Draft:Mat3ra
You can also browse Wikipedia:Featured articles and Wikipedia:Good articles to find examples of Wikipedia's best writing on topics similar to your proposed arti
Submission declined on 23 May 2026 by ChrysGalley (talk).
Where to get help
How to improve a draft
You can also browse Wikipedia:Featured articles and Wikipedia:Good articles to find examples of Wikipedia's best writing on topics similar to your proposed article. Improving your odds of a speedy review To improve your odds of a faster review, tag your draft with relevant WikiProject tags using the button below. This will let reviewers know a new draft has been submitted in their area of interest. For instance, if you wrote about a female astronomer, you would want to add the Biography, Astronomy, and Women scientists tags. Editor resources
|  |
This draft's references do not show that the subject meets Wikipedia's criteria for inclusion for organizations and companies. The draft requires multiple published secondary sources that:
Declined by Drmies 8 months ago.
| |
Submission declined on 2 December 2025 by Pythoncoder (talk). This draft appears to contain text generated by a large language model (such as ChatGPT). You cannot use LLMs to generate article content.
Declined by Pythoncoder 8 months ago.LLM-generated pages with certain obvious signs of being machine generated may be deleted without notice. Instead, only summarize in your own words a range of independent, reliable, published sources that discuss the subject. See the advice page on large language models for more information. | |
Submission declined on 1 December 2025 by Pythoncoder (talk). This draft appears to contain text generated by a large language model (such as ChatGPT). You cannot use LLMs to generate article content.
Declined by Pythoncoder 8 months ago.LLM-generated pages with certain obvious signs of being machine generated may be deleted without notice. Instead, only summarize in your own words a range of independent, reliable, published sources that discuss the subject. See the advice page on large language models for more information. | |
Comment: There is still no corporate depth per WP:SIRS. This is a classic example of a draft which was AI generated becoming probably impossible to rescue. It is no longer AI, due to all the amendments to it, but AI has gone down a rabbit hole from which a reverse ferret manoeuvre is not going to work. ChrysGalley (talk) 08:40, 23 May 2026 (UTC)
- Comment: The sourcing is very thin, and things like "was mentioned in" do not help. Drmies (talk) 02:32, 2 December 2025 (UTC)
| Mat3ra | |
| Type | Private |
| Industry | Computational materials science |
| Founded | 2014 |
| Headquarters | San Francisco Bay Area, California, United States |
| Website | https://mat3ra.com |
Mat3ra is a US-based company developing software for materials modeling. The key product of the company are the easy-to-use workflows for large scale cloud based computing including the molecular dynamics and density functional calculations of bulk materiials, defects, and interfaces. The company originally used Exabyte.io brand name before switching to Mat3ra in 2022, and wa sstarted by Timur Bazhhirov, UC Berkeley graduate.
In 2022, The Wall Street Journal reported that Exabyte Inc. raised US $3 million in seed funding for Mat3ra..[1]
Exabyte.io was mentioned in a 2020 review article in Advanced Science among data-driven materials science solutions.[2]
In 2017, The Register reported on cloud–HPC benchmarking work[3] by Exabyte.io comparing Azure, AWS, and other cloud vendors for LINPACK workloads.[4] HPCwire also covered this research.[5]
Exabyte Inc. received US $3.8 million in funding across seven awards under the U.S. government’s SBIR program, including from the Department of Defense, Department of Energy, and the Department of Commerce/NIST.[6]
Multiple market research reports covering materials informatics mentioned Mat3ra and Exabyte.io.[7][8][9]
References
- ^ "Startup That Models Materials at Atomic Scale Raises Seed Capital". The Wall Street Journal. 4 February 2022.
- ^ Himanen, Lauri; Geurts, Amber; Foster, Adam Stuart; Rinke, Patrick (2020). "Data-Driven Materials Science: Status, Challenges, and Perspectives". Advanced Science. 7 (2) 1903667. doi:10.1002/advs.201903667. ISSN 2198-3844. PMC 6974932. PMID 31993299.
- ^ Mohammadi, Mohammad; Bazhirov, Timur (2018-03-15). "Comparative benchmarking of cloud computing vendors with high performance linpack". Proceedings of the 2nd International Conference on High Performance Compilation, Computing and Communications. HP3C. New York, NY, USA: Association for Computing Machinery. pp. 1–5. arXiv:1702.02968. doi:10.1145/3195612.3195613. ISBN 978-1-4503-6337-2.
- ^ "Clouds can compete with HPC, say boffins". The Register. 14 February 2017.
- ^ "HPC Clouds Ready? Azure Edges AWS in Linpack Benchmark Study". HPCwire. 15 February 2017.
- ^ "SBIR Portfolio for Awardee 694779". SBIR.gov.
- ^ "Materials Informatics Market Size to Hit USD ..." Precedence Research. 12 November 2025.
- ^ ltd, Research and Markets. "Material Informatics Market Size, Share & Forecast to 2030". www.researchandmarkets.com. Retrieved 2025-12-02.
- ^ "Material Informatics Market Size Report, 2022-2027". www.industryarc.com. Retrieved 2025-12-02.
Content Disclaimer
Informasi ini disarikan dari Wikipedia dan disajikan kembali untuk tujuan edukasi. Konten tersedia di bawah lisensi CC BY-SA 3.0. Kami tidak bertanggung jawab atas ketidakakuratan data yang bersumber dari kontribusi publik tersebut.
- The information displayed on this website is sourced in part or in whole from Wikipedia and has been adapted for the purpose of restating it. We strive to provide accurate and relevant information, however:
- There is no guarantee of absolute accuracy. Wikipedia is an open, collaborative project that can be edited by anyone, so information is subject to change.
- It is not intended to constitute professional advice. The content displayed is for informational and educational purposes only. For important decisions (e.g., medical, legal, or financial), please consult a professional.
- Content copyright. Wikipedia is licensed under the Creative Commons Attribution-ShareAlike License (CC BY-SA). This means that content may be reused with appropriate attribution and shared under a similar license.
- Responsible use. Any risk arising from the use of information from this website is entirely the responsibility of the user.
- provide significant coverage: discuss the subject in detail, excluding routine coverage like product launches, staff appointments, or financial reports and listings in databases or listicles;
- are reliable: from reputable outlets with editorial oversight;
- are independent: not connected to the subject, such as press releases, the subject's own website, or sponsored content.
Please add references that meet all three of these criteria. If none exist, the subject is not yet suitable for Wikipedia.