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Selectively Nitrogen Doped ALD-IGZO TFTs with Extremely High Mobility and Reliability
No full textAchieving high mobility and reliability in atomic layer deposition (ALD)-based IGZO thin-film transistors (TFTs) with an amorphous phase is vital for practical applications in relevant fields. Here, we suggest a method to effectively increase stability while maintaining high mobility by employing the selective application of nitrous oxide plasma reactant during plasma-enhanced ALD (PEALD) at 200 ??C process temperature. The nitrogen-doping mechanism is highly dependent on the intrinsic carbon impurities or nature of each cation, as demonstrated by a combination of theoretical and experimental research. The Ga2O3 subgap states are especially dependent on plasma reactants. Based on these insights, we can obtain high-performance indium-rich PEALD-IGZO TFTs (threshold voltage: ???0.47 V; field-effect mobility: 106.5 cm2/(V s); subthreshold swing: 113.5 mV/decade; hysteresis: 0.05 V). In addition, the device shows minimal threshold voltage shifts of +0.45 and ???0.10 V under harsh positive/negative bias temperature stress environments (field stress: ??2 MV/cm; temperature stress: 95 ??C) after 10000 s
Design of synthetic promoters for cyanobacteria with generative deep-learning model
No full textDeep generative models, which can approximate complex data distribution from large datasets, are widely used in biological dataset analysis. In particular, they can identify and unravel hidden traits encoded within a complicated nucleotide sequence, allowing us to design genetic parts with accuracy. Here, we provide a deep-learning based generic framework to design and evaluate synthetic promoters for cyanobacteria using generative models, which was in turn validated with cell-free transcription assay. We developed a deep generative model and a predictive model using a variational autoencoder and convolutional neural network, respectively. Using native promoter sequences of the model unicellular cyanobacterium Synechocystis sp. PCC 6803 as a training dataset, we generated 10 000 synthetic promoter sequences and predicted their strengths. By position weight matrix and k-mer analyses, we confirmed that our model captured a valid feature of cyanobacteria promoters from the dataset. Furthermore, critical subregion identification analysis consistently revealed the importance of the -10 box sequence motif in cyanobacteria promoters. Moreover, we validated that the generated promoter sequence can efficiently drive transcription via cell-free transcription assay. This approach, combining in silico and in vitro studies, will provide a foundation for the rapid design and validation of synthetic promoters, especially for non-model organisms
Organic Semiconductor-Based Photoelectrochemical Cells for Efficient Solar-to-Chemical Conversion
No full textOrganic semiconductor-based photoelectrodes are gaining significant attention in photoelectrochemical (PEC) value-added chemical production systems, which are promising architectures for solar energy harvesting. Organic semiconductors consisting of conjugated carbon-carbon bonds provide several advantages for PEC cells, including improved charge transfer, tunable band positions and band gaps, low cost, and facile fabrication using organic solvents. This review gives an overview of the recent advances in emerging single organic semiconductor-based photoelectrodes for PEC water splitting and the various strategies for enhancing their performance and stability. It highlights the importance of photoelectrodes based on donor-acceptor bulk heterojunction (BHJ) systems for fabricating efficient organic semiconductor-based solar energy-harvesting devices. Furthermore, it evaluates the recent progress in BHJ organic base photoelectrodes for producing highly efficient PEC value-added chemicals, such as hydrogen and hydrogen peroxide. Finally, this review highlights the potential of organic-based photoelectrodes for bias-free solar-to-chemical production, which is the ultimate goal of PEC systems and a step toward achieving reliable commercial technology
Water Skating Miniature Robot Propelled by Acoustic Bubbles
No full textThis paper presents a miniature robot designed for monitoring its surroundings and exploring small and complex environments by skating on the surface of water. The robot is mainly made of extruded polystyrene insulation (XPS) and Teflon tubes and is propelled by acoustic bubble-induced microstreaming flows generated by gaseous bubbles trapped in the Teflon tubes. The robot's linear motion, velocity, and rotational motion are tested and measured at different frequencies and voltages. The results show that the propulsion velocity is proportional to the applied voltage but highly depends on the applied frequency. The maximum velocity occurs between the resonant frequencies for two bubbles trapped in Teflon tubes of different lengths. The robot's maneuvering capability is demonstrated by selective bubble excitation based on the concept of different resonant frequencies for bubbles of different volumes. The proposed water skating robot can perform linear propulsion, rotation, and 2D navigation on the water surface, making it suitable for exploring small and complex water environments
POEM: Polarization of Embeddings for Domain-Invariant Representations
No full textHandling out-of-distribution samples is a long-lasting challenge for deep visual models. In particular, domain generalization (DG) is one of the most relevant tasks that aims to train a model with a generalization capability on novel domains. Most existing DG approaches share the same philosophy to minimize the discrepancy between domains by finding the domain-invariant representations. On the contrary, our proposed method called POEM acquires a strong DG capability by learning domain-invariant and domain-specific representations and polarizing them. Specifically, POEM co-trains category-classifying and domain-classifying embeddings while regularizing them to be orthogonal via minimizing the cosine-similarity between their features, i.e., the polarization of embeddings. The clear separation of embeddings suppresses domain-specific features in the domain-invariant embeddings. The concept of POEM shows a unique direction to enhance the domain robustness of representations that brings considerable and consistent performance gains when combined with existing DG methods. Extensive simulation results in popular DG benchmarks with the PACS, VLCS, OfficeHome, TerraInc, and DomainNet datasets show that POEM indeed facilitates the category-classifying embedding to be more domain-invariant
A Power/Hardware-Efficient SiPM Readout IC Embedded in a Boost Converter for Mobile Radiation Dosimeters
No full textA radiation detection system provides radiation intensity to protect human life from hazardous radiation. However, the prior portable radiation detection system (mobile radiation dosimeter) structures had a problem in that various subsystems had to be designed with complex circuits. First, since the radiation detector must be driven by a relatively high voltage, a high-efficient boost converter that can receive the battery voltage and generate a high bias voltage must be implemented. Second, sophisticated sensor interface circuits that can convert the analog signal generated by the radiation detector to digital value must also be implemented. To reduce the complexity of the mobile radiation dosimeters, a power and hardware-efficient radiation detection system IC is presented for mobile radiation dosimeters. The current value of a silicon photomultiplier (SiPM) used as a radiation detector is sensed from the control information of a boost converter in the process of regulating a voltage to bias the SiPM. Due to this embedded sensing function, no additional hardware and power consumption are required for implementing and operating separate sensor interface circuits while providing sufficient radiation sensing performance. The implemented radiation detection system IC achieves 0.217-mu A(rms) input referred noise performance over 1-kHz signal bandwidth and 10-mA maximum allowable linear input current range. In addition, the proposed dc-dc boost converter can generate a high enough voltage (similar to 27 V) to drive SiPM from a lithium-ion battery with an efficiency of 72%. The irradiation test with radiation check source (Cs-137) demonstrates that the bias voltage is well regulated in the presence of high-energy radiation particles
Power flow decoupling method of triple-active-bridge converter for islanding mode operation in DC microgrid systems
No full textA single multiwinding transformer-based triple-active-bridge (TAB) converter with high power density is a viable candidate for DC microgrid development. However, it comes with a power flow challenge where all the ports are coupled. A power flow decoupling method is proposed for applications of the TAB converter in this paper. The method uses a combination of Proportional Integral (PI) controllers and a lookup table (LUT) that stores decoupling matrices for dynamic decoupling. The proposed decoupling method considers port voltage variations and utilizes only two control variables for voltage regulation. It is designed for application in the islanding mode operation of DC microgrids for DC bus voltage regulation. The feasibility and effectiveness of the proposed power flow decoupling method are verified by simulations and experimental results using an implemented 2 kW TAB converter prototype. Finally, the proposed method shows a 98.95 and a 99.00% improvement in power decoupling according to load variations in the load port
Imaging through random media using coherent averaging
Get PDFA new phase retrieval method for imaging through random media is proposed and demonstrated. Although methods to recover the Fourier amplitude through random distortions are well established, recovery of the Fourier phase has been a more difficult problem and is still a very active and important research area. Here, it is shown that by simply ensemble averaging shift-corrected images, the Fourier phase of an object obscured by random distortions can be accurately retrieved up to the diffraction limit. The method is simple, fast, does not have any optimization parameters, and does not require prior knowledge or assumptions about the sample. The feasibility and robustness of the method are demonstrated by realizing all computational diffraction-limited imaging through atmospheric turbulence as well as imaging through multiple scattering media
Synchronization of Kuramoto oscillators with the distributed time-delays and inertia effect
No full textWe prove the complete and partial phase synchronization for the Kuramoto oscillators with distributed time-delays and inertia effect. Our results assert that the Kuramoto models incorporated with a small variation of distributed time-delays and inertia effect still exhibit synchronization. This shows the robustness of the synchronization phenomena of the original Kuramoto model in the perturbation of time-delay and inertia effects. We also present several numerical experiments supporting our main results and exhibiting interesting patterns
Benzotrithiophene-based Covalent Organic Framework Photocatalysts with Controlled Conjugation of Building Blocks for Charge Stabilization
No full textCovalent organic frameworks have recently shown high potential for photocatalytic hydrogen production. However, their structure-property-activity relationship has not been sufficiently explored to identify a research direction for structural design. Herein, we report the design and synthesis of four benzotrithiophene (BTT)based covalent organic frameworks (COFs) with different conjugations of building units, and their photocatalytic activity for hydrogen production. All four BTT-COFs had slipped parallel stacking patterns with high crystallinity and specific surface areas. The change in the degree of conjugation was found to rationally tune the rate of photocatalytic hydrogen evolution. Based on the experimental and calculation results, the tunable photocatalytic performance could be mainly attributed to the electron affinity and charge trapping of the electron accepting units. This study provides important insights for designing covalent organic frameworks for efficient photocatalysts