Removing External Degrees of Freedom from Transition-State Search Methods using Quaternions

Melander, Marko; Laasonen, Kari; Jónsson, Hannes

doi:10.1021/ct501155k

Cited by 26 publications

(22 citation statements)

References 26 publications

(75 reference statements)

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“…The system will seek to avoid high energy areas and hence rotate and/or translate away from these, which is not possible to the same extent for a constrained system. The NEB module supports the NEB-TR [87] method, which speeds up convergence for such systems by removing rotation and translation movement.…”

Section: Constraintsmentioning

confidence: 99%

The atomic simulation environment—a Python library for working with atoms

Larsen

Mortensen

Blomqvist

et al. 2017

J. Phys.: Condens. Matter

2,630

1,556

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The atomic simulation environment (ASE) is a software package written in the Python programming language with the aim of setting up, steering, and analyzing atomistic simulations. In ASE, tasks are fully scripted in Python. The powerful syntax of Python combined with the NumPy array library make it possible to perform very complex simulation tasks. For example, a sequence of calculations may be performed with the use of a simple 'for-loop' construction. Calculations of energy, forces, stresses and other quantities are performed through interfaces to many external electronic structure codes or force fields using a uniform interface. On top of this calculator interface, ASE provides modules for performing many standard simulation tasks such as structure optimization, molecular dynamics, handling of constraints and performing nudged elastic band calculations.

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Section: Constraintsmentioning

confidence: 99%

The atomic simulation environment—a Python library for working with atoms

Larsen

Mortensen

Blomqvist

et al. 2017

J. Phys.: Condens. Matter

2,630

1,556

View full text Add to dashboard Cite

show abstract

“…[117,118] The optimizers are implemented as described by Herbol with support for the removal of translation and rotation from the images, which has been shown to be crucial for successful optimizations. [119,120] Improved TS guesses can be obtained by using a CI [121,122] with one and two CIs being supported. After a few optimization cycles, the highest energy image (HEI) can be converted to a CI.…”

Section: Chain-of-states Methodsmentioning

confidence: 99%

pysisyphus: Exploring potential energy surfaces in ground and excited states

Steinmetzer

Kupfer

Gräfe

2020

Int J of Quantum Chemistry

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Predicting the energetics of chemical transformations requires localizing stationary points on a potential energy surface. While educts and products of a chemical reaction may be known, transition state optimization is challenging as good guesses may be unavailable. Extending stationary point searches to the excited state leads to additional difficulties as several states may be close in energy, requiring efficient state tracking. Here, we report the implementation of pysisyphus, an external optimizer, that allows localization of stationary points not only in the ground state but also for excited state by providing several state-tracking algorithms. pysisyphus offers all necessary tools for calculating reaction paths, starting from the optimization of the reactants, running chain-of-states methods such as the nudged elastic band or the growing string method with subsequent transition state optimization, and a concluding intrinsic reaction coordinate calculation.

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“…Dissociation pathways were calculated using the climbing image nudged elastic band method (CI-NEB) [37,38]. The concept of varying spring constants and quaternion based rotation-translation removal, as described in Ref.…”

Section: Methodsmentioning

confidence: 99%