| Download | - View supplementary information: Seeking metal–organic frameworks for hydrogen storage using classical and quantum active learning (PDF, 1.6 MiB)
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| DOI | Resolve DOI: https://doi.org/10.1039/D5CP02747K |
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| Author | Search for: Lourenço, Maicon PierreORCID identifier: https://orcid.org/0000-0002-0110-8318; Search for: Shukla, RishabhORCID identifier: https://orcid.org/0000-0002-0164-6407; Search for: Naseri, Mosayeb1ORCID identifier: https://orcid.org/0000-0003-0786-2175; Search for: Gaur, Daya; Search for: Singh, Utkarsh2; Search for: Gusarov, Sergey1ORCID identifier: https://orcid.org/0000-0003-2033-705X; Search for: Salahub, Dennis R.ORCID identifier: https://orcid.org/0000-0002-9848-3762 |
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| Affiliation | - National Research Council Canada. Digital Technologies
- National Research Council Canada. Quantum and Nanotechnologies
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| Format | Text, Article |
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| Abstract | Metal–organic frameworks (MOFs) are porous materials with applications from chemical sensing to gas storage and separation. This work explores classical and quantum active learning algorithms to optimize hydrogen storage in MOFs. |
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| Publication date | 2025-10-01 |
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| Publisher | Royal Society of Chemistry |
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| In | |
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| Language | English |
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| Peer reviewed | Yes |
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| Export citation | Export as RIS |
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| Report a correction | Report a correction (opens in a new tab) |
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| Record identifier | 492be644-8b93-4633-b9ac-f46fba491176 |
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| Record created | 2025-11-28 |
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| Record modified | 2026-02-20 |
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