Multi-Stack OLED Simulation with Setfos and Laoss – Automotive, Lighting, Microdisplays
OLEDWorks, a global leader in OLED technology, is pushing the limits of multi-stack OLED design for automotive lighting, solid-state lighting, and high-resolution microdisplays. In this case study, we explore how Fluxim’s Setfos and Laoss software tools helped accelerate OLEDWorks’ R&D—enabling faster prototyping, higher brightness, better angular performance, and more efficient production workflows. This article is based on a presentation by Dr. Jonathon Schrecengost, delivered during a Fluxim webinar in May 2025.
Webinar Timestamps
- 00:00 – Introduction by Fluxim and speaker welcome
- 01:20 – Overview of OLEDWorks and multistack OLED technology
- 03:00 – Automotive applications: Atala brand and digital taillights
- 06:15 – Advantages of OLED over LED in taillight segmentation
- 08:40 – Brightness, lifetime, and bendable OLED features
- 10:20 – Amber OLED turn signal design and Setfos modeling
- 14:00 – Multistack OLED fabrication and optimization
- 17:00 – OLED microdisplays and Setfos use in design
- 20:10 – Electroluminescence tuning and anti-node optimization
- 23:15 – Microdisplay RGB alignment and white OLED design
- 26:00 – Burn-in mitigation with stacked blue OLED layers
- 27:45 – Closing remarks and Setfos acceleration benefits
- 29:30 – Q&A on optical/electrical crosstalk and Laoss role
- 32:00 – Large-area OLED simulation and uniformity challenges
- 34:00 – Commercial fabrication methods and film uniformity
- 36:00 – Webinar wrap-up and upcoming sessions
TL;DR – AI Summary
OLEDWorks used Fluxim’s Setfos simulation software to design and optimize multi-stack OLEDs for demanding applications in automotive lighting and high-resolution microdisplays.
Key outcomes:
Setfos enabled precise modeling of optical cavities, brightness, emission spectra, and angular dependence, accelerating OLED development by a factor of 10.
Supported the creation of high-brightness amber OLED turn signals and addressable automotive taillights meeting ECE color and durability standards.
Facilitated development of monochrome and full-color OLED microdisplays, optimizing stack thickness and anti-node alignment for AR/VR applications.
While not directly featured in the case studies, Laoss is also used by OLEDWorks to ensure uniformity and reduce crosstalk in large-area OLED segments—highlighting the value of combining optical and electrical modeling simulation in real-world OLED development.
About OLEDWorks
OLEDWorks is a global leader in multi-stack OLED design, founded in 2010 by former Eastman Kodak employees with its headquarters in Rochester, New York. In 2015, the company expanded its manufacturing capabilities by acquiring Philips' OLED division, including a facility in Aachen, Germany, where a significant portion of its products are now manufactured. OLEDWorks has a history of innovation, with low-cost manufacturing enabled and key licenses signed with Universal Display Corp and Global OLED Technology. By 2020, OLEDWorks had already been selected for five automotive platforms by Audi, continuing to deliver brighter and longer-lasting multi-stack OLEDs. They use Setfos and Laoss for OLED simulation, design, and optimization.
OLEDWorks manufactures OLEDs for diverse applications, including high CRI (Colour Rendering Index), low-profile general lighting products, and has significantly entered the micro OLED display market4. Their Atala brand multi-stack OLEDs are key to their offerings.
Applications of OLEDs in Automotive, Lighting, and Displays
OLEDs offer unique capabilities that allow them to serve as primary light sources in various applications.
• Automotive Industry: OLEDs enhance the aesthetic and experience in vehicles, serving as interior lighting solutions, direct view displays, badging and logos, and taillights. Their diffuse nature creates glare-free internal lights for a comfortable experience. For taillights, OLEDs can function as both homogeneous and pixelated light sources simultaneously due to their surface emission and segmented pixel design, transitioning taillights into display-like components that improve vehicle-to-everything communication. OLEDWorks has increased individually addressable segments in their taillights up to 128. These can be found in Audi A8, Q8, Q7, Q6 e-tron, and A5 models. Future innovations include bendable taillights with ultra-thin profiles that conform to car shapes.
• Lighting Solutions: OLED technology is a type of solid-state lighting. Not only is it ultra-thin, flexible, lightweight, cool to the touch and free of glare, it is extraordinarily sustainable and energy efficient, significantly reducing power and fuel consumption and greenhouse emissions. OLEDWorks’ high efficacy solid-state OLED lighting panels reduce energy consumption compared to incandescent lighting, halogen lighting, and even solid-state lighting based on inorganic LEDs. OLED panels are 85% organic material and glass, do not contain toxic metals such as mercury, and have fewer components and a thinner profile compared to lighting based on inorganic LEDs.
Since OLEDs emit from the entire surface of the panel, they do not require the thermal heat sink used in inorganic LED lighting. Life cycle analysis (LCA) studies performed by the Department of Energy have shown that the thermal heat sink often has the highest environmental impact in the manufacturing and disposal steps related to the inorganic LED lighting.
• Microdisplay Applications: OLEDWorks offers WUXGA (1920x1200 resolution) and SXGA (1280x1024 resolution) microdisplay products, capable of supporting multiple stacks and high brightness. Multi-stack OLEDs provide greater selectivity in the composition of emissive layers, and white OLEDs with color filters are favoured for their simpler manufacturing process, higher yield, and throughput potential. Top-emitting OLEDs enable stronger tuning of the optical cavity and emissive layer positions to optimise color gamut, brightness, and viewing angle for products like daytime augmented reality (AR) applications. High brightness, exceeding 100,000 candela per square meter for monochrome green OLEDs, is crucial for visibility in ambient sunlight and for reducing motion blur in VR applications.
Case Study: Amber OLEDs for Automotive Lighting
Goal: Develop high-brightness amber OLEDs for ECE-compliant automotive turn signals.
Solution: Use Setfos to model optical cavities and emission characteristics, enabling a 6-stack OLED meeting performance and regulatory specs.
Developing an amber OLED for automotive turn signals requires meeting specific brightness targets, typically around 20,000 nits, and adhering to legal color standards defined by local laws. Automotive OLEDs must also withstand harsh temperature conditions ranging from -40°C to 105°C and achieve OLED lifetimes exceeding 20,000 hours in operation and 15 years in ambient conditions. Setfos simulation software significantly assists in this development process.
- Limit toward green: y ≤ x − 0.120
- Limit toward red: y ≥ 0.390
- Limit toward white: y ≥ 0.790 − 0.670x
The development process involves several steps:
Identify Ideal Material Combinations: The initial step involves selecting suitable materials for the OLED.
Model a Basic 1-Stack Amber OLED: A first approximation of a generic amber emitter is simulated. Setfos can generate a "map of all optical cavity solutions" to explore possibilities and select an ideal formulation. Setfos uses the transfer matrix formalism for multilayer structures to calculate passive optical properties like reflectance and transmittance. It can also simulate the optics of emissive multilayer structures by modelling the emission characteristics of dipoles within thin layers, accounting for interference effects.
Fabricate and Measure OLED Emission vs. Angle: The modelled 1-stack OLED is then fabricated, and its emission is measured as a function of viewing angle. Setfos can simulate angular dependence, allowing for comparison with measured data.
Extract Intrinsic Electroluminescence Spectrum: From the measured data, a more accurate intrinsic electroluminescence (EL) spectrum for the amber emitter is extracted. Setfos offers an "Emission Zone Fit" tool that can reconstruct the dipole distribution and extract the intrinsic luminescence spectrum of the emissive material by fitting optical emission spectra from measurements.
Model Multi-Stack OLEDs: With the accurate intrinsic EL spectrum, multi-stack OLEDs (from 1 to 'x' stacks, e.g., 6-stack for turn signals) are modelled. This step considers production constraints (manufacturability) and product specifications like color vs. viewing angle, brightness, and lifetime. Setfos can simulate how additional OLED stacks achieve higher brightness at equal current density, extending product lifetime and enabling higher brightness applications like stop light functions. The software also allows filtering solutions to ensure compliance with standards like ECE amber color.
Fabricate and Measure Multi-Stack OLED: The multi-stack OLED is fabricated and measured. If initial assumptions in the model were imperfect or coating imperfections lead to suboptimal results, remodelling with Setfos may be required. The Setfos-generated modeling map can then guide manufacturing for quicker optimisation.
Benefits of Setfos in developing OLEDs: Setfos significantly reduces the number of experiments required for development by approximately an order of magnitude compared to a purely empirical approach. This translates to a "10 times faster time to commercialisation at reduced development costs". Setfos also aids in quality control, helping to diagnose suboptimal performance if measurements don't match the model by suggesting potential issues like tooling factor inaccuracies.
Case Study: OLED Microdisplays for AR/VR
Goal: Design ultra-bright, full-color microdisplays with high resolution.
Approach: Use Setfos to align anti-nodes across RGB stacks and optimize brightness and color gamut for top-emitting OLEDs.
OLEDWorks, in joint development with Fraunhofer IPMS, has entered the microdisplay industry, offering WXGA and SXGA resolution microdisplays. Setfos is crucial for optimizing these OLED microdisplay formulations, enabling selective composition of emissive layers.
Developing Monochrome OLED Microdisplays with Setfos
In his presentation Jonathon outlined a general approach for developing monochrome OLED microdisplays using Setfos:
Simplify Computational Space: To simplify the search for an optimal solution, the OLED is initially simplified to a single organic layer, varying its thickness and the position of a delta function recombination zone from anode to cathode. Setfos can simulate the position of this recombination zone by varying transport and blocking layer thicknesses.
Generate Anti-Node Map: This simplification allows Setfos to generate a map of all possible anti-nodes across a range of optical cavity thicknesses. For a highly efficient 6-stack monochrome green OLED, for instance, a total OLED thickness of around 900 nanometres would be needed to achieve all six anti-nodes.
Optimize with Full NK Dispersion: Once potential anti-node locations are identified, the computational space is limited, and parameters are swept using the full N,K (refractive index and extinction coefficient) dispersion of all real layers in the OLED formulation. This leads to an optimized electroluminescent spectrum30. Setfos allows the definition of refractive index through tabulated N,K values or analytical dispersion models.
Developing Full-Color OLED Microdisplays with Setfos
Optimizing full-color multi-stack OLED microdisplays is more challenging due to the numerous possible permutations. The approach extends from monochrome development:
Solve Anti-Node Map Solutions for Primary Colors: The anti-node map solutions are first generated for all three primary colors (red, green, blue). This helps identify OLED thicknesses that yield reasonable overlap for these emitters.
Optimize Full Structure: For a 3-stack white OLED, for example, a thickness of approximately 900 nanometres shows good alignment of the three colors. An anti-node for each color is selected to optimize the full structure using all real organic layers.
Performance Enhancement with Additional Stacks: More stacks can be added to enhance performance based on intended use. For instance, to address burn-in issues with less stable blue emissive layers, additional blue stacks can be incorporated. This allows blue subpixels to run at a lower current density, extending their lifetime. Setfos is essential for understanding the available combinations of colors.
Setfos's ability to selectively tune or detune the optical cavity and emissive layer positions is key to optimizing color gamut, brightness, and viewing angle in top-emitting OLED microdisplays. The software also integrates various optical models, including light absorption, scattering, and dipole emission, allowing for comprehensive device simulation and optimization
How OLEDWorks Uses Laoss for Uniformity and Crosstalk Control
While Setfos focuses on optimizing the microscopic properties and layer stack of OLEDs, Fluxim's Laoss simulation software is vital for designing and optimizing large-area LEDs, solar cells, and panels by considering electrical, thermal, and optical aspects. Laoss is used at OLEDWorks to address challenges related to device scalability, complex backplanes, and ensuring uniform light emission across large OLED segments. “Laoss has been tremendous for being able to optimize anode bus lines in order to make uniform segments.”
Key applications of Laoss highlighted in the presentation and expanded upon by the manual include:
Optimizing Electrodes for Homogeneity: In large-area OLEDs, parasitic resistance in electrodes can lead to non-uniform light emission. Laoss is used to optimize anode bus lines to achieve uniform segments and homogeneous light output. . Laoss simulates the uniformity of emission by importing the current-voltage-luminance (JVL) characteristics of the OLED. It can model the potential distribution in the top and bottom electrodes and calculate ohmic losses to assess brightness uniformity. This allows for the simulation and optimisation of uniformity, for example, by introducing horizontal metal bars.
Addressing Crosstalk in Microdisplays: As pixels become smaller in microdisplays, controlling optical and electrical crosstalk becomes increasingly difficult. Laoss can calculate pixel crosstalk, which arises from lateral electric currents between pixels, particularly when OLEDs share common cathodes and hole injection layers. Laoss can simulate current density distributions and compare crosstalk currents to central pixel currents. It also has a case study for optical crosstalk in white OLEDs with color filters (WOLED/CF) displays, which is influenced by topography, geometry, and material parameters, using ray-tracing algorithms. OLEDWorks has made significant progress in reducing electrical crosstalk, especially at low current densities for low brightness applications, by adding multiple stacks.
Geometry Design and Simulation Setup: Laoss requires device geometries as input, typically in .dxf or .unv files, which can be created using CAD software like LibreCAD. Users can also select predefined, parametrized geometries. Laoss allows detailed definition of boundary conditions, meshing parameters, electrical coupling (using imported JV curves), and electrode sheet resistances. It can then run comprehensive simulations to display IV curves, ohmic losses, and current density distributions.
Combining Setfos and Laoss in OLED R&D
The combination of Setfos and Laoss provides a powerful simulation suite for OLED development. Setfos is adept at optimizing the optical and electrical properties of the OLED material stack at a microscopic level, including detailed layer structures and emission characteristics. Laoss, on the other hand, excels at simulating large-area device performance, focusing on macroscopic electrical and optical uniformity, current distribution, and thermal effects across the entire panel or display.
The direct coupling between Laoss and Setfos allows for comprehensive design and optimization workflows. For example, Setfos simulations can provide the local IV coupling laws for large PV cell simulations in Laoss. This allows for analyzing the influence of microscopic parameters (e.g., charge carrier mobility from Setfos) on the final performance of a large-area cell or module simulated in Laoss. This integrated approach ensures that both the material and device level performance are optimized, leading to faster time to market and reduced development costs.
In summary, by combining Setfos’ detailed layer-by-layer optical modeling with Laoss’ large-area current and thermal simulation, OLEDWorks accelerates time to market and ensures reliability at both micro and macro scales.
FAQs: OLED Simulation Tools
What are Laoss and Setfos, and what are their primary applications?
Laoss and Setfos are simulation software developed by Fluxim AG, designed for the design and optimisation of various optoelectronic devices. Laoss focuses on large-area LEDs, solar cells, and panels, offering capabilities in electrical, thermal, and optical simulations. Its applications include detailed device geometry design (e.g., with LibreCAD), PV and OLED simulations, including those with metal grids, full PV module simulations with series interconnections, and specific case studies like OPV simulations, AMOLED pixel crosstalk, optical crosstalk, and OLED lighting panel uniformity. It also handles basic OLED electrothermal and electrical/thermal AC simulations, such as Electrochemical Impedance Spectroscopy.
Setfos is a more comprehensive simulation tool that implements physical models for optical and electrical phenomena in organic and inorganic semiconductors. It can perform optical simulations for multilayer structures, including light scattering, emission, and absorption, as well as electrical simulations that account for charge transport, injection, recombination, and trap states. Setfos also offers coupling between its electrical and optical models, enabling advanced analysis like small-signal analysis (e.g., Impedance Spectroscopy). It is used for parameter sweeps and optimisation, and its utility features include 3D viewer for ray-tracer results.
Both software packages are integral to the design, analysis, and optimisation of display and energy harvesting technologies.
What types of physical phenomena can be simulated using Setfos?
Setfos can simulate a wide range of physical phenomena, crucial for the comprehensive analysis of optoelectronic devices. These include:
Optical Models:Transfer Matrix Formalism: For analysing multilayer structures.
Light Scattering: Detailed models for various scattering behaviours.
Optics of Emissive/Absorptive Multilayer Structures: Simulating how light is emitted or absorbed within complex layered devices.
Refractive Index Dispersion Models: Including Cauchy, Sellmeier, Drude, and Tauc-Lorentz models to describe how a material's refractive index changes with wavelength/energy.
Effective Medium Approximations (EMA): Such as Bruggeman and Maxwell-Garnett, for composite materials.
Sun Spectrum/Position Model and Energy Yield Calculation: Relevant for photovoltaic applications.
Electrical Models:Governing Equations: Semiconductor continuity equations and Poisson's equation to describe electron and hole charge transport, recombination, and the electric field.
Charge Injection Models: Various models for how charges enter the device from electrodes, including thermionic (Schottky) contacts and ohmic injection.
Recombination: Models for charge recombination within the device.
Trap States and Distributions: The ability to define single-level or distributed trap states (Gaussian or exponential) for electrons, holes, and amphoteric traps, and their interaction with charge carriers.
Mobile Ionic Charges: Simulation of the movement of anions and cations and their impact on device behaviour.
Excitonic Models: 1D and 3D excitonic diffusion models, and a 3D excitonic Master Equation Model that describes exciton dynamics, including Förster and Dexter transfer, singlet-triplet annihilation, and intersystem crossing (ISC).
Mobility Models: Various models for charge carrier mobility, including Constant Mobility, Field-Temperature-Dependent Mobility, and Extended Gaussian Disorder Model (EGDM) and Extended Correlated Disorder Model (ECDM), which account for energy disorder and carrier concentration effects.
Coupling Between Electrical and Optical Models: Setfos can simulate the interaction and coupling between electrical and optical phenomena, allowing for more realistic and integrated device characterisation.
Small Signal Analysis: Including Impedance Spectroscopy, where the device response to a sinusoidal voltage signal is analysed.
How does Laoss support the design and optimisation of device geometries?
Laoss supports the design and optimisation of device geometries primarily by allowing external CAD software, specifically LibreCAD, to define the complex shapes and structures of the devices.
The workflow typically involves:
Geometry Design with LibreCAD: Users create the detailed 2D geometry of the device in LibreCAD. This includes defining specific subdomains, such as "Inside Subdomain MetalFinger," which are crucial for Laoss to identify different parts of the structure and apply appropriate boundary conditions or material properties. An extra point within a subdomain, specifically named "Inside Subdomain NameOfChoice," is required for Laoss to correctly identify its interior.
Geometry Import: The designed geometry (e.g., as a .dxf file) is then imported into Laoss.
Material and Boundary Condition Assignment: Once imported, Laoss allows users to assign material properties and boundary conditions to the different geometrical elements. For instance, for backlight units, an "XYZ file" can define the topography, and a .dxf geometry file can specify domains like the LED domain (where light is emitted with a defined spectrum) or the bottom mirror domain (which can be set as fully reflective).
Optimisation: Laoss also facilitates optimisation examples, such as varying the metal finger width in PV devices to improve performance. This implies that the software can iteratively run simulations with modified geometrical parameters to find optimal designs.
By separating the intricate geometric design to a dedicated CAD tool and then importing it, Laoss provides flexibility and precision in handling the complex layouts of large-area LEDs, solar cells, and panels.
How are material properties and boundary conditions defined in Setfos and Laoss?
In both Setfos and Laoss, material properties and boundary conditions are defined through various means to accurately represent the physical behaviour of the simulated devices.
In Setfos:
Graphical User Interface (GUI): The GUI provides dedicated tabs and sub-tabs for setting up layer structures and defining properties.
Layer Structure Tab: Users set up the individual layers, including their thicknesses (in nm, µm, or mm).
Refractive Index Tab: Optical properties like the real (n) and imaginary (k) parts of the refractive index can be input as constant values, tabulated spectral data (.nk files), or defined by analytical dispersion models (e.g., Cauchy, Sellmeier, Drude, Tauc-Lorentz). Effective Medium Approximations (EMA) like Bruggeman can also be used for composite materials.
Emitter Tab: Properties related to light emission are defined, including the spatial distribution of emitting dipoles (Delta, Exponential, Gaussian) and luminescence spectra.
Photovoltaic Tab: Parameters specific to PV devices are set.
Scattering Tabs: Properties for bulk scattering and interface scattering can be defined, including bi-directional scattering distribution functions (BSDF).
Electrode Properties Tab: For electrical simulations, work functions (e.g., from a table of common elements), charge carrier concentrations, and other electrode-specific parameters are specified.
Semiconductor Properties Tab: Covers general layer properties like dielectric constant ($\epsilon_r$), HOMO/LUMO energies, density of states ($N_0$), and free carrier mobility parameters. Electrical doping (Acceptor and Donor) can be constant or position-dependent, imported from text files. Trap states (single-level, Gaussian, exponential) are also defined here.
Coupling Properties Tab: Manages the coupling between electrical and optical models.
Script Mode: For advanced users, simulations can be defined using script files, where parameters and models are specified with specific syntax (e.g., Layername.d, Layername.n, Drude.lambda_p.i). Electrical material parameters are defined in .em files.
Boundary Conditions for Electrical Models: These include definitions for current injection at electrodes (e.g., Jn, Jp), surface recombination velocity, and the application of voltages (e.g., Vapp). Gauss's law and current continuity are enforced at interfaces. The built-in voltage (Vbi) is determined by electrode work functions or defined charge carrier concentrations.
In Laoss:
Geometry-Based Assignment: After importing geometry from LibreCAD, Laoss links material properties and boundary conditions to the defined geometric domains.
Layer Stack: The "Layers" tab in "Project properties" allows renaming and defining the thicknesses of layers (e.g., "top surrounding," "bottom surrounding").
Topography and Optical Properties: For complex structures like backlight units, topography (.txt XYZ file) and geometry (.dxf file) are imported. Optical properties are attributed via domains specified in the geometry. For example, the LED domain is set to be emitting with a specific spectrum, and the bottom mirror domain can be made fully reflective using an angular TR file. Diffuse scattering and absorption losses can be considered by defining additional domains for walls and setting scattering properties using BSDF files (which can be generated using Setfos).
Electrical Boundary Conditions: For electrical simulations, specific edges of the geometry are designated as electrodes, and DC voltages are applied (e.g., 0.4 V on a top electrode and 0 V on a bottom electrode). Remaining edges can have zero current boundary conditions.
Electrodes Tab: The electrodes tab in the GUI allows setting sheet resistance and sheet elastance.
Both software provide comprehensive options for defining the physical characteristics and operational conditions of the simulated devices, either through intuitive GUIs or detailed script files.
What kind of results and output data can users expect from simulations in Setfos?
Setfos provides a variety of results and output data, which can be viewed, analysed, and exported in different formats. These outputs are crucial for understanding device performance and for further research or development.
Key types of outputs include:
Result View: This central feature allows users to visualise simulation results.
Plot Categories and Plot Types: Results are categorised (e.g., optical, electrical) and can be displayed using various plot types (e.g., IV curves, spectral data, angular distribution, carrier density profiles).
Plot Enrichment Tool: Tools for enhancing and customising plots.
Exporting Plots and Data: Results can be exported as plots (images) or raw data for external analysis.
Comparing Simulation Results: The software allows for direct comparison between different simulation runs.
3D Viewer for Ray-Tracer Results: For visualising optical paths and distributions in 3D.
Output Files and Formats:HDF5: A common format for storing large, complex datasets.
ASCII files: Simple plain text files, often tab-separated, used for tabulated spectral data (e.g., .nk files for refractive index), or other numerical outputs. Sweep results are arranged in blocks within these files.
Output Console View: Provides warnings and diagnostic information during the simulation process.
Physical Quantities and Parameters: Setfos outputs data related to various physical quantities, including:
Optical: Wavelength, energy, in-plane wave vector (k_inplane, u_inplane), effective refractive index (n_eff), total reflection, transmission, absorption, emission intensity, quantum efficiency (q), decay rate, lifetime (Tau), and absolute spectral emission (in W m⁻² sr⁻¹ nm⁻¹). It can also output bottom-leaked intensity (I_BT) and guided-mode intensity (I_GM).
Electrical: Electron and hole densities (n, p), electric field (~E), electron and hole current densities (~Jn,p), velocities (~vn,p), diffusion constants (Dn,p), mobility (µ), recombination rate density (R), exciton density (S), surface recombination velocity (SE), exciton current density (~Js), and occupied trap densities. For AC simulations, it provides admittance (Y), impedance (Z), capacitance (C), and conductance (G).
Optimisation Results: When parameter optimisation is performed, Setfos outputs the residuum, which quantifies the distance between simulation results and target results, helping users understand how well the optimisation objective was met.
Numerics Output: Information on simulation iterations and convergence (e.g., residua for current continuity).
The diverse range of output formats and data types ensures that users can thoroughly analyse the simulated device performance from multiple perspectives.
How does Setfos handle different charge transport mechanisms and energetic disorder in semiconductors?
Setfos incorporates advanced physical models to accurately describe charge transport mechanisms and account for energetic disorder in semiconductor materials, particularly relevant for organic semiconductors.
Here's how it handles these aspects:
Governing Equations: The foundation for electrical simulations involves solving the semiconductor continuity equations for electrons (n) and holes (p), coupled with Poisson's equation. These equations describe the generation, recombination, and movement of charges under an electric field (~E).
Charge Carrier Mobility Models: Setfos offers several models for charge carrier mobility (µ), which describes how easily charges move through the material:
Constant Mobility: A simple model where mobility is assumed to be constant.
Field and Temperature-Dependent Mobility: More complex models that consider the influence of the electric field and temperature on mobility.
Extended Gaussian Disorder Model (EGDM): This model is particularly suitable for polymeric materials and accounts for energetic disorder. It describes mobility as a product of a density-independent factor, a density-dependent factor (g1), and a field-dependent factor (g2). The g1 function incorporates the effect of carrier concentration (p/N0) and the width of the Gaussian energy distribution (σ̂). The g2 function describes the field dependence, which is also influenced by σ̂.
Extended Correlated Disorder Model (ECDM): Similar to EGDM, but more common for small-molecule compounds. It also models mobility as a product of density-independent, density-dependent, and field-dependent factors, with slightly different parameterisations (c2, δ, rr) reflecting the correlated nature of disorder in these materials.
Energetic Disorder (DOS - Density of States):Second Generation Models: Characterised by a broadened (disordered) density of states (DOS), typically described by a Gaussian distribution of energy levels around the HOMO and LUMO. The width of this Gaussian (σ) directly quantifies the energetic disorder, usually between 0.05 and 0.15 eV.
Fermi-Dirac Statistics: For these disordered systems, the local carrier density is calculated using Fermi-Dirac statistics, which accounts for the filling of these broadened energy bands. This means that carrier densities cannot exceed N0/2 (where N0 is the total density of states) throughout the device.
Spatially Correlated Disorder: While Gaussian disorder describes uncorrelated energy levels, Setfos also mentions the possibility of spatially correlated disorder using random dipole interactions, which can lead to different standard deviations of energy levels.
Trap States: Setfos allows the definition of various trap states (single-level or distributed Gaussian/exponential) which can capture and release charge carriers, significantly impacting transport properties and device performance. These traps can be donor-like, acceptor-like, or amphoteric.
Mobile Ionic Charges: The software also simulates the movement of mobile anions and cations, which can contribute to the overall charge distribution and electric field, further affecting carrier transport.
By incorporating these detailed models, Setfos enables researchers to investigate the complex interplay between material properties, energetic disorder, and charge transport, leading to a deeper understanding of device physics and more accurate simulations.
What are the key parameters and units used in Setfos for defining optical and electrical material properties?
Setfos uses a comprehensive set of parameters and units to define both optical and electrical material properties, ensuring accuracy and consistency in simulations.
Optical Material Parameters:
Refractive Index (n) and Extinction Coefficient (k):Layername.n: Real part of the refractive index.
Layername.k: Imaginary part of the refractive index.
Can be defined as a pair of constant values, or from tabulated spectral data (N-column .nk files, or separate n and k files).
For birefringent materials, Layername.ne (extraordinary real part) and Layername.ke (extraordinary imaginary part) are used.
Analytical Dispersion Models: Parameters for various models:
Cauchy: Cauchy.A.i, Cauchy.B.i, Cauchy.C.i, Cauchy.D.i, Cauchy.E.i, Cauchy.F.i (unitless or nm based).
Sellmeier: Sellmeier.B.i, Sellmeier.C.i, Sellmeier.G.i (unitless or nm based).
Drude: Drude.lambda_p.i (plasma wavelength, in nm), Drude.G.i (damping, in nm).
Tauc-Lorentz: Tauc.TA.i, Tauc.TC.i, Tauc.E0.i, Tauc.Eg.i (all in eV).
Effective Medium Approximation (EMA):EMA.fraction: Volume fraction of a medium in a composite.
Medium n: Refractive index of the constituent medium.
Units for Optical Sweeps:Wavelength: Typically in nm.
Energy: Equivalent to Wavelength, where E = h · c / λ.
k_inplane: In-plane wave vector (magnitude).
u_inplane: Normalized in-plane wave vector.
Electrical Material Parameters:
Charge Properties (Charges sub-tab):Dielectric Constant (εr): Unitless.
HOMO and LUMO energies: Energy levels, typically in eV.
Density of States (N0): In cm⁻³ or m⁻³.
Free Carrier Mobility Parameters:ConstMob: Constant mobility (m²/Vs).
FieldTempDepMob (Mue*ftd): Field-temperature-dependent zero-field mobility (m²/Vs).
FieldDepMob: Field-dependent mobility.
Mue* EGDM, Mue* ECDM: Zero-field mobilities for respective disorder models (m²/Vs).
c2EGDM, c2ECDM: Molecular orbital overlap integrals (unitless).
sigma: Energy states bandwidth for disorder models (eV).
Doping: Acceptor and Donor doping concentrations (cm⁻³). Can be constant or position-dependent (from file, first column in nm).
Recombination: Various recombination rates and coefficients (e.g., cm³s⁻¹).
Trap States: Parameters for trap density, energy levels, capture rates, and emission rates.
Exciton Properties: kr0 (intrinsic radiative decay rate, s⁻¹), knr (non-radiative decay rate, s⁻¹), Exc.i.Exc.j.AnnihilRate (annihilation rates), Exc.i.GenEff (electrical generation), Exc.i.OptGenEff (optical generation).
Units for Electrical Quantities:Length: nm, µm, mm.
Voltage: V, mV.
Current: A, mA.
Current Density: A/m², mA/cm².
Time: s, µs, ns.
Diffusion Constant: nm²/ns, m²/s.
Rate: s⁻¹, µs⁻¹, ns⁻¹.
Resistivity: Ohm·m, Ohm·cm.
Impedance: Ohm·cm², Ohm·m².
Admittance: Ohm⁻¹·cm⁻², Ohm⁻¹·m⁻².
Capacitance: F.
It is important to note that units are explicitly managed within Setfos, and for certain parameters, if no unit is given, the default unit is implicitly understood. The consistency of units across different parameter definitions is crucial for accurate simulation results.
What is the purpose of "parameter sweeps" and "parameter optimisation" in Setfos?
Parameter Sweeps:
The purpose of "parameter sweeps" in Setfos is to systematically vary one or more input parameters over a defined range and observe their effect on the simulation outputs. This allows users to:
Explore Design Space: Understand how device performance changes as a function of key material properties, geometry, or operating conditions (e.g., layer thickness, dipole position, wavelength, voltage).
Identify Trends: Observe trends and dependencies between input parameters and output characteristics (e.g., how current density changes with applied voltage, or how emission spectrum varies with layer thickness).
Generate Characteristic Curves: Automatically generate curves like Current-Voltage (IV) curves, spectral emission curves, or angle-dependent data, by sweeping the relevant parameters.
Prepare for Optimisation: Sweeps can help in narrowing down the range of parameters for a subsequent, more targeted optimisation process.
Sweeps can be defined with a minimum, maximum, and step size, and results from multiple sweeps are arranged in blocks in output files, making data analysis straightforward.
Parameter Optimisation:
"Parameter optimisation" in Setfos goes beyond simple exploration; its purpose is to automatically adjust selected input parameters to achieve specific target outcomes for the device performance. This involves:
Finding Optimal Device Designs: Identifying the best combination of parameters (e.g., layer thicknesses, material properties) to maximise or minimise a target quantity (e.g., power conversion efficiency, emission intensity, uniformity).
Minimising/Maximising Target Values: Users define an objective function or "target" (e.g., total device current, power, quantum efficiency) and specify whether it should be minimised, maximised, or optimised towards a given value.
Using a Residuum Metric: The optimisation process relies on a "residuum" (distance from the simulation result to the target result) to guide the search. This residuum can be weighted and can incorporate a standard deviation for each measurement point, allowing for more nuanced optimisation.
Iterative Refinement: The software iteratively runs simulations, adjusting parameters based on an algorithm, to converge towards the optimal solution. The number of iterations can be limited.
High-Dimensional Targets: Optimisation can handle targets that consist of multiple data points, such as spectral data or full JV-curves, provided as text files.
In essence, parameter sweeps are for understanding "what if" scenarios, while parameter optimisation is for finding the "best" scenario according to predefined criteria.
Can Setfos simulate the effects of mobile ions and trap states on device performance?
Yes, Setfos is capable of simulating the effects of both mobile ions and various trap states on device performance, making it a powerful tool for understanding complex semiconductor physics.
Mobile Ionic Charges: Setfos allows for the simulation of the impact of moving anions (a) and cations (c).
Continuity and Drift-Diffusion Equations: The movement of ions is described by continuity equations combined with drift-diffusion equations, similar to electrons and holes. These equations account for both drift (movement due to electric field) and diffusion (movement due to concentration gradients).
Poisson Equation Coupling: The Poisson equation, which determines the electric field, is solved self-consistently with the concentrations of electrons, holes, and mobile ions. This means that the presence and distribution of ions directly influence the electric field, which in turn affects the transport of all charge carriers, including the ions themselves.
Mobility Models for Ions: Different mobility models can be applied to ions, including Constant Mobility, Static Mobility (where ions are immobile), Poole-Frenkel Mobility, and Field-Temperature-Dependent Mobility.
Preconditioning: The "Precondition at... V" option allows for simulating preconditioned devices, where the ion distribution is calculated self-consistently for a specific "precondition" voltage before the main simulation, and then the ions are considered static for the actual simulation. This is important for devices that undergo an initial electrical conditioning step.
Trap States and Distributions: Setfos offers comprehensive features for defining and simulating trap states:
Arbitrary Number of Trap States: Users can define as many trap states as needed per layer.
Types of Trap States:Single-level Traps (Dirac Traps): Traps located at a single energy level.
Distributed Traps: Traps distributed across an energy range, typically following Gaussian or exponential distributions.
Charge States and Interaction: Traps can be:
Intrinsically Charged: Donor-like (hole traps) or empty Acceptor-like (electron traps).
Amphoteric: Can exist in three charge states (positive, neutral, negative), as seen in amorphous silicon.
Interaction with Bands: Traps can interact with either the valence band (HOMO), the conduction band (LUMO), or both.
Capture Rates: Users define the capture rates, which determine how efficiently charge carriers are trapped.
Shockley-Read-Hall (SRH) Recombination: Traps interacting with both bands can lead to SRH recombination, a crucial non-radiative recombination pathway.
Rate Equations: Setfos solves rate equations for the occupation of trap states, ensuring that the trapping and detrapping processes are accurately modelled in conjunction with the free carrier dynamics.
By integrating these features, Setfos provides a detailed understanding of how mobile ions and trap states influence current-voltage characteristics, efficiency, lifetime, and other critical performance metrics in optoelectronic devices.
What are the different ways to define the spatial distribution of emitting dipoles in Setfos?
In Setfos, the spatial distribution of emitting dipoles within an emitter layer is crucial for accurately simulating light emission. Users can define this distribution in several ways:
Coupling to a Drift-Diffusion Simulation:
This is the most physically rigorous method. When Setfos performs an electrical Drift-Diffusion simulation, it calculates the recombination profile (where electrons and holes recombine to form excitons/dipoles) across the emitter layer.
The generated dipoles are then distributed according to this calculated recombination profile. This allows for a self-consistent simulation where electrical transport and optical emission are intrinsically linked.
Explicit Distribution Models (for Optics-Only Calculations or when Drift-Diffusion coupling is not used):
These models allow users to directly specify the spatial profile of the dipoles within the emitting layer, typically for simplified optical simulations or when detailed electrical transport isn't the primary focus.
Delta (Dirac Delta function): This option defines dipoles at a single, discrete location within the emitting layer.
Parameter: Position [0..1] sets the relative position (0 = top, 1 = bottom of the layer).
Use Case: Useful for investigating the optical effects of emission originating from a very narrow zone or a specific interface.
Exponential: This defines an exponentially distributed recombination profile.
Parameters: Position [0..1] sets the relative position of the exponential peak within the layer, and Width (in nm) defines the exponential shape's width, decaying according to e⁻|x|/l.
Use Case: Suitable for systems where recombination naturally decays exponentially from an interface or peak.
Gaussian: This defines a Gaussian distributed recombination profile.
Parameters: Position [0..1] sets the relative position of the Gaussian peak within the layer, and Width (in nm) defines the Gaussian shape's width (σ in e⁻x²/(2σ²)).
Use Case: Appropriate for systems where recombination is concentrated around a specific point but has a more symmetric, bell-shaped spread.
These methods provide flexibility, allowing users to choose the level of complexity and physical realism required for their simulation, from detailed coupled electro-optical models to simplified optical-only analyses with predefined emission profiles.