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Grid Optimization

Grid optimizations perform geometry optimizations on a grid of chosen coordinates, or in other words give relaxed scans of the potential energy surface. They can be useful for:

  • Exploring a relevant region of a potential energy surface (PES)
  • Helping to find a particular transition state
  • Developing force field parameters, e.g. dihedral force constants

A grid optimization is specified via the GridOptimizationInput object, which requires an initial_molecule, an optimization_method for the energy method used in the optimizations, and a scans field that specifies both the set of coordinates for the scan, as well as the initial and final values.

There are two optional fields: energy_method and constraints.

The energy_method field can be specified to evaluate the final energy at the optimized geometries at each grid point. If it is not specified, the optimization_method is used for final energy evaluation.

The constraints field can be specified to add geometrical constraints to the remaining coordinates (e.g. for freezing the rotation of the -CH3 groups while performing relaxed scan on a C-C bond).

The results of a grid optimization are stored in the GridOptimizationResult object.


The following example demonstrates how to perform grid optimizations:

import sierra
from sierra.inputs import *

import numpy as np

# Geometry of an HOOH molecule
# note the coordinates are in Angstrom
HOOH = Molecule(
H 0 -0.3 1
O 0 0 0
O 0 1.2 0
H 0 1.5 1

# Perform a grid optimization along the dihedral angle
# at GFN1-xTB level of theory
# Note: the angles are in degrees
inp = GridOptimizationInput(
            "indices": [0, 1, 2, 3],
            "span": {"start": -20, "stop": 20, "nsteps": 3},

result =

final_relative_energies = {
    k: v - min(result.energies.values()) for k, v in result.energies.items()

print("Final relative energies (in Hartree) at each grid point:")
#> Final relative energies (in Hartree) at each grid point:
    (1,): 0.0008328854665666796,
    (0,): 8.881784197001252e-15,
    (2,): 0.0,




Constraints to place on the geometry optimizations.


The method for final energy evaluation. If None the final energies are computed using the level of theory specified by optimization_method.


The initial molecule for the grid optimization.


The method with which to optimize the molecule at each grid point.


Specifies the coordinates and grid density to scan over.



All of the fields in GridOptimizationInput and the following:


The energies of the optimized molecules at each grid point.

  • Type: Mapping[int, float]
  • Default: {}

A record of each optimization evaluation that the GridOptimization workflow completed.


The optimized molecules at each grid point.

  • Type: Mapping[int,Molecule]
  • Default: {}