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A conformational benchmark for optical property prediction with solvent-aware graph neural networks.

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Title: A conformational benchmark for optical property prediction with solvent-aware graph neural networks.
Authors: Potapov, Denis1,2 (AUTHOR) potapov@airi.net, Rogovoi, Sergei1,3 (AUTHOR), Khrabrov, Kuzma1 (AUTHOR), Ushenin, Konstantin1,4 (AUTHOR), Korovin, Alexey1 (AUTHOR), Ber, Anton1 (AUTHOR), Kadurin, Artur1,4,5,6 (AUTHOR), Tsypin, Artem1 (AUTHOR)
Source: Communications Chemistry. 2/18/2026, Vol. 9 Issue 1, p1-10. 10p.
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  Data: A conformational benchmark for optical property prediction with solvent-aware graph neural networks.
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  Data: <searchLink fieldCode="JN" term="%22Communications+Chemistry%22">Communications Chemistry</searchLink>. 2/18/2026, Vol. 9 Issue 1, p1-10. 10p.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=193006336
RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1038/s42004-026-01944-5
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      – Code: eng
        Text: English
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      – TitleFull: A conformational benchmark for optical property prediction with solvent-aware graph neural networks.
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              M: 02
              Text: 2/18/2026
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              Y: 2026
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            – TitleFull: Communications Chemistry
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