Dear Siesta users,
I'm trying to perform the optimization of a unit cell composed of four molecules of a neurotransmitter (for reference, the type of crystal is similar to: J. Appl. Phys. 129, 234702 (2021); https://doi.org/10.1063/5.0054383). It's a monoclinic crystal with equal alpha and gamma angles.
When I run the geometry optimization, the result is always the shortening of the a, b, c, alpha, and gamma, and the increase of beta (from 96° to 98-99°). However, it is expected that the a, b, and c parameters to increase. I thought it could be related to the pseudopotencial, and downloaded the PBE Pseudopotencial from different sources, but nothing changed.
Could someone help me to understand what's wrong?
I'm including the parameters I used to control the simulation
#
MD.TypeOfRun CG
MD.Steps 2000
MD.MaxDispl 0.001 Bohr
MD.MaxForceTol 0.01 eV/Ang
MD.VariableCell T
MD.MaxStressTol 0.02 GPa
MD.TargetPressure 0.0 GPa
#
WriteCoorStep T
WriteForces T
WriteMDHistory T
WriteCoorInitial T
#
DM.UseSaveDM T
MD.UseSaveXV T
MD.UseSaveCG T
Thank you for your help
If the lattice parameters of your crystal are becoming shorter after optimization with the Siesta code, there could be several reasons for this behavior. Here are some possible explanations:
Convergence Issues: The optimization process might not have reached a true minimum on the potential energy surface. Convergence criteria play a crucial role in geometry optimization. If the optimization does not reach a satisfactory convergence, it might lead to inaccurate results, including shorter lattice parameters.
Choice of Pseudopotentials: The pseudopotentials used in Siesta should be accurate and appropriate for the elements in your system. An incorrect or unsuitable pseudopotential might cause artificial interactions that lead to a non-physical contraction of the lattice.
Exchange-Correlation Functional: Siesta allows the use of various exchange-correlation functionals. The choice of functional can significantly affect the optimization results. The functional might not accurately describe the electronic behavior of your specific crystal, leading to incorrect lattice parameter changes.
Van der Waals (vdW) Interactions: Some materials exhibit strong vdW interactions that are not adequately captured by standard DFT functionals. Siesta can include semi-empirical dispersion corrections to account for these interactions, but if they are not considered, the resulting lattice parameters may be affected.
Symmetry Constraints: Incorrectly applied symmetry constraints might affect the optimization process and lead to undesired changes in the lattice parameters.
Initial Structure: If the initial atomic positions or lattice parameters are far from the equilibrium configuration, the optimization might not converge to the correct structure.
Finite-Size Effects: If the size of the unit cell is not large enough to represent the bulk crystal adequately, finite-size effects may influence the results.
To address these issues:
Check the convergence criteria for the geometry optimization and ensure they are appropriate for your system. Tighten the convergence thresholds if needed.
Verify that you are using the correct pseudopotentials for your elements and check their accuracy.
Try different exchange-correlation functionals to see if they lead to more reasonable results.
Consider adding vdW corrections to account for dispersion interactions.
Double-check that symmetry constraints are correctly applied.
Ensure that the initial atomic positions and lattice parameters are reasonable.
Increase the size of the unit cell to minimize finite-size effects
I hope that could help
Mustapha Lasmi
Thank you for your answer.
I'll try what you suggested
Previously, I tried different sources for Pseudopotentials.. from NNINC, Simune, and the Siesta website... all of them showed the same result. I'll try to create my own PPS, but ATOM manual was a bit confusing about some terms..
I'm using PBE functional, like in the article. I tested Grimme D2 correction, but the lattice parameters were shorter than PBE without correction.
1 thing changed the results. Use non-equal kpoints (i.e., 4x6x4), but it still finishes the calculation with lattice parameters shorter than the experimental. Besides, during half the CG steps, the Lattice parameters increased. After it, the beta angle changed and the other parameters started to decrease. Could It be the egg-box effect?
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