유기발광 디스플레이 수명 모델 제안 및 모델 검증 체계 연구

학위논문 (박사)-- 서울대학교 대학원 : 공과대학 기계항공공학부, 2018. 2. 윤병동.Despite the advantages of organic light-emitting diode (OLED) displays over liquid crystal displays, OLED displays suffer from reliability concerns related to luminance degradation and color shift. In particular, existing testing schemes are unable to reliably estimate the lifetime of large OLED displays (i.e., displays of 55 inches or larger). The limited number of test samples and the immature technology result in great hurdles for timely product development. This study proposes a statistical approach to develop a lifetime model for OLED panels. The proposed approach incorporates manufacturing and operational uncertainties, and accurately estimates the lifetime of the OLED panels under normal usage conditions. The proposed statistical analysis approach consists of: (1) design of accelerated degradation tests (ADTs) for OLED panels, (2) establishment of a systematic scheme to build bivariate lifetime models for OLED panels, (3) development of two bivariate lifetime models for OLED panels, and (4) statistical model validation for the heat dissipation analysis model for OLED TV design. This four-step statistical approach will help enable accurate lifetime prediction for large OLED panels subjected to various uncertainties. Thereby, this approach will foster efficient and effective OLED TV design to meet desired lifespan requirements. Furthermore, two bivariate acceleration models are proposed in this research to estimate the lifetime of OLED panels under real-world usage conditions, subject to manufacturing and operational uncertainties. These bivariate acceleration models take into account two main factors—temperature and initial luminance intensity. The first bivariate acceleration model estimates the luminance degradation of the OLED panelthe second estimates the panels color shift. The lifespan predicted by the proposed lifetime model shows a good agreement with experimental results. Ensuring the color shift lifetime is a great hurdle for OLED product development. However, at present, there is no effective way to estimate the color shift lifetime at the early stages of product development while the product design is still changing. The research described here proposes a novel scheme for color shift lifetime analysis. The proposed method consists of: (1) a finite element model for OLED thermal analysis that incorporates the uncertainty of the measured surface temperature, (2) statistical model validation, including model calibration, to verify agreement between the predicted results and a set of experimental data (achieved through adjustment of a set of physical input variables and hypothesis tests for validity checking to measure the degree of mismatch between the predicted and observed results), and (3) a regression model that can predict the color shift lifetime using the surface temperature at the early stages of product development. It is expected that the regression model can substantially shorten the product development time by predicting the color shift lifetime through OLED thermal analysis.Chapter 1. Introduction 1 1.1 Background and Motivation 1 1.2 Overview and Significance 2 1.3 Thesis Layout 6 Chapter 2. Literature Review 8 2.1 Accelerated Testing 8 2.2 Luminance Degradation Model for OLEDs 12 2.3 Color Shift of OLEDs 14 2.4 Verification and Validation Methodology 16 Chapter 3. OLED Degradation 28 3.1 Chromaticity and the Definition of Color Shift Lifetime 30 3.2 Degradation Mechanism 31 3.2.1 Luminance Degradation Mechanism 33 3.2.2 Color Shift Mechanism 34 3.3 Performance Degradation Models 36 3.3.1 Performance Degradation Model 36 3.3.2 Performance Color Shift Model 38 3.4 Acceleration Model 38 Chapter 4. Acceleration Degradation Testing (ADT) for OLEDs 42 4.1 Experimental Setup 42 4.2 Definition of the Time to Failure 46 4.2.1 The Time to Failure of Luminance 46 4.2.2 The Time to Failure of Color Shift 47 4.3 Lifespan Test Results 50 Chapter 5. Bivariate Lifetime Model for OLEDs 53 5.1 Fitting TTF Data to the Statistical Distribution 53 5.1.1 Estimation of Lifetime Distribution Parameters 53 5.1.2 Estimation of the Common Shape Parameter 58 5.1.3 Likelihood-Ratio Analysis 62 5.2 Bivariate Lifetime Model 64 5.2.1 Luminance Lifetime Model 64 5.2.2 Color Shift Lifetime Model 66 5.3 Validation of the Lifetime Model 67 Chapter 6. Statistical Model Validation of Heat Dissipation Analysis Model 77 6.1 Estimation Method for TTF using Surface Temperature 79 6.2 Thermal Analysis Model for OLED Displays 81 6.3 Statistical Calibration using the EDR Method 82 6.4 Validity Check 87 6.5 Results and Discussion 90 Chapter 7. Case Study 93 7.1 Computational Modeling 93 7.2 Estimation of Color Shift 95 7.3 Estimation of Luminance Degradation 96 Chapter 8. Contributions and Future Work 98 8.1 Contributions and Impacts 98 8.2 Suggestions for Future Research 103 References 104Docto

Methods for modeling degradation of electrical engineering components for lifetime prognosis

Reliability of electrical components is an issue studied to improve the quality of products, and to plan maintenance in case of failure. Reliability is measured by studying the causes of failure and the mean time to failure. One of the methods applied in this field is the study of component aging, because failure often occurs after degradation. The objective of this thesis is to model the degradation of components in electrical engineering, in order to estimate their lifetime. More specifically, this thesis will study large area organic white light sources (OLEDs). These sources offer several advantages in the world of lighting thanks to their thinness, their low energy consumption and their ability to adapt to a wide range of applications. The second components studied are electrical insulators applied to pairs of twisted copper wires, which are commonly used in low voltage electrical machines. First, the degradation and failure mechanisms of the various electrical components, including OLEDs and insulators, are studied. This is done to identify the operational stresses for including them in the aging model. After identifying the main causes of aging, general physical models are studied to quantify the effects of operational stresses. Empirical models are also presented when the physics of degradation is unknown or difficult to model. Next, methods for estimating the parameters of these models are presented, such as multilinear and nonlinear regression, as well as stochastic methods. Other methods based on artificial intelli­gence and online diagnosis are also presented, but they will not be studied in this thesis. These methods are applied to degradation data of organic LEDs and twisted pair insulators. For this purpose, accelerated and multifactor aging test benches are designed based on factorial experimental designs and response surface methods, in order to optimize the cost of the experiments. Then, a measurement protocol is described, in order to optimize the inspection time and to collect periodic data. Finally, estimation methods tackle unconstrained deterministic degradation models based on the measured data. The best empirical model of the degradation trajectory is then chosen based on model selection criteria. In a second step, the parameters of the degradation trajectories are modeled based on operational constraints. The parameters of the aging factors and their interactions are estimated by multilinear regression and according to different learning sets. The significance of the parameters is evaluated by statistical methods if possible. Finally, the lifetime of the experiments in the validation sets is predicted based on the parameters estimated by the different learning sets. The training set with the best lifetime prediction rate is considered the best

Degradation of the luminance and impedance evolution analysis of an OLED under thermal and electrical stress

Organic light emitting diodes are one of the most innovative light sources. They do not require semiconductor fabrication techniques like the LED family, they are simple to construct and are used in many original applications. The inconvenient of this product is that it does not have a long lasting useful life with more then 10000 hours. Therefore, this paper will present a parametric method to design an aging model of the OLED based on luminance decay and electrical impedance evolution. Accelerated tests using thermal factor and currentdensity will be applied to large warm white OLED panels. A log-normal model for the luminance decay will be merged withdesign of experiments method to include the stress factors as well as impedance characteristics resulting in an effective degradation model that can estimate the lifetime of the OLED

Charge-carrier dynamics in organic LEDs

Anyone who decides to buy a new mobile phone today is likely to buy a screen made from organic light-emitting diodes (OLEDs). OLEDs are a relatively new display technology and will probably account for the largest market share in the upcoming years. This is due to their brilliant colors, high achievable display resolution, and comparably simple processing. Since they are not based on the rigid crystal structure of classical semiconductors and can be produced as planar thin-film modules, they also enable the fabrication of large-area lamps on flexible substrates – an attractive scenario for future lighting systems. Despite these promising properties, the breakthrough of OLED lighting technology is still pending and requires further research. The charge-carrier dynamics in an OLED determine its device functionality and, therefore, enable the understanding of fundamental physical concepts and phenomena. From the description of charge-carrier dynamics, this work derives experimental methods and device concepts to optimize the efficiency and stability of OLEDs. OLEDs feature an electric current of charge carriers (electrons and holes) that are intended to recombine under the emission of light. This process is preceded by charge-carrier injection and their transport to the emission layer. These three aspects are discussed together in this work. First, a method is presented that quantifies injection resistances using a simple experiment. It provides a valuable opportunity to better understand and optimize injection layers. Subsequently, the charge carrier transport at high electrical currents, as required for OLEDs as bright lighting elements, will be investigated. Here, electro-thermal effects are presented that form physical limits for the design and function of OLED modules and explain their sudden failure. Finally, the dynamics and recombination of electro-statically bound charge carrier pairs, so-called excitons, are examined. Various options are presented for manipulating exciton dynamics in such a way that the emission behavior of the OLED can be adjusted according to specific requirements.:List of publications . . . . . . . . . . . . . . . . . v List of abbreviations . . . . . . . . . . . . . . . . . ix 1 Introduction . . . . . . . . . . . . . . . . . 1 2 Fundamentals . . . . . . . . . . . . . . . . . 5 2.1 Light sources and the human society . . . . . . . . . . . . . . . . . 5 2.1.1 Human light perception . . . . . . . . . . . . . . . . . . . . 8 2.1.2 Physical light quantification . . . . . . . . . . . . . . . . . . 10 2.1.3 Non-visual light impact . . . . . . . . . . . . . . . . . . . . . 13 2.1.4 Implications for modern light sources . . . . . . . . . . . . . 15 2.2 Organic semiconductors . . . . . . . . . . . . . . . . . . . . . . . . 17 2.2.1 Molecular energy states . . . . . . . . . . . . . . . . . . . . . 18 2.2.2 Intramolecular state transitions . . . . . . . . . . . . . . . . 24 2.2.3 Molecular films . . . . . . . . . . . . . . . . . . . . . . . . . 31 2.2.4 Electrical doping . . . . . . . . . . . . . . . . . . . . . . . . 34 2.2.5 Charge-carrier transport . . . . . . . . . . . . . . . . . . . . 36 2.2.6 Exciton formation and recombination . . . . . . . . . . . . . 38 2.2.7 Exciton transfer . . . . . . . . . . . . . . . . . . . . . . . . . 41 2.3 Organic light-emitting diodes . . . . . . . . . . . . . . . . . . . . . 44 2.3.1 Structure and operation principle . . . . . . . . . . . . . . . 44 2.3.2 Metal-semiconductor interfaces . . . . . . . . . . . . . . . . 47 2.3.3 Typical operation characteristics . . . . . . . . . . . . . . . . 49 2.4 Colloidal nanocrystal emitters . . . . . . . . . . . . . . . . . . . . . 52 2.4.1 Terminology: Nanocrystals and quantum dots . . . . . . . . 52 2.4.2 The particle-in-a-box model . . . . . . . . . . . . . . . . . . 54 2.4.3 Surface passivation . . . . . . . . . . . . . . . . . . . . . . . 55 3 Materials and methods . . . . . . . . . . . . . . . . . 57 3.1 Materials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 3.1.1 OLED materials . . . . . . . . . . . . . . . . . . . . . . . . . 57 3.1.2 Materials for photoluminescence . . . . . . . . . . . . . . . . 60 3.2 Sample preparation . . . . . . . . . . . . . . . . . . . . . . . . . . . 62 3.2.1 Thermal evaporation . . . . . . . . . . . . . . . . . . . . . . 62 3.2.2 Solution processing . . . . . . . . . . . . . . . . . . . . . . . 64 3.3 Spectroscopy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 3.3.1 Absorbance spectroscopy . . . . . . . . . . . . . . . . . . . . 66 3.3.2 Photoluminescence quantum yield . . . . . . . . . . . . . . . 66 3.3.3 Excitation sources . . . . . . . . . . . . . . . . . . . . . . . 67 3.3.4 Sensitive EQE for absorber materials . . . . . . . . . . . . . 68 3.4 Exciton-lifetime analysis . . . . . . . . . . . . . . . . . . . . . . . . 69 3.4.1 Triplet lifetime . . . . . . . . . . . . . . . . . . . . . . . . . 69 3.4.2 Singlet-state lifetime . . . . . . . . . . . . . . . . . . . . . . 70 3.4.3 Lifetime extraction . . . . . . . . . . . . . . . . . . . . . . . 70 3.5 OLED characterization . . . . . . . . . . . . . . . . . . . . . . . . . 73 3.5.1 Current-voltage-luminance and quantum efficiency . . . . . . 73 3.5.2 Temperature-controlled evaluation . . . . . . . . . . . . . . . 74 4 Charge-carrier injection into doped organic films . . . . . . . . . . . . . . . . . 77 4.1 Ohmic injection contacts . . . . . . . . . . . . . . . . . . . . . . . . 79 4.2 Device architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 4.2.1 Conception . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 4.2.2 Device symmetry . . . . . . . . . . . . . . . . . . . . . . . . 80 4.2.3 Device homogeneity . . . . . . . . . . . . . . . . . . . . . . . 83 4.3 Resistance characteristics . . . . . . . . . . . . . . . . . . . . . . . . 84 4.3.1 Experimental results . . . . . . . . . . . . . . . . . . . . . . 84 4.3.2 Equivalent-circuit development . . . . . . . . . . . . . . . . 85 4.4 Impedance spectroscopy . . . . . . . . . . . . . . . . . . . . . . . . 92 4.4.1 Measurement fundamentals . . . . . . . . . . . . . . . . . . 92 4.4.2 Thickness dependence . . . . . . . . . . . . . . . . . . . . . 93 4.4.3 Temperature dependence . . . . . . . . . . . . . . . . . . . . 95 4.5 Depletion zone variation . . . . . . . . . . . . . . . . . . . . . . . . 97 4.6 Molybdenum oxide as a case study . . . . . . . . . . . . . . . . . . 99 5 Charge-carrier transport and self-heating in OLED lighting . . . . . . . . . . . . . . . . .101 5.1 Joule self-heating in OLEDs . . . . . . . . . . . . . . . . . . . . . . 104 5.1.1 Electrothermal feedback . . . . . . . . . . . . . . . . . . . . 104 5.1.2 Thermistors . . . . . . . . . . . . . . . . . . . . . . . . . . . 105 5.1.3 Cooling strategies . . . . . . . . . . . . . . . . . . . . . . . . 106 5.2 Self-heating causes lateral luminance inhomogeneities in OLEDs . . 108 5.2.1 The influence of transparent electrodes . . . . . . . . . . . . 108 5.2.2 Luminance inhomogeneities in large OLED panels . . . . . . 110 5.3 Electrothermal OLED models . . . . . . . . . . . . . . . . . . . . . 112 5.3.1 Perceiving an OLED as thermistor array . . . . . . . . . . . 112 5.3.2 The OLED as a single three-layer thermistor . . . . . . . . . 114 5.3.3 A numerical 3D model of heat and current flow . . . . . . . 116 5.4 OLED stack and experimental conception . . . . . . . . . . . . . . 118 5.5 The Switch-back effect in planar light sources . . . . . . . . . . . . 120 5.5.1 Predictions from numerical 3D modeling . . . . . . . . . . . 121 5.5.2 Experimental proof . . . . . . . . . . . . . . . . . . . . . . . 124 5.5.3 Variation of vertical heat flux . . . . . . . . . . . . . . . . . 127 5.5.4 Variation of the OLED area . . . . . . . . . . . . . . . . . . 131 5.6 Electrothermal tristabilities in OLEDs . . . . . . . . . . . . . . . . 133 5.6.1 Observing different burn-in schematics . . . . . . . . . . . . 133 5.6.2 Bistability and tristability in organic semiconductors . . . . 134 5.6.3 Experimental indications for attempted branch hopping . . . 138 5.6.4 Saving bright OLEDs from burning in . . . . . . . . . . . . 144 5.6.5 Taking another view onto the camera pictures . . . . . . . . 145 6 Charge-carrier recombination and exciton management . . . . . . . . . . . . . . . . .147 6.1 Optical down conversion . . . . . . . . . . . . . . . . . . . . . . . . 149 6.1.1 Spectral reshaping of visible OLEDs . . . . . . . . . . . . . 149 6.1.2 Infrared-emitting OLEDs . . . . . . . . . . . . . . . . . . . . 155 6.2 Dual-state Förster transfer . . . . . . . . . . . . . . . . . . . . . . . 158 6.2.1 Terminology . . . . . . . . . . . . . . . . . . . . . . . . . . . 158 6.2.2 Verification . . . . . . . . . . . . . . . . . . . . . . . . . . . 159 6.3 Singlet fission and triplet fusion in rubrene . . . . . . . . . . . . . . 161 6.3.1 Photoluminescence of pure and doped rubrene films . . . . . 163 6.3.2 Electroluminescence transients of rubrene OLEDs . . . . . . 172 6.4 Charge transfer-state tuning by electric fields . . . . . . . . . . . . . 177 6.4.1 CT-state tuning via doping variation . . . . . . . . . . . . . 177 6.4.2 CT-state tuning via voltage . . . . . . . . . . . . . . . . . . 180 6.5 Excursus: Exciton-spin mixing for wavelength identification . . . . 183 6.5.1 Characteristics of the active film . . . . . . . . . . . . . . . . 184 6.5.2 Conception . . . . . . . . . . . . . . . . . . . . . . . . . . . 186 6.5.3 Setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 187 6.5.4 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 188 6.5.5 Application demonstrations . . . . . . . . . . . . . . . . . . 192 6.5.6 All-organic device . . . . . . . . . . . . . . . . . . . . . . . . 195 6.5.7 Device limitations and prospects . . . . . . . . . . . . . . . . 198 7 Conclusion and outlook . . . . . . . . . . . . . . . . . 207 7.1 Charge-carrier injection into doped films . . . . . . . . . . . . . . . 207 7.2 Charge-carrier transport in hot OLEDs . . . . . . . . . . . . . . . . 208 7.2.1 Prospects for OLED lighting facing tristable behavior . . . . 209 7.2.2 Outlook: Accessing the hidden PDR 2 region . . . . . . . . . 210 7.3 Charge-carrier recombination and spin mixing . . . . . . . . . . . . 211 7.3.1 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . 211 7.3.2 Outlook . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 211 Bibliography. . . . . . . . . . . . . . . . . 215 Acknowledgements . . . . . . . . . . . . . . . . . 249Wer sich heute für ein neues Mobiltelefon entscheidet, kauft damit wahrscheinlich einen Bildschirm aus organischen Leuchtdioden (OLEDs). Durch ihre brillanten Farben, die hohe erreichbare Auflösung und eine vergleichsweise einfache Prozessierung werden OLEDs als relativ neue Bildschirmtechnologie in den nächsten Jahren wohl den größten Marktanteil ausmachen. Da sie nicht auf der starren Kristallstruktur klassischer Halbleiter beruhen und als planare Dünnschichtmodule produziert werden können, ermöglichen sie außerdem die Fertigung großer Flächenstrahler auf flexiblen Substraten – ein sehr attraktives Szenario für zukünftige Beleuchtungssysteme. Trotz dieser vielversprechenden Eigenschaften steht der Durchbruch der OLED-Technologie als Leuchtmittel noch aus und erfordert weitere Forschung. Die Dynamik der Ladungsträger (Elektronen und Löcher) in einer OLED charakterisiert wichtige Teile der Bauteilfunktion und ermöglicht daher das Verständnis grundlegender physikalischer Konzepte und Phänomene. Diese Arbeit leitet anhand dieser Beschreibung experimentelle Methoden und Bauteilkonzepte ab, um die Effizienz und Stabilität von OLEDs zu optimieren. OLEDs zeichnen sich dadurch aus, dass ein elektrischer Strom aus Ladungsträgern (Elektronen und Löchern) möglichst effizient unter Aussendung von Licht rekombiniert. Diesem Prozess geht eine Ladungsträgerinjektion und deren Transport zur Emissionsschicht voraus. Diese drei Aspekte werden in dieser Arbeit zusammenhängend diskutiert. Als erstes wird eine Methode vorgestellt, die Injektionswiderstände anhand eines einfachen Experimentes quantifiziert. Sie bildet eine wertvolle Möglichkeit, Injektionsschichten besser zu verstehen und zu optimieren. Anschließend wird der Ladungsträgertransport bei hohen elektrischen Strömen untersucht, wie sie für OLEDs als helle Beleuchtungselemente nötig sind. Hier werden elektro-thermische Effekte vorgestellt, die physikalische Grenzen für das Design und die Funktion von OLED Modulen bilden und deren plötzliches Versagen erklären. Abschließend wird die Dynamik der stark elektrostatisch gebundenen Ladungsträgerpaare, sogenannter Exzitonen, kurz vor deren Rekombination untersucht. Es werden verschiedene Möglichkeiten vorgestellt sie so zu manipulieren, dass sich das Abstrahlverhalten der OLED anhand bestimmter Anforderungen einstellen lässt.:List of publications . . . . . . . . . . . . . . . . . v List of abbreviations . . . . . . . . . . . . . . . . . ix 1 Introduction . . . . . . . . . . . . . . . . . 1 2 Fundamentals . . . . . . . . . . . . . . . . . 5 2.1 Light sources and the human society . . . . . . . . . . . . . . . . . 5 2.1.1 Human light perception . . . . . . . . . . . . . . . . . . . . 8 2.1.2 Physical light quantification . . . . . . . . . . . . . . . . . . 10 2.1.3 Non-visual light impact . . . . . . . . . . . . . . . . . . . . . 13 2.1.4 Implications for modern light sources . . . . . . . . . . . . . 15 2.2 Organic semiconductors . . . . . . . . . . . . . . . . . . . . . . . . 17 2.2.1 Molecular energy states . . . . . . . . . . . . . . . . . . . . . 18 2.2.2 Intramolecular state transitions . . . . . . . . . . . . . . . . 24 2.2.3 Molecular films . . . . . . . . . . . . . . . . . . . . . . . . . 31 2.2.4 Electrical doping . . . . . . . . . . . . . . . . . . . . . . . . 34 2.2.5 Charge-carrier transport . . . . . . . . . . . . . . . . . . . . 36 2.2.6 Exciton formation and recombination . . . . . . . . . . . . . 38 2.2.7 Exciton transfer . . . . . . . . . . . . . . . . . . . . . . . . . 41 2.3 Organic light-emitting diodes . . . . . . . . . . . . . . . . . . . . . 44 2.3.1 Structure and operation principle . . . . . . . . . . . . . . . 44 2.3.2 Metal-semiconductor interfaces . . . . . . . . . . . . . . . . 47 2.3.3 Typical operation characteristics . . . . . . . . . . . . . . . . 49 2.4 Colloidal nanocrystal emitters . . . . . . . . . . . . . . . . . . . . . 52 2.4.1 Terminology: Nanocrystals and quantum dots . . . . . . . . 52 2.4.2 The particle-in-a-box model . . . . . . . . . . . . . . . . . . 54 2.4.3 Surface passivation . . . . . . . . . . . . . . . . . . . . . . . 55 3 Materials and methods . . . . . . . . . . . . . . . . . 57 3.1 Materials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 3.1.1 OLED materials . . . . . . . . . . . . . . . . . . . . . . . . . 57 3.1.2 Materials for photoluminescence . . . . . . . . . . . . . . . . 60 3.2 Sample preparation . . . . . . . . . . . . . . . . . . . . . . . . . . . 62 3.2.1 Thermal evaporation . . . . . . . . . . . . . . . . . . . . . . 62 3.2.2 Solution processing . . . . . . . . . . . . . . . . . . . . . . . 64 3.3 Spectroscopy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 3.3.1 Absorbance spectroscopy . . . . . . . . . . . . . . . . . . . . 66 3.3.2 Photoluminescence quantum yield . . . . . . . . . . . . . . . 66 3.3.3 Excitation sources . . . . . . . . . . . . . . . . . . . . . . . 67 3.3.4 Sensitive EQE for absorber materials . . . . . . . . . . . . . 68 3.4 Exciton-lifetime analysis . . . . . . . . . . . . . . . . . . . . . . . . 69 3.4.1 Triplet lifetime . . . . . . . . . . . . . . . . . . . . . . . . . 69 3.4.2 Singlet-state lifetime . . . . . . . . . . . . . . . . . . . . . . 70 3.4.3 Lifetime extraction . . . . . . . . . . . . . . . . . . . . . . . 70 3.5 OLED characterization . . . . . . . . . . . . . . . . . . . . . . . . . 73 3.5.1 Current-voltage-luminance and quantum efficiency . . . . . . 73 3.5.2 Temperature-controlled evaluation . . . . . . . . . . . . . . . 74 4 Charge-carrier injection into doped organic films . . . . . . . . . . . . . . . . . 77 4.1 Ohmic injection contacts . . . . . . . . . . . . . . . . . . . . . . . . 79 4.2 Device architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 4.2.1 Conception . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 4.2.2 Device symmetry . . . . . . . . . . . . . . . . . . . . . . . . 80 4.2.3 Device homogeneity . . . . . . . . . . . . . . . . . . . . . . . 83 4.3 Resistance characteristics . . . . . . . . . . . . . . . . . . . . . . . . 84 4.3.1 Experimental results . . . . . . . . . . . . . . . . . . . . . . 84 4.3.2 Equivalent-circuit development . . . . . . . . . . . . . . . . 85 4.4 Impedance spectroscopy . . . . . . . . . . . . . . . . . . . . . . . . 92 4.4.1 Measurement fundamentals . . . . . . . . . . . . . . . . . . 92 4.4.2 Thickness dependence . . . . . . . . . . . . . . . . . . . . . 93 4.4.3 Temperature dependence . . . . . . . . . . . . . . . . . . . . 95 4.5 Depletion zone variation . . . . . . . . . . . . . . . . . . . . . . . . 97 4.6 Molybdenum oxide as a case study . . . . . . . . . . . . . . . . . . 99 5 Charge-carrier transport and self-heating in OLED lighting . . . . . . . . . . . . . . . . .101 5.1 Joule self-heating in OLEDs . . . . . . . . . . . . . . . . . . . . . . 104 5.1.1 Electrothermal feedback . . . . . . . . . . . . . . . . . . . . 104 5.1.2 Thermistors . . . . . . . . . . . . . . . . . . . . . . . . . . . 105 5.1.3 Cooling strategies . . . . . . . . . . . . . . . . . . . . . . . . 106 5.2 Self-heating causes lateral luminance inhomogeneities in OLEDs . . 108 5.2.1 The influence of transparent electrodes . . . . . . . . . . . . 108 5.2.2 Luminance inhomogeneities in large OLED panels . . . . . . 110 5.3 Electrothermal OLED models . . . . . . . . . . . . . . . . . . . . . 112 5.3.1 Perceiving an OLED as thermistor array . . . . . . . . . . . 112 5.3.2 The OLED as a single three-layer thermistor . . . . . . . . . 114 5.3.3 A numerical 3D model of heat and current flow . . . . . . . 116 5.4 OLED stack and experimental conception . . . . . . . . . . . . . . 118 5.5 The Switch-back effect in planar light sources . . . . . . . . . . . . 120 5.5.1 Predictions from numerical 3D modeling . . . . . . . . . . . 121 5.5.2 Experimental proof . . . . . . . . . . . . . . . . . . . . . . . 124 5.5.3 Variation of vertical heat flux . . . . . . . . . . . . . . . . . 127 5.5.4 Variation of the OLED area . . . . . . . . . . . . . . . . . . 131 5.6 Electrothermal tristabilities in OLEDs . . . . . . . . . . . . . . . . 133 5.6.1 Observing different burn-in schematics . . . . . . . . . . . . 133 5.6.2 Bistability and tristability in organic semiconductors . . . . 134 5.6.3 Experimental indications for attempted branch hopping . . . 138 5.6.4 Saving bright OLEDs from burning in . . . . . . . . . . . . 144 5.6.5 Taking another view onto the camera pictures . . . . . . . . 145 6 Charge-carrier recombination and exciton management . . . . . . . . . . . . . . . . .147 6.1 Optical down conversion . . . . . . . . . . . . . . . . . . . . . . . . 149 6.1.1 Spectral reshaping of visible OLEDs . . . . . . . . . . . . . 149 6.1.2 Infrared-emitting OLEDs . . . . . . . . . . . . . . . . . . . . 155 6.2 Dual-state Förster transfer . . . . . . . . . . . . . . . . . . . . . . . 158 6.2.1 Terminology . . . . . . . . . . . . . . . . . . . . . . . . . . . 158 6.2.2 Verification . . . . . . . . . . . . . . . . . . . . . . . . . . . 159 6.3 Singlet fission and triplet fusion in rubrene . . . . . . . . . . . . . . 161 6.3.1 Photoluminescence of pure and doped rubrene films . . . . . 163 6.3.2 Electroluminescence transients of rubrene OLEDs . . . . . . 172 6.4 Charge transfer-state tuning by electric fields . . . . . . . . . . . . . 177 6.4.1 CT-state tuning via doping variation . . . . . . . . . . . . . 177 6.4.2 CT-state tuning via voltage . . . . . . . . . . . . . . . . . . 180 6.5 Excursus: Exciton-spin mixing for wavelength identification . . . . 183 6.5.1 Characteristics of the active film . . . . . . . . . . . . . . . . 184 6.5.2 Conception . . . . . . . . . . . . . . . . . . . . . . . . . . . 186 6.5.3 Setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 187 6.5.4 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 188 6.5.5 Application demonstrations . . . . . . . . . . . . . . . . . . 192 6.5.6 All-organic device . . . . . . . . . . . . . . . . . . . . . . . . 195 6.5.7 Device limitations and prospects . . . . . . . . . . . . . . . . 198 7 Conclusion and outlook . . . . . . . . . . . . . . . . . 207 7.1 Charge-carrier injection into doped films . . . . . . . . . . . . . . . 207 7.2 Charge-carrier transport in hot OLEDs . . . . . . . . . . . . . . . . 208 7.2.1 Prospects for OLED lighting facing tristable behavior . . . . 209 7.2.2 Outlook: Accessing the hidden PDR 2 region . . . . . . . . . 210 7.3 Charge-carrier recombination and spin mixing . . . . . . . . . . . . 211 7.3.1 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . 211 7.3.2 Outlook . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 211 Bibliography. . . . . . . . . . . . . . . . . 215 Acknowledgements . . . . . . . . . . . . . . . . . 24

Dynamic power management: from portable devices to high performance computing

Electronic applications are nowadays converging under the umbrella of the cloud computing vision. The future ecosystem of information and communication technology is going to integrate clouds of portable clients and embedded devices exchanging information, through the internet layer, with processing clusters of servers, data-centers and high performance computing systems. Even thus the whole society is waiting to embrace this revolution, there is a backside of the story. Portable devices require battery to work far from the power plugs and their storage capacity does not scale as the increasing power requirement does. At the other end processing clusters, such as data-centers and server farms, are build upon the integration of thousands multiprocessors. For each of them during the last decade the technology scaling has produced a dramatic increase in power density with significant spatial and temporal variability. This leads to power and temperature hot-spots, which may cause non-uniform ageing and accelerated chip failure. Nonetheless all the heat removed from the silicon translates in high cooling costs. Moreover trend in ICT carbon footprint shows that run-time power consumption of the all spectrum of devices accounts for a significant slice of entire world carbon emissions. This thesis work embrace the full ICT ecosystem and dynamic power consumption concerns by describing a set of new and promising system levels resource management techniques to reduce the power consumption and related issues for two corner cases: Mobile Devices and High Performance Computing

Emerging and Disruptive Next-Generation Technologies for POC: Sensors, Chemistry and Microfluidics for Diagnostics

Recently, the attention paid to self-care tests and the easy and large screening of a high number of people has dramatically increased. Indeed, easy and affordable tools for the safe management of biological fluids together with self-diagnosis have emerged as compulsory requirements in this time of the COVID-19 pandemic, to lighten the pressure on public healthcare institutions and thus limiting the diffusion of infections. Obviously, other kinds of pathologies (cancer or other degenerative diseases) also continue to require attention, with progressively earlier and more widespread diagnoses. The contribution to the development of this research field comes from the areas of innovative plastic and 3D microfluidics, smart chemistry and the integration of miniaturized sensors, going in the direction of improving the performances of in vitro diagnostic (IVD) devices. In our Special Issue, we include papers describing easy strategies to identify diseases at the point-of-care and near-the-bed levels, but also dealing with innovative biomarkers, sample treatments, and chemistry processes which, in perspective, represent promising tools to be applied in the field

Design Techniques for Energy-Quality Scalable Digital Systems

Energy efficiency is one of the key design goals in modern computing. Increasingly complex tasks are being executed in mobile devices and Internet of Things end-nodes, which are expected to operate for long time intervals, in the orders of months or years, with the limited energy budgets provided by small form-factor batteries. Fortunately, many of such tasks are error resilient, meaning that they can toler- ate some relaxation in the accuracy, precision or reliability of internal operations, without a significant impact on the overall output quality. The error resilience of an application may derive from a number of factors. The processing of analog sensor inputs measuring quantities from the physical world may not always require maximum precision, as the amount of information that can be extracted is limited by the presence of external noise. Outputs destined for human consumption may also contain small or occasional errors, thanks to the limited capabilities of our vision and hearing systems. Finally, some computational patterns commonly found in domains such as statistics, machine learning and operational research, naturally tend to reduce or eliminate errors. Energy-Quality (EQ) scalable digital systems systematically trade off the quality of computations with energy efficiency, by relaxing the precision, the accuracy, or the reliability of internal software and hardware components in exchange for energy reductions. This design paradigm is believed to offer one of the most promising solutions to the impelling need for low-energy computing. Despite these high expectations, the current state-of-the-art in EQ scalable design suffers from important shortcomings. First, the great majority of techniques proposed in literature focus only on processing hardware and software components. Nonetheless, for many real devices, processing contributes only to a small portion of the total energy consumption, which is dominated by other components (e.g. I/O, memory or data transfers). Second, in order to fulfill its promises and become diffused in commercial devices, EQ scalable design needs to achieve industrial level maturity. This involves moving from purely academic research based on high-level models and theoretical assumptions to engineered flows compatible with existing industry standards. Third, the time-varying nature of error tolerance, both among different applications and within a single task, should become more central in the proposed design methods. This involves designing “dynamic” systems in which the precision or reliability of operations (and consequently their energy consumption) can be dynamically tuned at runtime, rather than “static” solutions, in which the output quality is fixed at design-time. This thesis introduces several new EQ scalable design techniques for digital systems that take the previous observations into account. Besides processing, the proposed methods apply the principles of EQ scalable design also to interconnects and peripherals, which are often relevant contributors to the total energy in sensor nodes and mobile systems respectively. Regardless of the target component, the presented techniques pay special attention to the accurate evaluation of benefits and overheads deriving from EQ scalability, using industrial-level models, and on the integration with existing standard tools and protocols. Moreover, all the works presented in this thesis allow the dynamic reconfiguration of output quality and energy consumption. More specifically, the contribution of this thesis is divided in three parts. In a first body of work, the design of EQ scalable modules for processing hardware data paths is considered. Three design flows are presented, targeting different technologies and exploiting different ways to achieve EQ scalability, i.e. timing-induced errors and precision reduction. These works are inspired by previous approaches from the literature, namely Reduced-Precision Redundancy and Dynamic Accuracy Scaling, which are re-thought to make them compatible with standard Electronic Design Automation (EDA) tools and flows, providing solutions to overcome their main limitations. The second part of the thesis investigates the application of EQ scalable design to serial interconnects, which are the de facto standard for data exchanges between processing hardware and sensors. In this context, two novel bus encodings are proposed, called Approximate Differential Encoding and Serial-T0, that exploit the statistical characteristics of data produced by sensors to reduce the energy consumption on the bus at the cost of controlled data approximations. The two techniques achieve different results for data of different origins, but share the common features of allowing runtime reconfiguration of the allowed error and being compatible with standard serial bus protocols. Finally, the last part of the manuscript is devoted to the application of EQ scalable design principles to displays, which are often among the most energy- hungry components in mobile systems. The two proposals in this context leverage the emissive nature of Organic Light-Emitting Diode (OLED) displays to save energy by altering the displayed image, thus inducing an output quality reduction that depends on the amount of such alteration. The first technique implements an image-adaptive form of brightness scaling, whose outputs are optimized in terms of balance between power consumption and similarity with the input. The second approach achieves concurrent power reduction and image enhancement, by means of an adaptive polynomial transformation. Both solutions focus on minimizing the overheads associated with a real-time implementation of the transformations in software or hardware, so that these do not offset the savings in the display. For each of these three topics, results show that the aforementioned goal of building EQ scalable systems compatible with existing best practices and mature for being integrated in commercial devices can be effectively achieved. Moreover, they also show that very simple and similar principles can be applied to design EQ scalable versions of different system components (processing, peripherals and I/O), and to equip these components with knobs for the runtime reconfiguration of the energy versus quality tradeoff