Physical vapor deposition is used widely to produce organic electronics devices, in particular for OLEDs and in recent years have seen a number of surprising observations, such as deposition-induced emitter orientation and built-in electrostatic potentials in thin organic films. In this paper, we compare two different modeling approaches, which both aim to simulate the physical vapor deposition (PVD) process for small organic molecules; A molecular dynamics approach, based on a classical bead-spring force field and time integration and a Metropolis Monte Carlo approach, where the intramolecular degrees are limited to the torsional rotations. To analyze the resulting structures, we calculate the density and radial distribution functions (RDF) of all films. We observe a good agreement for the RDFs, but an approximately 10% higher density for the films generated by the molecular dynamics approach. Additionally, we investigate the anisotropic nature of such morphologies by calculating the ordinary and extra-ordinary refractive index for each material. Finally, we calculate electron and hole mobilities with an Kinetic Monte Carlo protocol.

Organic Electronics, 2022, 102, 106439, 1566-1199

Organic light emitting diodes (OLED) play an important role in commercial displays and are promising candidates for energy-efficient lighting applications. The performance of OLEDs is determined by a multifaceted interplay of materials and device architectures. The optimization of doped injection layers, to overcome the charge injection barrier from the electrodes to the organic layers, is critical for high-efficiency OLED devices, but has been driven mainly by chemical intuition and experimental experience. Therefore in this work, using a computer-aided method for material and device modeling, the parametric kinetic Monte Carlo model, we studied the effect of doped hole injection layers on the injection barrier in dependence on material and layer properties. We were able to quantitatively elucidate the influence of doping concentration, material properties, and layer thickness on the injection barrier and device conductivity, leading to the conclusion that our kMC model is suitable for virtual device design.

Front. Chem., 2022, 9, 2296-2646

Organic semiconductors (OSC) are key components in applications such as organic photovoltaics, organic sensors, transistors and organic light emitting diodes (OLED). OSC devices, especially OLEDs, often consist of multiple layers comprising one or more species of organic molecules. The unique properties of each molecular species and their interaction determine charge transport in OSCs—a key factor for device performance. The small charge carrier mobility of OSCs compared to inorganic semiconductors remains a major limitation of OSC device performance. Virtual design can support experimental R&D towards accelerated R&D of OSC compounds with improved charge transport. Here we benchmark a de novo multiscale workflow to compute the charge carrier mobility solely on the basis of the molecular structure: We generate virtual models of OSC thin films with atomistic resolution, compute the electronic structure of molecules in the thin films using a quantum embedding procedure and simulate charge transport with kinetic Monte-Carlo protocol. We show that for 15 common amorphous OSC the computed zero-field and field-dependent mobility are in good agreement with experimental data, proving this approach to be an effective virtual design tool for OSC materials and devices.

Front. Chem, 2021, 9, 2296-2646

In amorphous organic semiconductor devices, electrons and holes are transported through layers of small organic molecules or polymers. The overall performance of the device depends both on the material and the device configuration. Measuring a single device configuration requires a large effort of synthesizing the molecules and fabricating the device, rendering the search for promising materials in the vast molecular space both nontrivial and time-consuming. This effort could be greatly reduced by computing the device characteristics from the first principles. Here, we compute transport characteristics of unipolar single-layer devices of prototypical hole- and electron-transporting materials, N,N′-di(1-naphthyl)-N,N′-diphenyl-(1,1′-biphenyl)-4,4′-diamine (α-NPD) and 2,2′,2″-(1,3,5-benzinetriyl)-tris(1-phenyl-1-H-benzimidazole) (TPBi) using a first-principles multiscale approach that requires only the molecular constituents and the device geometry. This approach of generating a digital twin of the entire device can be extended to multilayer stacks and enables the computer design of materials and devices to facilitate systematic improvement of organic light-emitting diode (OLED) devices.

J. Chem. Theory Comput., 2021, 17, 10, 6416–6422

The ionization potential, electron affinity, and cation/anion polarization energies (IP, EA, P⁽⁺⁾, P⁽⁻⁾) of organic molecules determine injection barriers, charge carriers balance, doping efficiency, and light outcoupling in organic electronics devices, such as organic light-emitting diodes (OLEDs). Computing IP and EA of isolated molecules is a common task for quantum chemistry methods. However, once molecules are embedded in an amorphous organic matrix, IP and EA values change, and accurate predictions become challenging. Here, we present a revised quantum embedding method [Friederich et al. J. Chem. Theory Comput. 2014, 10 (9), 3720−3725] that accurately predicts the dielectric permittivity and ionization potentials in three test materials, NPB, TCTA, and C60, and allows straightforward interpretation of their nature. The method paves the way toward reliable virtual screening of amorphous organic semiconductors with targeted IP/EA, polarization energies, and relative dielectric permittivity.

J. Chem. Theory Comput., 2021, 17, 6, 3727-3738

Organic semiconductors are indispensable for today’s display technologies in the form of organic light-emitting diodes (OLEDs) and further optoelectronic applications. To find or even design new organic semiconductors with higher charge carrier mobility, computational approaches, in particular multiscale models, are becoming increasingly important. Therefore, we overcome the problem of computationally very costly simulations due to the long timescale requirements, by integrating machine learning models into multiscale simulations. This allows us to obtain unprecedented insight into relevant microscopic materials properties, in particular static and dynamic disorder contributions for a series of application-relevant molecules. We find that static disorder and thus the distribution of shallow traps are highly asymmetrical for many materials, impacting widely considered Gaussian disorder models and furthermore analyze characteristic energy level fluctuation times and compare them to typical hopping rates to evaluate the importance of dynamic disorder for charge transport.

J. Chem. Theory Comput., 2021, 17, 6, 3750-3759

Conductivity doping of organic semiconductors is an essential prerequisite for many organic devices, but the specifics of dopant activation are still not well understood. Using many-body simulations that include Coulomb interactions and dopant ionization/de-ionization events explicitly we here show significant doping efficiency even before the electron affinity of the dopant exceeds the ionization potential of the organic matrix (p-doping), similar to organic salts. We explicitly demonstrate that the ionization of weak molecular dopants in organic semiconductors is a disorder-, rather than thermally induced process. Practical implications of this finding are a weak dependence of the ionized dopant fraction on the electron affinity of the dopant, and an enhanced ionization of the weak dopants upon increasing dopant molar fraction. As a result, strategies towards dopant optimization should aim for presently neglected goals, such as the binding energy in host-dopant charge-transfer states being responsible for the number of mobile charge carriers. Insights into reported effects are provided from the analysis of the density of states, where two novel features appear upon partial dopant ionization. The findings in this work can be used in the rational design of dopant molecules and devices.

Phys.Chem.Chem.Phys., 2020, 22, 10256

Doping in organic semiconductors is often described in terms of models inherited from the inorganic or “classical” theory, which neglects explicit contribution of strong Coulomb interactions and the localization of the charge carriers from organic counterparts.

Here, we consider the localization of the charge carriers and their mutual interactions in the realistic energetic landscape, using kinetic Monte Carlo (kMC) method. We show that strong Coulomb interactions of the ionized host-dopant pair (integer charge-transfer complex, ICTC) lead to the formation of the EA+ (polaron) levels, which are shifted with respect to the IP of the host molecules. At the same time, the Coulomb gap is defined not only by the energy of the ICTC, but also by the material disorder. The total HOMO disorder of a doped semiconductor can decrease in the highly disordered doped material. This effect causes well-documented superlinear increase of the average mobility of charge carriers upon doping, an unexpected effect, considering that each ionized dopant creates Coulomb traps for charge carriers. We call this effect the disorder-compensation effect. Due to this effect, the intrinsic disorder of the host material is less important, which broadens the space of the host molecules that may be used in OLEDs.

Nat. Commun. 2019, 10, 4547

We present a workflow for simulations of multilayer OLED stacks in which microscopic rates of processes involving charges and excitons are computed from first principles. The multiscale approach covers the generation of atomistic morphologies of disordered organic materials, determination of their electronic properties, and finally simulation of charge transport and excitonic processes using kinetic Monte Carlo (kMC). Applying the workflow to undoped layers made up of various organic compounds as well as prototypical OLED emission layers consisting of TCTA doped with Ir(ppy)₃, we find remarkable agreement with experimental field-dependent mobility measurements as well as triplet-triplet annihilation (TTA) and triplet-polaron quenching (TPQ) rates extracted from photoluminescence quenching experiments. To demonstrate how this workflow may help understand and optimize microscopic processes underlying OLED performance, we show that, for a simplified lattice system, TPQ becomes the efficiency bottleneck at high current densities and can be significantly reduced by increasing the host material’s electron affinity.

Digest of technical papers, 2019, 50 (1), 259–262

Materials for organic electronics are presently used in prominent applications, such as displays in mobile devices, while being intensely researched for other purposes, such as organic photovoltaics, large-area devices, and thin-film transistors. Many of the challenges to improve and optimize these applications are material related and there is a nearly infinite chemical space that needs to be explored to identify the most suitable material candidates. Established experimental approaches struggle with the size and complexity of this chemical space. Herein, the development of simulation methods is addressed, with a particular emphasis on predictive multiscale protocols, to complement experimental research in the identification of novel materials and illustrate the potential of these methods with a few prominent recent applications. The potential of machine learning and methods based on artificial intelligence is discussed to further accelerate the search for new materials.

Adv. Mat, 2019, 31, 1808256

Charge transport in disordered organic semiconductors is generally described as a result of incoherent hopping between localized states. In this work, we focus on multicomponent emissive host-guest layers as used in organic light-emitting diodes (OLEDs), and show using multiscale ab initio based modeling that charge transport can be significantly enhanced by the coherent process of molecular superexchange. Superexchange increases the rate of emitter-to-emitter hopping, in particular if the emitter molecules act as relatively deep trap states, and allows for percolation path formation in charge transport at low guest concentrations.

Phys. Rev. Lett. 117, 276803

A first principles based multiscale model is presented, which accurately predicts charge carrier mobility of different materials varying over ten orders of magnitude. The model allows for the decomposition of the carrier mobility into molecule-specific quantities. The availability of fast and parameter-free screening tools to compute macroscopic materials properties may enable in-silico screening of the chemical compound space for the development of highly efficient opto-electronic devices.

Adv. Funct. Mater., 26: 5757–5763