Central Pacific El Niño Improves North Atlantic Winter Forecasts

Abstract The wintertime North Atlantic Oscillation is a major mode of variability affecting climate across the Northern Hemisphere, yet its seasonal prediction skill over the North Atlantic remains lower than that over the Pacific. We examine North Atlantic Oscillation predictability through Pacific teleconnections using reanalysis data and multi-model hindcasts from seasonal-to-decadal forecasting systems. Here we show that Central Pacific El Niño events significantly enhance both North Atlantic Oscillation forecast skill and the predictable signal over the North Atlantic. Reanalysis and equatorial Pacific pacemaker experiments reveal that Central Pacific El Niño enhances sea surface temperature variability over the Aleutian region, modulates Atlantic storm-track activity, and strengthens the Pacific–Atlantic teleconnection. Coupled Model Intercomparison Project Phase 6 simulations suggest that more frequent Central Pacific El Niño occurrence under greenhouse warming may favor this teleconnection. These results identify Central Pacific El Niño-driven Pacific–Atlantic teleconnections as an important source of North Atlantic Oscillation predictability and seasonal forecast skill. Seasonal forecasts for the North Atlantic have long lagged behind those for the Pacific. A new study finds that forecasts of the North Atlantic Oscillation (NAO) become considerably more accurate during winters marked by Central Pacific El Niño. A team, led by Professor Myong-In Lee of the Department of Civil, Urban, Earth, and Environmental Engineering at UNIST traced the improvement to a stronger climate connection between the North Pacific and North Atlantic. The NAO is a major pattern of atmospheric variability that shapes winter weather across Europe and North America. The study involved researchers from the Korea Institute of Science and Technology (KIST) and the Met Office Hadley Center in the United Kingdom. Across several seasonal forecasting systems, the correlation between predicted and observed NAO conditions for January and February was 0.48 over the full study period. During Central Pacific El Niño winters, it rose to 0.78, showing a marked increase in forecast skill. The researchers found that Central Pacific El Niño strengthens a chain of climate interactions linking the two ocean basins. It increases sea surface temperature variability near the Aleutian region of the North Pacific, shifting the position and intensity of the storm track. The resulting changes in atmospheric circulation extend across North America to the North Atlantic, where they influence the NAO. Because ocean temperatures change more slowly than the atmosphere, these North Pacific temperature patterns can persist long enough to provide an early signal of atmospheric conditions that develop later over the North Atlantic. “The North Atlantic has strong internal atmospheric variability, which makes predictable signals difficult for climate models to capture,” said Kiwook Kim, the study's first author. “During Central Pacific El Niño, the stronger connection between the Pacific and Atlantic effectively opens a window of opportunity for more skillful NAO forecasts The findings also shed light on the signal-to-noise paradox, in which the real atmosphere proves more predictable than climate models suggest. The researchers found that models may underestimate the connection between North Pacific sea surface temperatures and North Atlantic circulation, limiting their ability to capture this predictable signa. “Where El Niño develops in the Pacific matters for how its influence reaches the North Atlantic,” said Professor Lee. “If climate models can better capture this connection, we may be able to improve seasonal outlooks for the NAO and related winter extremes, including cold spells and heavy snowfall. The study was published in Communications Earth & Environment , a sister journal to Nature Portfolio journals, on August 27, 2026. The research was supported by the Korea Meteorological Administration and by the Ministry of Science and ICT (MSIT) through the National Research Foundation of Korea (NRF). Journal Reference Kiwook Kim, Myong-In Lee, Daehyun Kang, and Adam A. Scaife, “Central Pacific El Niño-driven Pacific–Atlantic teleconnections are an important source of North Atlantic Oscillation predictability,” Commun. Earth Environment. , (2026).

2026.10.06

Beyond Ideal Conditions

《Editor's Note: Research works by controlling variables. But the problems it ultimately confronts rarely offer the same courtesy. Heat gets into storage tanks. Expertise shifts from one question to the next. Satellite images arrive out of season. Materials face conditions far beyond the laboratory norm. The obvious response is to restore control —keep the heat out, remove the variation, recreate the ideal test. But what happens when ideal conditions are no longer an option? This month, UNIST researchers took that question in different directions. Some intervene before a problem takes hold —or after a familiar line of defense has failed. Others design for rather variation than uniformity, or put promising results to more demanding tests. The approaches differ, but the underlying shift is the same —rather than trying to restore control, they rethink the solution around what actually changes. 》 CHANGE WHERE YOU INTERVENE “Sometimes the best place to solve a problem is not where it appears.” For atomically thin semiconductors, contamination during fabrication can be especially difficult to undo. Plasma exposure changes the chemistry of photoresist, causing residue to bind more strongly to MoS₂. Aggressive cleaning, meanwhile, risks damaging the material itself. Rather than trying to remove the residue afterward, UNIST researchers placed a removable, 5-nanometer metal layer over the semiconductor before patterning, preventing the contamination from reaching its surface. The resulting transistors showed roughly a tenfold reduction in contact resistance and a similar increase in on-current. Liquid hydrogen presents the problem from the opposite direction. Even well-insulated tanks cannot keep heat out indefinitely. Instead of treating insulation as the only line of defense, researchers investigated whether metal-organic frameworks could capture evaporating hydrogen after heat enters the tank and slow the buildup of pressure. In modeling, IRMOF-20 preserved about 97 percent of the volumetric capacity of liquid hydrogen while extending the projected storage period from roughly 64 to 221 days. One solution acts before the problem reaches the material: the other takes effect after a familiar line of defense has been breached. In both cases, changing where researchers intervene changes what can be done about the problem. ■ New Process Shields 2D Semiconductors from Fabrication Residue (Small) ■ Rethinking Liquid Hydrogen Storage with MOFs (Nature Communications) WORK WITH WHAT CHANGES “When the world refuses to stay consistent, the method has to change with it.” Personalization gets harder when expertise refuses to stay fixed. A person who is an expert in one subject may be a novice in another—and even within the same field, expertise can change from question to question. ExPerT responds to that variation rather than smoothing it away. By combining the semantics of each query with patterns in a user's typing behavior, the framework estimates expertise for individual questions and adjusts the detail, terminology, and complexity of its answers accordingly. In a study involving 40 participants and 1,270 queries, it reduced expertise-estimation error by 65.7 percent compared with the strongest baseline. For wildfire assessment, the changing conditions are not the user but the landscape. Satellite images taken before and after a fire may come from different seasons, allowing natural changes in vegetation to be mistaken for fire damage. Instead of requiring seasonally matched images, UNIST researchers use nearby unburned vegetation to estimate seasonal change and correct the comparison. Across 12 US wildfires, it achieved a correlation of 0.72 with field observations using seasonally mismatched imagery—nearly matching the 0.73 obtained with images from similar seasons. One method adapts to knowledge that changes from question to question—the other accounts for landscapes that change with the season. Neither requires the variation to disappear before the analysis can begin. ■ AI Personalization Adapts Answers to What Users Know (ACL '26) ■ Assessing Wildfire Burn Severity Across Seasons (Remote Sens. Environ.) TEST WHAT HOLDS UP “A promising result means more when it holds up under a more demanding test.” Perovskite solar cells (PSCs) have reached impressive efficiencies, but performance under controlled conditions tells only part of the story. UNIST researchers developed a molecular interface that delivered a certified power-conversion efficiency of 26.37 percent, then subjected the cells to repeated swings between −100°C and +100°C. After 16 cycles, they retained about 91 percent of their initial efficiency—putting their stability to a far more demanding test. AI highlight detection faces a different gap between promising results and meaningful tests. Existing benchmarks have largely relied on videos lasting only a few minutes, even though real sports broadcasts can run for hours. SVHighlights closes the gap with 320 videos across eight sports and 640.18 hours of footage. Its videos average about two hours—roughly 30 to 60 times longer than those in existing datasets—allowing AI models to be evaluated under conditions much closer to the task they are meant to perform. One study subjects a material to extreme temperature swings, while the other tests AI against the scale of the task it is meant to perform. Both ask the same question: Does a promising result still hold when the test starts to resemble the challenge it is meant to meet? ■ PSCs Hold Up Under Extreme Temperature Swings (Joule) ■ AI Sports Highlight Detection to a More Realistic Test (ACM KDD '26) Explore the latest issue and follow 『The UNIST Brief』 on LinkedIn to stay updated. Subscribe via LinkedIn

2026.10.01

Rethinking Liquid Hydrogen Storage with Metal-Organic Frameworks

Liquid hydrogen (LH₂) is attractive for long-distance energy transport because of its high volumetric energy density. But even well-insulated tanks cannot completely prevent heat from entering. As the liquid warms, hydrogen evaporates and pressure builds, leading to boil-off losses during storage and transport. A research team, led by Professor Hyunchul Oh of the Department of Chemistry at UNIST, together with Professor Hoi Ri Moon of Ewha Womans University, and researchers at the Technical University of Munich in Germany, has investigated whether porous materials could help limit these losses. The team used metal-organic frameworks (MOFs)—highly porous crystalline materials—to capture evaporating hydrogen and delay its release as heat enters the tank. MOFs contain networks of nanoscale pores that can absorb hydrogen onto their internal surfaces. At cryogenic temperatures, interactions between hydrogen molecules and the pore walls help keep the gas confined, slowing pressure buildup. The approach complements conventional insulation—instead of focusing only on limiting heat entering the tank, it also changes how hydrogen responds once heat gets in. The key question is whether that benefit comes at the expense of storage capacity. A porous material takes up space that would otherwise hold liquid hydrogen. The researchers therefore compared two MOFs with very different structures—IRMOF-20, a rigid framework with a large pore volume, and MIL-53(AI), a flexible framework whose pores expand and contract as hydrogen is adsorbed. IRMOF-20 offers a particularly favorable balance. When the researchers accounted for the space occupied by the material, the system retained about 97% of the volumetric capacity of neat liquid hydrogen. This was possible because hydrogen confined within the pores packed densely enough to compensate for much of the space taken by the MOF. The researchers then modeled how the materials would affect boil-off in a transport-scale liquid hydrogen tank. Under the mid-vacuum insulation conditions examine, neat liquid hydrogen was predicted to deplete after about 64 days. With IRMOF-20, that period increased to approximately 221 days—more than three times as long. Experiments offered clues to why IRMOF-20 performed this way. Adsorption measurements indicated that hydrogen confined within its pores reached an effective density higher than that of bulk liquid hydrogen. Inelastic neutron scattering also showed restricted molecular rotation inside the pores, providing indirect evidence of strong interactions between hydrogen and the framework. Together, the results suggest that nanoscale confinement can both pack hydrogen dedensely and stabilizze it against release as temeprature rises. MIL-53(AI) behaved differently. It retained hydrogen more strongly as temperature increased, but its volumetric capacity was only about 53% of that of liquid hydrogen. The contrast highlights a central design choice for porous materials in cryogenic hydrogen storage—larger pore volume favors capacity, while stronger confinement can improve thermal retention. “By considering pore volume, hydrogen density, and desorption behavior together, we found that poros materials could reduce boil-off while preserving much of the storage capacity needed for liquid hydrogen transport,” said Professor Oh. “These calculations represent an idealized upper bound, so further work is needed to determine how closely this performance can be reproduced in practical tank systems.” Jaewoo Park of UNIST served as first author, with contributions from Dr. Monica Jiménez-Ruiz of the Institut Laue-Langevin in France and Dr. Margarita Russina of Helmholtz-Zentrum Berlin fur Materialien und Energie in Germany, among others. The research was supported by the National Research Lab (NRL 2.0) Program, including the Institute for Multiscale Matter and Systems (IMMS), and the BrainLink program of the National Research Foundation of Korea. The findings were published in Nature Communications on September 7, 2026.

2026.09.30

New Study Puts AI Sports Highlight Detection to a More Realistic Test

Finding the defining moments in a two-hour sports broadcast is very different from analyzing a video that lasts only a few minutes. Yet most benchmarks for AI highlight detection have been built around short-form video, leaving a gap between how these systems are tested and the content they are meant to analyze. Led by Professor Taehwan Kim of the Graduate School of Artificial Intelligence at UNIST has developed SVHighlights (Sport Video Highlights) , a benchmark for highlight detection in long sports videos. It contains 320 videos across eight sports, totaling 640.18 hours, with each video averaging two hours—roughly 30 to 60 times longer than those in existing benchmarks. Building a benchmark at this scale would normally require people to watch hundreds of hours of footage and mark highlights by hand. The researchers instead used official highlight videos produced from the same broadcasts as reference points, developing an algorithm that automatically matches those scenes to their original locations in the full-length video. The algorithm compares frames at the pixel level while accounting for their order in time—an important distinction in sports broadcasts, where replays can look identical to the original play. Human involvement is largely limited to identifying game boundaries and checking the automatically generated matches. Genuine alignment errors accounted for just 0.18% of frames during manual verification. The team also developed TF-SELECTOR, a training-free framework for detecting highlights in long videos. Rather than evaluating isolated clips, it groups related shots into coherent segments and uses visual descriptions, transcripts, and audio volume to provide context for a large language model, which assigns each segment a highlight score. On SVHighlights, TF-SELECTOR surpassed the second-best baselines by 2.50 points in HIT@1, 4.04 points in HIT@K, and 2.95 points in IoU, measures of how accurately a system identifies and locates highlights. “By using official highlight videos that broadcasters have already produced, we can replace much of the labor-intensive annotation normally required to build this kind of dataset,” said Professor Kim. “Because the same approach can be used to expand the benchmark, SVHighlights could provide a more realistic basis for evaluating long-form video analysis and developing better highlight-detection methods.” Donggyu Lee and Youngbin Ki of UNIST contributed equally as first authors. Their work was presented at the 2026 ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), held August 9-13 on Jeju Island. The dataset and code are available on the team's project page (https://leedongkyu2019.github.io/SVHighlights/). The research was supported by the Ministry of Science and ICT (MSIT) through the grants of the Institute of Information & Communications Technology Planning & Evaluation (IITP), including the AI Star Fellowship and Artificial Intelligence Graduate School programs at UNIST. Journal Reference Donggyu Lee, Youngbin Ki, Jeonghun Kang, and Taehwan Kim, “SVHighlights: Towards Extremely Long Sport Video Highlight Detection,” ACM KDD , (2026).

2026.09.29

Less Than a Drop of Water Generates Electricity for Up to 45 Hours

Abstract Hydrovoltaic power generation offers a promising route for sustainable energy generation, yet existing systems typically rely on evaporation-driven flow or environmental moisture gradients, limiting device encapsulation and compact integration. Here, we introduce a confinement-induced ion-selective mechanism that enables sealed hydrovoltaic power generation from minimal water input. By engineering asymmetric nanochannel confinement in MXene/cellulose nanofiber (CNF) composites, localized hydration generates spatially distinct cation selectivity, establishing a persistent ion gradient and a confinement-dependent Donnan potential that drives capacitive charge accumulation. The harvested energy derives from substantial interfacial free energy released upon hydration of nanochannels with a high surface-to-volume ratio. Slow capillary migration then delays relaxation of the ion gradient, sustaining this charging and prolonging the resulting direct current (DC) output, without reliance on evaporation-driven flow or ambient humidity. Consequently, a single 3 µL water droplet enables stable DC output for up to 45 h. The device operates robustly under airflow (5–20 L min−1), relative humidity (17%–90%), and various electrolytes (tap water, seawater, and sweat), demonstrating humidity-insensitive, sealed operation. This confinement-governed hydrovoltaic framework expands the mechanistic understanding of water-enabled energy generation and provides a scalable platform for wearable and distributed electronics. A hydrovoltaic generator developed at UNIST can produce electricity for up to 45 hours from just 3 microliters (µL) of water, without relying on evaporation or ambient humidity. Led by Professor Hyunhyub Ko of the School of Energy and Chemical Engineering at UNIST, the research team developed a thin-film device that creates an ion imbalance within its own nanoscale channels. This allows the generator to operate while sealed, addressing a key limitation of hydrovoltaic systems that depend on evaporation or moisture in the surrounding air. Many hydrovoltaic devices rely on evaporation or environmental moisture to sustain electrical output, making their performance sensitive to humidity and airflow. The UNIST device instead generates electricity through the way water and dissolved ions move through channels built into the film itself. The film consists of stacked MXene nanosheets and cellulose nanofibers (CNFs). When water enters the film, one end swells while the other remains constrained, creating channels that gradually narrow from one side to the other. These narrowing channels interact differently with positively charged ions in the water, creating an uneven distribution of ions across the film. The resulting ion imbalance creates an electrical potential across the film. Water then moves slowly through the channels by capillary action, helping maintain the ion imbalance and sustain the electrical output for an extended period. A single device measures just 5 by 7 millimeters, with an active film only 15 micrometers thick. With a single 3 µL dose of water, it maintained voltage for more than 20 hours and continued producing an output for up to approximately 45 hours. The thin, flexible films can also be stacked to increase output. In one demonstration, the researchers connected 48 two-layer units in series to directly power a digital clock. The generator worked with tap water, seawater, and sweat, and remained stable across relative humidity levels from 17% to 90% and airflow rates from 5 to 20 L min⁻¹. “Most hydrovoltaic systems rely on evaporation or moisture in the surrounding air, but our device creates the necessary ion difference within the film itself,” said Professor Ko. “This allows it to maintain electrical output even when sealed. Its thin, flexible structure also makes it possible to stack multiple devices, which could support future applications in wearable electronics, compact sensors, and distributed devices.” The study was published online in Advanced Materials on August 12, 2026. Sangyun Na and Geonyoung Jung of UNIST contributed equally as first authors. The research was supported by the National Research Foundation of Korea (NRF), the National Research Council of Science & Technology (NST), and the InnoCORE Program of the Ministry of Science and ICT (MSIT) and Gwangju Institute of Science and Technology (GIST). Journal Reference Sangyun Na, Geonyoung Jung, Yoojin Chang, et al. , “Confinement-Induced Donnan Potential Enables Sealed Hydrovoltaic Power From Microliter Water,” Adv. Mater., (2026).

2026.09.29

Stretchable QLEDs Bring High-Resolution Displays Closer to Soft Electronics

A research team, affiliated with UNIST has developed intrinsically stretchable quantum-dot light-emitting diodes (QLEDs) that combine high brightness, fine pixel patterning, and mechanical stretchability in a single device platform. Led by Professor Moon Kee Choi of the Department of Materials Science and Engineering at UNIST, the team worked with Professor Jiwoong Yang's team at DGIST and Associate Director Dae-Hyeong Kim of the IBS Center for Nanoparticle Research to develop a fabrication strategy known as LIFT—ligand engineering at the interface and intaglio film transfer printing. The method enabled stretchable light-emitting layers to be patterned at high resolution while preserving the electrical and mechanical properties needed for high-performance devices. Stretchable displays are being explored for wearable electronics, electronic skin, and soft robotics, where conventional rigid displays cannot readily conform to moving or irregular surfaces. Many existing designs accommodate stretching by allowing the connections between pixels to deform while the light-emitting pixels themselves remain relatively rigid. As the display expands, this can reduce the proportion of the surface that actively emits light. Making the emissive material itself stretchable could overcome this limitation, but it introduces a different set of problems. Soft, elastomeric materials are difficult to pattern into sharply defined microscopic pixels, while the polymers that provide stretchability can interfere with charge transport and reduce light-emitting efficiency. The researchers addressed both problems by engineering the surface of a quantum-dot nanocomposite. They selectively replaced polymer-rich regions at the surface with short, polar ligands, creating a nanoscale interface that lowers the barrier to hole injection while preserving the mechanical compliance of the underlying material. They paired this interface engineering with a thermally assisted transfer-printing process. Applying heat during printing concentrates mechanical strain along the boundaries of each pattern, allowing the soft emissive film to separate cleanly and form sharply defined pixels rather than stretching or tearing during transfer. Using the process, the team patterned quantum-dot emissive layers at resolutions of up to 16,000 pixels per inch (PPI) and produced red, green, and blue stretchable patterns. The researchers also demonstrated a 12 × 12 multicolor passive-matrix display, showing that the technique could be extended beyond individual pixels to an addressable display architecture. The fully stretchable QLEDs remained functional at strains exceeding 65% and reached a maximum luminance of 53,300 cd m⁻², with an external quantum efficiency of 8.0%. In conventional device architectures, the engineered emissive layers achieved an external quantum efficiency of up to 23.9%. “This work provides a way to improve both the performance and resolution of intrinsically stretchable displays,” said Professor Choi. “The approach could help advance soft optoelectronic systems that require light-emitting devices to conform closely to the human body or other deformable surfaces.” Supported by programs of the Ministry of Science and ICT (MSIT) and the National Research Foundation of Korea (NRF), including the Mid-Career Researcher Program and the Nano & Materials Technology Development Program, the study was published online in Nature Nanotechnology on September 14, 2026. Journal Reference Jisu Yoo, Kyunghoon Lee, Ji Su Kim, et al ., “High-resolution intrinsically stretchable quantum-dot displays through thermally assisted intaglio transfer printing,” Nat. Nanotechnol., , (2026).

2026.09.28