SINUS | Generative discovery of de novo chemical designs using diffusion modeling and transformer deep neural networks with application to deep eutectic solvents

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Title

Generative discovery of de novo chemical designs using diffusion modeling and transformer deep neural networks with application to deep eutectic solvents

Authors

Rachel K. Luu
Marcin Wysokowski (WTCH) ^{[ 1 ][ 7.6 ][ P ]}
Markus J. Buehler

^{[ 1 ]} Instytut Technologii i Inżynierii Chemicznej, Wydział Technologii Chemicznej, Politechnika Poznańska | ^{[ P ]} employee

Scientific discipline (Law 2.0)

[7.6] Chemical sciences

Year of publication

2023

Published in

Applied Physics Letters

Journal year: 2023 | Journal volume: vol. 122 | Journal number: no. 23

Article type

scientific article

Publication language

english

Date of online publication

06.06.2023

Pages (from - to)

234103-1 - 234103-10

DOI

10.1063/5.0155890

URL

https://pubs.aip.org/aip/apl/article/122/23/234103/2894780

Comments

Article number: 234103

License type

CC BY (attribution alone)

Open Access Mode

czasopismo hybrydowe

Open Access Text Version

final published version

Release date

06.06.2023

Date of Open Access to the publication

at the time of publication

Full text of article

Access level to full text

public

Ministry points / journal

100

Impact Factor

3,5

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