This shows you the differences between two versions of the page.
Both sides previous revision Previous revision Next revision | Previous revision Next revision Both sides next revision | ||
probe_particle_model [2017/01/02 16:16] krejcio |
probe_particle_model [2017/01/26 23:01] krejcio |
||
---|---|---|---|
Line 79: | Line 79: | ||
If an electrostatic Hartree potential is obtained from some DFT calculations, it can be read *.xsf or *.cube files. The electrostatic force field is created by running: | If an electrostatic Hartree potential is obtained from some DFT calculations, it can be read *.xsf or *.cube files. The electrostatic force field is created by running: | ||
- | python PATH_TO_YOUR_PROBE_PARTICLE_MODEL/generateLJFF.py -i YOUR_INPUT_FILE.xsf | + | python PATH_TO_YOUR_PROBE_PARTICLE_MODEL/generateLJFF.py -i YOUR_INPUT_FILE |
If default parameters are used, than you have monopole represented by an Gaussian cloud of charge with its FWHM of 0.7 Ǎ. The monopole can be changed to non-tilting dipoles or quadrupoles by adding flag: -t type, where type ∈ {s,px,py,pz,dx2,dy2,dz2,dxy,dxz,dyz}; s stands for monopole (default), p for dipoles, d for quadrupoles. The FWHM of the Gaussian cloud can be changed by adding flag: -s FWHM. | If default parameters are used, than you have monopole represented by an Gaussian cloud of charge with its FWHM of 0.7 Ǎ. The monopole can be changed to non-tilting dipoles or quadrupoles by adding flag: -t type, where type ∈ {s,px,py,pz,dx2,dy2,dz2,dxy,dxz,dyz}; s stands for monopole (default), p for dipoles, d for quadrupoles. The FWHM of the Gaussian cloud can be changed by adding flag: -s FWHM. | ||
Line 101: | Line 101: | ||
If you want to make a scan for different probe, you have to change the probeType in __params.ini__ and to recompute L-J forces. | If you want to make a scan for different probe, you have to change the probeType in __params.ini__ and to recompute L-J forces. | ||
+ | |||
+ | **The number of grid divisions in *.xsf files is enlarged by one in each direction. Therefore, gridN have to be numbers of cubicles in *.xsf file reduced by one, if geometry is read from *.xyz, but electrostatics from .xsf** | ||
===== Simulating AFM ===== | ===== Simulating AFM ===== | ||
Line 139: | Line 141: | ||
python PATH_TO_YOUR_PROBE_PARTICLE_MODEL/plot_results.py --df --krange min max nK --qrange min max nQ --arange min max nA | python PATH_TO_YOUR_PROBE_PARTICLE_MODEL/plot_results.py --df --krange min max nK --qrange min max nQ --arange min max nA | ||
+ | |||
+ | ===== References ===== | ||
+ | |||
+ | Prokop Hapala, Georgy Kichin, Christian Wagner, F. Stefan Tautz, Ruslan Temirov, and Pavel Jelínek, Mechanism of high-resolution STM/AFM imaging with functionalized tips, Phys. Rev. B 90, 085421 – http://journals.aps.org/prb/abstract/10.1103/PhysRevB.90.085421 | ||
+ | |||
+ | Prokop Hapala, Ruslan Temirov, F. Stefan Tautz, and Pavel Jelínek, Origin of High-Resolution IETS-STM Images of Organic Molecules with Functionalized Tips, Phys. Rev. Lett. 113, 226101 – http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.113.226101 |