Solution-Processed Oxide and Sulfide Semiconductors for Thin-Film Electronics

Department of PhysicsSolution-processing of metal oxides and sulfides is considered as one of the promising electronics technologies due to its simple, cheap, and large-area processability. This thesis covers developing solution-processing techniques for metal oxides and sulfides, and their device applications. Firstly, newly developed sol-gel method for amorphous HfO2, ZrO2, and Ta2O5 is introduced. The processed oxides exhibited high visible transparency and dielectric constant (??), and excellent electrical insulation. Then, they were applied to thin film transistors (TFTs) as high-?? gate dielectrics. The incorporation of solution-processed metal oxides led to the devices exhibiting comparable field-effect mobility and significantly reduced operating voltage (~ 95% reduction) than the devices with a conventional SiO2 gate dielectric. Next chapter is devoted to the introduction of efficient and universal metal sulfide precursors. Simple mixing of alkanethiolates with metal acetates (or isopropoxides) allowed the formation of soluble metal thiolates, which are the resultant precursors for metal sulfides. Decomposition of metal thiolates occurred via SN1 reaction, giving carbon-free metal sulfide films with volatile dialkylsulfide byproducts. It is further found that mixing two (or three) precursors results in ternary (or quaternary) sulfide compounds. Based on this, CdS TFTs and CuInS2 thin film solar cells are fabricated and characterized. Following chapters deal with another solution-processing approach, synthesizing colloidal nanoparticles. To prepare efficient electron transporting layer for polymer solar cells, colloidal ZnO and TiO2 nanoparticles are prepared. By using the nanoparticle solutions, ZnO and TiO2 thin films were successfully deposited on ITO substrates without any possible damages to pre-coated Ag quantum dots on the substrates. It is observed that surface plasmon resonance peaks are strongly affected by the refractive index of surrounding oxide medium. Computer simulation further unveils detailed behavior of incident photons interacting with Ag quantum dots surrounded by solution-processed metal oxide media. Finally, simple and efficient strategy to boost colloidal stability of ZnO nanoparticles are discussed. The addition of a coordination complex, titanium diisopropoxide bis(acetylacetonate) significantly improved colloidal stability of ZnO nanoparticles in methanol, isopropanol, and chlorobenzene. Acetylacetonates on the surface of the nanoparticles effectively reduced the aggregation between the nanoparticles and the electron donation from Ti filled up deep level traps, which results in the reduced trap-assisted radiative recombination. In the device applications, it is confirmed that the colloidal stability of functionalized ZnO nanoparticles is prolonged at least 2 months. Not only comparable material properties of solution-processed oxide and sulfide thin films with those of the films prepared via conventional processing, but additional positive contributions to the device performance show their great potential for thin film electronics technology.clos

Two Methods for Spoofing-Aware Speaker Verification: Multi-Layer Perceptron Score Fusion Model and Integrated Embedding Projector

The use of deep neural networks (DNN) has dramatically elevated the performance of automatic speaker verification (ASV) over the last decade. However, ASV systems can be easily neutralized by spoofing attacks. Therefore, the Spoofing-Aware Speaker Verification (SASV) challenge is designed and held to promote development of systems that can perform ASV considering spoofing attacks by integrating ASV and spoofing countermeasure (CM) systems. In this paper, we propose two back-end systems: multi-layer perceptron score fusion model (MSFM) and integrated embedding projector (IEP). The MSFM, score fusion back-end system, derived SASV score utilizing ASV and CM scores and embeddings. On the other hand,IEP combines ASV and CM embeddings into SASV embedding and calculates final SASV score based on the cosine similarity. We effectively integrated ASV and CM systems through proposed MSFM and IEP and achieved the SASV equal error rates 0.56%, 1.32% on the official evaluation trials of the SASV 2022 challenge.Comment: 5 pages, 4 figures, 5 tables, accepted to 2022 Interspeech as a conference pape

One-Step Knowledge Distillation and Fine-Tuning in Using Large Pre-Trained Self-Supervised Learning Models for Speaker Verification

The application of speech self-supervised learning (SSL) models has achieved remarkable performance in speaker verification (SV). However, there is a computational cost hurdle in employing them, which makes development and deployment difficult. Several studies have simply compressed SSL models through knowledge distillation (KD) without considering the target task. Consequently, these methods could not extract SV-tailored features. This paper suggests One-Step Knowledge Distillation and Fine-Tuning (OS-KDFT), which incorporates KD and fine-tuning (FT). We optimize a student model for SV during KD training to avert the distillation of inappropriate information for the SV. OS-KDFT could downsize Wav2Vec 2.0 based ECAPA-TDNN size by approximately 76.2%, and reduce the SSL model's inference time by 79% while presenting an EER of 0.98%. The proposed OS-KDFT is validated across VoxCeleb1 and VoxCeleb2 datasets and W2V2 and HuBERT SSL models. Experiments are available on our GitHub

Convolution channel separation and frequency sub-bands aggregation for music genre classification

In music, short-term features such as pitch and tempo constitute long-term semantic features such as melody and narrative. A music genre classification (MGC) system should be able to analyze these features. In this research, we propose a novel framework that can extract and aggregate both short- and long-term features hierarchically. Our framework is based on ECAPA-TDNN, where all the layers that extract short-term features are affected by the layers that extract long-term features because of the back-propagation training. To prevent the distortion of short-term features, we devised the convolution channel separation technique that separates short-term features from long-term feature extraction paths. To extract more diverse features from our framework, we incorporated the frequency sub-bands aggregation method, which divides the input spectrogram along frequency bandwidths and processes each segment. We evaluated our framework using the Melon Playlist dataset which is a large-scale dataset containing 600 times more data than GTZAN which is a widely used dataset in MGC studies. As the result, our framework achieved 70.4% accuracy, which was improved by 16.9% compared to a conventional framework

High colloidal stability ZnO nanoparticles independent on solvent polarity and their application in polymer solar cells

Significant aggregation between ZnO nanoparticles (ZnO NPs) dispersed in polar and nonpolar solvents hinders the formation of high quality thin film for the device application and impedes their excellent electron transporting ability. Herein a bifunctional coordination complex, titanium diisopropoxide bis(acetylacetonate) (Ti(acac)2) is employed as efficient stabilizer to improve colloidal stability of ZnO NPs. Acetylacetonate functionalized ZnO exhibited long-term stability and maintained its superior optical and electrical properties for months aging under ambient atmospheric condition. The functionalized ZnO NPs were then incorporated into polymer solar cells with conventional structure as n-type buffer layer. The devices exhibited nearly identical power conversion efficiency regardless of the use of fresh and old (2 months aged) NPs. Our approach provides a simple and efficient route to boost colloidal stability of ZnO NPs in both polar and nonpolar solvents, which could enable structure-independent intense studies for efficient organic and hybrid optoelectronic devices

Geographical variations and influential factors in prevalence of cardiometabolic diseases in South Korea.

Geographical variations and influential factors of disease prevalence are crucial information enabling optimal allocation of limited medical resources and prioritization of appropriate treatments for each regional unit. The purpose of this study was to explore the geographical variations and influential factors of cardiometabolic disease prevalence with respect to 230 administrative districts in South Korea. Global Moran's I was calculated to determine whether the standardized prevalences of cardiometabolic diseases (hypertension, stroke, and diabetes mellitus) were spatially clustered. The CART algorithm was then applied to generate decision tree models that could extract the diseases' regional influential factors from among 101 demographic, economic, and public health data variables. Finally, the accuracies of the resulting model-hypertension (67.4%), stroke (62.2%), and diabetes mellitus (56.5%)-were assessed by ten-fold cross-validation. Marriage rate was the main determinant of geographic variation in hypertension and stroke prevalence, which has the possibility that married life could have positive effects in lowering disease risks. Additionally, stress-related variables were extracted as factors positively associated with hypertension and stroke. In the opposite way, the wealth status of a region was found to have an influence on the prevalences of stroke and diabetes mellitus. This study suggested a framework for provision of novel insights into the regional characteristics of diseases and the corresponding influential factors. The results of the study are anticipated to provide valuable information for public health practitioners' cost-effective disease management and to facilitate primary intervention and mitigation efforts in response to regional disease outbreaks

Optically Tunable Plasmonic Two-Dimensional Ag Quantum Dot Arrays for Optimal Light Absorption in Polymer Solar Cells

The application of localized surface plasmon resonance (LSPR) phenomena is an effective strategy to enhance the performance of polymer solar cells (PSCs) because of their ability to efficiently scatter light and dramatically increase light absorption in the active layer of PSCs. Unlike previous reports investigating LSPR materials in PSCs, we have.approached the LSPR phenomenon from a physical perspective by examining the influence of the surrounding environment LSPR properties. Uniformly ordered two-dimensional 10 nm Ag quantiun dot arrays (2D Ag-QAs) were prepared and utilized in PSCs. The 2D Ag QAs were incoiliorated into-electron transport layers with different. efractive indices, which showed a significant liathochrornic shift as the, refractive index increased and excellent agreement with theoretical calculations taking intrinsic size effects, nonlocal response, and plasmon, coupling effects into account. When incorporated into PSCs, power conversion efficiencies of op to, 8.51% were realized a 12.5% enhancement compared to devices without Ag QAs