Organization · source-verified

Anthrogen

Author or publisher unknown · Publication date unknown

Materials, Waste & Circular Economy

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Author unknown. Date unknown. Anthrogen. https://www.linkedin.com/company/anthrogen/?viewAsMember=true (AI & Environment Resource Hub; record org-151; collection snapshot 2026-09-15).

Classification and context

Included in the original Organization collection. Labels below are metadata based suggestions. They are not verified findings, claims of effectiveness, or endorsements.

pathway

topic

lifecycle

orientation

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Available source metadata

Author or creator
Unknown or not supplied
Publisher
Unknown or not supplied
Publication date
Unknown or not supplied
Date precision
unknown
Geographic scope
North America
Language
unknown
Peer review
unknown
Source status
verified
Last verified
2026-09-06T18:23:58.169Z
Snapshot import
2026-09-06
Legacy domain
Yes
Legacy subdomain
Unknown or not supplied
organization stage
Solving the Earth's largest challenge at it's smallest scale. We use genetically engineered bacteria and enzymatic cascades to produce polymers for carbon capture, fuels, industrials, and biotech.

Provenance and review

Source sheet: Organization · Row 155 · Original ID: org-151.

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Listed location is not necessarily the geographic reach of their work. Presence is not an endorsement. Source link reachable · checked 2026-09-06. Source identity and required metadata verified. The import date is not the original date added.

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Related through shared environmental topics

Ordered by the number of shared provisional topic labels. This indicates a browsing connection, not agreement between sources.

Shared topics: Materials and critical minerals; E-waste and circularity

Scientific Paper · 2025-05-09

A Framework to Evaluate Machine Learning Crystal Stability Predictions

Matbench Discovery is a benchmarking framework for machine learning models used in materials discovery, highlighting the importance of task-specific metrics and demonstrating that universal interatomic potentials can effectively pre-screen stable inorganic materials in high-throughput workflows.

Nature

Shared topics: Materials and critical minerals; E-waste and circularity

Organization · North America

Adaptis

Materials, Waste & Circular Economy

Source metadata available

Shared topics: Materials and critical minerals; E-waste and circularity

Organization · North America

AIMATX

Materials, Waste & Circular Economy

Source metadata available

Shared topics: Materials and critical minerals; E-waste and circularity

Multimedia · 2025-03-14

America Wastes $6+ Billion Worth Of Recyclables A Year. Can Robots And AI Help? | AI In Action

The United States throws away $6.5 billion worth of reusable material every year, and the recycling rate has remained flat for over a decade. Now, tech companies are using artificial intelligence and robotics to make the process safer, more efficient, and more common. But can they really raise the recycling rate in a country with more than 9,000 recycling programs?

Source metadata available