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.
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.
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.
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
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?