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When I change c lattice parameter and optimize the structure with DFT-D, every time I get a significantly different geometry with different energy? Why is this happening with DFT-D?

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    $\begingroup$ In general, the end point of an optimization depends on the starting geometry. Starting from a different geometry can lead you to wind up in different minimum. $\endgroup$ – Tyberius Jun 18 '20 at 14:53
  • $\begingroup$ @RagonLoso, how different are these starting structures? Are they minor 0.1Å tweaks? What are the molecules? Finally, what is the magnitude of the difference in the energies? $\endgroup$ – jezzo Jun 18 '20 at 15:49
  • $\begingroup$ I personally find this question but very specific. What kind of structure are we talking about? What kind of DFA? Convergence criteria, programs involved, algorithms, etc.. An important question would also be how you reduced the issue down to the dispersion correction (which one?) $\endgroup$ – Martin - マーチン Jun 19 '20 at 22:24
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Simply put, a geometry optimization finds a local minimum. Many such minima may exist for a given system and it is up to the user to ensure that a reasonable minimum is used for further calculations. Techniques may include using many handmade starting geometries, using a random mutation algorithm or starting from known, experimental structures.

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