Daegu Gyeongbuk Institute of Science and Technology
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A review of biocompatible polymer-functionalized two-dimensional materials: Emerging contenders for biosensors and bioelectronics applications
Get PDFBioelectronics, a field pivotal in monitoring and stimulating biological processes, demands innovative nanomaterials as detection platforms. Two-dimensional (2D) materials, with their thin structures and exceptional physicochemical properties, have emerged as critical substances in this research. However, these materials face challenges in biomedical applications due to issues related to their biological compatibility, adaptability, functionality, and nano-bio surface characteristics. This review examines surface modifications using covalent and non-covalent-based polymer-functionalization strategies to overcome these limitations by enhancing the biological compatibility, adaptability, and functionality of 2D nanomaterials. These surface modifications aim to create stable and long-lasting therapeutic effects, significantly paving the way for the practical application of polymer-functionalized 2D materials in biosensors and bioelectronics. The review paper critically summarizes the surface functionalization of 2D nanomaterials with biocompatible polymers, including g-C3N4, graphene family, MXene, BP, MOF, and TMDCs, highlighting their current state, physicochemical structures, synthesis methods, material characteristics, and applications in biosensors and bioelectronics. The paper concludes with a discussion of prospects, challenges, and numerous opportunities in the evolving field of bioelectronics. © 2024TRUEsciescopu
Organic Photodetectors Operating under Strong Sunlight: Combining Machine-Learning and Time-Dependent Density Functional Theory for Molecular Design of Diarylethene-Type Photochromic n-Type Dopants Mixed with p-Type Organic Semiconductors
No full textLinear dynamic ranges (LDR) of organic photodetectors, which are typically narrow due to the low charge mobilities of organic semiconductors, have been extended by doping them with diarylethene (DAE) photochromic switches. The speculated mechanism is that DAE acts as n-type trap only in its aromatic closed form which is predominant under strong sunlight. This mechanism involves photo-switchable change transfer between p-type donor polymer and DAE. We thus herein design optimal DAE dopants according to a set of design rules embracing the roles of their HOMO/LUMO energies. We first identified two optimal dopants out of 133 candidates, using time-dependent density functional theory (TDDFT) to calculate the HOMO/LUMO energies of their open/closed isomers (532 data). We then predicted those of 40,000 candidates through machine learning, identified additional optimal dopants, and confirmed them with TDDFT. One of the designed dopants indeed succeeded in LDR extension in real experiments
Cobalt Nitride-Implanted PtCo Intermetallic Nanocatalysts for Ultrahigh Fuel Cell Cathode Performance
No full textStable and active oxygen reduction electrocatalysts are essential for practical fuel cells. Herein, we report a novel class of highly ordered platinum-cobalt (Pt-Co) alloys embedded with cobalt nitride. The intermetallic core-shell catalyst demonstrates an initial mass activity of 0.88 A mgPt-1 at 0.9 V with 71% retention after 30,000 potential cycles of an aggressive square-wave accelerated durability test and loses only 9% of its electrochemical surface area, far exceeding the US Department of Energy 2025 targets, with unprecedented stability and only a minimal voltage loss under practical fuel cell operating conditions. We discover that regulating the atomic ordering in the core results in an optimal lattice configuration that accelerates the oxygen reduction kinetics. The presence of cobalt nitride decorated within PtCo superlattices guarantees a larger barrier to Co dissolution, leading to the excellent endurance of the electrocatalysts. This work brings up a transformative structural engineering strategy for rationally designing high-performing Pt-based catalysts with a unique atomic configuration for broad practical uses in energy conversion technology. © 2024 American Chemical Society.FALSEsciescopu
Brain-Inspired Hyperdimensional Computing in the Wild: Lightweight Symbolic Learning for Sensorimotor Controls of Wheeled Robots
No full textEfficiency and performance are significant challenges in applying Machine Learning (ML) to robotics, especially in energy-constrained real-world scenarios. In this context, Hyperdimensional Computing offers an energy-efficient alternative but has been underexplored in robotics. We introduce ReactHD, an HDC-based framework tailored for perception-action-based learning for sensorimotor controls of robot tasks. ReactHD employs hypervectors to encode sensory inputs and learn the suitable high-dimensional pattern for robot actions. It also integrates two HD-based lightweight symbolic learning techniques: HDC-based supervised learning by demonstration (HDC-IL) and HD-Reinforcement Learning (HDC-RL) to enable precise, reactive robot behaviors in complex environments. Our empirical evaluations show that ReactHD achieves robust and accurate learning outcomes comparable to state-of-the-art deep learning while substantially improving the performance and energy consumption efficiency by 14.2× and 15.3×. To the best of our knowledge, ReactHD is the first HDC-based framework deployed in real-world settings. © 2024 IEEE
TRANSFER METHOD OF THE OXIDE SINGLE CRYSTAL THIN FILM, AND APPLICATION THEROF
No full text본 발명은 단결정 산화물 박막의 전사 방법에 관한 것으로, 보다 상세하게는 (a) 제1 기판 위에 화학 안정성을 가지는 용매에 용해되는 희생층을 형성하는 단계, (b) 상기 희생층 위에 단결정 산화물 박막을 성장시켜 적층체를 형성하는 단계, (c) 상기 적층체를 용매에 담금에 따라 상기 용매 내에서 상기 희생층을 용해하여 상기 제1 기판과 상기 단결정 산화물 박막을 분리하는 단계, 및 (d) 제2 기판을 상기 용매에 담근 후 들어 올리면서 용매 위에 부유된 상기 단결정 산화물 박막을 떠올려 제2 기판 상에 전사하는 단계를 포함하는 것으로, 특정 단결정 기판 위에 성장된 단결정 산화물 박막을 유연 기판 혹은 결정성에 관계없는 기판 위에 전사하여 기능성 소자를 제조할 수 있는 단결정 산화물 박막의 전사 방법에 관한 것이다
Improved the conductivity of PEDOT:PSS by magnetic field for bio-electrode applications
No full textPoly(3,4-ehtylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) is a mixture of two ionomers. Especially, its conductive polymer PEDOT is well-known conductive polymer widely utilized for organic and stretchable device fabrication. However, PEDOT:PSS itself is not conductive polymer owing to another ionomer PSS so that pretreatment is necessary to enable PEDOT. Recently, it is found that hydrothermal (HT) treatment significantly increases the activity of PEDOT:PSS up to 250 times [1]. Also, this treatment has advantages in that it is compatible with biological environments since it doesn’t leave organic solution or strong acid. Here, we introduce additional improvement of PEDOT:PSS activation, more than twice, applying magnetic field over hydrothermal treatment. We also exhibit analysis of molecular structure with Raman spectroscopy, XPS, and GIWAXS. The results shows enhanced attraction force between PEDOT:PSS and water molecules
CO2에서 CH4으로의 효율적인 광화학적인 전환을 위한 조촉매와 환원된 2D TiO2의 시너지적 계면 공학
No full textsurface oxygen vacancy, ternary junction, CO2 photoreduction, morphology tuning, 2-dimensional TiO2, hydroxyl group1. Introduction 1
1.1. Research Background 1
1.2. Photocatalytic CO2 reduction 1
1.3. About this study 3
1.4. References 4
2. Characterization and analysis equipment 5
2.1. Characterization 5
2.1.1. High-resolution transmission electron microscopy (HR-TEM) 5
2.1.2. Brunauer-Emmett-Teller (BET) 6
2.1.3. X-ray diffraction (XRD) 7
2.1.4. Raman spectroscopy 9
2.1.5. Photoluminescence spectroscopy (PL) 10
2.1.6. UV-Visible spectroscopy (UV-VIS) 12
2.1.7. X-ray photoelectron spectroscopy (XPS) 14
2.1.8. Electron Paramagnetic Resonance (EPR) 16
2.1.9. Gas chromatograph (GC) 18
2.1.10. Fourier-transform infrared spectroscopy (FTIR) 19
2.2. References 20
3. Synergistic Interface Engineering of Cocatalyst and Reduced 2D - TiO2 for Efficient Photocatalytic CO2 to CH4 Conversion 22
3.1. Introduction 22
3.2. Experiment 23
3.2.1. Materials 23
3.2.2. Synthesis of 2D-RT 24
3.2.3. Synthesis of G/2D-RT 24
3.2.4. Synthesis of Cu/G/2D-RT 25
3.2.5. Characterization 26
3.2.6. Solar-light-driven catalytic CO2 reduction with H2O vapors 26
3.2.7. Apparent Quantum Yield (AQY) calculation 27
3.3. Results and discussion 28
3.4. Conclusions 45
3.5. References 46
4. Acknowledgement 50
5. 요 약 문 51MasterdCollectio
Digital Twin Battery Modeling and Simulations: A New Analysis and Design Tool for Rechargeable Batteries
No full textThe intricate correlation between microstructural properties and performance in lithium rechargeable batteries necessitates advanced methods to elucidate their mechanisms. In this regard, digital twin simulations have been utilized by creating virtual replicas that simulate battery behaviors and performances under various conditions. However, the relationship between microstructural parameters and battery performances is still not fully understood. This focus review aims to revisit the state of digital twin simulations, with a particular focus on its effectiveness for analyzing microstructures and unraveling the hidden parameters. For this purpose, we explore microstructure formation and validation methods as top-down and bottom-up simulation techniques and provide a comprehensive view of multiphysics approaches for understanding the electrochemical, mechanical, and thermal behaviors. Finally, we discuss the potential of artificial intelligence (AI)-driven multiscale modeling strategies and dynamic simulations, offering insights into how digital twin technology can advance battery design and optimization for enhanced performance and safety. © 2024 American Chemical Society.FALSEsciescopu
High-speed tissue metabolism measurement using a combination of diffuse speckle contrast analysis and near-infrared spectroscopy
Get PDFThis study presents and validates a multimodal optical system combining diffuse speckle contrast analysis (DSCA) and near-infrared spectroscopy (NIRS) with a unique system design for high-speed tMRO2 monitoring. The optical system for simultaneous dual-wavelength illumination and detection by a single camera is constructed using dichroic mirrors without an external trigger device. Phantom experiments and in-vivo arterial occlusion tests are conducted by varying the camera exposure time from 0.5 ms to 10 ms to validate system performance. We analyze and compare the results according to the exposure time to acquire the optimal relative tMRO2 (rtMRO2) signal by dual-exposure time control. The in-vivo experiment confirmed that the relative blood flow (rBF) and tissue oxygenation index (TOI) signals from the two modalities had a trade-off with the camera exposure time. We obtained the optimal rtMRO2 using dual-exposure time control. We conclude that the proposed DSCA/NIRS provides real-time rtMRO2 assessment, which can provide biomarkers for diagnosing vascular diseases. © 2024 The Author(s). Published with license by Taylor & Francis Group, LLC.TRUEsciescopu
Target-aware cross-modality unsupervised domain adaptation for vestibular schwannoma and cochlea segmentation
Get PDFThere is growing interest in research on segmentation for the vestibular schwannoma (VS) and cochlea using high-resolution T2 (hrT2) imaging over contrast-enhanced T1 (ceT1) imaging due to the contrast agent side effects. However, the hrT2 imaging remains a problem of insufficient annotated data, which is fatal for building more robust segmentation models. To address the issue, recent studies have adopted unsupervised domain adaptation approaches that translate ceT1 images to hrT2 images. However, previous studies did not consider the size and visual characteristics of the target objects, such as VS and cochlea, during image translation. Specifically, those works simply performed normalization on the entire image without considering its significant impact on the quality of the translated images. These approaches tend to erase the small target objects, making it difficult to preserve the structure of these objects when generating pseudo-target images. Furthermore, they may also struggle to accurately reflect the unique style of the target objects within the images. Therefore, we propose a target-aware unsupervised domain adaptation framework, designed for translating target objects, each tailored to their unique visual characteristics and size using target-aware normalization. We demonstrate the superiority of the proposed framework on a publicly available challenge dataset. Codes are available at https://github.com/Bokyeong-Kang/TANQ.TRUEsciescopu