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Innovating User Experience in the Era of Generative AI
This study is the result of a collaborative effort by Professor Jang Hyun Kim of the School of Global Convergence and members of the Data Science & Social Analytics Lab (DSSAL), including Dongyan Nan (Ph.D. graduate, now Assistant Professor at Macau University of Science and Technology), Seungjong Sun (Ph.D. candidate), Shunan Zhang (Ph.D. graduate, now Fellow at Huaqiao University in China), and Xiangying Zhao (Ph.D. graduate). The purpose of this research is to gain an in-depth understanding of user behavior toward Generative Artificial Intelligence. Focusing on ChatGPT as a representative example, the study identifies key factors that influence users’ continued usage intention and recommendation intention. Theoretically, it proposes a new integrated model that extends the Expectation Confirmation Model (ECM) by incorporating Information System Success Theory (ISST), privacy concerns, and perceived innovativeness. This approach addresses the limitations of prior studies, which largely focused on initial usage intention, and instead highlights both cognitive and emotional determinants of post-adoption behavior—providing meaningful academic contributions. A total of 252 Korean ChatGPT users participated in an online survey, and the results were analyzed using structural equation modeling. The findings show that the proposed integrated model effectively explains users’ continued use and recommendation behaviors. Information Quality and System Quality emerged as core variables that enhance both types of behavioral intentions by strengthening confirmation, perceived usefulness, and satisfaction. Perceived innovativeness also had a positive effect on user satisfaction, demonstrating that users form more favorable experiences when they view ChatGPT as a creative and cutting-edge technology. Conversely, privacy concerns negatively affected satisfaction, although the impact was relatively small—suggesting that users may be willing to accept certain privacy risks in exchange for convenience and utility. Based on these findings, the study offers practical implications for promoting the adoption of generative AI services. Service providers can enhance user engagement by improving model accuracy and stability to reduce information bias, designing user-friendly interfaces, and effectively promoting the creativity and innovativeness of AI technologies. Professor Kim noted, “By comprehensively analyzing the determinants of continued use and recommendation of generative AI, this study offers new insights into user experience–based AI adoption research. We plan to further advance the model by expanding our research to include voice- and image-based generative AI in the future.” His research team continues to explore the intersection of AI and user experience (UX) and has published numerous SSCI/SCIE-indexed papers in related fields. ※ Title: Analyzing behavioral intentions toward Generative Artificial Intelligence: the case of ChatGPT ※ Journal: Universal Access in the Information Society ※ Link: https://doi.org/10.1007/s10209-024-01116-z ※ Portal(Pure): https://pure.skku.edu/en/persons/janghyun-kim/ Dongyan Nan(Ph.D. graduate, now Assistant Professor at Macau University of Science and Technology), Shunan Zhang(Ph.D. graduate, now Fellow at Huaqiao University in China), Xiangying Zhao(Ph.D. graduate)
- No. 339
- 2025-11-13
- 432
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Political Bias: Even AI Journalists Aren’t an Exception
Professor Joo-Wha Hong, together with Professor Herbert Chang of Dartmouth College and Professor David Tewksbury of the University of Illinois at Urbana-Champaign, published this study in Digital Journalism, a leading international journal in the field of communication. The research experimentally examined how audiences perceive and evaluate both AI- and human-authored political news. Grounded in the theoretical frameworks of the machine heuristic and the hostile media effect, the study investigated how the author’s identity (human vs. AI) and readers’ political orientations influence perceptions of news credibility and journalist credibility. The experiment was conducted with 442 adult participants in the United States through an online survey. Participants were randomly assigned to read articles on four politically sensitive issues (i.e., abortion law, gun control, minimum wage, and health-care reform) authored either by AI or human journalists and published under three different news outlets representing distinct ideological leanings (i.e., liberal, neutral, and conservative). This design enabled the researchers to analyze interactions among author identity, reader ideology, and political distance from the media outlet. Results revealed that readers trusted and evaluated human-written articles more favorably, yet perceived AI journalists as less biased and more neutral. In other words, while readers regarded AI as a “more objective and emotionally detached journalist,” they still tended to view AI as biased when its political stance differed from their own—a sign of an ambivalent attitude toward machine-generated content. Furthermore, evaluations of AI journalists were moderated by the extent to which individuals accepted AI as a rational and objective actor. The relative hostile media effect also appeared for AI: as the political distance between readers and news outlets increased, trust and likability decreased, regardless of whether the article was written by a human or AI. This study highlights that artificial intelligence is not merely a technical substitute for human journalists but a new social actor capable of shaping public trust and political perceptions. It empirically demonstrates how audiences cognitively process AI-generated content and how their beliefs about AI’s capabilities influence evaluations of information credibility. Looking ahead, the research team plans to extend this line of inquiry to examine public responses to AI’s broader social roles, such as counselor, educational partner, creative collaborator, and conversational companion. These efforts aim to provide crucial insights into the social legitimacy and trust-building mechanisms of AI as it becomes increasingly embedded in human social life. ※ Title: Can AI Become Walter Cronkite? Testing the Machine Heuristic, the Hostile Media Effect, and Political News Written by Artificial Intelligence ※ Journal: Digital Journalism ※ Link: https://doi.org/10.1080/21670811.2024.2323000 ※ Research Portal(Pure): https://pure.skku.edu/en/persons/joo-wha-hong/
- No. 338
- 2025-11-03
- 1326
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Elucidation of Single-Nuclear Transcriptomic and Molecular Signaling Mechanisms, Preclinical Validation of Therapeutics
Professor Yunjong Lee’s research team (first authors: Ji Hun Kim, Ph.D. student; Hyo Jung Kim, Ph.D.; and Prof. Yunjong Lee) at the Department of Pharmacology, Sungkyunkwan University School of Medicine, has developed a conditional Tet-off transgenic mouse model expressing ZNF746 (PARIS) specifically in midbrain dopaminergic neurons to elucidate the molecular pathogenesis of Parkinson’s disease (PD) and to enable preclinical evaluation of therapeutic agents. PARIS (ZNF746) is a substrate of the autosomal recessive PD gene Parkin and is known as a transcriptional repressor that accumulates in the brains of PD patients, playing a direct pathogenic role in dopaminergic neuronal degeneration. PARIS represses key regulators of cellular survival, including PGC-1α, a master regulator of mitochondrial biogenesis, and MDM4, an upstream modulator of the apoptosis regulator p53, thereby leading to metabolic dysfunction and neuronal death. This study was conducted in collaboration with Professor Jaeyoul Joo’s research group (co-first authors: Prof. Jaeyoul Joo and Soomin Yang) at the College of Pharmacy, Hanyang University, who performed single-nuclear transcriptome analysis to systematically characterize cell-type-specific pathological alterations. A major challenge in PD research has been the lack of an animal model that faithfully reproduces the progressive and relatively selective degeneration of dopaminergic neurons, the hallmark pathology of the disease. To overcome this limitation, Prof. Lee’s team established a Tet-off genetic switch–based model that enables adult-onset, dopaminergic neuron–specific expression of PARIS, avoiding developmental lethality caused by early transgene expression. This model successfully recapitulates progressive motor deficits, clinically relevant extent of dopaminergic neuronal loss, mitochondrial dysfunction, and neuroinflammatory activation over a two-month period, overcoming key limitations of previous transgenic PD models. Using this model, the team further conducted preclinical drug validation studies, demonstrating that L-DOPA, a symptomatic dopamine replacement therapy, ameliorates motor deficits, while the c-Abl inhibitor Nilotinib suppresses neurodegeneration and neuroinflammation, thereby exerting disease-modifying effects. These results establish this model as a robust preclinical platform for evaluating both symptomatic and disease-modifying therapeutic candidates for PD. In addition, by combining single-nuclear transcriptomic and protein-level analyses of the midbrain region, the study identified the c-Abl–PARIS signaling axis as a key pathogenic pathway that suppresses PGC-1α–mediated mitochondrial biogenesis, activates p53-dependent apoptotic signaling, and promotes glial inflammatory remodeling. Collectively, this research presents a novel PARIS-expressing PD mouse model that overcomes the limited pathological fidelity of conventional transgenic systems, providing a powerful experimental platform for elucidating molecular pathomechanisms and assessing preclinical efficacy of therapeutic candidates targeting neurodegeneration and inflammation in Parkinson’s disease. ※ Title: Preclinical studies and transcriptome analysis in a model of Parkinson’s disease with dopaminergic ZNF746 expression ※ Journal: Molecular Neurodegeneration ※ Paper Link: https://doi.org/10.1186/s13024-025-00814-3 ※ Portal(Pure): https://pure.skku.edu/en/persons/yunjong-lee/
- No. 337
- 2025-10-24
- 1254
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Design of an Origami-Based Hybrid Pneumatic Joint and Implementation of a High-Torque Manipulator
This study developed a hybrid pneumatic joint by combining a soft pneumatic-driven origami chamber and a rigid frame with a fixed rotational axis. The hybrid joint appropriately limited the excessive compliance, which was a drawback of existing inflatable joints, and was able to maintain high torque and control accuracy over a wide range of motion. This was expanded into a meter-scale hybrid robot manipulator, which stably performed pick-and-place tasks of heavy objects such as fruit. The objective of this study is the development of a hybrid joint with a hard/soft combined structure that compensates for the drawbacks of existing pneumatic-driven inflatable joints, such as excessive compliance and high control difficulty. This joint has the advantage that deformation is predictable due to the origami structure, it can operate under both positive and negative pressure without the chamber shape collapsing through the use of facet reinforcement, and excessive expansion of the chamber can be prevented through the use of internal constraint. Additionally, the origami chamber, when combined with a rigid frame, allows the use of general rotational angle measurement sensors such as rotary encoders or potentiometers. The origami chamber was made of tarpaulin, a type of functional fabric, and combined with a 3D-printed frame to form the hybrid joint. Unlike existing pneumatic-based joints, the joint developed in this study has the advantage of being capable of bidirectional actuation by alternating positive/negative pressure in a single chamber, and bidirectional, antagonistic actuation can also be realized by placing two origami chambers facing each other. Furthermore, by applying opposing pressures to the antagonistic chambers, a type of cooperation between chambers that significantly enhances the joint’s torque is possible, which can generate twice the torque of the original at the same chamber pressure limit. Finally, the developed hybrid joints were configured into a 3-degree-of-freedom hybrid manipulator. This robotic arm showed excellent range of motion even under applied payload and, based on compliance, operated normally even under external shocks, demonstrating a well-blended result of the advantages of soft robots and rigid-body-based robots. Furthermore, it repeatedly performed the task of receiving fruit over 1kg from a user and placing it into a fixed basket without issue, proving its applicability to everyday human tasks. ※ Paper Title: Hybrid Hard-Soft Robotic Joint and Robotic Arm Based on Pneumatic Origami Chambers ※ Journal: IEEE/ASME Transactions on Mechatronics ※ DOI: https://doi.org/10.1109/TMECH.2024.3411629 ※ Research Portal(Pure): https://pure.skku.edu/en/persons/hugo-rodrigue
- No. 336
- 2025-10-16
- 1449
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Identification of spin decoherence mechanism in VB- defect qubits of h-BN
The team led by Prof. Hosung Seo systematically studied the magnetic-field–dependent behavior of spin decoherence in the negatively charged boron vacancy (VB⁻) defect of hexagonal boron nitride (h-BN) and proposed practical guidelines for extending the coherence time (T₂). The study shows that the decoherence mechanism undergoes a transition across distinct magnetic-field regimes and provides recommended magnetic field ranges together with their microscopic origins for quantum information applications. As a next-generation 2D materials platform for quantum technologies, the VB⁻ defect in h-BN offers an optically addressable spin qubit operating at room temperature. However, its short T₂ time has been a critical bottleneck to practical applications, calling for both practical strategy and microscopic understanding to enhance coherence. In this work, the researchers combined density functional theory calculations with the generalized cluster-correlation expansion (CCE) to quantitatively investigate the decoherence across a broad range of magnetic fields. The results show that the isotopic composition of boron and nitrogen markedly affects T₂, and that a critical magnetic field strength (called transition boundary) exists, above which T₂ increases by two orders of magnitude. The analysis also identifies distinct modulations in coherence at particular magnetic fields originating from specific nuclear spins in h-BN. This study presents a unified theoretical framework for the distinctive decoherence physics of h-BN, characterized by a dense nuclear-spin bath with high-nuclear-spin isotopes. Building on this framework, we propose design guidelines for spin qubits in 2D materials based on isotopic engineering and magnetic-field control. These guidelines support the quantum-devices design and the optimization of sensing conditions for h-BN based quantum information technologies. This research was supported by the National Research Foundation of Korea (NRF), by Creation of the Quantum Information Science R&D Ecosystem through the NRF, and the education and training program of the Quantum Information Research Support Center at SKKU, funded through the NRF. The excellence of this work was recognized with publication in the Advanced Functional Materials (Impact Factor: 19.0), a leading international journal in the field of Applied Physics, on Aug. 24, 2025. ※ Paper Title: Magnetic-Field Dependent VB− Spin Decoherence in Hexagonal Boron Nitrides: A First-Principles Study ※ Journal: Advanced Functional Materials ※ DOI: https://doi.org/10.1002/adfm.202511274 VB- spin decoherence as functions of magnetic fields and transition boundary for decoherence
- No. 335
- 2025-10-10
- 1224
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Metalens-Based Volumetric Photoacoustic Imaging Technology for Brain Organoids
A collaborative research group led by Professor Inki Kim (Department of Biophysics, Sungkyunkwan University), in partnership with Professors Byullee Park and Jong-Chan Park, has successfully developed a large-area volumetric photoacoustic microscopy (PAM) platform utilizing a metalens. This breakthrough enables unprecedented three-dimensional imaging of neuromelanin within brain organoids, with profound implications for the study of neurodegenerative diseases such as Parkinson’s disease. Photoacoustic imaging is a hybrid modality that combines optical excitation with ultrasonic detection: pulsed laser light is delivered into biological tissue, where absorbed photons induce thermoelastic expansion and generate ultrasonic waves. While optical imaging suffers from severe scattering within tissue, ultrasound experiences minimal attenuation, permitting deeper penetration. Thus, PAM uniquely offers the synergistic advantages of optical-resolution imaging and ultrasonic depth reach, and has been actively applied in oncology, vascular studies, and metabolic research without the need for exogenous labels. Conventional PAM, however, is constrained by the fundamental trade-off between resolution and depth of focus. As imaging departs from the optical focal plane, both signal strength and resolution rapidly decline, making label-free volumetric imaging of thick biological constructs such as organoids extremely challenging. To overcome this limitation, the research team engineered a novel phase-controlled metalens capable of generating a non-diffracting needle beam. By merging phase maps corresponding to lenses of distinct focal lengths into a single titanium dioxide (TiO₂)-based metasurface, the group produced a lens that preserves diffraction-limited resolution while extending the depth of focus by more than 13.5-fold compared to conventional optics. This innovation, unachievable with traditional refractive lens designs, represents a transformative step in lens engineering. The needle-beam metalens was subsequently integrated into a photoacoustic microscope, enabling high-resolution volumetric visualization of neuromelanin distribution within living brain organoids. Neuromelanin, a critical biomarker for Parkinson’s disease and other neurodegenerative disorders, has previously been inaccessible to quantitative imaging due to the optical opacity of brain tissue models. Using this platform, the team successfully captured three-dimensional maps of neuromelanin across forebrain and midbrain organoids, and experimentally demonstrated dynamic changes in melanin distribution as a function of culture duration. These findings hold direct significance for elucidating the pathological mechanisms of Parkinson’s disease, as disease onset and progression are strongly age-related. According to Professor Kim: “Our metalens-based photoacoustic microscopy is not limited to brain organoids, but can be broadly applied to diverse classes of organoid systems. This technology thus provides a versatile tool for probing pathological mechanisms and assessing pharmacological efficacy across a wide spectrum of biomedical research domains.” The study, entitled “Axially multifocal metalens for 3D volumetric photoacoustic imaging of neuromelanin in live brain organoid”, has been published in Science Advances (Impact Factor 12.5). The work was supported by the National Research Foundation of Korea (NRF) through the STEAM: Global Convergence Research Program, the K-Brain Project, the Sejong Science Fellowship, and the Young Investigator Program. ※ Title: Axially multifocal metalens for 3D volumetric photoacoustic imaging of neuromelanin in live brain organoid ※ Journal: Science Advances (IF: 12.5) ※ Link: https://doi.org/10.1126/sciadv.adr0654 ▲Figure 1. Needle beam metalens with extended depth of focus and its application to brain organoid imaging ▲ Figure 2. Photoacoustic imaging of the 3D melanin distribution within a brain organoid using a needle beam metalens ▲ Figure 3. Metalens-based neuromelanin quantification for Parkinson’s disease research
- No. 334
- 2025-09-26
- 2253
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Development of Biocompatible and Stretchable Semiconductor for Implantable Devices
A research team led by Professor Suk Ho Bhang of the School of Chemical Engineering at Sungkyunkwan University and Professor Jin Young Oh of the Department of Chemical Engineering at Kyung Hee University has developed a core technology for next-generation implantable bioelectronic devices. The team succeeded in realizing a highly stretchable and biocompatible organic transistor that mimics the mechanical softness of biological tissue while maintaining stable function during long-term implantation. This breakthrough offers new possibilities for advancing the performance of clinical implantable devices such as pacemakers, neurostimulators, and insulin pumps. The research addressed the long-standing challenge of tissue damage and inflammation caused by the rigidity of conventional silicon-based semiconductors. By blending semiconducting nanofibers (DPPT-TT) with a medical-grade elastomer (BIIR) and applying a vulcanization process, the team fabricated a semiconducting film that combines skin-like elasticity with stable electrical performance. In addition, the incorporation of dual-layer silver and gold metallization enabled robust operation without corrosion in biofluid environments. The fabricated transistors maintained stable performance even under strains exceeding 50 percent and were successfully applied to drive basic logic circuits such as inverters, NOR gates, and NAND gates. In vitro tests with human dermal fibroblasts and macrophages revealed no signs of toxicity or inflammatory response, while in vivo subcutaneous implantation in BALB/c mice confirmed long-term biocompatibility. Notably, the study demonstrated reduced fibrous capsule formation, a major cause of decreased functionality in implantable devices. The team emphasized that this achievement could serve as a fundamental platform for next-generation implantable electronics, with strong potential applications in real-time physiological signal monitoring, neural interfacing, and personalized therapeutic systems. This work was supported by the Ministry of Trade, Industry and Energy and the Korea Evaluation Institute of Industrial Technology (KEIT) through the Materials and Components Technology Development Program, as well as by the Ministry of Science and ICT and the National Research Foundation of Korea (NRF) through the Excellent Young Researcher Program, the University-Centered Research Institute Program, and the Engineering Research Center (ERC) Program. The findings were published in the international journal Nature Electronics and were subsequently highlighted in a Nature Electronics Research Briefing (IF: 40.9, JCR < 0.1%) on September 2. Paper Title: A biocompatible elastomeric organic transistor for implantable electronics First authors: Kyu Ho Jung, Dr. Jiyu Hyun, Corresponding authors: Prof. Suk Ho Bhang, Prof. Jin Young Oh Journal: Nature Electronics DOI: 10.1038/s41928-025-01444-9
- No. 333
- 2025-09-23
- 1755
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Development of Hydrogel-Based Triboelectric Nanogenerators That Maintain Durability and Output in Dry Environments
Professor Kyungwho Choi’s team (first author: Thien Trung Luu) of the School of Mechanical Engineering at Sungkyunkwan University, in collaboration with Professor Younghoon Lee’s team in the Department of Mechanical Engineering at Kyung Hee University, proposed a strategy to overcome the principal weakness of hydrogel electrodes—performance degradation in dry environments—through kosmotropic-ion embedding. By employing sulfate/sulfite ions (SO₄²⁻/SO₃²⁻) to simultaneously form internal crystalline domains and a surface charge-blocking layer (CBL), the team realized a triboelectric nanogenerator (TENG) technology that enhances both mechanical stability and triboelectric output even under arid conditions. As a result, the TENG fabricated via the kosmotropic process achieved a more than threefold increase in power density and maintained stable output even at 700% strain. The researchers further demonstrated that the developed hydrogel sustains stable performance over 15,000 contact–separation cycles, and continues to operate reliably after 6 hours at 50 °C as well as after 30 days of storage at room temperature, thereby overcoming the rapid performance drop typically caused by water evaporation in hydrogel electrodes. They explain that these characteristics arise from ion concentration and the formation of localized polarization regions during partial dehydration, while the CBL suppresses charge leakage, enabling persistent response to mechanical stimuli. Professor Choi, the lead investigator, stated, “Although hydrogel electrodes are renowned for their flexibility and stretchability, they clearly lose their properties in dry environments; the significance of this study lies in overcoming that limitation. Building on this technology, we will continue to develop high-output, highly stable energy-harvesting systems and pursue applications in wearable devices and sustainable energy systems.” This research was supported by the 4th BK21 Future HRD Education and Research Center for Human-Centered Convergence Mechanical Solution and by the Korea government (MSIT). The results were published in Chemical Engineering Journal (JCR top 3%; IF 13.2) in August 2025 Title: Kosmotropic ions embedded hydrogel for significantly enhancing deformability and performance of iontronic triboelectric nanogenerators Journal: Chemical Engineering Journal DOI: https://doi.org/10.1016/j.cej.2025.167062
- No. 332
- 2025-09-19
- 822
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Breakthrough in 3D Integration: Monolithic AI Memory and Room-Temperature Ferromagnetism via a Single-Step Plasma Proces
Sungkyunkwan University announced that Prof. Taesung Kim’s research group in the Department of Mechanical Engineering has achieved a dual breakthrough in next-generation artificial intelligence (AI) semiconductors and spintronic devices by utilizing van der Waals (vdW) materials. The team successfully fabricated a vdW 2D/3D heterojunction neuromorphic memory device through a single plasma process that simultaneously bonded nanocrystals with a van der Waals lattice, while also endowing bulk vanadium selenide (VSe₂), which intrinsically lacks ferromagnetism, with artificial room-temperature ferromagnetic functionality. With the advent of AI and hyper-connected societies, the demand for neuromorphic memory devices capable of performing memory and computation simultaneously has intensified. However, conventional CMOS-based memory technologies have faced inherent limitations in power consumption and scalability, while metal oxide-based ReRAM has been constrained by grain-boundary effects and filamentary inhomogeneity, which compromise long-term reliability and large-scale integration. To overcome these challenges, the researchers implemented a single-step plasma sulfurization process in which ion penetration and ion-penning effects of Ar and H₂S were precisely controlled, enabling the direct formation of a three-dimensional monolithic integrated architecture without additional deposition or bonding. This approach demonstrated reliable long-term potentiation (LTP), long-term depression (LTD), and analog synaptic weight modulation, with stable operation confirmed for over 1.8×10⁷ switching cycles. Moreover, the research team also succeeded in realizing two-dimensional room-temperature ferromagnetism, which had long been considered unattainable. Previously, two-dimensional magnetic materials could only be obtained through monolayer exfoliation and exhibited magnetic ordering solely at cryogenic temperatures, precluding practical application. By nanocrystallizing and isolating the lattice of inherently nonmagnetic bulk VSe₂, the team artificially induced ferromagnetic ordering at room temperature. Notably, magnetic force microscopy (MFM) observations revealed that nanocrystalline grain boundaries function as pinning centers for magnetic domains, thereby elucidating a previously unrecognized structure-magnetism coupling mechanism in vdW ferromagnets. These dual achievements hold profound significance in simultaneously broadening both the universality and applicability of the van der Waals material platform. The 3D monolithic neuromorphic memory offers an alternative architecture that overcomes the physical and process-related limitations of conventional silicon-based integration, while the realization of room-temperature ferromagnetism paves the way for next-generation spintronics and quantum devices. Prof. Taesung Kim emphasized, "Through the development of Single-Step plasma process, we aim to establish a novel vdW material platform that enables the artificial injection of synaptic behavior and room-temperature ferromagnetism, thereby accelerating both next-generation AI semiconductors and spintronic technologies." This research was jointly conducted with the IBS Center for Quantum Nanoscience, Washington University in St. Louis, the Korea Institute of Machinery and Materials, and the Park Systems R&D Center, and the two research projects were published in "Advanced Science" on May 28 and August 27, respectively. Authors: Corresponding author: Prof. Taesung Kim; Joint first authors: Jinhyoung Lee (Ph.D. candidate), Gunhyoung Kim (Ph.D. candidate), Hyunho Seok (Postdoctoral Fellow), Hyunbin Choi (Ph.D. candidate), Sujeong Han (M.S. candidate). Article 1: Monolithically-integrated van der Waals Synaptic Memory via Bulk Nano-crystallization Article 2: Artificial Room-Temperature Ferromagnetism of Bulk van der Waals VSe2 Journal Link 1: https://doi.org/10.1002/advs.202510961 Journal Link 2: https://doi.org/10.1002/advs.202504746
- No. 331
- 2025-09-16
- 1176
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Scientific Verification of Sanitary Pad Safety Announced
Prof. Chun Gwon Park’s research team from the Department of Biomedical Engineering, in collaboration with Prof. Juhee Kim’s team at the University of Hawaii and Prof. Sena Kim at Chungbuk National University, has published the results of an international joint study comprehensively evaluating the chemical safety and potential toxicity of sanitary pads available on the market. This study, released on August 29, 2025, carries significant meaning as the first comprehensive analysis addressing the safety of sanitary products closely linked to women’s health. The global collaborative research team analyzed 29 types of sanitary pads distributed domestically and internationally, focusing on volatile organic compound (VOC) emissions, microplastic detection, and in vitro evaluation of cytotoxicity. The results showed that toluene* was detected in multiple products at levels ranging from 0.04 to 2.79 μg per pad. While this is lower than the existing occupational safety threshold (37 mg/m³), the researchers noted that closer scrutiny is needed considering skin absorption characteristics and prolonged use. *Toluene: A widely used industrial VOC that can be harmful to health upon repeated exposure to skin or mucous membranes. In addition, all sanitary pad products were found to contain polypropylene (PP)-based microplastics, while some products also contained small amounts of other types of microplastics, such as PET and PE. With growing concerns about the impact of microplastics on human health, this study is noteworthy for scientifically demonstrating the potential for microplastic exposure through close-contact sanitary products. In vitro cytotoxicity evaluation revealed that some sanitary pads reduced cell viability to below 80%, indicating moderate cytotoxicity. Notably, certain products labeled as “organic” also exhibited cytotoxic effects, underscoring the need for further verification studies. These findings suggest that the types of chemicals used in the manufacturing process and their treatment methods may directly influence the toxicity levels of the products. Prof. Park stated, “This study delivers meaningful results by raising awareness of the safety issues surrounding sanitary products based on concrete scientific data. For products that remain in close contact with the skin for extended periods, transparency of ingredients and thorough safety verification are essential.” The study, jointly conducted by researchers from Sungkyunkwan University, the University of Hawaii, and Chungbuk National University, is expected to serve as a foundation for public health policies and regulatory standards aimed at protecting women’s health and ensuring consumer safety. The findings were published in the Journal of Hazardous Materials (Impact Factor 12.2), one of the most influential journals in the field of environmental risk assessment and safety research.
- No. 330
- 2025-09-12
- 631
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Unveiling the Mechanism of Flowering Time Regulation through Protein Phase Separation
A research team led by Professor Jae-Hoon Jung from the Department of Biological Sciences has revealed that liquid–liquid phase separation (LLPS) in plant cells is delicately and reversibly regulated by changes in ambient temperature and that this phenomenon serves as a key mechanism for determining the timing of flowering in plants. This study was conducted in collaboration with Professor Pil Joon Seo’s group in the Department of Chemistry at Seoul National University (first author Dr. Hong Gil Lee) and Professor Jong-Chan Lee’s group in the Department of New Biology at DGIST (first author Ph.D. candidate Jinkwang Kim). The team discovered that GIGANTEA (GI), a core regulator of flowering, undergoes reversible phase separation depending on temperature. At lower temperatures (22°C), GI forms inactive nuclear condensates inside the plant cell nucleus. At higher temperatures (28°C), these condensates dissolve, and GI becomes dispersed and activated. Notably, GI in its dispersed state—rather than in condensates—binds to the floral repressor SVP and promotes its degradation, thereby accelerating flowering under warm temperature conditions. Furthermore, the researchers found that FKF1, a blue-light photoreceptor, selectively binds to the intrinsically disordered region (IDR) of GI, enabling the temperature-specific and reversible dissolution of GI condensates at elevated temperatures, thereby activating GI. Previously, in a 2020 Nature paper, Professor Jung’s team identified temperature-dependent phase separation of the ELF3 protein as a plant-specific temperature-sensing mechanism. In this study, they demonstrated that phase separation of a key flowering regulator is a central mechanism enabling plants to fine-tune their development in response to even slight changes in air temperature. This work highlights the potential of developing precision control technologies for plant growth and development based on intracellular phase separation, which could play a crucial role in ensuring stable food production and enhancing agricultural competitiveness under climate change. This research was supported by the National Research Foundation of Korea (NRF) and the Rural Development Administration, and was published online in Nature Plants on July 4th. ※ Paper Title: High-temperature-induced FKF1 accumulation promotes flowering through the dispersion of GI and degradation of SVP ※ DOI: https://doi.org/10.1038/s41477-025-02019-4 ※ Authors: Prof. Hong Gil Lee (first author, SNU), Ph.D. candidate Jinkwang Kim (first author, DGIST). Ph.D. candidate Kyung-Ho Park (first author, SKKU Department of Biological Sciences), researcher Sol-Bi Kim (co-author, SKKU Department of Biological Sciences), Prof. Jae-Hoon Jung (corresponding author, SKKU Department of Biological Sciences), Prof. Jong-Chan Lee (corresponding author, DGIST), Prof. Pil Joon Seo (corresponding author, SNU) Figure. Working model of FKF1–GI in temperature-responsive flowering
- No. 329
- 2025-09-09
- 1923
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SKKU Next-Generation Channeling Research Center Team led by Prof. Sang-Hyo Kim Leads AI-Based Error Correction Codes for
Prof. Sang-Hyo Kim’s research team at the Department of Electrical and Computer Engineering, Sungkyunkwan University (IITP NRC: SKKU Next-Generation Channel Coding Research Center) has developing next-generation wireless error correction code technologies powered by artificial intelligence (AI), establishing a foundation to lead 6G and future communication technologies. In this study, Prof. Kim’s team developed a Multiple-Masks Attention–based decoding method built upon the Transformer architecture, a core structure of large language models. By leveraging the structural diversity of codes, this approach significantly improves the decoding performance of short block error correction codes and demonstrates the potential for application in ultra-reliable low-latency communications (URLLC) for autonomous driving, industrial IoT, and AI-based wireless networks (AI-RAN). In addition, the team applied a boosted learning method to neural decoders for LDPC (Low-Density Parity-Check) codes, which are currently used in 5G communication systems, achieving extremely low error rates. This result meets the ultra-reliability requirements demanded by 6G, marking an important milestone that is expected to contribute to future 6G standardization and commercialization. These research achievements were realized through collaboration with Prof. Yongjune Kim (POSTECH), Prof. Hee-Youl Kwak (University of Ulsan), Dr. Seong-Joon Park (POSTECH), and Emeritus Prof. Jong-Seon No (Seoul National University). The related technologies were published as two papers in the IEEE Journal on Selected Areas in Communications (JSAC) (JCR Top 1.0%, IF 17.2) in April and July 2025. Furthermore, the team presented their work on the Cross-Message Passing Transformer (CrossMPT) decoder at ICLR 2025, one of the world’s top three conferences in machine learning and deep learning, where the academic and technical value of their AI-based error correction technology was internationally recognized. Prof. Kim stated, “AI technology is providing a new paradigm for wireless communications. We expect our research to contribute to the advancement of 6G technologies, AI-native networks, machine-to-machine and AI-to-AI communications, and ultimately the realization of semantic communications.” Established in 2024, the IITP-NRC Next-Generation Channel Coding Research Center at SKKU is the only dedicated research hub in Korea focusing on channel coding (error correction code) technologies for 6G and future communications. The program will continue through 2031. This research has been supported by the Network Research Center (NRC) program of the Institute for Information & Communications Technology Planning & Evaluation (IITP), Channel Coding/Decoding and Channel Estimation for Next-Generation Communications, and by the National Research Foundation of Korea (NRF). ※ Paper 1: Multiple-Masks Error Correction Code Transformer for Short Block Codes (Published in July 2025) ※ Paper 2: Boosted Neural Decoders: Achieving Extreme Reliability of LDPC Codes for 6G Networks (2025년 4월 게재) ※ Journal: IEEE Journal on Selected Areas in Communications (JCR top 1% in Electrial Engineering) ▲ IIT-NRC SKKU Next Generation Channel Coding Research Center ▲ Architecture of Error Correction Code Transformer with Multiple Masks
- No. 328
- 2025-09-05
- 2055
