Organic Photodiodes and Their Optoelectronic Applications

Recently, organic photodiodes (OPDs) have been acknowledged as a next-generation device for photovoltaic and image sensor applications due to their advantages of large area process, light weight, mechanical flexibility, and excellent photoresponse. This dissertation targets for the development and understanding of high performance organic photodiodes for their medical and industrial applications for the next-generation. As the first research focus, A dielectric / metal / dielectric (DMD) transparent electrode is proposed for the top-illumination OPDs. The fabricated DMD transparent electrode showed the maximum optical transmittance of 85.7 % with sheet resistance of 6.2 ohm/sq. In the second part of the thesis, a development of novel transfer process which enables the dark current suppression for the inverted OPD devices will be discussed. Through the effort, we demonstrated OPD with high D* of 4.82 x 10^12 Jones at reverse bias of 1.5 V with dark current density (Jdark) of 7.7 nA/cm2 and external quantum efficiency (EQE) of 60 %. Additionally in the third part, we investigate a high performance low-bandgap polymer OPD with broadband spectrum. By utilizing the novel transfer process to introduce charge blocking layers, significant suppression of the dark current is achieved while high EQE of the device is preserved. A low Jdark of 5 nA/cm2 at reverse bias of 0.5 V was achieved resulting in the highest D* of 1.5 x 10^13 Jones. To investigate the benefit for the various OPD applications, we developed a novel 3D printing technique to fabricate OPD on hemispherical concave substrate. The techniques allowed the direct patterning of the OPD devices on hemispherical substrates without excessive strain or deformation. Lastly, a simulation of the OPD stacked a-ITZO TFT active pixel sensor (APS) pixel with external transimpedance amplifier (TIA) readout circuit was performed.PHDElectrical & Computer Eng PhDUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/137168/1/hyunskim_1.pd

Bio-inspired Adaptable Facade Control Reflecting User\u27s Behavior

The purpose of this research is to develop the process of methodology in designing adaptable façade. This study focuses on the processes of façade operation control for each resident’s unit according to the user’s lifestyle. This study aims to develop the design methods that are applicable to the adaptable facade, which is inspired by the design inspiration of the biomimicry. The ideal façade to increase comfort in internal space is an adaptable façade that can constantly respond to changes in the environments. This chapter attempts in active adoption of adaptable facade that makes it possible to respond to changing requirements and environments, eventually enabling the creation of customized services for users. This chapter explores the processes of designing an adaptable façade controlled by three rules inspired by the behaviors of flocks of birds. This chapter shows how adopted bird intelligence can produce various façade controls. Also, this chapter demonstrates biomimetic façade control that has been implemented by behavior-based design. Through this demonstration, this chapter identifies the potentials of biomimetic design in facade using rules of bird flocking as source of design inspiration. This study concludes that a behavior-based approach provides flexibly responding façade to environments increasing users’ quality of life

Unraveling condition specific gene transcriptional regulatory networks in Saccharomyces cerevisiae

BACKGROUND: Gene expression and transcription factor (TF) binding data have been used to reveal gene transcriptional regulatory networks. Existing knowledge of gene regulation can be presented using gene connectivity networks. However, these composite connectivity networks do not specify the range of biological conditions of the activity of each link in the network. RESULTS: We present a novel method that utilizes the expression and binding patterns of the neighboring nodes of each link in existing experimentally-based, literature-derived gene transcriptional regulatory networks and extend them in silico using TF-gene binding motifs and a compendium of large expression data from Saccharomyces cerevisiae. Using this method, we predict several hundreds of new transcriptional regulatory TF-gene links, along with experimental conditions in which known and predicted links become active. This approach unravels new links in the yeast gene transcriptional regulatory network by utilizing the known transcriptional regulatory interactions, and is particularly useful for breaking down the composite transcriptional regulatory network to condition specific networks. CONCLUSION: Our methods can facilitate future binding experiments, as they can considerably help focus on the TFs that must be surveyed to understand gene regulation. (Supplemental material and the latest version of the MATLAB implementation of the United Signature Algorithm is available online at [1] or [see Additional files 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]

Accelerated Life Testing to Predict Service Life and Reliability for an Appliance Door Hinge

Appliance manufacturers have traditionally performed physical testing using prototypes to assess reliability and service integrity of new product designs. However, for white goods where service lives are measured in years or decades, the use of endurance testing to analyze long time reliability is uneconomical. As accelerated life testing (ALT) is more efficient and less costly than traditional reliability testing, the methodology is finding increased usage by appliance manufacturers. In the present study, a simulation-based ALT approach was used to predict the service life of a polyacetal hinge cam from a consumer refrigerator. A predictive life stress model based on cumulative surface wear under accelerated stress conditions was developed and used to predict time to failure under consumer use. Results show that the life stress model demonstrated good agreement with performance testing data and reasonably predicts hinge life

Optimal thermal storage operation strategies with heat pumps and solar collector

Energy consumption inside of building plays a key role occupying as 30-40% by the data of United Nations Statics Division (UNSD). Energy efficient building with light, medium and massive type discusses for designing the high efficient system component inside of building model. Control strategy between two tanks and solar collector completes the task by the Matlab codes and building simulation software. Result compares with the Pareto Efficiency curve for achieving the energy saving component and low cost operation. In this thesis, to achieve the goal of energy strategy and get the higher efficiencies of building energy, most common building type of single family house (light, medium and massive type) is suggested to renovate the energy system of the house. The domestic hot water consumption and space heating heat demand is the main target to satisfy the energy need in the house, two geothermal heat pumps and two thermal tanks with one solar collector studies for the respond of the energy requirement. Simulation software, IDA ICE (version 4.7.1) employs for the energy-utilized data set and Matlab studies for the control and the optimization result. IDA ICE can generate one tank model with one heat pump and solar collector, in the scope of the two tanks and two heat pumps model, one tank model is made separately only for the usage of domestic hot water consumption and the other is made only for the space heating. After producing two tanks model separately named as high temperature tank and low temperature tank, both combine with the Matlab software for the control strategy and optimization. To make the result after the control of the system components, energy balance equation and Artificial neural network (ANN) introduces. ANN is required for making the structure of the heat demand of solar collector and heat pump. Multi objective optimization presents and non-dominant sorting genetic algorithm (NSGA II) shows the Pareto Front of the result. Pareto Front is the optimal selection of the tank size and solar collector area by using the two different objective functions. One is annual heat pump energy usage and the other is operating cost of components considering Life Cycle Cost (LCC). Validation conducts with one tank model. One tank model in medium type of building is chosen for validation and comparing the result with the IDA and MOBO (Multi-Objective Building Performance Optimization) together. MOBO is optimization software possible to find suitable decision variables in the huge number of possible combinations, which let achieve defined conflicting objective functions and satisfy specified constraint functions. Validation turns out tank model with Matlab and ANN with NSGA II generates same pace of IDA ICE and MOBO combination later on