electronics Article
Integration of Optical and Thermal Models for Organic Light-Emitting Diodes An-Chi Wei 1, *, Yih-Jong Huang 2 , Bo-Lin Huang 1 and Jyh-Rou Sze 3 1 2 3
*
Graduate Institute of Energy Engineering, National Central University, Taoyuan 320, Taiwan;
[email protected] Department of Mechanical Engineering, National Central University, Taoyuan 320, Taiwan;
[email protected] Instrument Technology Research Center, National Applied Research Laboratories, Hsinchu 300, Taiwan;
[email protected] Correspondence:
[email protected]; Tel.: +886-3-426-7378
Received: 29 November 2018; Accepted: 19 December 2018; Published: 23 December 2018
Abstract: This paper proposes a three-dimensional model for combinative analysis of the illuminative and thermal properties of organic light-emitting diodes (OLED). By means of the energy conversion ratio and energy conservation theory, two individual optical and thermal sub-models are integrated to form a single model constructed in a multi-physics platform. According to the measured luminous performance and temperature distribution of the fabricated OLED samples, the proposed model demonstrates sufficient accuracy. Moreover, the temperature distribution on the cross-section of the OLED can be derived from the proposed model and used as a valuable reference for manufacturers to select appropriate organic materials. Keywords: solid-state lighting; organic light emitting diode; OLED modeling; integrated thermal; optical model
1. Introduction With the development of solid-state lighting technology, light-emitting diodes (LED) have been applied to many different types of lighting products and have gradually dominated the common lighting market. Meanwhile organic light-emitting diodes (OLED) have shown high potential to replace surface lighting sources, such as indoor and decorative luminaires [1]. Although OLEDs are thin, flat, flexible, and provide a comfortable light source with a large-emitting area, challenges involving increasing panel sizes, improving luminous efficiency, and reducing manufacturing costs remain before OLEDs may be introduced to the lighting market [2]. Advanced OLED display technology has the advantages of high contrast and low energy consumption, while at the same time demonstrating a fast response time and a large viewing angle [1]. When used in lighting applications, on the other hand, OLEDs should exhibit uniform emissions, sufficient luminous flux, and appropriate luminous intensity distribution. Since OLED luminaires are generally regarded as large-area lighting devices, the ability of these light sources to exhibit uniform emissions is of great importance. The luminance uniformity of these sources is closely related to spatial temperature distribution [2–6], so greater attention has been focused on the thermal aspects of OLEDs [7]. Therefore, in addition to the conventional optical performance, the thermal characteristics of OLEDs will also be investigated in this study. Several studies have constructed models for investigating the optical and thermal properties of OLEDs, with some also accounting for their electrical properties. Such models employ fluid dynamics, successive network reductions, equivalent circuits, spectral power distributions, and so on [2–5,8–13]. Electronics 2019, 8, 17; doi:10.3390/electronics8010017
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This study proposes an alternative modelling approach: a three-dimensional (3D) model to be used to simultaneously explore the optical and thermal performances of OLEDs. The proposed 3D OLED model integrates the optical and thermal sub-models by means of the energy conservation theory. According to the comparisons between experiment and the simulation, the proposed 3D model can predict the luminous properties and the thermal distributions of OLEDs with acceptable accuracy. Herein, the limitations of OLED modeling are discussed, and successive modeling demands for future development of OLEDs are projected. 2. Model The proposed 3D OLED model is constructed using two sub-models, with each accounting for a specific property of the OLEDs. The thermal sub-model predicts the temperature distribution of an OLED device, while the optical sub-model simulates the luminous performance of the device. Using the parameters of the energy-conversion ratios, the two sub-models are then integrated into a single model. To construct such a 3D model, both sub-models are established geometrically in a multiphysics-embedded platform, COMSOL, and a bottom-emission OLED device is used as an example. The geometry of the example device is modeled using the following the layers: an upper cover (glass), followed by a cathode (Al), organics, an anode (indium tin oxide, ITO), and finally a base (glass). To model a practical OLED sample, we consider an available OLED whose base glass with the dimensions of 40 mm × 40 mm × 1 mm, and the dimensions of other layers are listed in Table 1. The details of each sub-model are described in the following sections. Table 1. Dimensions and optical properties of the layers. Area (cm2 )
Thickness (mm)
Refractive Index
References
Upper cover (glass)
3×3
1
1.5
[14]
Cathode (Al)
1×1
1 × 10−4
0.96526 + i 6.3996
[15]
Organics
1×1
1.8 × 10−4
1.75
[16]
Anode (ITO)
1×1
1.5 × 10−4
1.8
[14]
Base (glass)
4×4
1
1.5
[14]
Interface Property
Transparent, Fresnel equations considered Reflective, Lambertian scattering Transparent, Fresnel equations considered Transparent, Fresnel equations considered
*The refractive indexes of the layers referred to the data in literatures, which may cause deviations between simulated and measured results. Additionally, the refractive indexes of the organic materials in an OLED device generally range from 1.68 to 1.8 [16]. To model these integrant organic materials by one organic layer, an approximate refractive index of 1.75 is utilized herein.
2.1. Thermal Sub-Model To investigate the thermal effect in OLEDs, the governing mechanisms of heat dissipation, including conduction between layers, conduction at the electrodes, convection between the OLED and the environment, and radiation from the OLED are considered in the thermal sub-model. The types of thermal dissipation for each OLED layer along with their equations are shown in Figure 1.
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Governing equation: Thermal conduction
Upper cover Cathode(Al)
External natural convection
Input Electromagnetic heat rate
Light
Organic layer Anode(ITO) Base Thermal conduction
Figure 1. 1. Schematic Schematic representation representation of of the the electro-thermal simulation model. Figure
The governing governing equation equation of of the the boundary boundary conditions conditions is The is based based on on the the 3D 3D heat heat equation equation [17]: [17]: . ∂T ∂Ti i∇ ∇∇⋅ (·κ(κi ∇ TTi )i )++qqee == ρρii ccii ∂t i ∂t
(1) (1)
where κ , T , ρ , and c are the thermal conductivity, temperature, density, and specific heat of each . where κii, Tii, ρii, and ci i are the thermal conductivity, temperature, density, and specific heat of each considered layer, respectively; q is the power of the heat converted from the input electrical power, considered layer, respectively; qee is the power of. the heat converted from the input electrical power, Pelectric , per unit volume. The volumetric power qe can be expressed as: Pelectric, per unit volume. The volumetric power qe can be expressed as: .
.
qe = Qe /Vorganic q e = Qe / Vorganic
(2) (2)
.
where V volumeofofthe theorganic organiclayer. layer. Q is the electromagnetic heat rate and can be derived organicisisvolume where Vorganic Q eeis the electromagnetic heat rate and can be derived from the input electrical power: . from the input electrical power: Qe = k heat · Pelectric (3) Qe = kpower (3) heat ⋅ Pelectric where kheat is the proportion of input electrical converted to the thermal power. Equation (3) describes thermal conduction of the considered based on the thermal Fourier’s law ofEquation conduction. where kheatthe is the proportion of input electrical powerlayer converted to the power. (3) To describe the steady state conditions of the entire thermal system, the device and its surroundings describes the thermal conduction of the considered layer based on the Fourier’s law of conduction. aredescribe assumedthe to experience convection, and the equation can be asits [5]:surroundings To steady statenatural conditions of the entire thermal system, theexpressed device and
are assumed to experience natural convection, and the equation can be expressed as [5]: q0 = h · ( Tenv − Tb )
(4) (4) where h, Tenv , and Tb are the heat transfer coefficient, ambient temperature, and boundary temperature where h, Tenv,respectively. and Tb are Along the heat coefficient, ambient and asboundary of the device, withtransfer the material parameters of thetemperature, example device, listed in temperature of the device, respectively. Along with the material parameters of the example device, Table 2, and the parameters of governing equations, the thermal characteristics of the device, such as as listed in Table 2, and the governing equations, theproposed thermal thermal characteristics of the temperature distributions on parameters the surfaces,ofcan be calculated from the sub-model. device, such as temperature distributions on the surfaces, can be calculated from the proposed Table 2. Parameters of the layers in the thermal sub-model. thermal sub-model.
q0 = h ⋅ (Tenv − Tb )
Thermal Conductivity Specific Heat 3 ) sub-model. Table 2. Parameters of the layers in the (kg/m thermal Density (W/m·K) (J/kg ·K)
References
2 Thermal conductivity 1.4 [18,19] 2.4 × (𝑘𝑔/𝑚 103 3) Specific 8.2 × 10heat Density References (𝑊/𝑚∙𝐾) 237 [18,19] 2.7 × 103 9(𝐽/𝑘𝑔∙𝐾) × 102 3 32 3 0.2 [18,20] 1.2 × 10 1.7 × 10 1.4 2.4×10 8.2×10 [18,19] 3 2 8 [20] 7.2 × 10 3.4 × 10 3 2 237 2.7×10 3 9×10 2 [18,19] 1.4 [18,19] 2.4 × 103 8.2 × 10 3 Organics 0.2 1.2×10 1.7×10 [18,20] * The parameters of materials are derived from literatures and not from3 the measurements of2 the materials in use, Anode (ITO)in deviations between8 simulated and measured 7.2×10 3.4×10 [20] which may results results. Base (glass) 1.4 2.4×103 8.2×102 [18,19] *The parameters of materials are derived from literatures and not from the measurements of the materials in use, which may results in deviations between simulated and measured results.
Upper cover (glass) Cathode (Al) UpperOrganics cover (glass) Anode (ITO) Cathode (Al) Base (glass)
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2.2. Optical sub-model 2.2. Optical Sub-Model The optical sub-model of an OLED is constructed to investigate its lighting performance, including the luminous at a target plane, luminous intensity distribution, etc. The optical sub-modelflux, of anilluminance OLED is constructed to investigate its lighting performance, including Because such flux, performances relate the far-field characteristics of distribution, the device, the of the luminous illuminance at a to target plane, luminous intensity etc.propagation Because such light is modeled approximately using geometrical ray-tracing. Similarly to the thermal sub-model, performances relate to the far-field characteristics of the device, the propagation of light is modeled the laminationusing of multiple organic materials with sub-micron thicknesses is the regarded as one approximately geometrical ray-tracing. Similarly to the thermal sub-model, lamination of integrated organic layer inwith the sub-micron optical sub-model. In order to increase modeling accuracy, multiple organic materials thicknesses is regarded as onethe integrated organic layerthe in Fresnel equations are applied those refractive interfaces, while diffuse scattering calculated the optical sub-model. In orderfor to increase the modeling accuracy, thethe Fresnel equations areisapplied for for the reflective cathodewhile according to Lambert’s law. The refractive thickness, those refractive interfaces, the diffuse scattering cosine is calculated for the reflectiveindex, cathode accordingand to optical property of each of the example device areoptical listedproperty in Tableof1.each In order the Lambert’s cosine law. The layer refractive index, thickness, and layer to of quantify the example total out-coupling luminous flux, to a quantify far-field the spherical receiver is luminous built herein. light-extraction device are listed in Table 1. In order total out-coupling flux,The a far-field spherical efficiency (ηLEEherein. ), defined the ratio between the(ηout-coupling light power and the power that is receiver is built The as light-extraction efficiency ), defined as the ratio between the out-coupling LEE emitted from the organic layer, can then be calculated. To analyze the luminous intensity light power and the power that is emitted from the organic layer, can then be calculated. To analyze and the illuminance distributions, a flat receiver positioned 1 receiver m away positioned from the organic layer is constructed luminous intensity and illuminance distributions, a flat 1 m away from the organic in theis form of square mesh. dimensions the flat receiver areflat 5.5receiver m × 5.5are m,5.5 leading to m, an layer constructed in the formThe of square mesh. of The dimensions of the m × 5.5 ◦ ◦ analyzable of luminous intensity intensity betweenbetween 70° and70−70°. flatthereceiver acquires the leading to anrange analyzable range of luminous andOnce −70 .the Once flat receiver acquires illuminance data of of every mesh, the illuminance luminous the illuminance data every mesh, the illuminanceofofthe theithithmesh, mesh,EEi,i ,can canbe be converted converted into luminous intensity,Ii .IiConsider . Consider a ray emits from source toward the ith mesh, as shown in Figure 2. Assume intensity, a ray emits from thethe source toward the ith mesh, as shown in Figure 2. Assume that ri th th that the source themesh i small mesh i, and θi of is incidence the angle is therdistance betweenbetween the source and the i and small whose areawhose is dAi , area and θisi isdA the angle i is the distance th mesh. Then the projected of incidence forThen the ithe areaonoftothe mesh normal on to the surface normal to the for the ith mesh. projected area of the ith mesh theithsurface to the ray can be counted th th ray can be counted as da i = dA i cosθ . According to the radiometry, the luminous flux through · daii/ as dai = dAi · cosθi . According to the radiometry, the luminous flux through the i mesh is Ei · dAi = Ii the i 2 2 is Ei dAi = formula Ii dai / risi .then A conversion rmesh derived asformula follows: is then derived as follows: i . A conversion 2
Z2 I i = Ei × Z3 Ii = Ei × cos 3θ i cos θi
(5) (5)
where Z is the normal distance between the source and the flat receiver. where Z is the normal distance between the source and the flat receiver.
Source
z
θi ri Area normal to the incident ray
Receiver
ith mesh
Figure 2. Schematic representation of the conversion between the illuminance and luminous intensity. Figure 2. Schematic representation of the conversion between the illuminance and luminous intensity. the proposed method for building an optical sub-model is adaptive for use with an Notably,
arbitrary optical simulation tool that is based on geometric ray-tracing. In order to link the thermal Notably, the proposed method for building an optical sub-model is adaptive for use with an sub-model, the optical simulation is performed using the same modeling platform, COMSOL, but a arbitrary optical simulation tool that is based on geometric ray-tracing. In order to link the thermal different module; namely, the ray optics module. Since a ray-tracing tool generally regards light sub-model, the optical simulation is performed using the same modeling platform, COMSOL, but a propagation as ray trajectories, a greater number of rays result in higher simulation accuracy, but with different module; namely, the ray optics module. Since a ray-tracing tool generally regards light longer calculation time. The constructed optical sub-model is then pretested to optimize the number propagation as ray trajectories, a greater number of rays result in higher simulation accuracy, but of rays required. It is found that when the number of rays is greater than 5 million, the light with longer calculation time. The constructed optical sub-model is then pretested to optimize the extraction efficiency calculated from the simulated luminous flux attains a stable value of η LEE = 27.3%. number of rays required. It is found that when the number of rays is greater than 5 million, the light Because such a pretest considers only the emitted light power and does not account for the thermal extraction efficiency calculated from the simulated luminous flux attains a stable value of ηLEE = effects, this test may also be performed using other optical simulation tools in order to confirm the 27.3%. Because such a pretest considers only the emitted light power and does not account for the results derived from COMSOL. LightTools is chosen because of its wide acceptance in the lighting thermal effects, this test may also be performed using other optical simulation tools in order to industry. After the optimization of the number of rays, the simulation via LightTools calculates the confirm the results derived from COMSOL. LightTools is chosen because of its wide acceptance in the lighting industry. After the optimization of the number of rays, the simulation via LightTools
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η LEE as 26.7%, close to that calculated by COMSOL. Both results are reasonable when compared to experimental data from literatures [21,22]. 2.3. Integration of Sub-Models The proposed optical and thermal sub-models are then integrated based on energy conservation theory. It is assumed that the input electric power, Pelectric , for the OLED device is converted to both optical and thermal power, and that other types of converted energy are negligible. Based on energy conservation theory, the input electric power ideally can be expressed as [9,13]: Pelectric = Plight + Pheat
(6)
where Plight is the power of light generation, and Pheat is the thermal power, which is equivalent to the power of heat: Pheat = Qe . Similarly to kheat , which is the ratio of the power of heat source to the input electrical power, a parameter klight is defined as a ratio of the power for light generation to the input electrical power: Plight = k light · Pelectric (7) From Equations (2), (6), and (7), the relationship between kheat and klight can be derived as: k heat = 1 − k light
(8)
According to the light extraction and optical loss mechanisms of OLEDs [14,23,24], the power for light generation results from several phenomena and is expressed as: Plight = Pelectric · ηEE · γ · ηS/T · ηrad
(9)
where η EE , γ, η S/T , and η rad are the electrical efficiency, the ratio of injected charge carriers that form excitons, the singlet and triplet fractions of excitons, and the ratio of the singlet and the triplet excitons which cause luminescent radiation, respectively. The last term, η rad , can be comprehended as the synthetic results of the photoluminescence of the acceptor and the transfer of singlet and triplet excitons from donors to acceptors [25]. Equations (7) and (9) show also that klight is the synthetic effect of η EE , γ, η S/T , and η rad . The luminescent light then encounters several optical ray-trapping mechanisms, such as the total internal effects in the substrate and other layers, as well as the surface plasma attenuation, etc. Only the extracted rays contribute to the final out-coupling light power, Poutput : Poutput = Plight · η LEE
(10)
A parameter of radiant efficiency, η o/e , is defined herein as the ratio of the output light power and the input electric power. From Equations (6)–(10), η o/e can be derived as: ηo/e = Poutput /Pelectric = k light · η LEE = ηEE · γ · ηS/T · ηrad · η LEE
(11)
Since the product of the central three terms is known as the internal quantum efficiency, IQE = γ · η S/T · η rad , and the product of IQE and η LEE equals the external quantum efficiency, EQE, the radiant efficiency can be also expressed as: ηo/e = ηEE · IQE · η LEE = ηEE · EQE
(12)
On the other hand, since the input electric power, Pelectric , is assumed to be transformed only of the optical and thermal powers, the full amount of electric power is implied to be received by the
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OLED device with an electrical efficiency, η EE , of unity. The internal quantum efficiency, IQE, and klight Electronics PEER REVIEW therefore2018, can7,bex FOR regarded as equivalent:
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Using Eqs. (2), (6)–(8), and (12), the power IQEfor =light k lightgeneration, Plight, that for heat, Pheat , and that (13) of the output, Poutput, can be calculated using the proposed sub–models. In order to resolve these equations, the input(2), electric , equivalent the product the Using Equations (6)–(8),power, and (12),Pelectric the power for lightto generation, Plight ,of that forinput heat, Pcurrent that heat , and and voltage, and Pthe parameter klight must bethe provided. Plight and Pheat to have beenthese derived, the of the output, , can be calculated using proposedOnce sub–models. In order resolve equations, output aforementioned thermal performances can be calculated using the proposed models. In the input electricoptical power,and Pelectric , equivalent to the product of the input current and voltage, and the other words, optical and thermal be linked as one synergetic model based on parameter klightthe must be provided. Oncesub-models Plight and Pcan been derived, the aforementioned optical heat have energy conservation theory and given parameters. and thermal performances can be the calculated using the proposed models. In other words, the optical and In this study, the sub-model is calculated using theon ray-optics module of COMSOL thermal sub-models canoptical be linked as one synergetic model based energy conservation theory andand the utilizes both a far-field receiver and a large receiver, which correspond to coarse and fine given parameters. resolutions, respectively. The thermal issub-model is calculated by themodule finite element method (FEM) In this study, the optical sub-model calculated using the ray-optics of COMSOL and utilizes via the heat-transfer-in-solid and the electric-current modules of COMSOL with its geometry both a far-field receiver and a large receiver, which correspond to coarse and fine resolutions, respectively. constructed in the far-field configuration. The two configurations arevia then integrated to The thermal sub-model is calculated by the finite element method (FEM) thefurther heat-transfer-in-solid become one model. The final model consists of the two sub-models, while their individual energy and the electric-current modules of COMSOL with its geometry constructed in the far-field configuration. ratios areconfigurations determined based on further energy integrated conservation theory.one model. The final model consists of the The two are then to become two sub-models, while their individual energy ratios are determined based on energy conservation theory. 3. Experiments and Discussions 3. Experiments and Discussions 3.1. Sample preparation 3.1. Sample Preparation Green phosphorescent OLEDs were fabricated by the conventional processes to demonstrate Green phosphorescent OLEDs were fabricated bysubstrate the conventional processes to demonstrate the the proposed model experimentally. Firstly, the glass was coated with the ITO, which was proposed model experimentally. Firstly, the glass substrate was coated with the ITO, which was then then etched to form the patterned anode. Next, the multiple organic layers were evaporated onto the etched to form patterned Next, the multiple organic layers were evaporated the patterned patterned ITO,the followed by anode. the evaporation of the Al/LiF cathode. Finally, the glassonto passivation was ITO, followed by the evaporation of the Al/LiF cathode. Finally, the glass passivation was allocated above allocated above the cathode, and glue was used to seal the sample. Among the organic layers, the the cathode, and glue waswas usedthe to seal the sample.ofAmong the organic layers, the essential green essential green emitter combination WPH-401 and WPGD-831 fabricated byemitter Shine was the combination WPH-401 WPGD-831 by Shine Materials Technology Materials TechnologyofCo. Ltd. Theand dimensions are fabricated listed in Table 1, and the emitting area is 1Co. cm2Ltd. , as 2 , as shown in Figure 3. Eight samples The dimensions are listed in Table 1, and the emitting area is 1 cm shown in Figure 3. Eight samples were made via the same process with identical parameters for the were madeinvestigation. via the same process with identical parameters for the following investigation. following
Figure 3. Green OLED sample.
3.2. Electrical Electrical properties Properties 3.2. The current-voltage current-voltage (I-V) (I-V) curves curves of of the the OLED were measured The OLED samples samples were measured using using aa semiconductor semiconductor device analyzer (Keysight B1500A). In laboratorial experiments, even the same run of of the the process device analyzer (Keysight B1500A). In laboratorial experiments, even the same run process practically produces samples with a certain discrepancy. Thus, the measured results of the practically produces samples with a certain discrepancy. Thus, the measured results of the eight eight samples were were then then averaged averaged and and converted convertedto toaacurrent currentdensity density-voltage the samples - voltage (J-V) (J-V) curve curve by by counting counting the emitting area, area, as as shown shown in in Figure Figure 4. 4. This This shows shows that that when when the the operation operation voltage voltage is is 55 V, V, the emitting the average average
current and input electrical power are 23 mA and 115 mW, respectively. In this example, these parameters are then used as input values for the proposed model.
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current and input electrical power are 23 mA and 115 mW, respectively. In this example, these values for the proposed model. 7 of 14
parameters thenPEER usedREVIEW as input Electronics 2018, are 7, x FOR 80 70
Current density
60 50
Pelectric = = 115 mW
40 30 23 20 10 0 0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
5.5
6
6.5
7
7.5
8
8.5
V Figure4.4.Average AverageJ-V J-Vcurve. curve. Figure.
The luminous flux of each sample was measured using a 15-cm-diameter integrating sphere The luminous flux of each sample was measured using a 15-cm-diameter integrating sphere (ISUZU IOC-6) equipped with a spectrometer. Under an operation voltage of 5 V, the current, (ISUZU IOC-6) equipped with a spectrometer. Under an operation voltage of 5 V, the current, radiant power, Poutput , and radiant efficiency, η o/e , of each sample were measured and calculated. radiant power, Poutput , and radiant efficiency, ηo/e, of each sample were measured and calculated. It is It is noteworthy that, although the output radiant power was measured in the unit of milliwatt, this noteworthy that, although the output radiant power was measured in the unit of milliwatt, this data data can be converted to the commonly used luminous-flux unit of lumen by means of the photopic can be converted to the commonly used luminous-flux unit of lumen by means of the photopic spectral luminous efficiency curve. Thus, the out-coupling luminous flux was also obtained, and the spectral luminous efficiency curve. Thus, the out-coupling luminous flux was also obtained, and the averaged result was 5.3 lm, equivalent to 9.74 mW for the samples herein. Although the measured averaged result was 5.3 lm, equivalent to 9.74 mW for the samples herein. Although the measured current through each sample differed, the resultant radiant efficiencies were similar. The average current through each sample differed, the resultant radiant efficiencies were similar. The average radiant efficiency of the samples was then calculated as (η o/e )ave = 8.45%. By means of the optical radiant efficiency of the samples was then calculated as (ηo/e )ave = 8.45%. By means of the optical sub-model and the aforementioned parameters, the relationship between klight and η o/e is obtained, sub-model and the aforementioned parameters, the relationship between klight and ηo/e is obtained, and klight is calculated to be 0.31 at the measured radiant efficiency. Once klight is obtained, the internal and klight is calculated to be 0.31 at the measured radiant efficiency. Once klight is obtained, the internal quantum efficiency, IQE, can be derived from Eq. (13). Next, using Eq. (8), the ratio kheat is calculated quantum efficiency, IQE, can be derived from Eq. (13). Next, using Eq. (8), the ratio kheat is calculated to be 0.69. Since klight and kheat are now determined, both sub-models provide absolute rather than to be 0.69. Since klight and kheat are now determined, both sub-models provide absolute rather than relative results. relative results. 3.3. Thermal Properties 3.3. Thermal properties The thermal properties of the fabricated samples were investigated via temperature measurements. The thermal properties of the fabricated samples were investigated via temperature The temperature distribution on the upper cover of the OLED was measured using a thermal imager measurements. The temperature distribution on the upper cover of the◦ OLED was measured using ◦a (InfraTec VarioCAM), while the ambient temperature was set as 24.6 C with the accuracy of ±0.3 C thermal imager (InfraTec VarioCAM), while the ambient temperature was set as 24.6 °C with the As shown in Figure 5, the resultant maximum and minimum temperatures of the samples are in the accuracy of ±0.3 °C As shown in Figure 5, the resultant maximum and minimum temperatures of the ranges of 30 ◦ C–32.5 ◦ C and 24.5 ◦ C–25.6 ◦ C, respectively, resulting in respective averages of 31.4 ◦ C samples are in the ranges of 30 °C - 32.5 °C and 24.5 °C - 25.6 °C, respectively, resulting in respective and 25.1 ◦ C. averages of 31.4 °C and 25.1 °C.
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30.16
35 30
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31.17
31.67
31.97
31.67
32.14
31.97
31.06
32.14
32.32
30.70
32.32
Temperature(℃) Temperature(℃)
31.17 31.06 30.70 30.16 25.11 24.86 25.24 25.00 25.53 25.56 24.90 30 24.70 25 25.11 24.86 25.24 25.00 25.53 25.56 24.90 24.70 25 20 20 15 15 10 10 5
5 0 1
0 1
2
3
4
Sample
2 Temperature 3 4 Min.
5
6
7
5 6 7 Max. Temperature
8 8
Sample Min. Temperature Max. Temperature Figure. 5. Measured temperature distributions of each sample. The red region in the temperature map is corresponding to the emission area of each sample with the dimension cm × 1 cm. map Figure 5. Measured temperature The red region in of the temperature Figure. temperaturedistributions distributionsofofeach eachsample. sample. The red region in1 the temperature is corresponding to the areaarea of each sample withwith the dimension of 1 cm 1 cm. map is corresponding to emission the emission of each sample the dimension of 1×cm × 1 cm.
To evaluate the proposed thermal sub-model, an ambient temperature of 24.6 °C and a heat ◦ C and transfer coefficient of 5 W/m2thermal K were sub-model, assigned; the temperatureofof distribution then To evaluate evaluate the proposed proposed thermal sub-model, ansimulated ambienttemperature temperature 24.6°C heat To the an ambient 24.6 andwas aaheat 2 K were obtained, as illustrated in Figure 6(a). The simulated maximum and minimum temperatures of the 2 transfer coefficient of 5 W/m assigned; the simulated temperature distribution was then transfer coefficient of 5 W/m K were assigned; the simulated temperature distribution was then upper cover of the OLED are 31.0 °C and 26.3 °C, respectively. To compare these results with those obtained,asasillustrated illustratedininFigure Figure6(a). 6a. The The simulated simulated maximum maximum and and minimum minimumtemperatures temperaturesof ofthe the obtained, ◦ C for ◦ C, respectively. of the experiment, relative errors the models were calculated as the ratio of the difference upper cover of the OLED are 31.0 and 26.3 To compare these results with those upper cover of the OLED are 31.0 °C and 26.3 °C, respectively. To compare these results with thoseof between the measured and simulated values to thewere measured [9]. 1.3% and 4.6% experiment, relative errors for the were calculated asvalue the as ratio ofratio the were difference between ofthe the experiment, relative errors for models the models calculated theThese of the difference for measured the maximum minimum temperatures, respectively. Since the thermal sub-model the and and simulated values to the measured value [9]. These were and 4.6% for the between the measured and simulated values to the measured value [9].proposed These1.3% were 1.3% and 4.6% was able to provide results close to those of the experiment, such a model was also applied maximum and minimum temperatures, respectively. Since the proposed thermal sub-model was able for the maximum and minimum temperatures, respectively. Since the proposed thermal sub-modelto investigate the cross-sectional temperature Thesuch inset between Figure 6(b) andthe to provide close to those thethose experiment, such a model wasaalso applied toalso investigate was able toresults provide results closeof to of distribution. the experiment, model was applied to(c) illustrates the the temperature temperature map of the central cross-section and defines the coordinates, Figs. cross-sectional distribution. The inset between Figure 6b,c illustrates the temperature investigate cross-sectional temperature distribution. The inset between Figure 6(b)while and map (c) 6(b) and (c) plot the temperature profile along the z axis. The results indicate that the temperature of the central cross-section and defines the coordinates, while Figure 6b,c plot the temperature profile illustrates the temperature map of the central cross-section and defines the coordinates, while Figs.at theand thin layers of the measured samples °C, thin close to thethat measured results in at the along the zplot axis.the The results indicate that the temperature at results the organic layers the measured 6(b) (c)organic temperature profile along the zwas axis.~31.0 The indicate theof temperature ◦ literature [7].~31.0 The simulated cross-sectional temperature distribution is meaningful reference for samples was C, close the measured results in~31.0 the literature simulated cross-sectional the thin organic layers of thetomeasured samples was °C, close[7]. to The thea measured results in the OLED manufacturers when selecting organic materials with appropriate thermal properties, such temperature is across-sectional meaningful reference for OLED manufacturers when selecting organic literature [7]. distribution The simulated temperature distribution is a meaningful reference foras the glass transition temperature, Tg. In addition, the proposed thermal sub-model materials with appropriate thermal properties, such asalthough the glass transition temperature, Tg. In addition, OLED manufacturers when selecting organic materials with appropriate thermal properties, such was as demonstrated on a small OLED, its governing equations for the conduction, convection, and although the proposed thermal sub-model was demonstrated on a small OLED, its governing equations the glass transition temperature, Tg. In addition, although the proposed thermal sub-model was radiation mechanisms are alsoand appropriate toequations large OLEDs. Thus, by extending theOLEDs. device for the conduction, convection, radiation are the also appropriate to large demonstrated on a small OLED, its governingmechanisms for conduction, convection, and dimensions in the thermal sub-model, the temperature distribution of a surface-like OLED can Thus, by extending the device dimensions in the thermal sub-model, the temperature distribution of be a radiation mechanisms are also appropriate to large OLEDs. Thus, by extending the device modeled. surface-like OLED can be modeled. dimensions in the thermal sub-model, the temperature distribution of a surface-like OLED can be modeled.
(°C) 31.0 31 (°C) 31.0 31 30.5
Emission area
30.5 30
Emission area 30 29.5 29.5 29 29 28.5 26.3 28.5
(a) (a).6. Cont. Figure
26.3
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of 14 9 of914
z
Temperature (℃)
Temperature (℃)
y
Z (mm)
(b)
Z (nm)
(c)
Figure 6. Simulated temperature distributions (a) on the upper cover glass and (b) along the central Figure 6. Simulated distributions (a)The on emission the upperarea cover (b) along the central cross-section, and temperature (c) an enlarged graph of (b). is 1glass cm2 and corresponding to the OLED dimension shown 3. graph of (b). The emission area is 1cm2 corresponding to the OLED cross-section, and (c) in anFigure enlarged dimension shown in Figure 3.
3.4. Optical Properties
3.4. Optical The properties illuminance distribution of every sample was measured by means of a digital lux meter (TES 1330A). A flat screendistribution was utilizedof as every a receiver at a distance of 1 m away from the The illuminance sample was measured by means of asample. digital The lux emission meter surface of the sample, represented by the insert of Figure 7, was oriented parallel to the screen and (TES 1330A). A flat screen was utilized as a receiver at a distance of 1 m away from the sample. The the centers of the and screen were coaxial. The illuminance thetocentral emission surface of sample the sample, represented by the insert of Figure 7,was wasmeasured oriented along parallel the horizontal and central vertical axes on the screen. The solid curve in Figure 7 shows the normalized screen and the centers of the sample and screen were coaxial. The illuminance was measured along the measured data along these two and theThe dashed simulated theaverage central of horizontal and central vertical axes onaxes, the screen. solidcurve curverepresents in Figure 7the shows the illuminance after normalization. The simulated illuminance distribution agreed closely with normalized average of the measured data along these two axes, and the dashed curve represents thethe measured data, whileafter a difference was noted at distances of more than 2 m awayagreed from the screen simulated illuminance normalization. The simulated illuminance distribution closely center. Because the measured beyond thisatdistance is lower than 0.012 lux, whichfrom is beyond with the measured data, while ailluminance difference was noted distances of more than m away the the accuracy of the lux meter that was used, the error is attributed to the precision of the instrument. screen center. Because the measured illuminance beyond this distance is lower than 0.01 lux, which Additionally, although done for an OLED with a small emission is beyond the accuracy ofthe thedemonstrated lux meter thatmeasurement was used, thewas error is attributed to the precision of the area, it is also applicable to a large surface light by extending the distance between the light source instrument. Additionally, although the demonstrated measurement was done for an OLED with and a the emission flat screen.area, Suchit aisdistance is suggested to at least 20 times the diameter of the emission area small also applicable to a be large surface light byof extending the distance between ◦. geometrically restrict the angular discrepancy within thetolight source and the flat screen. Such a distance is 1.5 suggested be to at least 20 times of the On the other hand, a goniophotometer (AMA LID-100) was applied to directly measure diameter of the emission area to geometrically restrict the angular discrepancy within 1.5. theOn intensity distribution. The solid line in Figure 8 provides an average intensity distribution the other hand, a goniophotometer (AMA LID-100) was applied to directly measure the measured along theThe zero-latitude zero-longitude directions, referringdistribution to photometry type C. intensity distribution. solid line inand Figure 8 provides an average intensity measured Additionally, from the measured illuminance distribution, the luminous intensity distribution was along the zero-latitude and zero-longitude directions, referring to photometry type C. Additionally, calculated, shown by the dashed line in Figure 8. Using the proposed model, the simulated luminous from the measured illuminance distribution, the luminous intensity distribution was calculated, intensity distribution wasinobtained, by the dotted linethe in Figure 8. The curves inintensity this figure shown by the dashed line Figure 8.represented Using the proposed model, simulated luminous have all been normalized to facilitate comparison. Next, the beam angles were calculated distribution was obtained, represented by the dotted line in Figure 8. The curves in this figurefrom havethe ◦ , 124◦ , and 130◦ , goniophotometer measurement, illuminance measurement, and simulation to be 127 all been normalized to facilitate comparison. Next, the beam angles were calculated from the respectively. Themeasurement, simulated curve largely agrees with the experimental data, except for instances with goniophotometer illuminance measurement, and simulation to be 127, 124, and ◦ . Since the locations where the discrepancies between the measured and half angles more than ~60 130, respectively. The simulated curve largely agrees with the experimental data, except for ◦ this discrepancy in intensity simulated illuminances occurred at half angles of greaterwhere than 63 instances with half angles more thanare ~60. Since the locations the, discrepancies between the distribution is also attributed to the precision of the lux meter. On the whole, since the63, measured measured and simulated illuminances occurred are at half angles of greater than this and simulated results are largely consistent with each other, the proposed model for investigation discrepancy in intensity distribution is also attributed to the precision of the lux meter. On the of illumination acceptable. whole, since theismeasured and simulated results are largely consistent with each other, the proposed
model for investigation of illumination is acceptable.
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Simulation Simulation Measured Measured
Normalized illuminance
Normalized illuminance
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Position (mm)
(mm) Figure 7. Measured Position and simulated illuminance distributions. Figure 7. Measured and simulated illuminance distributions. Figure 7. Measured and simulated illuminance distributions.
-90
Normalized luminous intensity
Normalized luminous intensity
1
-90 -70
0.8
0.6
0.4
0.2
-70 -50
-50 -30
-300 -10
1
Simulation Simulation
0.8
From goniophotometer From goniophotometer
0.6
From illuminance From illuminance 0.4
0.2
0 -10 10
10 30
Angle (°) Angle (°)
30 50
50 70
70 90
90
Figure 8. Luminous intensity distributions derived from goniophotometer measurement, Figure 8. Luminous intensity distributions derived from goniophotometer measurement, illuminance and simulation. Figure 8.measurement, Luminous intensity distributions derived from goniophotometer measurement, illuminance illuminance measurement, and simulation. measurement, and simulation.
3.5. Discussions 3.5. Discussions 3.5. Discussions According to the simulated temperature distribution of the cross-section, the temperature According to the simulated temperature distribution of the cross-section, the to the simulated temperature of the cross-section, thetemperature temperature variance -4 °C. distribution variance According for the organic layer is 2.43×10 It means that the organic materials withstand a -4 − 4 ◦ variance for forthe theorganic organiclayer layer is 2.43×10 °C. Itmeans meansthat that the organic materials withstand a is 2.43 × 10 C. It the organic materials withstand a temperature temperature gradient of 1.35 °C/mm, which is also a reference for material selection. Based on the ◦ C/mm, temperature gradient of 1.35 °C/mm, which is also a reference materialselection. selection.Based Based on on the the result of gradient of 1.35 is also a reference forfor material result of temperature gradient,which when the thermal parameters are known, the threshold condition of result of temperature temperature gradient, when the thermal parameters are known, the threshold condition of of some gradient, the thermal are known, Since the threshold condition some thermal issues, suchwhen as burn-in effect,parameters may be analyzable. the issues of burn-in, some thermal such as burn-ineffect, effect,may may analyzable. Since the issues of burn-in, thermalissues, issues, suchin asOLED burn-in be be analyzable. the issues of the burn-in, uniformity uniformity and lifetime display are related closely toSince the temperature, proposed model and uniformity and lifetime in OLED display are related closely to the temperature, the proposed model lifetime intoOLED display are related closely the temperature, thedisplay proposed model is of applicable is applicable the investigation of not only thetolighting but also the application OLED to is applicable to the investigation of not only the lighting but display also theapplication display application of OLED the investigation of not only the lighting but also the of OLED devices. devices. devices. aforementioned embodiment of proposed the proposed model considered the structure The The aforementioned embodiment of the model considered the structure and and the the The parameters aforementioned embodiment of the experimental proposed model considered the structure andbethe according to our available resources. The model, though, can utilized parameters according to our available experimental resources. The model, though, can be utilized for parameters according to our available experimental resources. The model, though, can be utilized other diverse a desiccative layer between the Al for other diverse conditions. conditions. AAbottom-emission bottom-emissionOLED OLEDwith with a desiccative layer between thecathode Al for otherand diverse conditions. A bottom-emission OLED with a desiccative layer between the Al the upper cover is taken as another example. Assume that the desiccative layer is 500 µm in cathode and the upper cover is taken as another example. Assume that the desiccative layer is 500 cathode and the upper coverwith is taken as another example. Assume that the desiccative layer is are 500the same thickness and filled the nitrogen gas (N ), and the configurations of other layers 2 μm in thickness and filled with the nitrogen gas (N2), and the configurations of other layers are the μm in thickness and filled with the nitrogen gas (N2in ), and the9a. configurations ofproposed other layers are theapproach, aforementioned embodiment, as as shown on theon modeling sameasas aforementioned embodiment, shown Figure in Figure 9Based (a). Based the proposed modeling same as aforementioned embodiment, as shown in Figure 9 (a). Based on the proposed modeling the simulation results show that such a N gap brings about the maximum temperature of 33.8 ◦ C 2 approach, the simulation results show that such a N2 gap brings about the maximum temperature ◦ approach,atthe simulation results show that such a N 2 gap brings about the maximum temperature upper cover,cover, equivalent to ~2toC~2higher thanthan that that of the without N2 .NThe reason of the of 33.8 the °C at the upper equivalent °C higher of one the one without 2. The reason of 33.8 °Ctemperature at the upperincrement cover, equivalent to ~2 °C higher than that of the one without N 2 . The reason lies inlies thein lowthe thermal conductivity of N2 , which the dissipation rate of the temperature increment low thermal conductivity of Nreduces 2, which reduces the of the temperature increment lies inthe theheat lowaccumulates thermal conductivity of and N2, causes which the reduces the of the generated heat. Then in the device higher maximum dissipation rate of the generated heat. Then the heat accumulates in the device and causes the dissipation rate of the generated heat. Then the heat result accumulates in thesuch device and causes the temperature of the upper cover. The modelled has reflected a phenomenon, as shown higher maximum temperature of the upper cover. The modelled result has reflected such a in higher maximum temperature of the upper cover. The modelled result has reflected such a Figure 9b. as Asshown for theinoptical the OLED the N2 gap significant change phenomenon, Figureperformance, 9 (b). As for the optical with performance, theshows OLEDno with the N2 gap phenomenon, as shown in Figure 9 (b). As for the optical performance, the OLED with the N2 gap shows no significant change in simulation, compared with the one without N2. That is because shows no significant change in simulation, compared with the one without N2. That is because those emitting rays propagating toward the N2 gap are all blocked by the Al cathode. Besides those emitting rays propagating toward the N2 gap are all blocked by the Al cathode. Besides
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in simulation, compared with the one without N2 . That is because those emitting rays propagating Electronics 2018, 7, x FOR PEER REVIEW 11 of 14 toward the N2 gap are all blocked by the Al cathode. Besides structures or configurations, OLEDs operated in altered surroundingOLEDs conditions, suchinasaltered a hot, surrounding cold or windy environment, structures or configurations, operated conditions, suchcan as aalso hot,be cold analyzed by the proposed model with appropriate parameters, including the ambient temperature, or windy environment, can also be analyzed by the proposed model with appropriate parameters, theincluding convectionthe coefficient, Consequently, proposed model is exploitable for various applications ambientetc. temperature, thethe convection coefficient, etc. Consequently, the proposed likemodel automotive lightingfor and street lighting. is exploitable various applications like automotive lighting and street lighting. (°C) 33.8 31
Upper cover Nitrogen gas(N2) Cathode(Al)
30.5
Emission area
30
Organic layer 29.5
Anode(ITO)
29
Base
28.5 26.3
(a)
(b)
Figure 9. Another embodiment of the OLED with a desiccative layer filled 2. (a) Schematic Figure 9. Another embodiment of the OLED with a desiccative layer filled withwith N2 . N(a) Schematic representation of structure, simulated temperature distributions on the upper cover glass. representation of structure, andand (b) (b) simulated temperature distributions on the upper cover glass.
TheThe proposed model utilizes pluralplural optical and thermal parameters, such as such the refractive index, proposed model utilizes optical and thermal parameters, as the refractive theindex, thermal and the specific heatspecific of every layer. By means ofBy these parameters, model theconductivity thermal conductivity and the heat of every layer. means of thesethe parameters, herein calculates light propagation heat dissipation the emitting layer through thethrough rest the model herein calculates light and propagation and heat from dissipation from the emitting layer layers on the geometrical ray-tracing theory and the aforementioned heat transfer heat equations. the based rest layers based on the geometrical ray-tracing theory and the aforementioned transfer Eventually, the optical and thermal performances in the air are obtained. Hence, the precision of these equations. Eventually, the optical and thermal performances in the air are obtained. Hence, the parameters affects the accuracy of the model. theofrefractive indexParticularly, of the organicthe precisionsignificantly of these parameters significantly affects Particularly, the accuracy the model. layer is not exact butofanthe approximate value integrant materials. Then the refractive index organic layer is of notthe exact but anorganic approximate value ofthe thedirections integrantof organic rays refracted from the organic layer are estimated and may cause the discrepancy between the simulated materials. Then the directions of the rays refracted from the organic layer are estimated and may andcause measured optical performance. Similarly, the thermal parameters of theperformance. organic layerSimilarly, may incurthe the discrepancy between the simulated and measured optical uncertainty the simulated performance. major limitation of proposed model lies thermal in parameters of thermal the organic layer Thus, may the incur uncertainty inthe the simulated thermal in the uncertain material-parameters of the organic layer, which may reduce the modeling accuracy. performance. Thus, the major limitation of the proposed model lies in the uncertain Although the proposed demonstrates a far-field luminous simulation, it is also material-parameters of themodel organic layer, whichonly mayfor reduce the modeling accuracy. able to be integrated with the near-field optical models via the algorism of the FEM, bringing about Although the proposed model demonstrates only for a far-field luminous simulation, it is also nano-scale applications. For example, along optical with the development of OLEDs,ofthe and thermal able to be integrated with the near-field models via the algorism theoptical FEM, bringing about interactions between the organic of analong OLEDwith devicethe require deeper inspection. These nano-scale applications. For layers example, development of OLEDs, thenano-scale optical and properties analysis and theoretical predictions using electromagnetic-wave (EM-wave) theory thermalrequire interactions between the organic layers of an OLED device require deeper inspection. These without approximations. FEManalysis is one ofand the approaches can deal with EM-wave issues, nano-scale properties Since require theoretical that predictions usingsuch electromagnetic-wave the(EM-wave) proposed model, integrates FEM and Since ray optics, for that thesecan interlayer theorywhich without approximations. FEM provides is one of compatibility the approaches deal with investigations. Another example arises from the insufficient efficiency of OLEDs, while nano-techniques, such EM-wave issues, the proposed model, which integrates FEM and ray optics, provides such as surface plasma polaritons and graphene quantumAnother dots [26–28], are investigated for new compatibility for these interlayer investigations. example arises from the solutions. insufficient Then, there exist modeling demands for these nano-structures. Again, the light propagation efficiency of OLEDs, while nano-techniques, such as surface plasma polaritons andthrough graphene these nano-structures is outare of the regime of ray-optics and has toThen, be analyzed by means of thedemands completefor quantum dots [26–28], investigated for new solutions. there exist modeling EM-wave theory. Then using FEM embedded with EM-wavethrough equations for varying structure parameters, these nano-structures. Again, the light propagation these nano-structures is out of the such as the diameter and the thickness of the nano-structures, the emission efficiency can be calculated regime of ray-optics and has to be analyzed by means of the complete EM-wave theory. Thenand using optimized. Afterwards, through a macro-scale for the geometric the as restthe refractive FEM embedded with EM-wave equationsmodel for varying structure optimization parameters, of such diameter structures the OLED, of the emittedthe light can be suppressed, andbe thecalculated lighting characteristics, and theofthickness of the theloss nano-structures, emission efficiency can and optimized. such as luminousthrough intensityadistribution, canmodel be designed. when the coverage of aofmodel is extended Afterwards, macro-scale for theThus, geometric optimization the rest refractive from nano- to macro-scales, notthe onlyloss the efficiency of OLEDlight devices their lighting performance structures of the OLED, of the emitted canbut bealso suppressed, and the lighting cancharacteristics, be optimized. such as luminous intensity distribution, can be designed. Thus, when the coverage of a model is extended from nano- to macro-scales, not only the efficiency of OLED devices but also their lighting performance can be optimized. The technologies of integrated modeling of OLED devices are listed in Table 3. Each technology investigates specific performances of OLEDs. The study presented here particularly integrates the
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The technologies of integrated modeling of OLED devices are listed in Table 3. Each technology investigates specific performances of OLEDs. The study presented here particularly integrates the FEM thermal and ray-traced optical models for OLEDs lighting applications by means of the energy conservation theory. With the development of these modeling technologies, the designers can predict and optimize the performances of OLEDs, benefiting the reduction in both manufacturing costs and development period of the novel OLEDs. Table 3. Integrated-modeling technologies for OLED devices. Simulation Targets
Modeling Technology Successive network reduction (SURND)
Optical Features
•
Luminance distribution of a lighting panel [2]
Thermal Features
•
Temperature distribution of the active layer [8]
Electrical Features
• •
Finite-element method (FEM)
•
Luminance distribution of a lighting panel [3]
• • •
FEM + Computational fluid dynamics (CFD)
•
Luminance distribution of a lighting panel
• •
Photo-electro-thermal theory (PET) + Spectral power distribution (SPD)
•
• • Equivalent circuits model
• • •
Doping device model + Thin-film optics
•
Time-dependent temperature [4] Temperature distribution of a lighting panel [4] Vertical temperature profile [4]
• • •
Voltage distribution of the active layer [8] Current density distribution of the ITO layer [8]
[2,8]
Temperature- dependent current density [3] Voltage and current distribution [4] Time-dependent current density [4]
[3,4]
Convection coefficient distribution Temperature distribution of a lighting panel
[5]
Temperature-dependent and input-powerdependent correlated color temperature (CCT) Input-power-dependent luminous flux Luminance uniformity at different current Luminance non-uniformity [10] Luminance distribution of a lighting panel [11] Current-dependent luminous flux and efficacy [12]
References
[9]
• •
Current-dependent temperature [12] Thermal changing ratio [13]
• •
•
Electroluminescent (EL) spectra
•
Current distribution of a panel [10] I-V curve [11,12]
[10–13]
[28]
•
Carrier density and recombination of electrons and holes J-V curve
•
Voltage effect considered
[29]
•
Voltage distribution at OLED junction
[30]
Voltage-dependent luminance
• Current-dependent luminance Radial Basis Neural Network
•
Luminescence power of OLED emitting layer
Vertical natural convection models FEM + Ray tracing
• •
Illuminance distribution Luminous intensity distribution
•
Temperature distribution of a lighting panel
•
Temperature distribution of a lighting panel Temperature distribution across the junction
•
Proposed herein
4. Conclusions In this study, a 3D model was constructed for analyzing and predicting the thermal effects and optical performances of an OLED lighting device. Two sub-models—an optical model and a thermal model—were integrated into a single model using a ratio of energy conversion. Compared with other OLED modeling approaches [2–13,29–31], the proposed model exploited the measured output radiant-power to simulate not only lighting performance, such as illuminance and luminous intensity distribution with acceptable accuracy, but also to predict the 3D temperature distribution, including that of the upper cover and that along the cross-section of the OLED devices. In addition, comparisons between the experimental and simulated results were carried out to confirm the accuracy of the integrated model. Moreover, the cross-sectional temperature of OLED devices was obtained, which
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provide manufacturers with guidelines for producing organic layers with appropriate glass transition temperatures, Tg. Hence, the proposed model is beneficial in not only predicting the optical and thermal characteristics of OLED lighting devices, but also designing their fabrication parameters, and even selecting materials for improving device performance. Author Contributions: Conceptualization, methodology, project administration, and writing—review & editing, A.-C.W.; Investigation, software, validation, and writing—original draft preparation, Y.-J.H.; Visualization and software, B.-L.H.; Funding acquisition, J.-R.S. Acknowledgments: The authors appreciate the assistance in OLED device manufacturing of Electronic and Optoelectronic System Research Laboratories in Industrial Technology Research Institute (ITRI), Taiwan, R.O.C. This study is financially supported by the Ministry of Science and Technology, Taiwan, R. O.C. under the contracts: No. MOST 105-2221-E-008-088-MY2, No. MOST 107-2221-E-008-093, and 107-2221-E-492-026-MY3. Conflicts of Interest: The authors declare no conflict of interest.
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