GaN Power AI/ML Patent Snapshot 2026
The intersection of GaN power devices and AI/ML methodologies is an extremely nascent filing space, with only a single patent family on record — filed in China in 2025 by Qingdao Jiaen Semiconductor. The field is effectively pre-competitive, presenting both an open runway and significant first-mover uncertainty for teams considering dedicated R&D investment.
A single filer defines an embryonic competitive space
Qingdao Jiaen Semiconductor holds the sole patent family in scope, ranking first by default in the applicant table. The top five filers account for 100% of the ranked applicants visible in this query’ combined total — a figure that, at this corpus size, reflects the complete absence of rival activity rather than deliberate concentration.
There is no discernible tier structure: no challenger tier, no second-wave entrants, and no evidence of a competitive cohort that would signal this niche has matured. The entire corpus rests on one filing event.
| # | Applicant | Patent families | Share |
|---|---|---|---|
| 1 | Qingdao Jiaen Semiconductor Co., Ltd. | 1 |
Qingdao Jiaen Semiconductor’s position implies neither dominance in a contested field nor a defensible moat — rather, it reflects the fact that this precise application of AI/ML to GaN power devices has not yet attracted systematic patent investment from any major semiconductor or power-electronics player.
Because this corpus covers only a single family filed in 2025, publication-lag effects are maximal: additional filings from 2024 onward are likely still unpublished and will not appear until 18–24 months post-priority. Longer-window growth, applicant concentration, and technology-route coverage are therefore more reliable signals than the latest-year bar alone.
A single 2025 filing anchors a flat, decade-long trend
The annual filing trend shows zero activity from 2017 through 2024, with one family appearing in 2025. The technology composition reflects the dual nature of the topic: semiconductor device classes alongside AI/ML computing classes.
Annual filing trend
Activity is zero across all years from 2017 to 2024, with one family recorded in 2025. The 2025 entry should be treated cautiously given publication lag; it is not possible to characterize a trend from a single data point. The 2026 count of zero is expected at this stage of the publication cycle.
↗ Hover for values · click a bar to ask EurekaTechnology composition
The single family is classified under four IPC branches: G06F (electric digital data processing), G06N (computing based on AI models), H01L (semiconductor devices), and H10W. This multi-class spread confirms the cross-domain nature of the work — combining device-physics claims with algorithmic or model-based claims — but the sample is too small to infer relative emphasis across the industry.
↗ Hover for values · click a bar to ask EurekaHighly cited patent families surfaced by the query
Citation-heavy patent families returned by the query. Use this section as citation context, not as a curated list of the most topic-specific patents.
一种增强型氮化镓功率半导体器件的封装方法
本发明提供一种增强型氮化镓功率半导体器件的封装方法，属于芯片制造技术领域，本发明首先通过三维电场分布仿真优化电极间距与介电层参数，继而使用银烧结工艺实现芯片与散热基板的高效热连接，并设计多层场板结构分散高电场区域。随后施加高介电常数树脂层和低离子含量环氧模塑料进行绝缘和封装，再涂覆硅氧烷改性聚酰亚胺保护层。通过电场耐受性测试、高加速寿命测试和热循环试验验证可靠性，利用聚焦离子束技术形成微纳米沟道结构缓解局部高电场区域，最终基于深度学习框架的电场分布与可靠性预测模型评估器件性能与寿命，解决了氮化镓功率半导体器件在高电压工作环境下的可靠性问题。 (excerpt from the patent abstract)
Ranked by total forward citations. Citation counts favour older and broadly cited patent families, and broad or adjacent patents may appear when they match the search scope. Treat this section as citation context, not as a curated list of the most topic-specific patents. Some patent titles may be shown in their original, non-English language where an accurate translation could not be guaranteed.
Assignee snapshot from the current evidence set
The applicants below are visible in this query result. Because the evidence set is relatively small, read this section as a directional snapshot rather than a full competitive ranking.
Qingdao Jiaen Semiconductor
Qingdao Jiaen Semiconductor holds 1 patent family in scope, covering G06F digital data processing, G06N AI model computing, H01L semiconductor devices, and H10W — a cross-domain claim set consistent with a device-plus-algorithm approach to GaN power optimization. Applicant momentum data is not available for this filer, so trajectory cannot be assessed beyond the single 2025 filing.
families: 1No challenger on record
No second applicant has filed in this specific intersection of GaN power devices and AI/ML methods within the corpus. Major power-semiconductor players — including those active in GaN for power conversion — have not appeared here. This vacancy is the most strategically significant observation in the landscape: the challenger tier is entirely open.
families: 0Frequently asked questions
The current corpus contains 1 patent family in scope, filed in China in 2025. Because publication lag can suppress filings from the most recent 18–24 months, the true current count may be higher once pending applications are published.
Qingdao Jiaen Semiconductor is the sole filer identified in this corpus, holding 1 patent family. No other applicant appears in the ranking.
The single family is classified under G06F (electric digital data processing), G06N (computing based on AI models), H01L (semiconductor devices), and H10W. This multi-class spread reflects the cross-domain nature of combining GaN device physics with AI/ML methods.
All recorded activity is in China. No filings have been identified in the United States, European Patent Office, Japan, Korea, or via PCT at this stage of the corpus.
A formal lifecycle stage cannot be determined from the available evidence — the corpus is too small. The sole 2025 filing places the field at inception, prior to any observable filing ramp or competitive cohort formation.
No co-applicant pairs have been identified in the corpus. There is no evidence of university-industry or cross-company joint filings at this stage, which is consistent with the overall corpus size of one family.
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Patent data carries inherent limitations: recent filings (typically the most recent 18–24 months) are under-counted due to standard publication lag; counts may be reported at either a patent-family or a patent-record basis and are not always directly comparable; classification, applicant-name, and citation data may contain errors, duplicates, or omissions; and the underlying search query defines and constrains the scope shown. As a result, the analysis may be incomplete or inaccurate and may not reflect the full technology landscape.
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