| Autor: |
Mario BARBATTI, Mattia Bondanza, Rachel Crespo-Otero, Baptiste Demoulin, Pavlo Dral, Giovanni Granucci, Fabris Kossoski, Hans Lischka, Benedetta Mennucci, Saikat Mukherjee, Marek Pederzoli, Maurizio Persico, Max Pinheiro Jr, Jiri Pittner, Felix Plasser, Eduarda Sangiogo Gil, Lijljana Stojanovic |
| Rok vydání: |
2022 |
| DOI: |
10.26434/chemrxiv-2022-8st2h |
| Popis: |
Newton-X is an open-source computational platform to perform nonadiabatic molecular dynamics based on surface hopping and spectrum simulations using the nuclear ensemble approach. Both are among the most common methodologies in computational chemistry for photophysical and photochemical investigations. This paper describes the main features of these methods and how they are implemented in Newton-X. It emphasizes the newest developments, including zero-point-energy leakage correction, dynamics on complex-valued potential energy surfaces, dynamics induced by incoherent light, dynamics based on machine-learning potentials, exciton dynamics of multiple chromophores, and supervised and unsupervised machine learning techniques. Newton-X is interfaced with several third-party quantum-chemistry programs, spanning a broad spectrum of electronic structure methods. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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