Newton-X

Newton-X performs nonadiabatic molecular dynamics simulations and spectrum analysis using methods such as surface hopping and the nuclear ensemble approach to investigate photophysical and photochemical processes in electronically excited molecules and molecular assemblies.

Key Features:

• Surface Hopping Nonadiabatic Dynamics: Implements surface hopping for simulating nonadiabatic molecular dynamics.
• Nuclear Ensemble Approach and Spectrum Analysis: Uses the nuclear ensemble approach for spectrum simulation and analysis.
• Zero-Point-Energy Leakage Correction: Applies corrections for zero-point-energy leakage to improve energy conservation during dynamics.
• Dynamics on Complex-Valued Potential Energy Surfaces: Supports propagation on complex-valued potential energy surfaces to capture nonadiabatic transitions and electronic coherence effects.
• Dynamics Induced by Incoherent Light: Simulates molecular dynamics driven by incoherent light sources.
• Machine-Learning Potentials: Leverages machine-learning-derived potentials to accelerate and refine molecular dynamics simulations.
• Supervised and Unsupervised Machine Learning: Integrates supervised and unsupervised machine learning techniques for data analysis and model development within simulations.
• Exciton Dynamics in Multiple Chromophores: Models exciton dynamics across multiple chromophores for studying energy transfer processes.
• Interoperability with Quantum Chemistry Programs: Interfaces with third-party quantum chemistry programs and supports a broad spectrum of electronic-structure methods.

Scientific Applications:

• Photophysical and Photochemical Process Investigation: Studies photophysical and photochemical mechanisms at the molecular level.
• Nonadiabatic Dynamics of Excited States: Simulates nonadiabatic dynamics of electronically excited molecules and assemblies.
• Spectrum Simulation and Analysis: Generates and analyzes electronic spectra using the nuclear ensemble approach.
• Energy Transfer and Exciton Dynamics: Investigates energy transfer and exciton dynamics in multi-chromophore systems.
• Light-Induced Dynamics under Incoherent Illumination: Models molecular responses to incoherent light environments.

Methodology:

Computational methods explicitly include surface hopping, the nuclear ensemble approach, zero-point-energy leakage correction, propagation on complex-valued potential energy surfaces, dynamics induced by incoherent light, machine-learning potentials, supervised and unsupervised machine learning techniques, and exciton dynamics modeling, with interfaces to third-party quantum chemistry programs supporting diverse electronic-structure methods.