Calculation of energy band bending at organic-organic interfaces (neglecting CT effects)


Microscopic processes in organic semiconductors are strongly determined by transport energy levels. These transport levels are different for every molecule in an organic semiconductor, depending on their unique electrostatic environment. For molecules in the bulk of a pristine layer, these effects can be averaged and we usually describe transport levels in form of a Gaussian distribution (energy disorder) around the mean value of IP/HOMO and EA/LUMO. Molecules near organic-organic interfaces, however, have a different local environment depending how far they are from the interfaces. Charge transport across interfaces, which has a strong impact on device characteristics, depends strongly these transport energies. A detailed analysis of the energy landscape at organic-organic interfaces can therefore help to deepen the understanding of macroscopic device performance.

In this use case, we will investigate the energy landscape of a bilayer system. Therefore, we will create a model of an organic-organic interface of two different materials, and compute the electronic structure to analyze the energy landscape near the interface.

Generating a bilayer morphology

As first step, we need to generate the morphology, using Deposit with inputs from the Parametrizer and DihedralParametrizer module. Here, we deposit a-NPD as layer and use this as substrate for TPBi, to generate an interface. You can download the input for Parametrizer here (aNPD, TPBi ) to generate a morphology using the following settings and more details af morphology generation can be found in this webinar:

  • Parametrizer:

    • load aNPD.mol2 from your harddrive
    • optimize: Molecule: enabled (also leave DFTB pre-optimization enabled)
    • B3-LYP and def2-SVP, convergence set to Normal, ESP partial charge method
    • similar using TPBi.mol2
    • additional information can be found here
  • DihedralParametrizer:

    • load input from Parametrizer
    • use the setting which are explained here
    • resources: 32cores, 64GB RAM
  • Deposit:

    • first deposition: a-NPD:
      • two runs of Deposit are required, briefly described here and more details can be found here
      • simulation Parameters of the a-NPD layer:
        • Lx = Ly = 45, Lz = 150 -- If you want to use a wider box, make sure to keep Lx=Ly !
        • PBC enabled, PBC cutoff = 20.0
        • Number of molecules: 1200 -- with the above box, you should get a sample of about 12-14nm height for a-NPD.
        • Initial Temperature: 4000k, Final Temperature: 300K, SA Acc Temp: 5.0
        • Number of Steps: 150000, Number of SA cycles: 32
        • Dihedral moves: enabled
        • Postrelaxation: 10000
      • Molecules: Load input from DihedralParametrizer
      • Postprocessing: Extend morphology enabled, cut 7A of first layer
      • resources: 32cores, 64GB RAM
    • second deposition: TPBi:
      • use the same setting as for the first Deposit run
      • check the Restart from existing morphology in the Molecules tab
      • click the blue button at the Restartfile and select the
      • resources: 32cores, 64GB RAM

Computation of the energy landscape

Electronic structure analysis using QuantumPatch: A detailed description for QuantumPatch can be found here Here, we need to compute HOMO and LUMO energies of all sites in the morphology. Therefore, we select several molecules of a-NPD and TPBi and run individual DFT calculations for each of them. The size of the surrounding environment for each molecule, which is included in the calculation, can be defined by the shell setup of QuantumPatch. Then, we use an extrapolation method to predict the HOMO and LUMO energies for the not explicitly calculated molecules.
More details about QuantumPatch calculations can be found here.
We recommend to set the following options:

  • QuantumPatch: Remark: If you wish to run QP from the command line, you can find the settings template here.

    • General tab:
      • upload the structurePBC.cml from the second Deposit run
      • check Run QuanumPatch, uncheck Calculate Js and uncheck Include in-vacuo Lamdbda/EA/IP Calculation
      • select QuantumPatch Type Polarized and Charge Damping to 0.15
      • all other options in this tab can be ignored for this calculation
    • Engines:
      • define the quantum chemistry method of your choice. We introduce possible options here.
      • we recommend to use Turbomole with B3-LYP and def2-SVP
    • Shells:
      • keep 7 iterations at the Screened Iterations
      • select Number of Molecules of each Type as Inner Part Method, to ensure that you have a similar number of both molecule types in the core shell
      • number of Molecules defines the number of molecules in the core shell for each type, e.g. 50
      • the other options depend on the accuracy level of your choice: we recommend two dynamic shells 15 A with DFT, 25 A using a semi-empirical method and 60 A static shell.
    • LambdaEAIP:
      • can be ignored and should be an empty tab
    • Post processing:
      • check Predict site energy distribution, to generate essential output for the next LightForge calculation
      • the figure at the right shows an example of the requested Post processing settings.
      • check z Rotation to ensure the correct orientation of the outputfiles COM_ext.yml and EAIP_ext.dat for the later use in LightForge.
      • select the non PBC Structure of the final Deposit calculation, i.e. Deposit3_1/structure.cml
      • select to number of copies for your system of interest in x and y direction (z is not required due to the not periodic nature of the device)
      • select the Coulomb cutoff, we recommend to leave the 25 A
    • resources: 32cores, 64GB RAM or more depending on your computational resources.

These calculations create a morphology of 1200 a-NPD molecules at the bottom and 700 TPBi molecules on top of them (Deposit) and a quantum chemistry method calculated the distribution of the HOMO and LUMO energy levels of the molecules from the morphology. To visualize the energy levels we introduce the following two possible options:

  • The first option is to manually collect the data of from two files from the QuantumPatch output. The folder Analysis/files_for_KMC contains the COM_ext.yml, in which the center of mass of all molecules are listed, and the EAIP_ext.dat, in which the corresponding HOMO and LUMO energy values are listed. Then, the z-positions and corresponding energies for all molecules can be plot with e.g. XMGrace.
  • Alternatively, the LightForge software package can be used to visualize the results, which is explained here in more details.

Analysis of the energy landscape of the device

The following figure shows the distribution of the IP/HOMO and EA/LUMO energies of the molecules with respect to their z-position. Towards the interface in the middle of the device, energy levels of both materials are shifted upwards. In addition, there is a broadening of the energy levels of a-NPD molecules near the interface. Such molecule-specific changes in the local energy landscape may in- or decrease injection barriers between organic layers and thereby impact device performance. Remark: The decrease of the energy levels at the end of the device is caused by edge effects.

The results of the search are