Terahertz Spectroscopy Patents: Who Leads, Where the Gaps Are 2026
- Filing peaked in 2021 at 4 records, then fell to 1 by 2024 — a documented -75% swing, not a slow decline.
- G01N material analysis carries 82.6% of the 23 records in scope, while AI-based computing classes (G06N) touch only 4.3% — the analytics layer is barely claimed.
- The leader holds 4 records against a field of 19 ranked assignees, with most others holding a single filing — no single company has locked up the space.
Filing growth compares 2021 (4 records) with 2024 (1) — a three-year span. 2024 is the most recent year we treat as complete: publication lags filing by roughly 18 months, so 2025 onwards are still filling in and any growth rate that ends there would understate the field.
What this landscape covers
Terahertz spectroscopy sits between optical and microwave sensing, using the sub-millimetre band to probe molecular vibrations, crystalline structure and moisture content non-destructively. This landscape covers 23 published patent families filed between 2015 and the 2026 data cut-off, drawn from claims and descriptions referencing spectral fingerprinting, polymorph identification, sample preparation and quantitative calibration. It is a small, technically dense corpus rather than a mass-filed field, which changes how a freedom-to-operate review should be run against it.
Because publication typically lags filing by around 18 months, the 2025 and 2026 figures in any trend are undercounts, not a genuine drop-off. Family counts, used here as the primary unit, filter out the effect of jurisdictional refiling and continuations that can otherwise inflate a single underlying invention into multiple document counts.
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Trend and technology composition
The filing trend and IPC composition below are drawn directly from the 23 records in scope; class shares add to more than 100% because a single record can carry several IPC codes.
Filing trend, 2017-2026
Filings rose to a peak of 4 records in 2021 before falling to 1 by 2024, a decline of 75% over that three-year span — the most recent complete comparison this dataset supports. 2025 and 2026 are still filling in due to publication lag and should not be read as a continuation of the decline.
IPC subclass distribution
G01N (material analysis & testing) appears in 82.6% of the 23 records, confirming this is fundamentally a measurement-and-testing patent set. G01J (radiation measurement) and the two data-processing classes G06F and G06K each sit near 13-17%, while G06N (AI-based computing) appears in only 4.3% of records — a thin layer of claims connecting terahertz measurement to modern machine-learning pipelines.
Shares are the percentage of the 23 records in scope. A patent can carry several IPC classes, so the shares add up to more than 100%.
Go deeper on Terahertz Spectroscopy for Material Analysis with Eureka
This page is one run against one query. Ask Eureka your own question about terahertz spectroscopy for material analysis and every answer comes back with the patent numbers behind it.
Try EurekaMost-cited records and a representative recent filing
Adulteration and authenticity analysis method of organic substances and materials by terahertz spectroscopy
Disclosed are a THz-TDS system, a sample preparation and chemometric-based analysis method that enables the determination of quality control, adulteration and authenticity of all organic substances and materials, especially samples with high water content.Filed by Bursa Technical University, published 2024-05-02 — illustrates how recent filings pair terahertz time-domain measurement with chemometric analysis rather than claiming the hardware alone.
| # | Publication no. | Patent title | Citations |
|---|---|---|---|
| 1 | US20140070102A1 | Terahertz Spectroscopy Characterization with High Spectral and Spatial Resolution for Biological and Chemica… | 41 |
| 2 | US20060049356A1 | Terahertz spectroscopy | 39 |
| 3 | US20080203306A1 | Method and system for plasma-induced terahertz spectroscopy | 19 |
| 4 | US20100277718A1 | Method and system for plasma-induced terahertz spectroscopy | 14 |
| 5 | US20150046090A1 | System and method of determining rock properties using terahertz-band dielectric measurements | 13 |
| 6 | CN106872395A | 一种新型玉米转基因成分的物理检测方法 | 6 |
| 7 | US7652253B2 | Method and system for plasma-induced terahertz spectroscopy | 5 |
| 8 | US9513213B2 | System and method of determining rock properties using terahertz-band dielectric measurements | 3 |
| 9 | CN107084942A | 一种硫代巴比妥酸多晶型的太赫兹光谱检测方法 | 2 |
| 10 | US9417193B2 | Terahertz spectroscopy characterization with high spectral and spatial resolution for biological and chemical… | 1 |
Citation counts favour older documents simply because they have had longer to accumulate them; treat this table as a map of influential prior art, not of current commercial priority.
Patent titles are shown in the language they were filed in, not translated, so that each record stays verifiable against the original filing — a translated title will not match in Eureka or in any national register. Each row carries its publication number; clicking a row searches Eureka by that number.
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Browse MCP servers →What the numbers say about this field
Three patterns stand out once the filing trend, technology composition and citation data are read together.
Peak filing has already passed its complete-year comparison
The field peaked at 4 records in 2021 and had fallen to 1 by 2024, the last year this dataset can treat as complete. That is a real contraction in a small, low-volume field, not noise — though 2025-2026 figures are still incomplete due to publication lag and should not be read as extending the decline.
Claims cluster on measurement, not on the analytics layer
G01N (material analysis & testing) covers the large majority of records, while G06N (AI-based computing) appears in only one record. Companies pairing terahertz hardware with machine-learning calibration or classification have very little claimed prior art to design around.
A shallow lead, not a dominant incumbent
The leading assignee holds 4 records against a ranked field of 19 companies, with the fifth-place holder already down to 2 and the tenth-place holder at 1. That gradient points to a field still open to a well-drafted new filing rather than one closed off by a dominant incumbent.
Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to terahertz spectroscopy for material analysis, with the prior art for and against each one.
Who is filing, and where the gaps sit
The assignee ranking here covers 19 companies total — not a top-50 or top-100 cut — so read the gradient between positions rather than the raw rank numbers.
A modest lead over a long tail
The top assignee's 4 records sit ahead of a field where most other entrants hold a single filing. That is a lead worth watching but not a barrier that forecloses new entry.
Collaboration is concentrated around a few inventor teams
The strongest recurring pairings involve the same lead inventor working with different named co-inventors across separate filings, suggesting a small research group rather than a broad industry consortium behind the most-connected work.
No tracked leader shows fresh-year activity
Every assignee tracked for recent-year momentum, including the current leader, shows zero filings in the latest tracked year. Given the 18-month publication lag, this reads as a data-visibility gap rather than confirmed inactivity, but it means no incumbent currently shows a visible fresh claim.
| Assignee | Recent year | YoY |
|---|---|---|
| Zaozhuang University | 0 | — |
| Rensselaer Polytechnic Institute | 0 | — |
| Cambridge University Technical Services Ltd. | 0 | — |
| VAN HAL RONALD | 0 | — |
| SPECK ANDREW | 0 | — |
| SHEN YAOCHUN | 0 | — |
| MOYER AARON | 0 | — |
| HERRON MICHAEL M | 0 | — |
Where to take this analysis
The trends above point to specific next questions for an R&D or IP team rather than a finished conclusion.
Map the G06N gap against your own pipeline
If your work pairs terahertz measurement with machine-learning calibration or classification, the thin G06N coverage in this dataset is worth a dedicated search before you draft claims.
Explore the technology composition →Check the co-assignee clusters for licensing routes
The repeated co-filing pairs point to a small number of active research groups; understanding who they work with can shortcut a licensing or partnership search.
Review the players and momentum data →Re-run the trend once 2025-2026 fills in
Because publication lags filing by roughly 18 months, the most recent two years in this dataset are undercounts. A follow-up pull in a year will give a truer read on whether filing has actually stabilised.
Revisit the filing trend →Common questions about this landscape
This dataset identifies 23 published patent families filed between 2015 and the 2026 data cut-off, matched against terahertz spectroscopy claims and descriptions covering spectral fingerprinting, polymorph identification, moisture content, sample preparation and quantitative calibration. That is a small, technically concentrated corpus rather than a mass-filed field. Because publication lags filing by roughly 18 months, the true count for 2025 and 2026 will be higher once those filings publish.
The ranking covers 19 assignees, with the leader holding 4 records and a steep drop to single-digit and single-record counts further down the list. No company holds a dominant share of the field, and most entrants appear with only one filing. This spread suggests the field is still accessible to new entrants rather than closed off by an established incumbent.
Filing peaked at 4 records in 2021 and fell to 1 by 2024, a decline of 75% over that three-year window — the most recent period this dataset can treat as a complete comparison. Figures for 2025 and 2026 are still incomplete due to publication lag, so they should not yet be read as a continuation of that decline. A practitioner should treat the 2021-2024 comparison as the reliable signal and revisit the more recent years once they finish publishing.
G01N, the material analysis and testing classification, appears in 82.6% of the 23 records in scope, making this fundamentally a measurement-and-testing patent set. Radiation measurement (G01J) and data-processing classes (G06F, G06K) each appear in a smaller share, while AI-based computing (G06N) appears in only one record. That leaves the intersection of terahertz measurement and machine-learning-based analysis comparatively lightly claimed.
The thinnest coverage sits where terahertz measurement meets modern computational analysis: AI-assisted spectral classification, portable or field-deployable sample preparation, and quantitative moisture-content calibration models all show limited representation relative to the core measurement claims. A first claim in these areas would want to tie a specific terahertz measurement configuration to a defined calibration or classification method rather than claiming either element alone. A proper freedom-to-operate search should still check the most-cited prior art before drafting.
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Disclaimer. This page is generated from Patsnap Eureka data drawn from a limited snapshot of global patent and scientific-literature records, and is provided for general information and reference only.
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.
Nothing on this page constitutes an exhaustive prior-art, novelty, freedom-to-operate, or validity search, nor does it constitute legal, financial, investment, or professional advice, and it should not be relied upon as such. Any patent, commercial, or strategic decision should be verified independently and reviewed with qualified patent, legal, and domain professionals. Patsnap makes no warranties, express or implied, as to the accuracy, completeness, or fitness for any particular purpose of the information presented.
Machine translation. Assignee and organisation names originally recorded in Chinese, Japanese or Korean have been rendered into English by an AI translation step so that the tables stay readable. These renderings are best-effort and may not match a company’s registered English name; the original name is what the underlying patent record carries, and it is what any Eureka query launched from this page uses.