A Python/C based package, available at https://github.com/ondrejkrejci/PPSTM, which primary purpose is to simulate STM or dI/dV signal obtained with tilting tip apex (like CO, or Xe tip). It can work separately for a “rigid tip” STM, but for the tilting tip simulations, the original AFM code (Probe Particle model written by Prokop Hapala and Co. also in Python/C)http://github.com/ProkopHapala/ProbeParticleModel/ for simulation of tilting tip apex' AFM images, is necessary, too.
You can get it easily from terminal by running this command:
git clone https://github.com/ondrejkrejci/PPSTM
The original Probe Particle model (here it will be refered as PPAFM) can be downloaded and linked separately, or you can run an install_PPAFM.sh script, which will do it for you. The PPAFM model will be stored next to the PPSTM model.
The PP-STM code calculates an STM or dI/dV signal based on the input from various Linear Combination of Atomic Orbitals (LCAO)-DFT codes. These inputs are eigen-energies of eigen-states (molecular orbitals) and LCAO coefficients (for each state and atomic orbital of sample). Sample can be approximated by freestanding molecule, or by full system - molecule/substrate.
Nowadays these LCAO DFT codes can be used for the creation of necessary PP-STM inputs: Fireball http://sites.google.com/site/fireballofficialsite/, FHI-AIMS http://aimsclub.fhi-berlin.mpg.de and GPAW in the LCAO mode http://wiki.fysik.dtu.dk/gpaw/documentation/lcao/lcao.html
Detailed description of the PP-STM code principle is shown in PRB 95, 045407 (2017) - see the literature.
python-2.7; python-2.7-numpy(-1.8); gcc(-4.8); python-2.7-matplotlib(-1.3) - for plotting of figures;
python-ase(-3.8.1) & GPAW - needed for reading of GPAW inputs;
Generating force-fields and running AFM scans in PP-STM do not differ from those showed at http://nanosurf.fzu.cz/wiki/doku.php?id=probe_particle_model. The creation of input files for the PP-AFM pre-calcultions is described at http://nanosurf.fzu.cz/wiki/doku.php?id=dft_inputs. From a GPAW DFT code there is now way, how to get a hartree potential at the moment. But the L-J force field can still be created from an *.xyz or *.in file with geometry of the sample's system.
Since the PP-STM calculations takes much longer, than the PPAFM, the proposed strategy for the PP-STM is following.
To tune the parameters for the spring constant K, the charge Q, FWHM of the charge cloud σ and/or multipole a AFM pre-calculations should be done. Once the position of the sharp edges in the AFM figures is in agreement with the position of sharp edges in the STM maps, then the PP-STM simulations should proceed from the positions of the Probe Particle (PP) from these best simulations. Be aware, that when there are sharp edges in the STM, the scan is just between the height, when the 1st unwanted artifacts due to the proximity of tip appears, and 0.2-0.3 Â above it. If the scan was done with oscillating tip, then the figures which should be compared are df images, if the STM scan is done with fixed tip, then the figures of positions should be more important.
For the PP-STM calculations the positions of the PP are necessary. You can get them by running:
python PATH_TO_YOUR_PROBE_PARTICLE_MODEL/relaxed_scan.py --pos
- input parameters
- reading input files
- running fixed tip STM calculations
- running PP-dI/dV
- Example of STM with rigid tip Si (111) 7×7 reconstruction: Si_7x7
- Example of dI/dV scans above spin-polarized CuPc molecule with rigid tip: CuPc
- Example of PPSTM simulations with flexible CO tip: 4N-coronene
Ondrej Krejčí, Prokop Hapala, Martin Ondráček, and Pavel Jelínek, Principles and simulations of high-resolution STM imaging with a flexible tip apex, Phys. Rev. B 95, 045407 (2017); http://journals.aps.org/prb/abstract/10.1103/PhysRevB.95.045407