OpenAQ

A high-fidelity, spin-aware machine learning interatomic potential family that delivers DFT-level adsorption energy accuracy for industrially relevant catalysts at up to 20,000x the speed of physics-based calculations.

An inventory of NASA's airborne and field campaigns for Earth Science ASIA-AQAnalysisDC8_Data ASIA-AQAnalysisDC8_Data are analysis flag files derived from data products onboard the DC-8 aircraft during the Airborne and Satellite Investigation of Asian Air Quality (ASIA-AQ) campaign. Data flags identify plumes likely influenced by biomass burning and other combustion processes as well as identifies different air mass layers. Data collection for this product is complete. The ASIA-AQ campaign was an international cooperative field study designed to address local air quality challenges. Conducted from January-March 2024, ASIA-AQ deployed multiple aircraft to collect in situ and remote sensing measurements, along with numerous ground-based observations and modeling assessments. Data was collected over four countries including, the Philippines, Taiwan, South Korea and Thailand and flights were conducted in full partnership with local scientists and environmental agencies [...]

A fast CPU proteochemometric ML model for potency prediction in high-throughput screening and in silico drug discovery. It enables drug discovery teams to perform fast compound triage and early safety screening to identify protein-ligand pairs that are most likely to interact.

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