris Q, the platform's agentic layer, lets teams run landscape and white space analysis conversationally and chain the clustering, attribution, and gap analysis, and Agentic Monitoring tracks a defined approach over time and flags new patents and papers as they publish. Cypris provides enterprise API partnerships with OpenAI, Anthropic, and Google, and is built with enterprise-grade security. Cypris serves hundreds of enterprise customers across pharmaceuticals, chemicals, advanced materials, energy, and other regulated industries.
FAQ
What is long-duration energy storage? Long-duration energy storage is grid storage that can discharge for far longer than lithium-ion, from about ten hours to several days, to bridge multi-day gaps in wind and solar generation. It uses approaches such as iron-air and flow batteries, compressed air, gravity, and thermal storage. It complements, rather than replaces, short-duration lithium-ion.
Why isn't lithium-ion used for long-duration storage? Lithium-ion is not used for long-duration storage because, while excellent for short bursts of a few hours, it becomes uneconomical when the need is to store energy for tens of hours or several days. The cost of enough lithium-ion capacity to bridge multi-day gaps is prohibitive. LDES technologies use cheaper, often earth-abundant, materials for those durations.
What is the DOE Long Duration Storage Shot target? The US Department of Energy's Long Duration Storage Shot sets a target to reduce the cost of grid-scale storage for systems that deliver ten or more hours of duration by 90 percent by the end of the decade. It is technology-agnostic, covering electrochemical, mechanical, thermal, and chemical routes. It has anchored funding programs for iron-air, flow, and other LDES chemistries.
What approaches does the LDES landscape cover? The landscape covers metal-air batteries, especially iron-air, flow batteries in iron, vanadium, and organic chemistries, compressed-air storage, gravity storage, and thermal storage. Each uses different chemistry or physics and sits at a different maturity. Freedom-to-operate and white space analysis must treat them separately.
Where is the white space in LDES? The white space includes iron-air and metal-air electrochemistry, flow-battery electrolytes, side-reaction and degradation management, system integration and dispatchability, and mechanical and thermal storage. The routes sit at different maturity levels. The most open, high-value opportunities are in earth-abundant battery chemistries and in the durability and efficiency layers.
Why are side reactions such as hydrogen formation important? Side reactions such as hydrogen formation are important because in iron-air and iron flow batteries they lower efficiency and deplete the electrolyte's ability to store energy over time. Technologies that suppress or manage these reactions directly improve round-trip efficiency and lifetime. That makes side-reaction management a distinct, valuable layer.
What software helps analyze the long-duration energy storage patent landscape? Software for the LDES landscape should cluster activity by approach and layer, resolve developer and academic filers to canonical owners, search patents and scientific literature semantically, and monitor a policy-driven field continuously. Cypris does this across more than 500 million patents and scientific papers using a proprietary R&D ontology, semantic search, Cypris Q, and Agentic Monitoring.
Which teams use LDES patent landscape analysis? LDES patent landscape analysis is used by R&D, innovation, IP, and strategy teams at energy-storage, utility, materials, and grid companies, and their partners, as well as investors and policymakers. It informs which approach to back, where to file, and where competitors are concentrated. Cypris serves hundreds of enterprise customers across energy, advanced materials, chemicals, and other regulated industries.
Endnotes
- Fan, W., Lian, W., et al. (2026). Sustainable development of iron-air batteries as long-duration energy storage systems. Advanced Sustainable Systems, 10. https://doi.org/10.1002/adsu.202501101
- Sánchez-Díez, E., Flox, C., Marcilla, R., et al. (2020). Redox flow batteries: status and perspective towards sustainable stationary energy storage. Journal of Power Sources, 481. https://doi.org/10.1016/j.jpowsour.2020.228804
- Zhao, Y., Zhang, X., Yu, G., et al. (2023). Development of flow battery technologies using the principles of sustainable chemistry. Chemical Society Reviews, 52. https://doi.org/10.1039/d2cs00765g
- Zhang, H., & Sun, C. (2021). Cost-effective iron-based aqueous redox flow batteries for large-scale storage: a review. Journal of Power Sources, 493. https://doi.org/10.1016/j.jpowsour.2020.229445
- Zhang, H., & Sun, C. (2021). Review of first-generation redox flow batteries: iron-chromium system. ChemSusChem, 14. https://doi.org/10.1002/cssc.202101798
- U.S. Department of Energy (2021). Long Duration Storage Shot. https://www.energy.gov/eere/long-duration-storage-shot
- Li, Z., & Lu, Y.-C. (2020). Material design of aqueous redox flow batteries: fundamental challenges and mitigation strategies. Advanced Materials, 32(47). https://doi.org/10.1002/adma.202002132
- Rodby, K. E., et al. (2020). Assessing the levelized cost of vanadium redox flow batteries with capacity fade and rebalancing. Journal of Power Sources, 460. https://doi.org/10.1016/j.jpowsour.2020.227958
- Xu, K., Li, X., & Zhang, H. (2024). Flow battery for long duration energy storage: development, challenges and prospects. Chinese Science Bulletin, 69. https://doi.org/10.1360/tb-2024-0524
- Kwabi, D. G., Ji, Y., & Aziz, M. J. (2020). Electrolyte lifetime in aqueous organic redox flow batteries: a critical review. Chemical Reviews, 120(14). https://doi.org/10.1021/acs.chemrev.9b00599
- Rodby, K. E., Brushett, F. R., & Aziz, M. J. (2020). On lifetime and cost of redox-active organics for aqueous flow batteries. ACS Energy Letters, 5(4). https://doi.org/10.1021/acsenergylett.0c00140
Quantum computing has become the most dynamic segment of a rapidly expanding quantum patent landscape, and its structure is being set now, well before the technology is commercially mature. According to a joint study by the OECD and the European Patent Office, international patent families in quantum technologies grew sevenfold between 2005 and 2024 and have expanded at a compound annual growth rate of around 20 percent since 2014, far outpacing the 2 percent annual growth observed across all technologies, with quantum computing the field's most dynamic segment.¹ A peer-reviewed patent-landscape analysis puts additional numbers on the trend: about 29,700 quantum patents were granted worldwide between 2001 and 2025 at a compound annual growth rate near 14.5 percent, with more than 40 percent of those grants occurring in the last four years and the USPTO and EPO together now granting roughly 2,500 quantum patents per year.² An independent count across the Cypris corpus of more than 500 million patents and scientific papers shows the same acceleration concentrated in computing: quantum-computing patent families grew from roughly 250 in 2014 to more than 6,300 in 2024, with 2025 counts partial because of the publication lag. For R&D and IP teams, the strategic question is which qubit modality and layer to back, and where defensible positions remain, and both are patent-landscape questions.
The landscape divides across competing qubit modalities, each a distinct region of patenting with different owners and maturity. Across the Cypris corpus, superconducting qubits, including transmon and fluxonium designs, are the most heavily patented hardware route, well ahead of photonic qubits, which come second; a large and strategically critical error-correction and fault-tolerance cluster follows, then topological, semiconductor spin, and trapped-ion approaches, with quantum annealing a further distinct method. The assignee record maps onto that structure: the most active filers include IBM and Google, followed by Microsoft, D-Wave, Baidu, Fujitsu, Intel, and Northrop Grumman, alongside specialized firms such as IonQ, Rigetti, and Quantinuum, whose modality choices track the split between superconducting and trapped-ion routes. Error correction matters because current devices are noisy and a single logical qubit may require on the order of dozens or more physical qubits, making error-correction IP a foundational and heavily contested area. The academic and government roots of the field are visible in the patent record, as much foundational work was supported by national research programs.
Two features shape the strategic picture. First, quantum hardware patents behave more like semiconductor-device patents than software patents: they protect specific physical configurations, materials, and fabrication processes, and are consequently harder to design around, a distinction sharpened by the narrowing of software-patent eligibility since the US Supreme Court's Alice decision in 2014.³,⁴ A patent on a key fabrication step for superconducting qubits, for example, can affect every maker of that hardware, not only direct competitors. Second, the field is entering a more focused phase: the OECD-EPO analysis found that after a decade of exceptional growth the sector is entering a new phase in which rapid expansion gives way to more focused development and maturing technologies,¹ and bibliometric analysis of the field similarly reads it as maturing.⁵ National strategies reinforce this, with the OECD tracking close to 250 quantum policies across 40 countries and the European Union, and the US extending its National Quantum Initiative through the CHIPS and Science Act of 2022.⁶ Because applications publish about eighteen months after filing, the most recent activity is under-represented.
Where the quantum white space is
Error correction. Reducing the physical-qubit overhead per logical qubit is the central unsolved problem and a foundational, heavily contested IP area with room for high-value positions.
Less-crowded modalities. Photonic, semiconductor spin, and topological approaches are earlier and less densely patented than superconducting qubits, offering more white space.
Control and cryogenic systems. Scalable control electronics, cryogenic signal distribution, and calibration are enabling layers where activity is comparatively sparse.
Application and algorithm layers. Domain-specific quantum algorithms and applications, distinct from hardware, are a differentiated area away from the crowded hardware ground.
Fabrication processes. Because hardware patents are hard to design around, specific fabrication and materials processes are high-value, defensible targets.
How AI-powered landscape and white space analysis helps
Resolving multiple modalities and layers across a fast-moving, government-seeded field requires more than keyword search. AI-powered analysis addresses this with semantic search that clusters activity by modality and layer across varied terminology, attribution that normalizes corporate, academic, and government filers to canonical entities, and continuous monitoring that tracks a maturing landscape. Because quantum advances appear in scientific literature before they are patented, reading both patents and literature gives the earliest signal of where the frontier and the white space are moving.
Where Cypris fits
Cypris runs patent landscape and white space analysis for fast-moving deep-tech fields such as quantum computing across a corpus of more than 500 million patents and scientific papers, organized through a proprietary R&D ontology. The ontology clusters activity by qubit modality, superconducting, trapped-ion, photonic, semiconductor spin, and topological, and by layer, hardware, control, error correction, and algorithms, and normalizes filers to canonical entities, so a team can resolve which modalities and layers are crowded and which remain open as white space. Semantic search across patents and scientific literature connects filings to the underlying physics research, which is where quantum advances appear first, and captures the strong academic and government contribution. Cypris Q, the platform's agentic layer, lets teams run landscape and white space analysis conversationally and chain the clustering, attribution, and gap analysis, and Agentic Monitoring tracks a defined modality over time and flags new patents and papers as they publish. Cypris provides enterprise API partnerships with OpenAI, Anthropic, and Google, and is built with enterprise-grade security. Cypris serves hundreds of enterprise customers across pharmaceuticals, chemicals, advanced materials, energy, and other regulated industries.
FAQ
How fast is quantum patenting growing? Quantum patenting has grown rapidly. According to the OECD and EPO, international patent families in quantum technologies grew sevenfold between 2005 and 2024 and have expanded at a compound annual growth rate of around 20 percent since 2014, far outpacing the 2 percent growth across all technologies, with quantum computing the most dynamic segment. A peer-reviewed analysis counts about 29,700 quantum patents granted from 2001 to 2025 at a compound annual growth rate near 14.5 percent.
What are the main qubit modalities in the patent landscape? The main qubit modalities are superconducting qubits, trapped-ion qubits, photonic qubits, semiconductor spin qubits, and topological qubits, with quantum annealing a further distinct approach. Superconducting qubits are the most heavily patented hardware route. Each modality is a distinct region of the landscape with different owners and maturity.
Why is quantum error correction a key IP area? Quantum error correction is a key IP area because current quantum devices are noisy and a single logical qubit may require on the order of dozens or more physical qubits. Overcoming this overhead is the central unsolved problem, so error-correction methods are foundational and heavily contested. They cut across all hardware modalities.
How are quantum hardware patents different from software patents? Quantum hardware patents protect specific physical configurations, materials, and fabrication processes, so they behave more like semiconductor-device patents than software patents. They are consequently harder to design around, a distinction sharpened by the narrowing of software-patent eligibility since the US Supreme Court's Alice decision in 2014. A key fabrication patent can affect every maker of that hardware.
Is the quantum landscape maturing? The quantum landscape shows signs of maturing. The OECD-EPO analysis found that after a decade of exceptional growth the sector is entering a new phase in which rapid expansion gives way to more focused development, even as patenting continues. This makes early, defensible positions more valuable.
Where is the white space in quantum computing? The white space in quantum computing includes error correction, the less-crowded modalities such as photonic, semiconductor spin, and topological qubits, control and cryogenic systems, application and algorithm layers, and specific fabrication processes. Superconducting-qubit hardware is comparatively crowded. The higher-value opportunities are in error correction and less-patented modalities.
Why does quantum analysis need scientific literature? Quantum analysis needs scientific literature because quantum advances appear in physics research before they are patented, and much foundational work is academic and government-funded, so the literature gives the earliest signal. Analyzing patents alone gives a lagging view. Cypris analyzes both across more than 500 million patents and scientific papers.
Which teams use quantum computing patent landscape analysis? Quantum computing patent landscape analysis is used by R&D, IP, and strategy teams at technology companies, quantum startups, national laboratories, and universities, as well as investors assessing quantum assets. It informs which modality and layer to back, where to file, and where freedom-to-operate risk sits. Cypris serves hundreds of enterprise customers across research-intensive and regulated industries.
Endnotes
- OECD & European Patent Office (2025). Mapping the global quantum ecosystem: a comprehensive analysis based on innovation, firm, investment, skills, trade and policy data. EPO, Munich / OECD Publishing, Paris. https://www.oecd.org/en/publications/mapping-the-global-quantum-ecosystem_010c37da-en.html
- Minssen, T., Aboy, M., & Crespo, C. (2025). Mapping the patent landscape of quantum technologies: evolving patenting trends and policy implications (2025 update). Perspectives in Law, Business and Innovation. https://doi.org/10.1007/978-981-95-8371-3_4
- Kop, M., Minssen, T., & Aboy, M. (2022). Intellectual property in quantum computing and market power: a theoretical discussion and empirical analysis. Journal of Intellectual Property Law & Practice, 17(8). https://doi.org/10.1093/jiplp/jpac060
- Alice Corp. Pty. Ltd. v. CLS Bank International, 573 U.S. 208 (2014). US Supreme Court. https://www.law.cornell.edu/supct/cert/13-298
- Haunschild, R., Scheidsteger, T., Bornmann, L., & Ettl, C. (2021). Bibliometric analysis in the field of quantum technology. Quantum Reports, 3(3). https://doi.org/10.3390/quantum3030036
- OECD (2025). Quantum technologies: national strategies and policy overview. OECD, Paris. https://www.oecd.org/en/topics/sub-issues/quantum-technologies.html