AI & Environment Resource HubAuthor or publisher unknown · Publication date unknown
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.
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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 2026-10-04).
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Source sheet: Organization · Row 155 · Original ID: org-151.
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Shared topics: Materials and critical minerals; E-waste and circularity
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.
Shared topics: Materials and critical minerals; E-waste and circularity
Adaptis is a diverse team of carbon reduction experts supercharged by a proprietary software platform for evaluating and optimizing building performance, whole-life carbon, and capex. We generate and recommend decarbonization scenarios, build project sequences, and keep all the data live in real-time so financial decision-makers can find answers in 15 minutes, not 15 days.
Shared topics: Materials and critical minerals; E-waste and circularity
Exponential acceleration meets materials innovation. Our AI-integrated platform is transforming how advanced materials are discovered, designed, and deployed - bringing next-generation solutions from concept to reality.
Shared topics: Materials and critical minerals; E-waste and circularity
This dataset provides a large and diverse collection of DFT calculation trajectories for heterogeneous catalysis research. It encompasses a wide range of adsorbates and catalyst surfaces. The data is designed for training and testing machine learning interatomic potentials. AQCat25 consists of approximately 5K materials, 40K intermediate-catalyst systems, and 11.1M frames.