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Materials, Waste & Circular Economy
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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
Materials, Waste & Circular Economy
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?
Shared topics: Materials and critical minerals; E-waste and circularity
Materials, Waste & Circular Economy