Book a demo

Aluminum SLM Powder Feedstock Patents: Leaders & Filing Trends 2026

Aluminum SLM Powder Feedstock Patents: Leaders & Filing Trends 2026
https://www.patsnap.com/resources/blog/rd-blog/aluminum-alloy-selective-laser-melting-powder-feedstock-patent-landscape-patent-landscape/ · Patsnap · data cut-off 2026-08-31 · downloaded from the live page
Patent Landscape · Advanced Manufacturing
Aluminum Alloy Selective Laser Melting Powder Feedstock Patents

A data-backed look at aluminum alloy selective laser melting powder feedstock patents: who is filing, how concentrated the field is, where the classification white space sits, and what the most-cited records claim, throu

52
Published Records
38%
Top-5 Share of All Records
+50%
Filing Growth 2021→2024
CN
Leading Jurisdiction

Filing growth = 2021 (6 records) → 2024 (9); 2024 is the last year we treat as complete. Top-5 share = the 5 largest assignees ÷ all 52 records in scope (CR5), not the ranked leaders only.

Check your own idea
Published byPatsnap Research··6 min readSourced from Patsnap Eureka
Overview

What this landscape covers

This landscape covers 52 published records filed between 2015 and the 2026 data cut-off that combine aluminium alloy chemistry with selective laser melting powder feedstock, drawn from IPC classes covering additive manufacturing, powder metallurgy and alloys. Filing is concentrated but not consolidated: the top 5 assignees hold 38.5% of records and the top 10 hold 59.6%, leaving a long tail of single-filing universities and materials companies, overwhelmingly filed through the Chinese patent office.

The technology composition skews heavily toward core powder metallurgy and additive manufacturing classification, with alloy composition claims (C22C) present in 84.6% of records. Adjacent branches — joining processes, ceramic composites, casting and radiation-shielding applications — each appear in only one or two records, marking them as the thinnest layers of claimed prior art in this dataset.

Filing trend and IPC composition, 2017-2026
  1. 1CENT SOUTH UNIV6
  2. 2XIAN BRIGHT ADDTIVE TECH CO LTD4
  3. 3TONGJI UNIV4
  4. 4SOUTH CHINA UNIV OF TECH3
  5. 5HUAZHONG UNIV OF SCI & TECH3
  6. 6FUJIAN UNIV OF TECH3
  7. 7Anhui Zhongti New Material Technology Co., Ltd.2
  8. 8CHINA NUCLEAR POWER TECH RES INST CO LTD2
  9. 9CRRC IND INST CO LTD2
  10. 10Yangzhou Zhuoguang New Material Technology Co., Ltd.2
Source: Patsnap Eureka. Assignee ranking and totals. Derived from a Patsnap search on Aluminum Alloy Selective Laser Melting Powder Feedstock Patent Landscape covering 2015–2026, data cut-off 2026-08-31. Counts reflect published records only and shift as new filings publish.Run this in Eureka MCP

Let an AI agent run this analysis on your own technology

Pick a task. Every answer cites the patents behind it.

10,000 free credits to start
Filing data

Filing trends and technology composition

The dataset covers 52 published records dated 2015-01-01 through 2026-08-31, with China accounting for the large majority of receiving offices. Because publication lags filing by roughly 18 months, the most recent years in the trend below are still filling in.

Filing activity is recent and still rising

No records appear before 2017. Filing climbed to a peak of 13 records in 2023, and the 2021-to-2024 window shows a +50% increase (6 records to 9), with 2024 the last year that can be treated as complete.

Filing activity is recent and still rising048111502017201820192020202120221320232024202522026Most recent year is partial — publication lag means later filings are not yet visible.

Publication lags filing by roughly 18 months, so 2025 onwards are still filling in. Growth rates on this page therefore end at 2024; running them to the last bar would understate the field.

Powder metallurgy and additive manufacturing dominate the classification mix

B22F (powder metallurgy) appears in all 52 records and B33Y (additive manufacturing) in 96.2% of them, confirming the dataset's core scope. C22C (alloys) reaches 84.6% of records, while C22F (non-ferrous metal treatment) sits at 25.0%. A handful of adjacent classes — casting, welding, ceramics and radiation shielding — appear in only one or two records each.

Powder metallurgy and additive manufacturing dominate the classification mixB22F · Powder metallurgy52100.0%B33Y · Additive manufacturing (3D pri…5096.2%C22C · Alloys4484.6%C22F · Non-ferrous metal treatment1325.0%B22D · Metal casting23.8%B23K · Welding, soldering & brazing11.9%C04B · Ceramics, cement & refractories11.9%G21F · Radiation protection & shieldi…11.9%

Shares are the percentage of the 52 records in scope. A patent can carry several IPC classes, so the shares add up to more than 100%.

Source: Patsnap Eureka. Filing trend and technology composition. Derived from a Patsnap search on Aluminum Alloy Selective Laser Melting Powder Feedstock Patent Landscape covering 2015–2026, data cut-off 2026-08-31. Counts reflect published records only and shift as new filings publish.

Go deeper on Aluminum Alloy Selective Laser Melting Powder Feedstock Patent Landscape with Eureka

This page is one run against one query. Ask Eureka your own question about aluminum alloy selective laser melting powder feedstock patent landscape and every answer comes back with the patent numbers behind it.

Try Eureka
Key patents

Representative filing and the most-cited records

Representative record
CN117920990A2024-04-26

CN117920990A — 7075 aluminium alloy composite powder and selective laser melting forming method

福建理工大学

The filing describes a 7075 aluminium alloy composite powder made from 1.0-2.0 wt.% Ti powder and 1.0-2.0 wt.% Ta powder with the balance as 7075 aluminium alloy powder, together with the selective laser melting method that processes it. The solid spherical Ti and Ta particles act as nucleating agents, refining grain structure and suppressing hot cracking while improving the alloy's corrosion resistance.Filed 2024-04-26 by Fujian University of Technology.

CN117920990A — patent drawing 1CN117920990A — patent drawing 2
View full record
Most-cited records in the dataset
#Publication no.Patent titleCitations
1CN111496244A一种增材制造高强铝合金粉及其制备方法和应用50
2CN110756806A一种基于激光选区熔化技术的Ti/Al异种合金的成形方法34
3CN105112708A一种激光重熔扫描碳化物弥散增强铝合金的快速制造方法32
4CN110257657A基于激光选区熔化技术制备石墨烯增强铝合金材料的方法29
5CN108486429A稀土铒元素增强SLM专用AlSi7Mg铝合金粉末及其应用21
6CN110184512A一种激光选区熔化用铝合金粉及其制备共晶强化铝合金的方法20
7CN111155007A一种基于选择性激光熔化成形技术的高强度2000系铝合金制备方法19
8US20220033946A1Composition design optimization method of aluminum alloy for selective laser melting12
9CN116445776A一种适用于选区激光熔化技术的高强铝合金粉末及工艺方法11
10CN109290583A一种消除7075铝合金选择性激光熔化成型裂纹的方法11

Citation counts reflect the searched corpus and favour older filings; treat them as a measure of influence on later claim drafting rather than of current commercial importance.

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.

Source: Patsnap Eureka. Citation counts and representative records. Derived from a Patsnap search on Aluminum Alloy Selective Laser Melting Powder Feedstock Patent Landscape covering 2015–2026, data cut-off 2026-08-31. Counts reflect published records only and shift as new filings publish.Run this in Eureka MCP
Run it yourself

Put your own technology through the same analysis

 
Where to run it
Fastest

Eureka on the web

When you want the answer in the next five minutes.

The agent works the prompt against patents and technical literature, citing every source.

Run your analysis now →
For builders

MCP server & REST API

When it has to run inside your own pipeline.

Patent search, landscape analysis and assignee resolution as MCP tools. Drop them into any agent framework, or call REST directly.

Browse MCP servers →
Signals

What the evidence points to

Four findings stand out once the filing, classification and citation data are put side by side. Together they mark where claim space is dense, where it is thin, and where influence in the corpus concentrates.

Concentration
38.5%
of 52 records held by top 5 assignees

Filing sits with a small group, not one company

The leading assignee holds 6 records, and the top 5 combined account for 20 records — 38.5% of all 52 records in scope. The top 10 extend that to 59.6%. No single filer dominates outright, which leaves room for new entrants to build a credible position.

Assignee ranking, 52 records
Growth
+50%
filings, 2021 to 2024

Recent growth is real, not a data artefact

Filings rose from 6 in 2021 to 9 in 2024, a +50% increase, with 2023 the peak year so far at 13 records. Because publication lags filing by roughly 18 months, 2025-2026 figures are still filling in and should not be read as a decline.

Filing trend, 2017-2026
Composition
84.6%
of 52 records classified under C22C (alloys)

Alloy chemistry is the crowded layer

B22F and B33Y classifications appear in essentially every record, confirming the dataset's scope, while C22C alloy classification reaches 84.6% of records. Casting, welding, ceramics and radiation-shielding classes each appear in only one or two records.

IPC composition, 52 records
Influence
50 citations
on the most-cited record in the set

Citation weight sits with the older, foundational filings

The most-cited record covers a high-strength aluminium alloy powder for additive manufacturing, cited 50 times; the next most-cited cover dissimilar-alloy forming and carbide-reinforced processing. High citation counts here mark influence on later drafting, not current commercial relevance.

Most-cited records table
Eureka AI Agent
Looking for what nobody has claimed yet?

Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to aluminum alloy selective laser melting powder feedstock patent landscape, with the prior art for and against each one.

Find the white space →
Co-filing is limited
AssigneeCo-assigneeShared families
Central South UniversityCRRC Industry Institute Co., Ltd.2
South China University of TechnologyChina General Nuclear Power Research Institute Co., Ltd.1
China General Nuclear Power Research Institute Co., Ltd.China General Nuclear Power Group Co., Ltd.1
China General Nuclear Power Research Institute Co., Ltd.China General Nuclear Power Corporation1

Only 4 co-assignee pairs appear across the dataset, the strongest linking two Chinese research institutes on 2 shared records. Most filers, including universities with several solo records, are not co-filing with corporate partners.

Source: Patsnap Eureka. Co-assignee relationships and derived observations. Derived from a Patsnap search on Aluminum Alloy Selective Laser Melting Powder Feedstock Patent Landscape covering 2015–2026, data cut-off 2026-08-31. Counts reflect published records only and shift as new filings publish.Run this in Eureka MCP
What's next

Go from landscape to claim-level detail

The figures above show where filing concentrates and where it is thin. The next step is testing a specific composition or process claim against the records that sit closest to it.

Search the full record set

Run a targeted search across the 52 records to pull the specific claims and citation chains behind any composition or processing route you are evaluating.

Search in Eureka

Map white space before you draft

Use the classification breakdown to confirm which adjacent branches — joining, ceramics, regulated end-use — are genuinely under-claimed before committing a first claim to one of them.

Explore white space in Eureka

Track new filings as they publish

Filing is still rising and 2025-2026 records are only partially published; set up monitoring so new entrants and citing filings surface as soon as they appear.

Set up monitoring in Eureka
Source: Patsnap Eureka. Forward-looking reading of the same dataset. Derived from a Patsnap search on Aluminum Alloy Selective Laser Melting Powder Feedstock Patent Landscape covering 2015–2026, data cut-off 2026-08-31. Counts reflect published records only and shift as new filings publish.Run this in Eureka MCP
FAQ

Frequently asked questions

Answers are grounded in the same dataset. Derived from a Patsnap search on Aluminum Alloy Selective Laser Melting Powder Feedstock Patent Landscape covering 2015–2026, data cut-off 2026-08-31. Counts reflect published records only and shift as new filings publish.Run this in Eureka MCP

Research Aluminum Alloy Selective Laser Melting Powder Feedstock Patent Landscape in depth with Eureka

Go past this page: query the whole aluminum alloy selective laser melting powder feedstock patent landscape corpus yourself, in your own scope.
Every answer comes back with patent numbers you can open.

Try Eureka

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.

Help us improve this page

Found incorrect or outdated information? Let us know and we'll get it fixed.