Learning the best nanoscale heat engines through evolving network topology
While the thermodynamic power and efficiency of nanoscale heat engines in noninteracting regimes has been well-explored, revealing effect of many-body interactions remains a challenge. Here, the authors develop a reinforcement learning framework to achieve optimal power and efficiency in nanoengines...
Guardado en:
Autores principales: | , |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/a84d6d528971441da8fc0e3f5f04e7fe |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|