Machine learning and reaction dynamics: from spectroscopic constants of diatomic molecules to buffer gas chemistry
Saved in:
| Main Author: | |
|---|---|
| Format: | Thesis Electronic eBook |
| Language: | English |
| Published: |
Berlin
2023
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| Subjects: | |
| Online Access: | Volltext |
| Physical Description: | 1 Online-Ressource (9, 246 Seiten) Diagramme |
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| 650 | 4 | |a Buffer gas cell chemistry | |
| 650 | 4 | |a Laser cooling | |
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| indexdate | 2024-07-20T05:26:07Z |
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| spelling | Liu, Xiangyue Verfasser (DE-588)1321181965 aut Machine learning and reaction dynamics from spectroscopic constants of diatomic molecules to buffer gas chemistry vorgelegt von Xiangyue Liu Berlin 2023 1 Online-Ressource (9, 246 Seiten) Diagramme txt rdacontent c rdamedia cr rdacarrier Dissertation Freie Universität Berlin 2024 Machine learning Molecular dynamics Spectroscopic constants Diatomic molecules Buffer gas cell chemistry Laser cooling (DE-588)4113937-9 Hochschulschrift gnd-content Erscheint auch als Druck-Ausgabe Liu, Xiangyue Machine learning and reaction dynamics (DE-604)BV049578087 https://refubium.fu-berlin.de/handle/fub188/42143 Resolving-System kostenfrei Volltext |
| spellingShingle | Liu, Xiangyue Machine learning and reaction dynamics from spectroscopic constants of diatomic molecules to buffer gas chemistry Machine learning Molecular dynamics Spectroscopic constants Diatomic molecules Buffer gas cell chemistry Laser cooling |
| subject_GND | (DE-588)4113937-9 |
| title | Machine learning and reaction dynamics from spectroscopic constants of diatomic molecules to buffer gas chemistry |
| title_auth | Machine learning and reaction dynamics from spectroscopic constants of diatomic molecules to buffer gas chemistry |
| title_exact_search | Machine learning and reaction dynamics from spectroscopic constants of diatomic molecules to buffer gas chemistry |
| title_exact_search_txtP | Machine learning and reaction dynamics: From spectroscopic constants of diatomic molecules to buffer gas chemistry |
| title_full | Machine learning and reaction dynamics from spectroscopic constants of diatomic molecules to buffer gas chemistry vorgelegt von Xiangyue Liu |
| title_fullStr | Machine learning and reaction dynamics from spectroscopic constants of diatomic molecules to buffer gas chemistry vorgelegt von Xiangyue Liu |
| title_full_unstemmed | Machine learning and reaction dynamics from spectroscopic constants of diatomic molecules to buffer gas chemistry vorgelegt von Xiangyue Liu |
| title_short | Machine learning and reaction dynamics |
| title_sort | machine learning and reaction dynamics from spectroscopic constants of diatomic molecules to buffer gas chemistry |
| title_sub | from spectroscopic constants of diatomic molecules to buffer gas chemistry |
| topic | Machine learning Molecular dynamics Spectroscopic constants Diatomic molecules Buffer gas cell chemistry Laser cooling |
| topic_facet | Machine learning Molecular dynamics Spectroscopic constants Diatomic molecules Buffer gas cell chemistry Laser cooling Hochschulschrift |
| url | https://refubium.fu-berlin.de/handle/fub188/42143 |
| work_keys_str_mv | AT liuxiangyue machinelearningandreactiondynamicsfromspectroscopicconstantsofdiatomicmoleculestobuffergaschemistry |