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An investigation of reach decisions during ongoing action controlMichalski, Julien 08 1900 (has links)
Les études neurophysiologiques de la prise de décision, traditionnellement ancrées dans des principes neuro-économiques, ont évoluées pour inclure une variété d’aires du cerveau. Partant d’abord du lobe frontal associé aux jugements de valeur, le champ s’est élargi pour inclure d’autres types de décisions incluant les décisions perceptuelles et les décisions incarnées qui impliquent notamment les aires sensorimotrices du cerveau. La théorie moderne de la prise de décision modèle l’activité neurale dans ces régions comme une compétition entre les différents stimuli et actions considérés par un individu. Cette compétition est résolue lorsque l’activité neurale associée à un stimulus ou une action choisie atteint un seuil critique. Toutefois, il reste à éclaircir comment ce modèle s’applique aux décisions effectuées alors que l’individu est déjà engagé dans une activité. Dans ce mémoire nous examinons ce type de décision chez des sujets humains dans une tâche de suivi continu. Des cibles « choix » apparaissaient sur un écran pendant que le sujet suivait de la main une cible qui se déplaçait doucement en continu. Le sujet pouvait ignorer ces cibles choix, ou abandonner la cible suivie pour toucher une cible choix, dans quel cas la cible sélectionnée devenait la nouvelle cible à suivre du doigt. Tel qu’attendu, nous avons observé que les sujets favorisaient les cibles plus proches, plus grandes, et les cibles alignées avec l’axe du mouvement. Toutefois nous avons été surpris de constater que les sujets ignoraient les coûts énergétiques du mouvement, tel que modélisés. Un biais pour minimiser les coûts du mouvement fut réintroduis lorsque la tâche fut divisée en séries de mouvements point-à-point, plutôt qu’un mouvement continu. Même si nous ne pouvons expliquer ce résultat surprenant, nous espérons qu’il inspire de futures études utilisant le paradigme expérimental de décision durant l’action. / Neurophysiological studies of decision-making have expanded over decades to involve many brain areas. The field broadened from neuroeconomics, mainly concerned with frontal regions, to perceptual or embodied decision-making involving several sensorimotor areas where neural activity is linked to the stimuli and actions necessary for the decision process. Current models of decision-making envision this neural activity as a competition between different actions that is resolved when enough activity favors one over the other. However, it is unclear how such models can explain decisions often present in natural behavior, where deliberation takes place while already engaged in an action. In this thesis, we examined the choices human subjects made as they were engaged in a continuous tracking task. While they were manually tracking a target on a flat screen, subjects were occasionally presented with a new target to which they could freely choose to switch, whereupon it became the new tracked target. As expected, we found that subjects were more likely to move to closer targets, bigger targets, or targets that were aligned to the direction of movement. However, we were surprised that subjects did not choose targets that minimized energetic cost, as calculated by a biomechanical model of the arm. A biomechanical bias was restored when the continuous movement was broken up into a series of point to point movements. While we cannot yet explain these findings with certainty, we hope they will inspire further studies using decide-while-acting paradigms.
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Stochastic Motion Stimuli Influence Perceptual Choices in Human ParticipantsFard, Pouyan R., Bitzer, Sebastian, Pannasch, Sebastian, Kiebel, Stefan J. 22 March 2024 (has links)
In the study of perceptual decision making, it has been widely assumed that random fluctuations of motion stimuli are irrelevant for a participant’s choice. Recently, evidence was presented that these random fluctuations have a measurable effect on the relationship between neuronal and behavioral variability, the so-called choice probability. Here, we test, in a behavioral experiment, whether stochastic motion stimuli influence the choices of human participants. Our results show that for specific stochastic motion stimuli, participants indeed make biased choices, where the bias is consistent over participants. Using a computational model, we show that this consistent choice bias is caused by subtle motion information contained in the motion noise. We discuss the implications of this finding for future studies of perceptual decision making. Specifically, we suggest that future experiments should be complemented with a stimulus-informed modeling approach to control for the effects of apparent decision evidence in random stimuli.
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A theoretical and experimental dissociation of two models of decision‐makingCarland, Matthew A. 08 1900 (has links)
La prise de décision est un processus computationnel fondamental dans de nombreux aspects du comportement animal. Le modèle le plus souvent rencontré dans les études portant sur la prise de décision est appelé modèle de diffusion. Depuis longtemps, il explique une grande variété de données comportementales et neurophysiologiques dans ce domaine. Cependant, un autre modèle, le modèle d’urgence, explique tout aussi bien ces mêmes données et ce de façon parcimonieuse et davantage encrée sur la théorie. Dans ce travail, nous aborderons tout d’abord les origines et le développement du modèle de diffusion et nous verrons comment il a été établi en tant que cadre de travail pour l’interprétation de la plupart des données expérimentales liées à la prise de décision. Ce faisant, nous relèveront ses points forts afin de le comparer ensuite de manière objective et rigoureuse à des modèles alternatifs. Nous réexaminerons un nombre d’assomptions implicites et explicites faites par ce modèle et nous mettrons alors l’accent sur certains de ses défauts. Cette analyse servira de cadre à notre introduction et notre discussion du modèle d’urgence. Enfin, nous présenterons une expérience dont la méthodologie permet de dissocier les deux modèles, et dont les résultats illustrent les limites empiriques et théoriques du modèle de diffusion et démontrent en revanche clairement la validité du modèle d'urgence. Nous terminerons en discutant l'apport potentiel du modèle d'urgence pour l'étude de certaines pathologies cérébrales, en mettant l'accent sur de nouvelles perspectives de recherche. / Decision‐making is a computational process of fundamental importance to many aspects of animal behavior. The prevailing model in the experimental study of decision‐making is the drift‐diffusion model, which has a long history and accounts for a broad range of behavioral and neurophysiological data. However, an alternative model – called the urgency‐gating model – has been offered which can account equally well for much of the same data in a more parsimonious and theoretically‐sound manner. In what follows, we will first trace the origins and development of the DDM, as well as give a brief overview of the manner in which it has supplied an explanatory framework for a large number of behavioral and physiological studies in the domain of decision‐making. In so doing, we will attempt to build a strong and clear case for its strengths so that it can be fairly and rigorously compared to potential alternative models. We will then re‐examine a number of the implicit and explicit theoretical assumptions made by the drift‐diffusion model, as well as highlight some of its empirical shortcomings. This analysis will serve as the contextual backdrop for our introduction and discussion of the urgency‐gating model. Finally, we present a novel experiment, the methodological design of which uniquely affords a decisive empirical dissociation of the models, the results of which illustrate the empirical and theoretical shortcomings of the drift‐diffusion model and instead offer clear support for the urgency‐gating model. We finish by discussing the potential for the urgency gating model to shed light on a number of clinical disorders, highlighting a number of future directions for research.
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The Organic Permeable Base Transistor:Kaschura, Felix 23 October 2017 (has links) (PDF)
Organic transistors are a core component for basically all relevant types of fully organic circuits and consumer electronics. The Organic Permeable Base Transistor (OPBT) is a transistor with a sandwich geometry like in Organic Light Emitting Diodes (OLEDs) and has a vertical current transport. Therefore, it combines simple fabrication with high performance due its short transit paths and has a fairly good chance of being used in new organic electronics applications that have to fall back to silicon transistors up to now. A detailed understanding of the operation mechanism that allows a targeted engineering without trial-and-error is required and there is a need for universal optimization techniques which require as little effort as possible. Several mechanisms that explain certain aspects of the operation are proposed in literature, but a comprehensive study that covers all transistor regimes in detail is not found. High performances have been reported for organic transistors which are, however, usually limited to certain materials. E. g., n-type C60 OPBTs are presented with excellent performance, but an adequate p-type OPBT is missing.
In this thesis, the OPBT is investigated under two aspects:
Firstly, drift-diffusion simulations of the OPBT are evaluated. By comparing the results from different geometry parameters, conclusions about the detailed operation mechanism can be drawn. It is discussed where charge carriers flow in the device and which parameters affect the performance. In particular, the charge carrier transmission through the permeable base layer relies on small openings. Contrary to an intuitive view, however, the size of these openings does not limit the device performance.
Secondly, p-type OPBTs using pentacene as the organic semiconductor are fabricated and characterized with the aim to catch up with the performance of the n-type OPBTs. It is shown how an additional seed-layer can improve the performance by changing the morphology, how leakage currents can be defeated, and how parameters like the layer thickness should be chosen. With the combination of all presented optimization strategies, pentacene OPBTs are built that show a current density above 1000 mA/cm^2 and a current gain of 100. This makes the OPBT useful for a variety of applications, and also complementary logic circuits are possible now. The discussed optimization strategies can be extended and used as a starting point for further enhancements. Together with the deep understanding obtained from the simulations, purposeful modifications can be studied that have a great potential. / Organische Transistoren stellen eine Kernkomponente für praktisch jede Art von organischen Schaltungen und Elektronikgeräten dar. Der “Organic Permeable Base Transistor” (OPBT, dt.: Organischer Transistor mit durchlässiger Basis) ist ein Transistor mit einem Schichtaufbau wie in organischen Leuchtdioden (OLEDs) und weist einen vertikalen Stromfluss auf. Somit wird eine einfache Herstellung mit gutem Verhalten und Leistungsfähigkeit kombiniert, welche aus den kurzen Weglängen der Ladungsträger resultiert. Damit ist der OPBT bestens für neuartige organische Elektronik geeignet, wofür andernfalls auf Siliziumtransistoren zurückgegriffen werden müsste. Notwendig sind ein tiefgehendes Verständnis der Funktionsweise, welches ein zielgerichtetes Entwickeln der Technologie ohne zahlreiche Fehlversuche ermöglicht, sowie universell einsetzbare und leicht anwendbare Optimierungsstrategien. In der Literatur werden einige Mechanismen vorgeschlagen, die Teile der Funktionsweise betrachten, aber eine umfassende Untersuchung, die alle Arbeitsbereiche des Transistors abdeckt, findet sich derzeit noch nicht. Ebenso gibt es einige Veröffentlichungen, die Transistoren mit hervorragender Leistungsfähigkeit zeigen, aber meist nur mit Materialien für einen Ladungsträgertyp erzielt werden. So gibt es z.B. n-typ OPBTs auf Basis von C60, für die bisher vergleichbare p-typ OPBTs fehlen.
In dieser Arbeit werden daher die folgenden beiden Aspekte des OPBT untersucht:
Einerseits werden Drift-Diffusions-Simulationen von OPBTs untersucht und ausgewertet. Kennlinien und Ergebnisse von Transistoren aus verschiedenen Parametervariationen können verglichen werden und erlauben damit Rückschlüsse auf verschiedenste Aspekte der Funktionsweise. Der Fluss der Ladungsträger sowie für die Leistungsfähigkeit wichtige Parameter werden besprochen. Insbesondere sind für die Transmission von Ladungsträgern durch die Basisschicht kleine Öffnungen in dieser nötig. Die Größe dieser Öffnungen stellt jedoch entgegen einer intuitiven Vorstellung keine Begrenzung für die erreichbaren Ströme dar.
Andererseits werden p-typ OPBTs auf Basis des organischen Halbleiters Pentacen hergestellt und charakterisiert. Das Ziel ist hierbei die Leistungsfähigkeit an die n-typ OPBTs anzugleichen. In dieser Arbeit wird gezeigt, wie durch eine zusätzliche Schicht die Morphologie und die Transmission verbessert werden kann, wie Leckströme reduziert werden können und welche Parameter bei der Optimierung besondere Beachtung finden sollten. Mit all den Optimierungen zusammen können Pentacen OPBTs hergestellt werden, die Stromdichten über 1000 mA/cm^2 und eine Stromverstärkung über 100 aufweisen. Damit kann der OPBT für eine Vielzahl von Anwendungen eingesetzt werden, unter anderem auch in Logik-Schaltungen zusammen mit n-typ OPBTs. Die besprochenen Optimierungen können weiterentwickelt werden und somit als Startpunkt für anschließende Verbesserungen dienen. In Verbindung mit erlangten Verständnis aus den Simulationsergebnissen können somit aussichtsreiche Veränderungen an der Struktur des OPBTs zielgerichtet eingeführt werden.
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A Bayesian Reformulation of the Extended Drift-Diffusion Model in Perceptual Decision MakingFard, Pouyan R., Park, Hame, Warkentin, Andrej, Kiebel, Stefan J., Bitzer, Sebastian 10 November 2017 (has links) (PDF)
Perceptual decision making can be described as a process of accumulating evidence to a bound which has been formalized within drift-diffusion models (DDMs). Recently, an equivalent Bayesian model has been proposed. In contrast to standard DDMs, this Bayesian model directly links information in the stimulus to the decision process. Here, we extend this Bayesian model further and allow inter-trial variability of two parameters following the extended version of the DDM. We derive parameter distributions for the Bayesian model and show that they lead to predictions that are qualitatively equivalent to those made by the extended drift-diffusion model (eDDM). Further, we demonstrate the usefulness of the extended Bayesian model (eBM) for the analysis of concrete behavioral data. Specifically, using Bayesian model selection, we find evidence that including additional inter-trial parameter variability provides for a better model, when the model is constrained by trial-wise stimulus features. This result is remarkable because it was derived using just 200 trials per condition, which is typically thought to be insufficient for identifying variability parameters in DDMs. In sum, we present a Bayesian analysis, which provides for a novel and promising analysis of perceptual decision making experiments.
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A Bayesian Reformulation of the Extended Drift-Diffusion Model in Perceptual Decision MakingFard, Pouyan R., Park, Hame, Warkentin, Andrej, Kiebel, Stefan J., Bitzer, Sebastian 10 November 2017 (has links)
Perceptual decision making can be described as a process of accumulating evidence to a bound which has been formalized within drift-diffusion models (DDMs). Recently, an equivalent Bayesian model has been proposed. In contrast to standard DDMs, this Bayesian model directly links information in the stimulus to the decision process. Here, we extend this Bayesian model further and allow inter-trial variability of two parameters following the extended version of the DDM. We derive parameter distributions for the Bayesian model and show that they lead to predictions that are qualitatively equivalent to those made by the extended drift-diffusion model (eDDM). Further, we demonstrate the usefulness of the extended Bayesian model (eBM) for the analysis of concrete behavioral data. Specifically, using Bayesian model selection, we find evidence that including additional inter-trial parameter variability provides for a better model, when the model is constrained by trial-wise stimulus features. This result is remarkable because it was derived using just 200 trials per condition, which is typically thought to be insufficient for identifying variability parameters in DDMs. In sum, we present a Bayesian analysis, which provides for a novel and promising analysis of perceptual decision making experiments.
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The Organic Permeable Base Transistor:: Operation Principle and OptimizationsKaschura, Felix 25 September 2017 (has links)
Organic transistors are a core component for basically all relevant types of fully organic circuits and consumer electronics. The Organic Permeable Base Transistor (OPBT) is a transistor with a sandwich geometry like in Organic Light Emitting Diodes (OLEDs) and has a vertical current transport. Therefore, it combines simple fabrication with high performance due its short transit paths and has a fairly good chance of being used in new organic electronics applications that have to fall back to silicon transistors up to now. A detailed understanding of the operation mechanism that allows a targeted engineering without trial-and-error is required and there is a need for universal optimization techniques which require as little effort as possible. Several mechanisms that explain certain aspects of the operation are proposed in literature, but a comprehensive study that covers all transistor regimes in detail is not found. High performances have been reported for organic transistors which are, however, usually limited to certain materials. E. g., n-type C60 OPBTs are presented with excellent performance, but an adequate p-type OPBT is missing.
In this thesis, the OPBT is investigated under two aspects:
Firstly, drift-diffusion simulations of the OPBT are evaluated. By comparing the results from different geometry parameters, conclusions about the detailed operation mechanism can be drawn. It is discussed where charge carriers flow in the device and which parameters affect the performance. In particular, the charge carrier transmission through the permeable base layer relies on small openings. Contrary to an intuitive view, however, the size of these openings does not limit the device performance.
Secondly, p-type OPBTs using pentacene as the organic semiconductor are fabricated and characterized with the aim to catch up with the performance of the n-type OPBTs. It is shown how an additional seed-layer can improve the performance by changing the morphology, how leakage currents can be defeated, and how parameters like the layer thickness should be chosen. With the combination of all presented optimization strategies, pentacene OPBTs are built that show a current density above 1000 mA/cm^2 and a current gain of 100. This makes the OPBT useful for a variety of applications, and also complementary logic circuits are possible now. The discussed optimization strategies can be extended and used as a starting point for further enhancements. Together with the deep understanding obtained from the simulations, purposeful modifications can be studied that have a great potential.:1 Introduction and Motivation
2 Theory
2.1 Organic Semiconductors
2.1.1 Organic Molecules and Solids
2.1.2 Charge Carrier Transport
2.1.3 Charge Carrier Injection
2.1.4 Doping
2.2 Organic Permeable Base Transistors
2.2.1 Structure
2.2.2 Basic Operation Principle
3 Overview of Different Transistor Architectures
3.1 Organic Field Effect Transistors
3.2 Organic Permeable Base Transistors
3.2.1 Development of the Permeable Base Transistor
3.2.2 Optimization Strategies
3.3 Comparison to Inorganic Transistors
3.4 Other Emerging Transistor Concepts
3.4.1 OSBT
3.4.2 Step-Edge OFET
3.4.3 VOFET
3.4.4 IGZO Devices
4 Experimental
4.1 Materials and their Properties
4.1.1 Pentacene
4.1.2 F6TCNNQ
4.1.3 Aluminum Oxide
4.2 Fabrication
4.2.1 Thermal Vapor Deposition
4.2.2 Chamber Details and Processing Procedure
4.2.3 Sample Structure
4.3 Characterization Methods and Tools
4.3.1 Electrical Characterization
4.3.2 Morphology
4.3.3 XPS
5 Simulations and Working Mechanism
5.1 Simulation Setup
5.1.1 Overview
5.1.2 OPBT Model
5.1.3 Drift-Diffusion Solver
5.1.4 Post-Processing of Simulation Data
5.2 Basic Concept
5.2.1 Base Sweep Regions
5.2.2 Correlation with charge carrier density and potential
5.3 Charge Carrier Accumulation
5.3.1 Accumulation at Emitter and Collector
5.3.2 Current Flow
5.3.3 Area contributing to the current flow
5.4 Current Limitation Mechanisms
5.4.1 Varying Size of the Opening
5.4.2 Channel Potential
5.4.3 Limitation of Base-Emitter Transport
5.4.4 Intrinsic Layer Variation
5.5 Opening Shapes
5.5.1 Cylindrical Opening and Symmetry
5.5.2 Truncated Cone Setup
5.6 Base Leakage Currents
5.6.1 Description of the Insulator
5.6.2 Top and Bottom Contribution
5.6.3 Validity of Calculation
5.7 Analytical Description of the OPBT base sweep
5.7.1 Description of operation regions
5.7.2 Transition Voltages and Full Characteristics
5.7.3 Comparison to Experiment
5.8 Output Characteristics
5.8.1 Saturation region
5.8.2 Linear region
5.8.3 Intrinsic Gain
5.9 Summary of Operation Mechanism
6 Nin-Devices and Structuring
6.1 Effect of Accumulation and Scalability
6.1.1 Active Area and Electrode Overlap
6.1.2 Indirect Structuring
8 Contents
6.1.3 Four-Wire Measurement
6.1.4 Pulsed Measurements
6.2 Mobility Measurement
6.2.1 Mobility Extraction from a Single IV Curve
6.2.2 Verification of the SCLC using Thickness Variations
6.3 Geometric Diode
7 Optimization of p-type Permeable Base Transistors
7.1 Introduction to p-type Devices
7.2 Characteristics of OPBTs
7.2.1 Diode characteristics
7.2.2 Base sweep
7.2.3 Output characteristics
7.3 Seed-Layer
7.3.1 Process of Opening Formation
7.3.2 Performance using different Seed-Layers
7.4 Built-in field
7.4.1 Effect on Performance
7.4.2 Explanation for the Transmission Improvement
7.5 Base Insulation
7.5.1 Importance of Base Insulation
7.5.2 Additional Insulating Layers and Positioning
7.5.3 Enhancement of Native Aluminum Oxide
7.6 Complete Optimization
7.6.1 Indirect Structuring in OPBTs
7.6.2 Combination of different Optimization Techniques
7.7 Potential of the Technology
7.7.1 Future Improvements
7.7.2 Achievable Performance
7.8 Demonstration of the Organic Permeable Base Transistor
7.8.1 Simple OLED driver
7.8.2 An Astable Oscillator using p-type OPBTs
7.8.3 An OLED Driver using n-type OPBTs controlled by Organic Solar Cells
8 Conclusion / Organische Transistoren stellen eine Kernkomponente für praktisch jede Art von organischen Schaltungen und Elektronikgeräten dar. Der “Organic Permeable Base Transistor” (OPBT, dt.: Organischer Transistor mit durchlässiger Basis) ist ein Transistor mit einem Schichtaufbau wie in organischen Leuchtdioden (OLEDs) und weist einen vertikalen Stromfluss auf. Somit wird eine einfache Herstellung mit gutem Verhalten und Leistungsfähigkeit kombiniert, welche aus den kurzen Weglängen der Ladungsträger resultiert. Damit ist der OPBT bestens für neuartige organische Elektronik geeignet, wofür andernfalls auf Siliziumtransistoren zurückgegriffen werden müsste. Notwendig sind ein tiefgehendes Verständnis der Funktionsweise, welches ein zielgerichtetes Entwickeln der Technologie ohne zahlreiche Fehlversuche ermöglicht, sowie universell einsetzbare und leicht anwendbare Optimierungsstrategien. In der Literatur werden einige Mechanismen vorgeschlagen, die Teile der Funktionsweise betrachten, aber eine umfassende Untersuchung, die alle Arbeitsbereiche des Transistors abdeckt, findet sich derzeit noch nicht. Ebenso gibt es einige Veröffentlichungen, die Transistoren mit hervorragender Leistungsfähigkeit zeigen, aber meist nur mit Materialien für einen Ladungsträgertyp erzielt werden. So gibt es z.B. n-typ OPBTs auf Basis von C60, für die bisher vergleichbare p-typ OPBTs fehlen.
In dieser Arbeit werden daher die folgenden beiden Aspekte des OPBT untersucht:
Einerseits werden Drift-Diffusions-Simulationen von OPBTs untersucht und ausgewertet. Kennlinien und Ergebnisse von Transistoren aus verschiedenen Parametervariationen können verglichen werden und erlauben damit Rückschlüsse auf verschiedenste Aspekte der Funktionsweise. Der Fluss der Ladungsträger sowie für die Leistungsfähigkeit wichtige Parameter werden besprochen. Insbesondere sind für die Transmission von Ladungsträgern durch die Basisschicht kleine Öffnungen in dieser nötig. Die Größe dieser Öffnungen stellt jedoch entgegen einer intuitiven Vorstellung keine Begrenzung für die erreichbaren Ströme dar.
Andererseits werden p-typ OPBTs auf Basis des organischen Halbleiters Pentacen hergestellt und charakterisiert. Das Ziel ist hierbei die Leistungsfähigkeit an die n-typ OPBTs anzugleichen. In dieser Arbeit wird gezeigt, wie durch eine zusätzliche Schicht die Morphologie und die Transmission verbessert werden kann, wie Leckströme reduziert werden können und welche Parameter bei der Optimierung besondere Beachtung finden sollten. Mit all den Optimierungen zusammen können Pentacen OPBTs hergestellt werden, die Stromdichten über 1000 mA/cm^2 und eine Stromverstärkung über 100 aufweisen. Damit kann der OPBT für eine Vielzahl von Anwendungen eingesetzt werden, unter anderem auch in Logik-Schaltungen zusammen mit n-typ OPBTs. Die besprochenen Optimierungen können weiterentwickelt werden und somit als Startpunkt für anschließende Verbesserungen dienen. In Verbindung mit erlangten Verständnis aus den Simulationsergebnissen können somit aussichtsreiche Veränderungen an der Struktur des OPBTs zielgerichtet eingeführt werden.:1 Introduction and Motivation
2 Theory
2.1 Organic Semiconductors
2.1.1 Organic Molecules and Solids
2.1.2 Charge Carrier Transport
2.1.3 Charge Carrier Injection
2.1.4 Doping
2.2 Organic Permeable Base Transistors
2.2.1 Structure
2.2.2 Basic Operation Principle
3 Overview of Different Transistor Architectures
3.1 Organic Field Effect Transistors
3.2 Organic Permeable Base Transistors
3.2.1 Development of the Permeable Base Transistor
3.2.2 Optimization Strategies
3.3 Comparison to Inorganic Transistors
3.4 Other Emerging Transistor Concepts
3.4.1 OSBT
3.4.2 Step-Edge OFET
3.4.3 VOFET
3.4.4 IGZO Devices
4 Experimental
4.1 Materials and their Properties
4.1.1 Pentacene
4.1.2 F6TCNNQ
4.1.3 Aluminum Oxide
4.2 Fabrication
4.2.1 Thermal Vapor Deposition
4.2.2 Chamber Details and Processing Procedure
4.2.3 Sample Structure
4.3 Characterization Methods and Tools
4.3.1 Electrical Characterization
4.3.2 Morphology
4.3.3 XPS
5 Simulations and Working Mechanism
5.1 Simulation Setup
5.1.1 Overview
5.1.2 OPBT Model
5.1.3 Drift-Diffusion Solver
5.1.4 Post-Processing of Simulation Data
5.2 Basic Concept
5.2.1 Base Sweep Regions
5.2.2 Correlation with charge carrier density and potential
5.3 Charge Carrier Accumulation
5.3.1 Accumulation at Emitter and Collector
5.3.2 Current Flow
5.3.3 Area contributing to the current flow
5.4 Current Limitation Mechanisms
5.4.1 Varying Size of the Opening
5.4.2 Channel Potential
5.4.3 Limitation of Base-Emitter Transport
5.4.4 Intrinsic Layer Variation
5.5 Opening Shapes
5.5.1 Cylindrical Opening and Symmetry
5.5.2 Truncated Cone Setup
5.6 Base Leakage Currents
5.6.1 Description of the Insulator
5.6.2 Top and Bottom Contribution
5.6.3 Validity of Calculation
5.7 Analytical Description of the OPBT base sweep
5.7.1 Description of operation regions
5.7.2 Transition Voltages and Full Characteristics
5.7.3 Comparison to Experiment
5.8 Output Characteristics
5.8.1 Saturation region
5.8.2 Linear region
5.8.3 Intrinsic Gain
5.9 Summary of Operation Mechanism
6 Nin-Devices and Structuring
6.1 Effect of Accumulation and Scalability
6.1.1 Active Area and Electrode Overlap
6.1.2 Indirect Structuring
8 Contents
6.1.3 Four-Wire Measurement
6.1.4 Pulsed Measurements
6.2 Mobility Measurement
6.2.1 Mobility Extraction from a Single IV Curve
6.2.2 Verification of the SCLC using Thickness Variations
6.3 Geometric Diode
7 Optimization of p-type Permeable Base Transistors
7.1 Introduction to p-type Devices
7.2 Characteristics of OPBTs
7.2.1 Diode characteristics
7.2.2 Base sweep
7.2.3 Output characteristics
7.3 Seed-Layer
7.3.1 Process of Opening Formation
7.3.2 Performance using different Seed-Layers
7.4 Built-in field
7.4.1 Effect on Performance
7.4.2 Explanation for the Transmission Improvement
7.5 Base Insulation
7.5.1 Importance of Base Insulation
7.5.2 Additional Insulating Layers and Positioning
7.5.3 Enhancement of Native Aluminum Oxide
7.6 Complete Optimization
7.6.1 Indirect Structuring in OPBTs
7.6.2 Combination of different Optimization Techniques
7.7 Potential of the Technology
7.7.1 Future Improvements
7.7.2 Achievable Performance
7.8 Demonstration of the Organic Permeable Base Transistor
7.8.1 Simple OLED driver
7.8.2 An Astable Oscillator using p-type OPBTs
7.8.3 An OLED Driver using n-type OPBTs controlled by Organic Solar Cells
8 Conclusion
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Device Physics of Organic Solar Cells: Drift-Diffusion Simulation in Comparison with Experimental Data of Solar Cells Based on Small MoleculesTress, Wolfgang 26 April 2012 (has links)
This thesis deals with the device physics of organic solar cells. Organic photovoltaics (OPV) is a field of applied research which has been growing rapidly in the last decade leading to a current record value of power-conversion efficiency of 10 percent. One major reason for this boom is a potentially low-cost production of solar modules on flexible (polymer) substrate. Furthermore, new application are expected by flexible or semitransparent organic solar cells. That is why several OPV startup companies were launched in the last decade.
Organic solar cells consist of hydrocarbon compounds, deposited as ultrathin layers (some tens of nm) on a substrate. Absorption of light leads to molecular excited states (excitons) which are strongly bound due to the weak interactions and low dielectric constant in a molecular solid. The excitons have to be split into positive and negative charges, which are subsequently collected at different electrodes. An effective dissociation of excitons is provided by a heterojunction of two molecules with different frontier orbital energies, such that the electron is transfered to the (electron) acceptor and the positive charge (hole) remains on the donor molecule. This junction can be realized by two distinct layers forming a planar heterojunction or by an intermixed film of donor and acceptor, resulting in a bulk heterojunction. Electrodes are attached to the absorber to collect the charges by providing an ohmic contact in the optimum case.
This work focuses on the electrical processes in organic solar cells developing and employing a one-dimensional drift-diffusion model. The electrical model developed here is combined with an optical model and covers the diffusion of excitons, their separation, and the subsequent transport of charges. In contrast to inorganics, charge-carrier mobilities are low in the investigated materials and charge transport is strongly affected by energy barriers at the electrodes.
The current-voltage characteristics (J-V curve) of a solar cell reflect the electrical processes in the device. Therefore, the J-V curve is selected as means of comparison between systematic series of simulation and experimental data. This mainly qualitative approach allows for an identification of dominating processes and provides microscopic explanations.
One crucial issue, as already mentioned, is the contact between absorber layer and electrode. Energy barriers lead to a reduction of the power-conversion efficiency due to a decrease in the open-circuit voltage or the fill factor by S-shaped J-V curve (S-kink), which are often observed for organic solar cells. It is shown by a systematic study that the introduction of deliberate barriers for charge-carrier extraction and injection can cause such S-kinks. It is explained by simulated electrical-field profiles why also injection barriers lead to a reduction of the probability for charge-carrier extraction. A pile-up of charge carriers at an extraction barrier is confirmed by measurements of transient photocurrents. In flat heterojunction solar cells an additional reason for S-kinks is found in an imbalance of electron and hole mobilities. Due to the variety of reasons for S-kinks, methods and criteria for a distinction are proposed. These include J-V measurements at different temperatures and of samples with varied layer thicknesses.
Most of the studies of this this work are based on experimental data of solar cells comprisiing the donor dye zinc phthalocyanine and the acceptor fullerene C60. It is observed that the open-circuit voltage of these devices depends on the mixing ratio of ZnPc:C60. A comparison of experimental and simulation data indicates that the reason is a changed donor-acceptor energy gap caused by a shift of the ionization potential of ZnPc. A spatial gradient in the mixing ratio of a bulk heterojunction is also investigated as a donor(acceptor)-rich mixture at the hole(electron)-collecting contact is supposed to assist charge extraction. This effect is not observed, but a reduction of charge-carrier losses at the “wrong” electrode which is seen at an increase in the open-circuit voltage.
The most important intrinsic loss mechanism of a solar cell is bulk recombination which is treated at the example of ZnPc:C60 devices in the last part of this work. An examination of the dependence of the open-circuit voltage on illumination intensity shows that the dominating recombination mechanism shifts from trap-assisted to direct recombination for higher intensities. A variation of the absorption profile within the blend layer shows that the probability of charge-carrier extraction depends on the locus of charge-carrier generation. This results in a fill factor dependent on the absorption profile. The reason is an imbalance in charge-carrier mobilities which can be influenced by the mixing ratio.
The work is completed by a simulation study of the influence of charge-carrier mobilities and different recombination processes on the J-V curve and an identification of a photoshunt dominating the experimental linear photocurrent-voltage characteristics in reverse bias.:Abstract - Kurzfassung . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . i
Publications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v
1 Introduction
1.1 Energy supply and climate change . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Development of (organic) photovoltaics . . . . . . . . . . . . . . . . . . 3
1.3 Structure and scope of this thesis . . . . . . . . . . . . . . . . . . . . . . 6
I Basics
2 Photovoltaic Energy Conversion
2.1 Fundamentals of solar thermal energy conversion . . . . . . . . . . .11
2.1.1 The solar spectrum . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
2.1.2 Black-body irradiation . . . . . . . . . . . . . . . . . . . . . . . . . . . . .14
2.1.3 Maximum power-conversion efficiency . . . . . . . . . . . . . . . . . 15
2.2 Basics of semiconductor physics . . . . . . . . . . . . . . . . . . . . . . 16
2.2.1 Band structure, electrons and holes . . . . . . . . . . . . . . . . . . 16
2.2.2 Quasi-Fermi levels and electrochemical potentials . . . . . . . . . .22
2.3 Transformation of thermal radiation into chemical energy . . . . . 28
2.4 From chemical energy to electrical energy . . . . . . . . . . . .. . . . . 29
2.5 Possible solar-cell realizations . . . . . . . . . . . . . . . . . . . . . . . . 33
2.5.1 The p-n junction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
2.5.2 Heterojunction and dye solar cells . . . . . . . . . . . . . . . . . . . . 36
2.5.3 The p-i-n concept with wide-gap transport layers . . . . . . . . . 37
2.6 Maximum efficiency – Shockley-Queisser limit . . . . . . . . . . . . . .38
2.7 Novel concepts and classification of solar cells . . . . . . . . . . . . . 41
3 Organic Solar Cells
3.1 Energetics of organic molecules . . . . . . . . . . . . . . . . . . . . . . . 43
3.1.1 From atoms to molecules . . . . . . . . . . . . . . . . . . . . . . . . . . 43
3.1.2 From single molecules to a molecular solid . . . . . . . . . . . . . . 50
3.2 Energy and charge transport in organic semiconductors . . . . . . 52
3.2.1 Exciton transport . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
3.2.2 Charge transport - Gaussian disorder model . . . . . . . . . . . . .53
3.3 Working principle of donor-acceptor heterojunction solar cells . .57
3.3.1 Particle losses, quantum efficiency, and photocurrent . . . . . . .57
3.3.2 Energy losses, potential energy, and photovoltage . . . . . . . . 62
3.3.3 Maximum power-conversion efficiency . . . . . . . . . . . . . . . . . 66
3.3.4 Understanding the J-V curve in the MIM picture . . . . . . . . . . .68
3.3.5 Introduction to analytical models describing the photocurrent 70
3.4 Metal-organic interfaces . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
3.4.1 Conventional metal-semiconductor interfaces: Barriers and Schottky
contacts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
3.4.2 Metal-organic interfaces: Disorder and ICT . . . . . . . . . . . . . . 79
3.5 Experimental realization of small-molecule solar cells . . . . . . . . 80
3.5.1 Stacks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81
3.5.2 Materials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .83
3.5.3 Fabrication details . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88
3.6 Basic characterization methods . . . . . . . . . . . . . . . . . . . . . . . 92
3.6.1 Current-voltage characteristics . . . . . . . . . . . . . . . . . . . . . . 92
3.6.2 Spectrally resolved measurements . . . . . . . . . . . . . . . . . . . 93
3.6.3 Transient measurements . . . . . . . . . . . . . . . . . . . . . . . . . . 95
4 Modeling
4.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97
4.2 The drift-diffusion model in general . . . . . . . . . . . . . . . . . . . . 99
4.2.1 Derivation and conditions . . . . . . . . . . . . . . . . . . . . . . . . . . 99
4.2.2 The Einstein Relation . . . . . . . . . . . . . . . . . . . . . . . . . . . . .103
4.2.3 Poisson’s equation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104
4.2.4 Differential equation system . . . . . . . . . . . . . . . . . . . . . . . .105
4.3 Implementation of the algorithm . . . . . . . . . . . . . . . . . . . . . . 106
4.3.1 Basics of the algorithm and discretization . . . . . . . . . . . . . . 107
4.3.2 Calculation of the electric field . . . . . . . . . . . . . . . . . . . . . . 108
4.3.3 Calculation of rates of change . . . . . . . . . . . . . . . . . . . . . . 109
4.3.4 Calculation of the time step . . . . . . . . . . . . . . . . . . . . . . . . 111
4.3.5 Detection of steady state and transient currents . . . . . . . . . 111
4.4 Implemented models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113
4.4.1 Charge carrier mobility . . . . . . . . . . . . . . . . . . . . . . . . . . . 114
4.4.2 Recombination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115
4.4.3 Traps . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119
4.4.4 Gaussian density of states . . . . . . . . . . . . . . . . . . . . . . . . 120
4.5 Contacts as boundary conditions . . . . . . . . . . . . . . . . . . . . . 121
4.6 Organic-organic interfaces . . . . . . . . . . . . . . . . . . . . . . . . . . 124
4.6.1 Charge transport . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124
4.6.2 Generation and recombination . . . . . . . . . . . . . . . . . . . . . . 127
4.7 The simulation tool . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129
4.8 Verification with analytical solutions . . . . . . . . . . . . . . . . . . . 129
4.8.1 Single-carrier devices . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130
4.8.2 The p-n junction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133
4.9 Experimental determination of material properties . . . . . . . . . 136
4.10 Summary and main input parameters . . . . . . . . . . . . . . . . . 140
II Results and Discussion
5 Simulation Study on Single-Layer Bulk-Heterojunction Solar Cells
5.1 Investigated device structure and definitions . . . . . . . . . . . . . 144
5.2 On the optimum mobility, contact properties, and the open-circuit
voltage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146
5.2.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .146
5.2.2 Investigated mobility and recombination models . . . . . . . . . .147
5.2.3 Recombination only in the BHJ (selective contacts) . . . . . . . . 149
5.2.4 Recombination (also) at electrodes (non-selective contacts) . .155
5.2.5 Injection barriers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .158
5.2.6 Effect of energy-level bending on the open-circuit voltage . . . 161
5.3 Photocurrent and characteristic points in simulated J-V curves . .163
5.3.1 Negligible bulk recombination . . . . . . . . . . . . . . . . . . . . . . . .164
5.3.2 Bulk-recombination-limited photocurrent . . . . . . . . . . . . . . . 167
5.4 The effect of disorder on the open-circuit voltage . . . . . . . . . . .169
5.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .172
6 Influence of Injection and Extraction Barriers on Open-Circuit Voltage and
J-V Curve Shape studied at a Variation of Hole Transport Layer and Donor
Materials
6.1 Methodological approach . . . . . . . . . . . . . . . . . . . . . . . . . . . .174
6.2 Current-voltage data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177
6.2.1 Fingerprints . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177
6.2.2 Current-voltage characteristics under illumination . . . . . . . . . 181
6.3 Detailed microscopic explanations . . . . . . . . . . . . . . . . . . . . . .181
6.3.1 Injection barriers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .184
6.3.2 Extraction barriers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .187
6.3.3 Comparison between flat and bulk heterojunction . . . . . . . . . 188
6.4 Current-voltage curves in a logarithmic plot . . . . . . . . . . . . . . .188
6.5 Detailed analysis of the material combination MeO-TPD and BPAPF as
donor and hole transport layer . . . . . . . . . . . . . . . . . . . . . . . . . . 190
6.5.1 The interfaces BPAPF/MeO-TPD and MeO-TPD/BPAPF measured
by photoelectron spectroscopy . . . . . . . . . . . . . . . . . . . . . . . . . . 190
6.5.2 Dependence of the J-V curve shape on layer thicknesses . . . . 195
6.5.3 Dependence of the S-kink on temperature . . . . . . . . . . . . . . 198
6.5.4 Transient measurements . . . . . . . . . . . . . . . . . . . . . . . . . . 200
6.6 Summary and final remarks . . . . . . . . . . . . . . . . . . . . . . . . . . 207
7 Imbalanced Mobilities causing S-shaped J-V Curves in Planar Heterojunction
Solar Cells
7.1 Imbalanced mobilities in simulation . . . . . . . . . . . . . . . . . . . . . 209
7.2 Experimental verification . . . . . . . . . . . . . . . . . . . . . . . . . . . . 214
7.2.1 Current-voltage characteristics . . . . . . . . . . . . . . . . . . . . . . 216
7.2.2 Transient photocurrents . . . . . . . . . . . . . . . . . . . . . . . . . . 219
7.3 Field-dependent exciton dissociation as an additional source of
S-kinks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .221
7.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 222
8 Open-Circuit Voltage and J-V Curve Shape of ZnPc:C60 Solar Cells with Varied
Mixing Ratio and Hole Transport Layer
8.1 Experimental approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . .223
8.2 The open-circuit voltage . . . . . . . . . . . . . . . . . . . . . . . . . . . .225
8.3 The role of the hole transport layer and of doping . . . . . . . . . .228
8.4 Explaining the open-circuit voltage as a function of mixing ratio 230
8.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 236
9 Effect of Concentration Gradients in ZnPc:C60 Bulk Heterojunction Solar Cells
9.1 Investigated devices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 237
9.2 Current-voltage results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 238
9.2.1 Fill factor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 241
9.2.2 Short-circuit current . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 242
9.2.3 Open-circuit voltage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 242
9.3 Voltage dependent external quantum efficiency data . . . . . . . . 245
9.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .247
10 Role of the Generation Profile and Recombination in ZnPc:C60 Solar Cells
10.1 Idea and solar-cell design . . . . . . . . . . . . . . . . . . . . . . . . . . 249
10.1.1 Absorption data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 251
10.1.2 Simulated generation profiles . . . . . . . . . . . . . . . . . . . . . . 253
10.2 Correlation of fill factor with generation profile and imbalance in
mobilities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 255
10.2.1 Current-voltage data . . . . . . . . . . . . . . . . . . . . . . . . . . . 255
10.2.2 Monochromatic J-V curves . . . . . . . . . . . . . . . . . . . . . . . . 258
10.2.3 Voltage dependent external quantum efficiency . . . . . . . . . 259
10.3 Recombination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 261
10.3.1 Exponential region of dark J-V curves . . . . . . . . . . . . . . . . 261
10.3.2 J-V data dependent on illumination intensity . . . . . . . . . . . 265
10.3.3 Lifetime of charge carriers . . . . . . . . . . . . . . . . . . . . . . . . 271
10.4 Comparison with simulations . . . . . . . . . . . . . . . . . . . . . . . . 273
10.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 278
11 Linear Saturation Behavior
11.1 Definition of the photoshunt . . . . . . . . . . . . . . . . . . . . . . . . 279
11.2 Quasi-linear photocurrent in simulation . . . . . . . . . . . . . . . . 280
11.3 Experimental approach and results . . . . . . . . . . . . . . . . . . . 281
11.3.1 Identification of the main source of the photoshunt . . . . . . 283
11.3.2 Investigation of the thickness dependence of the saturation 285
11.3.3 Photoshunt in flat heterojunction ZnPc/C60 solar cells . . . . 289
11.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 292
III Summary and Outlook
12 Main Results
12.1 Interpretation of current-voltage curves . . . . . . . . . . . . . . . . 295
12.2 Stack design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 300
12.3 Main conclusions on the applicability of the developed drift-diffusion
simulation to organic solar cells . . . . . . . . . . . . . . . . . . . . . . . . . . 302
13 Further Analyses and Possible Extensions of the Simulation
13.1 Frequency response . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 305
13.2 Reverse tunneling currents and tandem cells . . . . . . . . . . . . . 307
13.2.1 Reverse current . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 308
13.2.2 J-V curves of tandem cells . . . . . . . . . . . . . . . . . . . . . . . . 309
13.3 Further points to examine . . . . . . . . . . . . . . . . . . . . . . . . . . 311
Appendix
A Lists
A.1 List of symbols . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 315
A.2 List of abbreviations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 318
A.3 List of constants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 319
B Simulation data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 321
C Experimental data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 333
Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 335
Acknowledgments - Danksagung 361 / Diese Dissertation beschäftigt sich mit der Physik organischer Solarzellen. Die organische Photovoltaik ist ein Forschungsgebiet, dem in den letzten zehn Jahren enorme Aufmerksamkeit zu Teil wurde. Der Grund liegt darin, dass diese neuartigen Solarzellen, deren aktueller Rekordwirkungsgrad bei 10 Prozent liegt, ein Potential für eine kostengünstige Produktion auf flexiblem (Polymer)substrat aufweisen und aufgrund ihrer Vielfältigkeit neue Anwendungsbereiche für die Photovoltaik erschließen.
Organische Solarzellen bestehen aus ultradünnen (einige 10 nm) Schichten aus Kohlenwasserstoffverbindungen. Damit der photovoltaische Effekt genutzt werden kann, müssen die durch Licht angeregten Molekülzustände zu freien Ladungsträgern führen, wobei positive und negative Ladung an unterschiedlichen Kontakten extrahiert werden. Für eine effektive Trennung dieser stark gebundenden lokalisierten angeregten Zustände (Exzitonen) ist eine Grenzfläche zwischen Molekülen mit unterschiedlichen Energieniveaus der Grenzorbitale erforderlich, sodass ein Elektron auf einem Akzeptor- und eine positive Ladung auf einem Donatormolekül entstehen. Diese Grenzschicht kann als planarer Heteroübergang durch zwei getrennte Schichten oder als Volumen-Heteroübergang in einer Mischschicht realisiert werden. Die Absorberschichten werden durch Elektroden kontaktiert, wobei es für effiziente Solarzellen erforderlich ist, dass diese einen ohmschen Kontakt ausbilden, da ansonsten Verluste zu erwarten sind.
Diese Arbeit behandelt im Besonderen die elektrischen Prozesse einer organischen Solarzelle. Dafür wird ein eindimensionales Drift-Diffusionsmodell entwickelt, das den Transport von Exzitonen, deren Trennung an einer Grenzfläche und die Ladungsträgerdynamik beschreibt. Abgesehen von den Exzitonen gilt als weitere Besonderheit einer organischen Solarzelle, dass sie aus amorphen, intrinsischen und sehr schlecht leitfähigen Absorberschichten besteht.
Elektrische Effekte sind an der Strom-Spannungskennlinie (I-U ) sichtbar, die in dieser Arbeit als Hauptvergleichspunkt zwischen experimentellen Solarzellendaten und den Simulationsergebnissen dient. Durch einen weitgehend qualitativen Vergleich können dominierende Prozesse bestimmt und mikroskopische Erklärungen gefunden werden.
Ein wichtiger Punkt ist der schon erwähnte Kontakt zwischen Absorberschicht und Elektrode. Dort auftretende Energiebarrieren führen zu einem Einbruch im Solarzellenwirkungsgrad, der sich durch eine Verringerung der Leerlaufspanung und/oder S-förmigen Kennlinien (S-Knick) bemerkbar macht. Anhand einer systematischen Studie der Grenzfläche Lochleiter/Donator wird gezeigt, dass Energiebarrieren sowohl für die Ladungsträgerextraktion als auch für die -injektion zu S-Knicken führen können. Insbesondere die Tatsache, dass Injektionsbarrieren sich auch negativ auf den Photostrom auswirken, wird anhand von simulierten Ladungsträger- und elektrischen Feldprofilen erklärt. Das Aufstauen von Ladungsträgern an Extraktionsbarrieren wird durch Messungen transienter Photoströme bestätigt. Da S-Knicke in organischen Solarzellen im Allgemeinen häufig beobachtet werden, werden weitere Methoden vorgeschlagen, die die Identifikation der Ursachen ermöglichen. Dazu zählen I-U Messungen in Abhängigkeit von Temperatur und Schichtdicken. Als eine weitere Ursache von S-Knicken werden unausgeglichene Ladungsträgerbeweglichkeiten in einer Solarzelle mit flachem Übergang identifiziert und von den Barrierefällen unterschieden.
Weiterer Forschungsgegenstand dieser Arbeit sind Mischschichtsolarzellen aus dem Donator-Farbstoff Zink-Phthalozyanin ZnPc und dem Akzeptor Fulleren C60. Dort wird beobachtet, dass die Leerlaufspannung vom Mischverhältnis abhängt. Ein Vergleich von Experiment und Simulation zeigt, dass sich das Ionisationspotenzial von ZnPc und dadurch die effektive Energielücke des Mischsystems ändern. Zusätzlich zu homogenen Mischschichten werden Solarzellen untersucht, die einen Gradienten im Mischungsverhältnis aufweisen. Die Vermutung liegt nahe, dass ein hoher Donatorgehalt am Löcherkontakt und ein hoher Akzeptorgehalt nahe des Elektronenkontakts die Ladungsträgerextraktion begünstigen.
Dieser Effekt ist in dem hier untersuchten System allerdings vergleichsweise irrelevant gegenüber der Tatsache, dass der Gradient das Abfließen bzw. die Rekombination von Ladungsträgern am “falschen” Kontakt reduziert und somit die Leerlaufspannung erhöht.
Der wichtigste intrinsische Verlustmechanismus einer Solarzelle ist die Rekombination von Ladungsträgern. Diese wird im letzten Teil der Arbeit anhand der ZnPc:C60 Solarzelle behandelt. Messungen der Leerlaufspannung in Abhängigkeit von der Beleuchtungsintensität zeigen, dass sich der dominierende Rekombinationsprozess mit zunehmender Intensität von Störstellenrekombination zu direkter Rekombination von freien Ladungsträgern verschiebt. Eine gezielte Variation des Absorptionsprofils in der Absorberschicht zeigt, dass die Ladungsträgerextraktionswahrscheinlickeit vom Ort der Ladungsträgergeneration abhängt. Dieser Effekt wird hervorgerufen durch unausgeglichene Elektronen- und Löcherbeweglichkeiten und äußert sich im Füllfaktor.
Weitere Simulationsergebnisse bezüglich des Einflusses von Ladungsträgerbeweglichkeiten und verschiedener Rekombinationsmechanismen auf die I-U Kennlinie und die experimentelle Identifikation eines Photoshunts, der den Photostrom in Rückwärtsrichtung unter Beleuchtung dominiert, runden die Arbeit ab.:Abstract - Kurzfassung . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . i
Publications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v
1 Introduction
1.1 Energy supply and climate change . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Development of (organic) photovoltaics . . . . . . . . . . . . . . . . . . 3
1.3 Structure and scope of this thesis . . . . . . . . . . . . . . . . . . . . . . 6
I Basics
2 Photovoltaic Energy Conversion
2.1 Fundamentals of solar thermal energy conversion . . . . . . . . . . .11
2.1.1 The solar spectrum . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
2.1.2 Black-body irradiation . . . . . . . . . . . . . . . . . . . . . . . . . . . . .14
2.1.3 Maximum power-conversion efficiency . . . . . . . . . . . . . . . . . 15
2.2 Basics of semiconductor physics . . . . . . . . . . . . . . . . . . . . . . 16
2.2.1 Band structure, electrons and holes . . . . . . . . . . . . . . . . . . 16
2.2.2 Quasi-Fermi levels and electrochemical potentials . . . . . . . . . .22
2.3 Transformation of thermal radiation into chemical energy . . . . . 28
2.4 From chemical energy to electrical energy . . . . . . . . . . . .. . . . . 29
2.5 Possible solar-cell realizations . . . . . . . . . . . . . . . . . . . . . . . . 33
2.5.1 The p-n junction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
2.5.2 Heterojunction and dye solar cells . . . . . . . . . . . . . . . . . . . . 36
2.5.3 The p-i-n concept with wide-gap transport layers . . . . . . . . . 37
2.6 Maximum efficiency – Shockley-Queisser limit . . . . . . . . . . . . . .38
2.7 Novel concepts and classification of solar cells . . . . . . . . . . . . . 41
3 Organic Solar Cells
3.1 Energetics of organic molecules . . . . . . . . . . . . . . . . . . . . . . . 43
3.1.1 From atoms to molecules . . . . . . . . . . . . . . . . . . . . . . . . . . 43
3.1.2 From single molecules to a molecular solid . . . . . . . . . . . . . . 50
3.2 Energy and charge transport in organic semiconductors . . . . . . 52
3.2.1 Exciton transport . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
3.2.2 Charge transport - Gaussian disorder model . . . . . . . . . . . . .53
3.3 Working principle of donor-acceptor heterojunction solar cells . .57
3.3.1 Particle losses, quantum efficiency, and photocurrent . . . . . . .57
3.3.2 Energy losses, potential energy, and photovoltage . . . . . . . . 62
3.3.3 Maximum power-conversion efficiency . . . . . . . . . . . . . . . . . 66
3.3.4 Understanding the J-V curve in the MIM picture . . . . . . . . . . .68
3.3.5 Introduction to analytical models describing the photocurrent 70
3.4 Metal-organic interfaces . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
3.4.1 Conventional metal-semiconductor interfaces: Barriers and Schottky
contacts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
3.4.2 Metal-organic interfaces: Disorder and ICT . . . . . . . . . . . . . . 79
3.5 Experimental realization of small-molecule solar cells . . . . . . . . 80
3.5.1 Stacks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81
3.5.2 Materials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .83
3.5.3 Fabrication details . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88
3.6 Basic characterization methods . . . . . . . . . . . . . . . . . . . . . . . 92
3.6.1 Current-voltage characteristics . . . . . . . . . . . . . . . . . . . . . . 92
3.6.2 Spectrally resolved measurements . . . . . . . . . . . . . . . . . . . 93
3.6.3 Transient measurements . . . . . . . . . . . . . . . . . . . . . . . . . . 95
4 Modeling
4.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97
4.2 The drift-diffusion model in general . . . . . . . . . . . . . . . . . . . . 99
4.2.1 Derivation and conditions . . . . . . . . . . . . . . . . . . . . . . . . . . 99
4.2.2 The Einstein Relation . . . . . . . . . . . . . . . . . . . . . . . . . . . . .103
4.2.3 Poisson’s equation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104
4.2.4 Differential equation system . . . . . . . . . . . . . . . . . . . . . . . .105
4.3 Implementation of the algorithm . . . . . . . . . . . . . . . . . . . . . . 106
4.3.1 Basics of the algorithm and discretization . . . . . . . . . . . . . . 107
4.3.2 Calculation of the electric field . . . . . . . . . . . . . . . . . . . . . . 108
4.3.3 Calculation of rates of change . . . . . . . . . . . . . . . . . . . . . . 109
4.3.4 Calculation of the time step . . . . . . . . . . . . . . . . . . . . . . . . 111
4.3.5 Detection of steady state and transient currents . . . . . . . . . 111
4.4 Implemented models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113
4.4.1 Charge carrier mobility . . . . . . . . . . . . . . . . . . . . . . . . . . . 114
4.4.2 Recombination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115
4.4.3 Traps . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119
4.4.4 Gaussian density of states . . . . . . . . . . . . . . . . . . . . . . . . 120
4.5 Contacts as boundary conditions . . . . . . . . . . . . . . . . . . . . . 121
4.6 Organic-organic interfaces . . . . . . . . . . . . . . . . . . . . . . . . . . 124
4.6.1 Charge transport . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124
4.6.2 Generation and recombination . . . . . . . . . . . . . . . . . . . . . . 127
4.7 The simulation tool . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129
4.8 Verification with analytical solutions . . . . . . . . . . . . . . . . . . . 129
4.8.1 Single-carrier devices . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130
4.8.2 The p-n junction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133
4.9 Experimental determination of material properties . . . . . . . . . 136
4.10 Summary and main input parameters . . . . . . . . . . . . . . . . . 140
II Results and Discussion
5 Simulation Study on Single-Layer Bulk-Heterojunction Solar Cells
5.1 Investigated device structure and definitions . . . . . . . . . . . . . 144
5.2 On the optimum mobility, contact properties, and the open-circuit
voltage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146
5.2.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .146
5.2.2 Investigated mobility and recombination models . . . . . . . . . .147
5.2.3 Recombination only in the BHJ (selective contacts) . . . . . . . . 149
5.2.4 Recombination (also) at electrodes (non-selective contacts) . .155
5.2.5 Injection barriers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .158
5.2.6 Effect of energy-level bending on the open-circuit voltage . . . 161
5.3 Photocurrent and characteristic points in simulated J-V curves . .163
5.3.1 Negligible bulk recombination . . . . . . . . . . . . . . . . . . . . . . . .164
5.3.2 Bulk-recombination-limited photocurrent . . . . . . . . . . . . . . . 167
5.4 The effect of disorder on the open-circuit voltage . . . . . . . . . . .169
5.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .172
6 Influence of Injection and Extraction Barriers on Open-Circuit Voltage and
J-V Curve Shape studied at a Variation of Hole Transport Layer and Donor
Materials
6.1 Methodological approach . . . . . . . . . . . . . . . . . . . . . . . . . . . .174
6.2 Current-voltage data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177
6.2.1 Fingerprints . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177
6.2.2 Current-voltage characteristics under illumination . . . . . . . . . 181
6.3 Detailed microscopic explanations . . . . . . . . . . . . . . . . . . . . . .181
6.3.1 Injection barriers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .184
6.3.2 Extraction barriers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .187
6.3.3 Comparison between flat and bulk heterojunction . . . . . . . . . 188
6.4 Current-voltage curves in a logarithmic plot . . . . . . . . . . . . . . .188
6.5 Detailed analysis of the material combination MeO-TPD and BPAPF as
donor and hole transport layer . . . . . . . . . . . . . . . . . . . . . . . . . . 190
6.5.1 The interfaces BPAPF/MeO-TPD and MeO-TPD/BPAPF measured
by photoelectron spectroscopy . . . . . . . . . . . . . . . . . . . . . . . . . . 190
6.5.2 Dependence of the J-V curve shape on layer thicknesses . . . . 195
6.5.3 Dependence of the S-kink on temperature . . . . . . . . . . . . . . 198
6.5.4 Transient measurements . . . . . . . . . . . . . . . . . . . . . . . . . . 200
6.6 Summary and final remarks . . . . . . . . . . . . . . . . . . . . . . . . . . 207
7 Imbalanced Mobilities causing S-shaped J-V Curves in Planar Heterojunction
Solar Cells
7.1 Imbalanced mobilities in simulation . . . . . . . . . . . . . . . . . . . . . 209
7.2 Experimental verification . . . . . . . . . . . . . . . . . . . . . . . . . . . . 214
7.2.1 Current-voltage characteristics . . . . . . . . . . . . . . . . . . . . . . 216
7.2.2 Transient photocurrents . . . . . . . . . . . . . . . . . . . . . . . . . . 219
7.3 Field-dependent exciton dissociation as an additional source of
S-kinks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .221
7.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 222
8 Open-Circuit Voltage and J-V Curve Shape of ZnPc:C60 Solar Cells with Varied
Mixing Ratio and Hole Transport Layer
8.1 Experimental approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . .223
8.2 The open-circuit voltage . . . . . . . . . . . . . . . . . . . . . . . . . . . .225
8.3 The role of the hole transport layer and of doping . . . . . . . . . .228
8.4 Explaining the open-circuit voltage as a function of mixing ratio 230
8.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 236
9 Effect of Concentration Gradients in ZnPc:C60 Bulk Heterojunction Solar Cells
9.1 Investigated devices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 237
9.2 Current-voltage results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 238
9.2.1 Fill factor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 241
9.2.2 Short-circuit current . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 242
9.2.3 Open-circuit voltage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 242
9.3 Voltage dependent external quantum efficiency data . . . . . . . . 245
9.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .247
10 Role of the Generation Profile and Recombination in ZnPc:C60 Solar Cells
10.1 Idea and solar-cell design . . . . . . . . . . . . . . . . . . . . . . . . . . 249
10.1.1 Absorption data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 251
10.1.2 Simulated generation profiles . . . . . . . . . . . . . . . . . . . . . . 253
10.2 Correlation of fill factor with generation profile and imbalance in
mobilities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 255
10.2.1 Current-voltage data . . . . . . . . . . . . . . . . . . . . . . . . . . . 255
10.2.2 Monochromatic J-V curves . . . . . . . . . . . . . . . . . . . . . . . . 258
10.2.3 Voltage dependent external quantum efficiency . . . . . . . . . 259
10.3 Recombination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 261
10.3.1 Exponential region of dark J-V curves . . . . . . . . . . . . . . . . 261
10.3.2 J-V data dependent on illumination intensity . . . . . . . . . . . 265
10.3.3 Lifetime of charge carriers . . . . . . . . . . . . . . . . . . . . . . . . 271
10.4 Comparison with simulations . . . . . . . . . . . . . . . . . . . . . . . . 273
10.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 278
11 Linear Saturation Behavior
11.1 Definition of the photoshunt . . . . . . . . . . . . . . . . . . . . . . . . 279
11.2 Quasi-linear photocurrent in simulation . . . . . . . . . . . . . . . . 280
11.3 Experimental approach and results . . . . . . . . . . . . . . . . . . . 281
11.3.1 Identification of the main source of the photoshunt . . . . . . 283
11.3.2 Investigation of the thickness dependence of the saturation 285
11.3.3 Photoshunt in flat heterojunction ZnPc/C60 solar cells . . . . 289
11.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 292
III Summary and Outlook
12 Main Results
12.1 Interpretation of current-voltage curves . . . . . . . . . . . . . . . . 295
12.2 Stack design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 300
12.3 Main conclusions on the applicability of the developed drift-diffusion
simulation to organic solar cells . . . . . . . . . . . . . . . . . . . . . . . . . . 302
13 Further Analyses and Possible Extensions of the Simulation
13.1 Frequency response . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 305
13.2 Reverse tunneling currents and tandem cells . . . . . . . . . . . . . 307
13.2.1 Reverse current . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 308
13.2.2 J-V curves of tandem cells . . . . . . . . . . . . . . . . . . . . . . . . 309
13.3 Further points to examine . . . . . . . . . . . . . . . . . . . . . . . . . . 311
Appendix
A Lists
A.1 List of symbols . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 315
A.2 List of abbreviations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 318
A.3 List of constants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 319
B Simulation data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 321
C Experimental data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 333
Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 335
Acknowledgments - Danksagung 361
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Electromechanical Characterization of Organic Field-Effect Transistors with Generalized Solid-State and Fractional Drift-Diffusion ModelsYi Yang (10725198) 29 April 2021 (has links)
<p>The miniaturization and thinning of wearable, soft robotics and medical devices are soon to require higher performance modeling as the physical flexibility causes direct impacts on the electrical characteristics of the circuit – changing its behavior. As a representative flexible electronic component, the organic field effect transistor (OFET) has attracted much attention in its manufacturing as well as applications. However, as the strain and stress effects are integrated into multiphysics modelers with deeper interactions, the computational complexity and accuracy of OFET modeling is resurfacing as a limiting bottleneck.</p><p>The dissertation was organized into three interrelated studies. In the first study, the Mass-Spring-Damper (MSD) model for an inverted staggered thin film transistor (TFT) was proposed to investigate the TFT’s internal stress/strain fields, and the strain effects on the overall characteristics of the TFT. A comparison study with the finite element analysis (FEA) model shows that the MSD model can reduce memory usage and raises the computational convergence speed for rendering the same results as the FEA. The second study developed the generalized solid-state model by incorporating the density of trap states in the band structure of organic semiconductors (OSCs). The introduction of trap states allows the generalized solid-state model to describe the electrical characteristics of both inorganic TFTs and organic field-effect transistors (OFETs). It is revealed through experimental verification that the generalized solid-state model can accurately characterize the bending induced electrical properties of an OFET in the linear and saturation regimes. The third study aims to model the transient and steady-state dynamics of an arbitrary organic semiconductor device under mechanical strain. In this study, the fractional drift-diffusion (Fr-DD) model and its computational scheme with high accuracy and high convergence rate were proposed. Based on simulation and experimental validation, the transconductance and output characteristics of a bendable OFET were found to be well determined by the Fr-DD model not only in the linear and saturation regimes, but also in the subthreshold regime.</p>
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The Eyring-Kramers formula for Poincaré and logarithmic Sobolev inequalities / Die Eyring-Kramer-Formel für Poincaré- und logarithmische Sobolev-UngleichungenSchlichting, André 25 October 2012 (has links)
The topic of this thesis is a diffusion process on a potential landscape which is given by a smooth Hamiltonian function in the regime of small noise. The work provides a new proof of the Eyring-Kramers formula for the Poincaré inequality of the associated generator of the diffusion. The Poincaré inequality characterizes the spectral gap of the generator and establishes the exponential rate of convergence towards equilibrium in the L²-distance. This result was first obtained by Bovier et. al. in 2004 relying on potential theory.
The presented approach in the thesis generalizes to obtain also asymptotic sharp estimates of the constant in the logarithmic Sobolev inequality. The optimal constant in the logarithmic Sobolev inequality characterizes the convergence rate to equilibrium with respect to the relative entropy, which is a stronger distance as the L²-distance and slightly weaker than the L¹-distance. The optimal constant has here no direct spectral representation.
The proof makes use of the scale separation present in the dynamics. The Eyring-Kramers formula follows as a simple corollary from the two main results of the work: The first one shows that the associated Gibbs measure restricted to a basin of attraction has a good Poincaré and logarithmic Sobolev constants providing the fast convergence of the diffusion to metastable states. The second main ingredient is a mean-difference estimate. Here a weighted transportation distance is used. It contains the main contribution to the Poincaré and logarithmic Sobolev constant, resulting from exponential long waiting times of jumps between metastable states of the diffusion.
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