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

RELIABILITY TESTING & BAYESIAN MODELING OF HIGH POWER LEDS FOR USE IN A MEDICAL DIAGNOSTIC APPLICATION

While use of LEDs in fiber optics and lighting applications is common, their use in medical diagnostic applications is rare. Since the precise value of light intensity is used to interpret patient results, understanding failure modes is very important. The contributions of this thesis is that it represents the first measurements of reliability of AlGaInP LEDs for the medical environment of short pulse bursts and hence the uncovering of unique failure mechanisms. Through accelerated life tests (ALT), the reliability degradation model has been developed and other LED failure modes have been compared through a failure modes and effects criticality analysis (FMECA). Appropriate ALTs and accelerated degradation tests (ADT) were designed and carried out for commercially available AlGaInP LEDs. The bias conditions were current pulse magnitude and duration, current density and temperature. The data was fitted to both an Inverse Power Law model with current density J as the accelerating agent and also to an Arrhenius model with T as the accelerating agent. The optical degradation during ALT/ADT was found to be logarithmic with time at each test temperature. Further, the LED bandgap temporarily shifts towards the longer wavelength at high current and high junction temperature. Empirical coefficients for Varshini's equation were determined, and are now available for future reliability tests of LEDs for medical applications. In order to incorporate prior knowledge, the Bayesian analysis was carried out for LEDs. This consisted of identifying pertinent prior data and combining the experimental ALT results into a Weibull probability model for time to failure determination. The Weibull based Bayesian likelihood function was derived. For the 1st Bayesian updating, a uniform distribution function was used as the Prior for Weibull á-â parameters. Prior published data was used as evidence to get the 1st posterior joint á-â distribution. For the 2nd Bayesian updating, ALT data was used as evidence to obtain the 2nd posterior joint á-â distribution. The predictive posterior failure distribution was estimated by averaging over the range of á-â values. This research provides a unique contribution in reliability degradation model development based on physics of failure by modeling the LED output characterization (logarithmic degradation, TTF â<1), temperature dependence and a degree of Relevance parameter `R' in the Bayesian analysis

High throughput workflow for the computational design of new thermally activated delayed fluorescence emitters

This thesis explores the use of computational methods for discovering new TADF molecules, with a focus on developing a high-throughput virtual screening workflow that reduces costs and time associated with experimental screening. Using methods like STONED and SYBA, diverse molecule libraries were generated and evaluated to identify promising candidates for further investigation. The study also examines the challenges of using computational methods, such as discrepancies and limitations with computationally efficient methods. Modifications were made to parent molecules based on ΔSCF calculations and similarity map analysis. Overall, this study provides valuable insights into the use of computational methods for TADF molecule design and offers guidance for future research aimed at designing new TADF materials.Open Acces

A Nonlinear Random Coefficients Model for Degradation Testing

As an alternative to traditional life testing, degradation tests can be effective in assessing product reliability when measurements of degradation leading to failure can be observed. This article presents a degradation model for highly reliable light displays, such as plasma display panels and vacuum fluorescent displays (VFDs). Standard degradation models fail to capture the burn-in characteristics of VFDs, when emitted light actually increases up to a certain point in time before it decreases (or degrades) continuously. Random coefficients are used to model this phenomenon in a nonlinear way, which allows for a nonmonotonic degradation path. In many situations, the relative efficiency of the lifetime estimate is improved over the standard estimators based on transformed linear models

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

Computational fluid dynamics modeling and in situ physics-based monitoring of aerosol jet printing toward functional assurance of additively-manufactured, flexible and hybrid electronics

Aerosol jet printing (AJP)—a direct-write, additive manufacturing technique—has emerged as the process of choice particularly for the fabrication of flexible and hybrid electronics. AJP has paved the way for high-resolution device fabrication with high placement accuracy, edge definition, and adhesion. In addition, AJP accommodates a broad range of ink viscosity, and allows for printing on non-planer surfaces. Despite the unique advantages and host of strategic applications, AJP is a highly unstable and complex process, prone to gradual drifts in machine behavior and deposited material. Hence, real-time monitoring and control of AJP process is a burgeoning need. In pursuit of this goal, the objectives of the work are, as follows: (i) In situ image acquisition from the traces/lines of printed electronic devices right after deposition. To realize this objective, the AJP experimental setup was instrumented with a high-resolution charge-coupled device (CCD) camera, mounted on a variable-magnification lens (in addition to the standard imaging system, already installed on the AJ printer). (ii) In situ image processing and quantification of the trace morphology. In this regard, several customized image processing algorithms were devised to quantify/extract various aspects of the trace morphology from online images. In addition, based on the concept of shape-from-shading (SfS), several other algorithms were introduced, allowing for not only reconstruction of the 3D profile of the AJ-printed electronic traces, but also quantification of 3D morphology traits, such as thickness, cross-sectional area, and surface roughness, among others. (iii) Development of a supervised multiple-input, single-output (MISO) machine learning model—based on sparse representation for classification (SRC)—with the aim to estimate the device functional properties (e.g., resistance) in near real-time with an accuracy of ≥ 90%. (iv) Forwarding a computational fluid dynamics (CFD) model to explain the underlying aerodynamic phenomena behind aerosol transport and deposition in AJP process, observed experimentally. Overall, this doctoral dissertation paves the way for: (i) implementation of physics-based real-time monitoring and control of AJP process toward conformal material deposition and device fabrication; and (ii) optimal design of direct-write components, such as nozzles, deposition heads, virtual impactors, atomizers, etc

Air Force Institute of Technology Research Report 1997

This report summarizes the research activities of the Air Force Institute of Technology\u27s Graduate School of Engineering and the Graduate School of Logistics and Acquisition Management. It describes research interests and faculty expertise; list student theses/dissertations; identifies research sponsors and contributions; and outlines the procedure for contacting either school

A Physics of Failure Based Qualification Process for Flexible Display Interconnect Materials

The next paradigm shift in display technology involves making them flexible, bringing with it many challenges with respect to product reliability. To compound the problem, industry is continuously introducing novel materials and experimenting with device geometries to improve flexibility and optical performance. Hence, a method to rapidly qualify these new designs for high reliability applications is imperative. This dissertation involves the development of a qualification process for gate line interconnects used in flexible displays. The process starts with the observed failure mode of permanent horizontal lines in the displays, followed by the identification of the underlying failure mechanism. Finite element analyses are developed to determine the relationship between the physical flexing and the mechanical stress imposed on the traces. The design of an accelerated life test is performed based on the known agent of failure being cyclic bending that induces a tensile strain. A versatile dedicated test system is designed and integrated in order to rapidly capture changes in resistance of multiple traces during test. Dedicated test structures are also designed and fabricated to facilitate in-situ electrical measurements and direct observations. Since the test structures were consumed during the integration of the test system, random failure times are used in the process of determining a life-stress model. Different models are compared with respect to their applicability to the underlying failure mechanism as well as parameter estimation techniques. This methodology may be applied towards the rapid qualification of other novel materials, process conditions, and device geometries prior to their widespread use in future display systems