OLEDs are energy efficient, large area light sources with mechanical flexibility. An OLED is made of several layers of organic material placed between two electrodes. The total thickness of active layers is not more than a few hundreds of nanometers. Surface area on the other hand can be as large as a few meter squares. In principle there is no limitation on the shape and surface area of an OLED making them a promising candidate for future's large area lighting applications and displays.
The main purpose of using several layers is to increase efficiency. It helps first, to keep emitting layer at the center of the device so that the excited state on emitter molecules would not be quenched --the charge-carrier concentration is high at the regions close to the electrodes. Second, to prevent charge carriers to reach counter electrode and drop efficiency with leakage. Multilayer structure of a white OLED is more complicated due to the need of several emitting layers and different material combinations. Basically in a multilayer structure, one electrode is transparent to allow light emission and usually indium tin-oxide is used for this purpose. The back electrode is a reflective metal with high work function. Injecting charge carriers from metal to organic matter is difficult because of metal-organic interface effects. This difficulty can be overcome by and constructing an ohmic contact using injection layers made of highly doped organic layers. Usually injection layers are combined with charge transport layers in which transport of one type of charge-carrier (an electron or a hole) is blocked. After the charge-carriers reach the emitting layer they may form excited states on the emitter molecules. Electroluminescence occurs when the excited state decays radiatively.
Thin film devices of organic semiconductors are largely disordered. Molecules are packed in a random fashion. Since there is no lattice structure and periodic atomic potential, band structure does not exist. Charge carriers can stay on localized molecular states and the conduction occurs via thermally assisted tunneling or simply called as hopping. Optoelectronic properties of organic semiconductors are therefore different than that of traditional semiconductors. The most successful model of charge transport in organics is the Gaussian disorder model (GDM). This model relies on the idea that molecular energy levels of an organic semiconductor forms a Gaussian distribution because of the random nature of the molecular structure. The width of the distribution is called the disorder strength and its value has a direct influence on how properly the charge-transport is described.
Monte Carlo simulations
The GDM may be implemented using kinetic Monte Carlo methods provided that a well-defined rate is known for each electronic process needs to be considered. The first step is to construct a cubic array of point sites and assign energy values from a Gaussian distribution. The sites would represent the localized molecular states and the assigned energies are energy of the highest occupied molecular orbital or the lowest unoccupied molecular orbital for holes and electrons respectively. Next step is to implement the hopping process that takes place between a pair of sites. One way to achieve this is to consider a rate combining the Boltzmann-factor for hops upward in energy and an inverse exponential distance dependence (known as Miller-Abrahams rate). The simplest Monte Carlo simulation would then have the following algorithm: (1) Calculating the change in the energy landscape due to any present charge-carrier (change in electrostatic potential energy). (2) Constructing a cumulative array of normalized rates including all possible hopping events of the charge-carriers present in the simulation box --injection and collection from metallic electrodes may included as well. (3) Choosing a random number from [0,1) uniform distribution and calling the event that the number corresponds in the cumulative rate-array. (4) Updating the locations of charge-carriers after performing the chosen hopping event. The algorithm loops until the steady-state is reached.