Breakthrough QD Display Technology Achieves 4,000 PPI Resolution — Ideal for XR Glasses

Abstract Colloidal quantum dots (QDs) are leading candidates for next-generation optoelectronics owing to their tuneable bandgaps, narrow emission linewidths, and high luminescence quantum yields. For virtual-, augmented-, and mixed-reality display applications of these materials, patterning full-color QDs at μm-length scales is essential. However, existing photolithographic approaches often degrade QD luminance characteristics by exposing them to harsh processing conditions, or they compromise the structural fidelity of the resulting patterns. Here we report a photoresist-guided indirect (PIN) photopatterning strategy that includes (i) lithographic formation of sacrificial PR patterns, (ii) deposition of a crosslinked QD film on top, and (iii) PR stripping that removes the sacrificial PR, leaving behind crosslinked QD patterns on the substrate. QD crosslinking is mediated by a diazo-based ligand thermocrosslinker, Diazo-4-LiXer. Leveraging low-temperature (110–120 °C)-activated carbene chemistry, Diazo-4-LiXer bridges neighbouring QDs while maintaining their intrinsic photoluminescence and electroluminescence through repeated processing. Moreover, Diazo-4-LiXer enables thermocrosslinking without affecting the underlying photoresist pre-patterns, which serve as structural templates determining the thickness and fidelity of the QD patterns. Using PIN photopatterning, we realize high-fidelity RGB patterns exceeding 4,000 pixels per inch resolution and demonstrate integration-level scalability by fabricating a 10 × 10 passive-matrix full-colour RGB QD–LED array. Researchers, affiliated with UNIST have announced a significant advancement in quantum dot (QD) display technology, enabling ultra-fine, high-resolution patterning of QDs suitable for next-generation XR glasses. This innovation promises brighter, more vivid images even in outdoor environments. Professor BongSoo Kim from the Department of Chemistry at UNIST, in collaboration with Professor Moon Sung Kang of Sogang University and Dr. Chan-mo Kang at Electronics and Telecommunications Research Institute (ETRI), have developed a novel photopatterning technique that maintains the integrity of quantum dots while achieving micron-scale precision. To meet the demanding resolution required for XR displays—exceeding 3,000 pixels per inch (PPI)—the team’s method patterns quantum dots into 2-micrometer (μm) pixels. This enables over 4,000 PPI, meaning more than 10 million pixels can be packed into a space about the size of a coin, ensuring sharp, immersive visuals. The process employs a custom-developed additive, Diazo-4-LiXer, which facilitates thermocrosslinking at low temperatures (110–120°C) via carbene chemistry, preserving the quantum dots’ luminescent properties. It involves creating a sacrificial photoresist (PR) template, depositing a crosslinked quantum dot film, then removing the PR to leave behind precisely patterned quantum dots—without damage or shape distortion. This technique not only achieves high fidelity and density but also enables the fabrication of full-color RGB quantum dot LED arrays, demonstrating its potential for commercial application. Professor Kim commented, “Our method allows for ultra-high resolution patterning of quantum dots while maintaining their exceptional optical properties. It opens new avenues for advanced XR glasses and microdisplays, where brightness, color purity, and resolution are crucial.” The findings of this research have been published in Nature Communications on March 19, 2026. The study has been supported by the Samsung Research Funding & Incubation Center of Samsung Electronics, the National Research Foundation of Korea (NRF), and the Ministry of Science and ICT (MSIT). Journal Reference Hyeokjun Kim, Hyobin Ham, Chang Hyeok Lim, et al., "Photoresist-guided indirect photopatterning of quantum dots via carbene-mediated ligand thermocrosslinking," Nat. Commun., (2026).

2026.04.27

UNIST Demonstrates Global Competitiveness in Reinforcement Learning with Three Papers Accepted to ICLR 2026

UNIST has demonstrated strong international competitiveness in reinforcement learning, a core technology for physical AI, with three papers by Professor Seungyul Han’s research group from the Graduate School of Artificial Intelligence accepted to the International Conference on Learning Representations (ICLR 2026), held in Rio de Janeiro, Brazil, from April 23 to 27, 2026. ICLR, alongside NeurIPS and ICML, is widely regarded as one of the world’s leading artificial intelligence conferences. This year, approximately 5,300 papers—about 27% of more than 19,000 submissions—were accepted, making the selection of three papers from a single research group a notable achievement. The accepted studies address key challenges in reinforcement learning, where AI systems learn optimal actions through interaction with their environment—an approach essential for applications, such as robotics and autonomous systems operating in complex, real-world conditions. The first study proposes Self-Improving Skill Learning (SISL), a method designed to enable robust learning from noisy offline data. By decomposing long-horizon tasks into reusable skills and refining them through prioritized updates, SISL mitigates the impact of imperfect data and supports stable adaptation across complex tasks. The second study introduces Strict Subgoal Execution (SSE), which improves long-horizon planning by distinguishing feasible subgoals from unreachable ones. By leveraging past failures and partial successes, the method enhances planning efficiency and increases overall task reliability in goal-conditioned environments. The third study presents Successive Sub-value Q-learning (S2Q), a framework for multi-agent reinforcement learning (MARL) that retains multiple high-value action candidates. This approach enables agents to adapt more effectively in dynamic environments where optimal strategies shift over time, improving both coordination and overall performance. The research was led by Sanghyun Lee, Jaebak Hwang, and Yonghyeon Cho as first authors, respectively, and supported by programs funded by the Ministry of Science and ICT (MSIT) and the National Research Foundation of Korea (NRF). Professor Han said, “Our research demonstrates that reinforcement learning can be applied more reliably in environments with limited data and uncertainty, with strong potential for applications in autonomous driving, robotics, and smart manufacturing.” Journal Reference [1] Sanghyeon Lee, Sangjun Bae, Yisak Park, Seungyul Han, "Self-Improving Skill Learning for Robust Skill-based Meta-Reinforcement Learning," ICLR 2026. [2] Jaebak Hwang, Sanghyeon Lee, Jeongmo Kim, Seungyul Han, "Strict Subgoal Execution: Reliable Long-Horizon Planning in Hierarchical Reinforcement Learning," ICLR 2026. [3] Yonghyeon Jo, Sunwoo Lee, Seungyul Han, "Retaining Suboptimal Actions to Follow Shifting Optima in Multi-Agent Reinforcement Learning," ICLR 2026.

2026.04.27

New Study Unveils Region-Specific Dopamine Regulation in the Basal Ganglia

Abstract Dopamine affects voluntary movement by modulating basal ganglia function. However, the contribution of dopamine on striatopallidal synapses, an initial hub in the indirect pathway connecting the striatum to the GPe, remains poorly understood because of the sparse dopaminergic innervation. Here, we combine optogenetic projection targeting, whole cell patch clamp recordings in acute brain slices from mice, and computational modeling to overcome this limitation. We show that dopamine activates D2 receptors (D2Rs) and D4 receptors (D4Rs) differentially in distinct GPe subregions. In a pinwheel-like fashion, dorsolateral and ventromedial GPe expresses high levels of D2Rs, which exert presynaptic inhibition, while in dorsomedial and ventrolateral GPe D4Rs cause postsynaptic inhibition. Dopamine depletion by 6-OHDA reshapes the region-specific effect of dopamine, shifting it in the opposite direction and contributing to hypokinesia. These findings reveal the mechanism by which the different modality information conveyed spatially through the indirect pathway is differentially modulated by dopamine at striatopallidal synapses. Researchers at UNIST have identified a novel spatial rule, governing how dopamine modulates inhibitory signals in the brain’s basal ganglia, deepening our understanding of motor control and opening new avenues for targeted therapies in neurodegenerative diseases, such as Parkinson’s. The study, led by Professor Jae-Ick Kim of the Department of Biological Sciences, reveals that dopamine’s influence on synapses within the indirect pathway of the basal ganglia varies depending on the specific subregion. Using advanced techniques—including optogenetics, electrophysiology, and computational modeling—the team demonstrated that dopamine differentially regulates GABAergic inhibitory signals through distinct receptor types in different parts of the external globus pallidus (GPe). Specifically, dopamine reduces inhibitory GABA release via D2 receptors in the dorsolateral and ventromedial GPe regions, weakening inhibition. Conversely, in the dorsomedial and ventrolateral regions, dopamine acts through D4 receptors to suppress postsynaptic activity, also diminishing overall inhibition. This regional specificity suggests that dopamine fine-tunes motor signals in a highly localized manner. Remarkably, in a Parkinson’s model characterized by dopamine depletion, these region-specific modulation patterns are reversed, indicating that the spatial regulation of dopamine is critical for normal motor function. Such insights could inform the development of more precise interventions targeting specific brain regions and receptor subtypes. Professor Lee commented on the findings, "Understanding how dopamine differently modulates circuits based on region and receptor type provides a foundation for developing targeted therapies for movement disorders." Youngeun Lee, the lead researcher, added, "Our study highlights the importance of regional and receptor-specific modulation within the brain's motor circuits, which could lead to more effective treatment strategies." Published in Nature Communications on April 3, this research offers vital neurophysiological insights for designing treatments for movement disorders. This study has been supported by the Mid-Career Researcher Program and the Bio & Medical Technology Development Program of the National Research Foundation of Korea (NRF), funded by the Ministry of Science and ICT (MSIT). Journal Reference Youngeun Lina Lee, Maria Reva, Ki Jung Kim, et al ., “Distinct modes of dopamine modulation on striatopallidal synaptic transmission,” Nat. Commun ., (2026).

2026.04.27

Breakthrough Unveils How Alcohol Amplifies Liver Damage During Illness

Abstract Alcohol consumption has short- and long-term impacts on physical and mental health. Although multiple host and environmental factors contribute to alcohol-related disease, the innate immune sensors that detect toxic signals from alcohol remain poorly defined. Here, we show that alcohol cooperates with sterile- or infection-induced interferon signaling to drive inflammatory cell death, cytokine release, and liver injury in humans and mice. We identified the pattern recognition receptor Z-DNA binding protein 1 (ZBP1) as a key innate immune sensor mediating pyroptosis, apoptosis, and necroptosis in response to combined ethanol and interferon stimulation. While interferon elevated ZBP1, ethanol suppressed adenosine deaminase acting on RNA 1 (ADAR1) expression. Together, interferon and ethanol activated JNK signaling to promote Z-RNA formation, triggering ZBP1. These findings reveal a mechanism by which alcohol and interferon converge to induce ZBP1-dependent inflammatory cell death and liver pathology, providing mechanistic insight and highlighting potential therapeutic targets for alcohol-related disease. A research team, affiliated with UNIST has uncovered a novel molecular pathway explaining why alcohol consumption can lead to severe liver damage, particularly when individuals are already battling infections, such as cold and influenza. Led by Professor SangJoon Lee from the Department of Biological Sciences at UNIST, alongside Professors Rajendra Karki of Seoul National University and Si Ming Man of The Australian National University, the research sheds light on how alcohol interacts with the immune system to accelerate liver cell death and exacerbate liver disease. The team discovered that, in the presence of interferon—a key immune signaling molecule produced during infections—alcohol triggers an inflammatory cascade within liver cells. Specifically, alcohol increases the level of Z-RAN, an abnormal form of RNA, which is detected by the pattern recognition receptor Z-DNA binding protein 1 (ZBP1). This activation initiates inflammatory cell death, contributing to liver damage. Under normal circumstances, the protein ADAR1 suppresses Z-RNA formation, preventing unwarranted immune activation. However, the study revealed that alcohol impairs ADAR1 production, allowing Z-RNA to accumulate and activate ZBP1. This process involves the JNK signaling pathway, which was validated through animal experiments showing that inhibiting ZBP1 or blocking JNK signaling significantly reduced liver injury—even in the presence of alcohol and interferon. Professor Lee explained, "While the direct toxicity of alcohol on liver cells has long been recognized, our findings highlight an immune-mediated pathway that exacerbates liver damage during illness. This discovery opens new possibilities for targeted therapies, such as ZBP1 inhibitors, to treat alcohol-related liver diseases." The findings of this research were published in Science Advances on April 10, 2026. The study was supported by the National Research Foundation of Korea (NRF), the Korea Drug Development Find (KDDF), the Institute for Basic Science (IBS), the Circle Foundation, and Yuhan Corporation. It has also been supported through the Global Physician-Scientist Training Program and the ARPHA-H Project from the Korea Health Industry Development Institute (KHIDI) under the Ministry of Health and Welfare (MOHW). Journal Reference Yeonseo Jang, Hoeun Bae, SuHyeon Oh, et al ., “Innate immune sensing of dietary alcohol ignites inflammation to drive alcohol-related disease,” Adv. Sci ., (2026).

2026.04.24

UNIST Unveils Smart Contact Lens with Meniscus Pixel Printing for Vision-Based Robotic Control

Abstract Contact lenses are emerging as strong candidates for next-generation extended reality (XR) interfaces due to their lightweight and ergonomic form factor. However, integrating photodetector arrays onto the limited area of a lens remains challenging with conventional micropatterning approaches, which rely on masks, multistep processes, and specialized equipment that inherently limit throughput and scalability. To address these constraints, we introduce a Meniscus Pixel Printing (MPP) strategy that enables rapid, mask-free patterning of MAPbI3 perovskite photodetectors without costly or complex fabrication tools. MPP uses a self-confined meniscus at a pipette tip to deterministically transfer perovskite ink, enabling 200 µm pixels to be printed within 1 s per pixel. In addition to planar substrates, MPP demonstrates stable pixel patterning on curved surfaces, highlighting its geometric adaptability and process versatility. Using this approach, we fabricate a 10 × 10 perovskite photodetector array and demonstrate stable photoresponse, retaining 92% of its initial performance after two months of storage. To overcome limited pixel density, a deep-learning-based super-resolution (SR) model reconstructs 10 × 10 inputs into 80 × 80 optical information with 97.2% accuracy and 0.03 s latency. Additionally, an AI-based eye-tracking system recognizes nine eye gestures with 99.3% accuracy, enabling smooth hands-free robotic arm control. A research team, led by Professor Im Doo Jung from the Department of Mechanical Engineering at UNIST, has developed a groundbreaking smart contact lens that enables users to control robots through eye movements. This innovative device combines embedded optical sensors with AI-based signal processing, offering a lightweight, intuitive human-machine interface with vast potential across industries. The lens incorporates a 10×10 array of light sensors capable of detecting subtle changes in light distribution caused by eye movements, including gaze direction and blinks. These signals are transmitted to control external robotic systems, as demonstrated with a robotic arm. Notably, the team employed a novel Meniscus Pixel Printing (MPP) technique to directly print sensors onto the curved lens surface without masks or complex fabrication steps, ensuring high precision and customizability. In addition to robotic control, the system demonstrates vision sensing capabilities by reconstructing optical information. To address the limited signal resolution inherent to micro-scale devices, the researchers applied deep-learning-based super-resolution algorithms, reconstructing high-fidelity signals equivalent to an 80x80 sensor array in just 0.03 seconds. This enables real-time, accurate control based solely on eye movements, achieving recognition accuracies of up to 99.3% under experimental conditions. This technology marks a significant advancement in ultra-compact human-machine interfaces, enabling precise, hands-free control of electronic devices. Potential applications include remote robotic operation, medical assistive devices, exploration in hazardous environments, defense systems, and smart mobility. Published in the March 2026 issue of Advanced Functional Materials (Impact Factor: 19.0, JCR Top 5%)—a top-tier journal in materials science—the research was selected as the Front Cover of the latest issue. The study received support from the National Research Foundation of Korea (NRF), the Ministry of Science and ICT (MSIT), the Institute of Information & Communications Technology Planning & Evaluation (IITP), and the Ministry of Trade, Industry, and Energy (MOTIE). Journal Reference Byung-Hoon Gong, Dohyean Kim, Jiyun Jeong, et al ., “Meniscus Pixel Printing for Contact-Lens Vision Sensing and Robotic Control,” Adv. Funct. Mater. , (2026).

2026.04.23

Innovative Scalable Electrochemical Approach for Transforming Waste Glycerol into Hydrogen and High-Value Chemicals

Abstract Interest in electrochemical glycerol oxidation reactions (GORs) continues to grow as a promising strategy for hydrogen production. By replacing the oxygen evolution reaction (OER), GOR reduces energy consumption while generating hydrogen at the cathode and value-added formate at the anode, offering techno-economic advantages over conventional water electrolysis. However, its practical implementation is still hindered by reliance on precious metal catalysts and performance losses in scaled-up systems. Here, we synthesized a non-precious CuCo oxide (CCO) electrocatalyst at a tens-of-grams scale through co-precipitation and simple surface treatment. When applied to an anion exchange membrane (AEM) electrolyzer, the modified CuCo oxide achieved 110 mA cm−2 at 1.31 Vcell using a 7 cm2 non-precious GOR anode with 96% formate selectivity. The system was further scaled to a 79 cm2 anode, delivering 3.2 A at 1.31 Vcell. This study demonstrates a practical and economically favorable pathway for scalable hydrogen production via glycerol valorization in AEM electrolyzers. A joint research team, led by Professors Ji-Wook Jang, Hankwon Lim, and Hosik Lee from the School of Energy and Chemical Engineering at UNIST, in collaboration with Dr. Juchan Yang from the Energy & Environment Materials Research Division at Korea Institute of Materials Science (KIMS), has announced the development of a high-performance, scalable electrochemical system that transforms waste glycerol—an industrial byproduct of biodiesel production—into hydrogen and value-added chemicals, such as formate. This innovative system replaces the conventional oxygen evolution reaction (OER) in water electrolysis with glycerol oxidation, resulting in reduced energy consumption and enhanced efficiency. Using a copper-cobalt oxide catalyst, the system a current density of 110 mA/cm² at just 1.31 V, with 96% selectivity for formate. The technology was successfully scaled to a 79 cm² electrode, demonstrating its potential for industrial applications. This advancement provides a sustainable, cost-effective pathway for large-scale hydrogen production through glycerol valorization. By simultaneously generating hydrogen and valuable chemicals from waste biomass, the approach promises significant reductions in green hydrogen costs and improved resource efficiency. Additionally, integrating energy and chemical manufacturing processes supports global efforts toward carbon neutrality and a sustainable hydrogen economy. Moreover, its scalability and compatibility with continuous operation suggest promising prospects for industrial deployment and further scale-up to megawatt-level systems. Juchan Yang, Principal Researcher at KIMS, emphasizes, “This study demonstrates the large-scale synthesis of low-cost, non-precious catalysts and their successful integration into a practical electrolyzer system, marking a significant step toward commercial viability.” Professor Ji-Wook Jang of UNIST adds, “Transforming biomass waste like glycerol into high-value chemicals and hydrogen not only accelerates carbon neutrality but also offers strategic advantages in building a sustainable hydrogen economy.” The findings of this research were published online in Joule (IF: 35.4) on March 18, 2026. The study was supported by the National Research Council of Science & Technology (NST), the Korea Institute of Energy Technology Evaluation and Planning (KETEP), the National Research Foundation of Korea (NRF), and the Korea Institute of Industrial Technology (KEIT). Core analyzes and computational modeling were conducted using supercomputing resources provided by the Korea Institute of Science and Technology Information (KISTI), with technical support, as well as the synchrotron radiation source at the 6D beamline of the Pohang Accelerator Laboratory. Journal Reference Ki-Yong Yoon, Seon Woo Hwang, Hee Yoon Roh et al. , “Commercial-scale glycerol valorization using surface-modified copper cobalt oxide catalyst in high-capacity anion exchange membrane electrolyzer,” Joule , (2026).

2026.04.23