Transition state optimisation on the surface of periclase
To study surface reactions I recommend the growing string method (GSM) for surfaces. Here is a nice quote from the paper which developed it (Ref. 1)


  GSM’s efficacy was confirmed by comparison with CI-NEB on
  an extensive set of reactions characteristic of modern surface chemistry studies. In these cases, GSM reduces the computational cost (in terms of gradient computations) by about 45% on average over CI-NEB. In addition to high efficiency, GSM has the advantage of operating in single-ended way to enable explorative study of chemical reactions. 


Key to the success of GSM is the use of the efficient hybrid delocalized coordinate system which greatly improves optimization and interpolation steps in comparison to NEB which uses Cartesian coordinates. 

The exact code to reproduce their work is not publicly available, although you may be able to request a copy. However you should be able to reproduce it and more, with this python version of the code that I have developed. 

Also, as others have pointed out, you should consider a higher level of theory like periodic wavefunction DFT (e.g. as implemented in VASP) . 

References: 


Jafari, M, Zimmerman, P. M.. "Reliable and efficient reaction path and transition state finding for surface reactions with the growing string method", J. Comput. Chem. 2017, 38, 645– 658. https://doi.org/10.1002/jcc.24720