Infrared Spectroscopy of Symmetric and Spherical Top Molecules for Space Observation, Volume 2
- Indbinding:
- Hardback
- Sideantal:
- 320
- Udgivet:
- 3. december 2021
- Størrelse:
- 10x10x10 mm.
- Vægt:
- 454 g.
- 2-3 uger.
- 14. december 2024
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- 1 valgfrit digitalt ugeblad
- 20 timers lytning og læsning
- Adgang til 70.000+ titler
- Ingen binding
Abonnementet koster 75 kr./md.
Ingen binding og kan opsiges når som helst.
Beskrivelse af Infrared Spectroscopy of Symmetric and Spherical Top Molecules for Space Observation, Volume 2
This book, Volume 4 in the series, is dedicated to the relationship between laboratory spectroscopy, recording ever-more-complex spectra using increasingly powerful instruments benefiting from the latest technology, and the development of observation using instruments that are embedded in mobile probes or nanosatellites.
The theoretical models described in Volumes 1, 2 and 3 are used in this volume, applying the cumulant theorem in the mean-field theory framework to interpret the near and mid-infrared spectra of symmetric top molecules, such as ammonia (NH3) and spherical molecules, such as methane (CH4). These molecules can be isolated in their gaseous form or subjected to the environmental constraints of a nano-cage (a substitution site, clathrate, fullerene or zeolite) or surfaces.
These methods are not only valuable in the fields of environmental sciences, planetology and astrophysics, but also fit into the framework of data processing and the concept of Big Data.
The theoretical models described in Volumes 1, 2 and 3 are used in this volume, applying the cumulant theorem in the mean-field theory framework to interpret the near and mid-infrared spectra of symmetric top molecules, such as ammonia (NH3) and spherical molecules, such as methane (CH4). These molecules can be isolated in their gaseous form or subjected to the environmental constraints of a nano-cage (a substitution site, clathrate, fullerene or zeolite) or surfaces.
These methods are not only valuable in the fields of environmental sciences, planetology and astrophysics, but also fit into the framework of data processing and the concept of Big Data.
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