Graduate School of Carbon Neutrality

AI data centers consume enormous amounts of electricity—not only to run thousands of GPUs, but also to keep them cool. A new study suggests that recovering waste heat while integrating on-site power generation and carbon capture could substantially reduce both their cost and carbon footprint. Led by Professor Hankwon Lim of the Graduate School of Carbon Neutrality at UNIST, a research team evaluated a data-center energy system combining solid oxide fuel cells (SOFCs), carbon capture, and organic Rankine cycle (ORC) cooling. Compared with a conventional grid-powered, air-cooled system, the proposed approach could reduce total system costs by approximately 48% and lifecycle greenhouse gas emissions by up to 72%. The system puts waste heat to work in two ways. High-temperature heat from the fuel cells supplies energy for the carbon-capture process, while heat removed from servers is recovered through an ORC to generate additional electricity. This reduces both the energy required for cooling and the amount of electricity the data center must draw from the grid. The researchers modeled a data center with 20,000 GPUs and compared eight combinations of power supply, cooling, and carbon capture using energy prices and electricity mixes in Korea, the United States, and the European Union. Across a broad range of cost and emissions priorities, the combination of SOFC power, carbon capture, and ORC cooling consistently ranked highest. ORC cooling performed particularly well across all three regions, reducing annual cooling-related electricity costs by as much as $19 million. Lower electricity demand also cuts annual greenhouse gas emissions by an estimated 80,000 to 150,000 metric tons, potentially avoiding $5 million to $10 million in annual carbon costs under carbon-pricing schemes such as the EU Emissions Trading System. The preferred source of electricity varied by region. Relatively inexpensive natural gas made SOFC generation economically attractive in the United States, while in Korea, where natural gas is more expensive, grid electricity remained more economical when cost was prioritized. “As AI data centers expand, electricity supply, cooling, and carbon emissions need to be considered together,” said Donghyoun Lee from the Graduate School of Carbon Neutrality at UNIST. “Our analysis shows how power generation, waste-heat recovery, and carbon capture can be evaluated as a single energy system.” “The best strategy will depend on local energy prices and the carbon intensity of electricity,” said Professor Lim. “This framework can help identify energy systems that balance cost and emissions for data centers of different sizes and in different regions.” The findings of this study have been published online in Chemical Engineering Journal on August 14, 2026. The research was supported by the National Research Foundation of Korea (NRF) and the Ministry of Science and ICT (MSIT). Journal Reference Donghyoun Lee, JeHyeon Seong, and Hankwon Lim, "An integrated solution for data center power supply, thermal management, and carbon capture evaluated through a multi-criteria decision analysis framework," Chem. Eng. J., (2026).

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).

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.

Platinum (Pt) nanoparticles can change shape while catalyzing a reaction, and the surface beneath them helps determine how that transformation unfolds. A research team, led by Professor Kwangjin An of the School of Energy and Chemical Engineering at UNIST, together with Professor Jeong Woo Han's group at Seoul National University, found that different crystal facets of titanium dioxide (TiO₂) produce distinct Pt structures before and during carbon monoxide oxidation. The resulting differences at the Pt–TiO₂ interface have a pronounced effect on catalytic activity. Pt is widely used in catalysts for applications ranging from emissions control to fuel cells. Because the metal is expensive, it is typically dispersed as nanoparticles on a support, whose surface structure can influence both particle shape and reactivity. The researchers examined Pt nanoparticles about 1.8 nanometers across on two facets of anatase TiO₂, known as (001) and (101). Despite their similar size, the particles took on markedly different shapes. On the (001) surface, Pt spread across the TiO₂ to form a relatively flat, hemispherical structure with a broad interface. On the (101) surface, it remained more compact and faceted. The difference persisted as CO oxidation began. Pt on TiO₂(001) extensive retained contact with the support as its surface restructured during the reaction. On TiO₂(101), the particles developed a more ordered, cuboctahedral shape and maintained a more limited interface with the support. The two structures also showed substantially different catalytic behavior. Under the conditions tested, the apparent activation energy for CO oxidation was 58.1 ± 0.3 kJ mol⁻¹ on the predominantly (001)-faceted catalyst, compared with 109.1 ± 1.5 kJ mol⁻¹ on its (101)-dominated counterpart. The difference became more pronounced after the first reaction cycle. Across subsequent reaction cycles, its apparent activation energy fell by 22.7% to 25.6% relative to the first run, while the (101)-based catalyst changed little. The researchers traced this behavior to the interface that developed between Pt and TiO₂ during the reaction. At that interface, oxygen from the TiO₂ lattice participates directly in converting CO to CO₂, leaving oxygen vacuums that must then be replenished. The broader interface formed on TiO₂(001) allows this oxygen cycle to proceed more readily. Calculations likewise found lower energy barriers for oxygen activation on the (001) surface throughout the reaction pathway. To follow these changes, the researchers combined electron microscopy and X-ray spectroscopy with computational modeling. The experiments captured differences in Pt structure before and after reaction, while simulations reproduced the distinct particle shapes favored by the two TiO₂ facets. Density functional theory calculations then connected those structures to differences in reaction energetics. “A catalyst may not be consumed by a reaction, but that does not mean its structure remains unchanged while it is working,” said Professor An. “Our results show that the surface supporting a metal nanoparticle can determine not only its initial structure, but also how that structure evolves during the reaction. Understanding these changes could help guide the design of catalysts that make more effective use of costly metals, such as platinum.” Jihun Kim of UNIST and Yunkyung Kim of Seoul National University contributed equally as first authors. Sinmyung Yoon, Jeong Woo Han, and Kwangjin An served as corresponding authors. The study was published in August 2026 issue of Nature Communications , with support from the Ministry of Science and ICT (MSIT) and the National Research Foundation of Korea (NRF). Journal Reference Jihun Kim, Yunkyung Kim, Daewon Oh, et al. ,“TiO2-facet-dependent reconstruction of Pt nanoparticles during CO oxidation,” Nat., Commun., (2026).

Students at UNIST brought low-carbon behaviours into their Chuseok celebrations this September, connecting sustainable travel with one of Korea's most important traditional holidays. and traditions into opportunities for everyday climate action. Held on September 22, 2026 UNIST REBOOT 2: The Chuseok Green Bridge Project brought together more than 80 Korean and international students for activities combining sustainable choices with the spirit of the holiday. The event was organized by the Graduate School of Carbon Neutrality in collaboration with the School of Energy and Chemical Engineering. The program builds on the first UNIST REBOOT campaign held in June, when more than 180 students took part in a five-day sustainability challenge and 87 completed all missions to become Net-Zero Masters. While the first campaign focused broadly on changing carbon-intensive habits, REBOOT 2 brought the concept into the Chuseok holiday period. Students were encouraged to document low-carbon choices, including the use of public transportation for holiday travel, and share their Chuseok wishes through an interactive sticker board. Participants also received holiday snack kits, while selected wish-board entries earned gifts intended for students to share with their parents. International students joined the activities alongside their Korean peers, adding a cross-cultural dimension to a program rooted in one of Korea's major holidays. “This second REBOOT project brought our two academic units together and was made possible by the enthusiastic participation of our students,” said Dong Suk Kim, Dean of the Graduate School of Carbon Neutrality. “We will continue to develop campus programs that reflect student ideas while making sustainability both meaningful and engaging.”

Abstract The adoption of autonomous smart devices necessitates new solutions for energy harvesting and storage to power them. Photo-rechargeable batteries, which integrate these functions into a single device, have gained traction as compact and cost-efficient solution for such applications. However, the implications of different system designs and material choices on photo-battery performance remain poorly understood. Here, we first compare the battery performance of solid Li-ion battery cathode materials (eg LiFePO4 and LiNi0.8Co0.1Mn0.1O2) with liquid catholytes (eg polyiodide and Cu2+/+(dmby)2) for photo-battery applications. The results indicate that the closely packed nature of solid-phase active materials allow for higher volumetric energy density and rate performance. Building on these findings, we present a device architecture for an integrated photo-rechargeable lithium metal battery incorporating a LiFePO4 cathode and a dye-sensitized PV-electrode. These compact photo-batteries can self-charge to 70% state of charge within 10 min under 1-sun illumination and also operate under indoor light. Through simultaneous photo-charging and discharging, we demonstrate that the battery output can be significantly enhanced solely by light energy, offering a clear strategy for future photo-battery design. Photo-rechargeable batteries combine light harvesting and energy storage in a single device, making them well suited to autonomous devices that cannot easily be connected to a power source or have their batteries replaced. But their performance depends on how the photovoltaic and battery components are designed to work together. A team, led by Professor Tae-Hyuk Kwon of the Department of Chemistry at UNIST and Professor Michael De Volder of the University of Cambridge has developed a modular photo-rechargeable lithium-metal battery that can be configured for different lighting conditions, including sunlight and indoor light. Rather than starting with a single battery design, the researchers first compared solid lithium-ion cathode materials with liquid catholytes to determine how each affects photo-battery performance. Solid cathodes, including lithium iron phosphate (LFP), delivered higher volumetric energy density and better rate performance, an advantage the researchers attribute to the more closely packed nature of solid active materials. Based on these findings, the team built an integrated photo-battery combining an LFP cathode, a lithium-metal anode, and a dye-sensitized photovoltaic electrode. The modular design allows the photovoltaic units to be arranged to provide the voltage required to charge the battery, while the battery component itself remains unchanged. Under 1-sun illumination, the device reached 70% state of charge within 10 minutes and delivered a discharge energy density of 327.8 mWh g⁻¹. A configuration designed for lower-light conditions also charged and discharged using 1,000-lux indoor light, roughly the illumination level of a well-lit office. The team also tested what happens when the battery receives light while supplying power. Under simultaneous photo-charging and discharging, the device delivered greater output than it did in the dark, showing that incoming light can contribute additional energy during use. The modular structure makes it possible to adjust the charging voltage by changing how the photovoltaic units are connected. In the system demonstrated in the study, the researchers combined the battery unit with four additional photovoltaic units, allowing configurations of one, three, or five units. All five were used when the higher voltage required by the lithium-metal battery was needed. “By changing the number and type of photovoltaic units, we can match the charging voltage required by different battery materials,” said Dr. Byungman Kim of the Department of Chemistry at UNIST, first author of the study. “This modular approach could provide a useful design strategy for photo-rechargeable batteries using a wider range of battery chemistries.” Professor Kwon added, “The ability to charge under both outdoor and indoor light could make photo-rechargeable batteries useful for IoT devices where wired power or frequent battery replacement is impractical.” The findings were published in the August 2026 issue of Energy Storage Materials . The research was supported by Korea Electric Power Corporation (KEPCO) and UK Research and Innovation (UKRI). Journal Reference Byung-Man Kim, Arvind Pujari, Sungtae Kim, et al. , “Design strategy for integrated photo-rechargeable batteries with high energy density,” Energy Storage Mater., (2026).

Abstract Change detection-based approaches that use satellite-derived spectral indices (SIs) and their pre- to post-fire differences (dSIs) to quantify burn severity have emerged as powerful alternatives to traditional field-based methods such as the Composite Burn Index (CBI). However, most studies have focused on improving model performance using ideal datasets—those with clearly defined burn areas and cloud-free pre- and post-fire imagery—while overlooking a key limitation: the requirement for phenological consistency between pre- and post-fire imagery. To address this gap, this study presents an Advanced burn Severity Analysis framework using Phenology-detrended indices (ASAP), which produces a refined burn severity index dataset that is robust to seasonal and phenological variability. The ASAP integrates automated delineation of analysis areas based on active fire detections, preparation of pre- and post-fire SI images suitable for vegetation analysis, and a phenology-detrending strategy to align seasonal vegetation conditions between image pairs. The key innovation of the framework is a novel phenology-detrended dSI (pdSI), which uses surrounding unburned areas to seasonally adjust the pre-fire baseline prior to calculating the pre- to post-fire difference, thereby enhancing wildfire-induced signals. Validation using CBI plots and Monitoring Trends in Burn Severity perimeters demonstrates that pdSI consistently matches or outperforms conventional dSIs. These improvements are especially pronounced when pre- and post-fire images are phenologically inconsistent, when phenology-sensitive indices such as differenced normalized difference vegetation index are applied, and in vegetation or climate types with strong seasonal variability, such as deciduous forests and herbaceous areas in temperate climates. Time-series analyzes further show that pdSI mitigates seasonal variability effects, delivering more stable and robust performance compared to conventional dSIs. The proposed framework was also successfully applied to recent large-scale wildfires in the Los Angeles area in 2025, demonstrating its strong applicability and reliability in operational contexts within the wildland–urban interface. Overall, this study provides a simple yet powerful solution to a long-standing challenge in change detection-based burn severity analysis. Satellite imagery is widely used to assess wildfire burn severity, but seasonal changes in vegetation can distort comparisons between pre- and post-fire images. A research team, led by Professor Jungho Im of the Department of Civil, Urban, Earth, and Environmental Engineering at UNIST has developed a framework that corrects for these seasonal differences, allowing a wider range of satellite imagery to be used for post-fire assessment. The framework, called ASAP (Advanced burn Severity Analysis with Phenology-detrended indices), uses nearby unburned vegetation to estimate how seasonal conditions have changed between the pre- and post-fire images. It then adjusts the pre-fire baseline before measuring the change caused by the wildfire. This matters because the spectral indices used to assess vegetation respond to both fire damage and normal seasonal change. If a summer image is compared directly with one taken in autumn, for example, leaf loss or declining vegetation activity may appear as part of the burn signal. ASAP uses comparable unburned areas to account for that background change rather than requiring the two images to be closely matched by season. The resulting phenology-detrended index (pdSI) consistently matched or outperformed conventional difference indices in comparisons with field-based burn-severity measurements. The gains were most apparent when pre- and post-fire images reflected differed seasonal conditions, particularly in vegetation with strong seasonal cycles, such as deciduous forests and herbaceous areas. Across 12 US wildfires, ASAP maintained a correlation of 0.72 with field observations using seasonally mismatched imagery, nearly identical to the 0.73 achieved with imagery from similar seasonal conditions. The framework also automates key parts of the analysis, using active-fire detections to define the area to be assessed and screening imagery for clouds and areas unsuitable for vegetation analysis. This reduces the manual preparation needed before burn severity can be mapped. When applied to five wildfires in the Los Angeles area in January 2025, ASAP reduced the misclassification of unburned areas caused by seasonal vegetation differences and more clearly identified the extent of fire-affected areas. “Conventional satellite-based assessments often depend on finding pre- and post-fire images taken under similar seasonal conditions,” said Professor Im. “By accounting for seasonal vegetation change, we can broaden the range of usable imagery and move toward more consistent, automated burn-severity assessment.” The approach could support faster assessment after large wildfires and provide more timely information for recovery planning and satellite-based disaster monitoring. Taejun Sung and Seyoung Yang served as co-first authors of the study. The research was supported by the Korea Forest Service and the Ministry of Education. The findings were published in the September issue of Remote Sensing of Environment. Journal Reference Taejun Sung, Seyoung Yang, Woohyeok Kim, et al. , “Enhancing satellite-based wildfire monitoring: An advanced framework for burn severity analysis with phenology-detrended indices,” Remote Sens. Environ., (2026).

Summary The advent of self-assembled monolayer (SAM)-based hole-selective layers (HSLs) has revolutionized inverted perovskite solar cells (i-PSCs) by enabling record efficiencies, but they are constrained by incomplete surface coverage and interfacial heterogeneity. We devise topology-governed SAMs featuring isomeric linker patterns (LY-ortho [o], LY-meta [m], and LY-para [p]) and uncover the principle that conformational ordering dictates surface coverage and interfacial interaction coupling with perovskite. The topology-optimized LY-m forms a homogeneously dense, stable HSL with superior energy alignment and interfacial passivation. Devices incorporating LY-m achieve a record-high open-circuit voltage of 1.231 V, accompanied by an efficiency of 26.39% (certified 26.37%), while maintaining robust operational stability and scalability. Beyond laboratory metrics, LY-m-based devices withstand −100°C to 100°C thermal cycling with only ∼9% loss, far exceeding the operational limits of state-of-the-art commercial SAMs, while maintaining over 80% of their initial performance at 85°C (T80 ≅ 2,000 h). This work resolves the long-standing role of linker topology and paves the way for extreme-environment-resilient and scalable perovskite photovoltaics. Temperature swings are a major challenge for perovskite solar cells (PSCs), particularly in environments such as space, where materials may repeatedly move between extreme cold and heat. Led by Professors Changduk Yang and Seungjae Shin of the Department of Energy and Chemical Engineering and Professor Myung Hoon Song of the Department of Materials Science and Engineering at UNIST, the team developed perovskite solar cells that withstand such extremes by stabilizing a critical molecular interface. The cells retained about 91% of their initial efficiency after cycling between −100°C and +100°C, with a certified power-conversion efficiency of 26.37%. The key to this advancement is a self-assembled monolayer (SAM), a molecule-thin layer that helps move electrical charges between the electrode and the perovskite absorber. Under severe thermal stress, SAM molecules can shift or cluster, disrupting the interface and degrading performance. The team addressed this problem by changing where the molecular components of the SAM connect. They synthesized three versions with different linker positions and found that LY-m adopted a tilted orientation, allowing its molecules to pack densely and uniformly on the electrode. This arrangement also suppresses the molecular reorganization that can occur under large temperature swings. In thermal-cycling tests, LY-m cells were held alternately at −100°C and +100°C for 30 minutes at each temperature over 16 cycles. They remained operational with only about a 9% loss in efficiency, while cells using a commercial SAM failed under the same conditions. LY-m cells also reached a peak efficiency of 26.39%, with a certified efficiency of 26.37% and an open-circuit voltage of 1.231 V. At 85°C, they maintained more than 80% of their initial performance for approximately 2,000 hours. The approach also performed well at larger scales: a 1 cm² cell achieved 23.25% efficiency, while a 3 × 1 cm² mini-module reached 21.20%. “By changing only the position of the molecular connection, we were able to control how the molecules pack on the electrode,” said Professor Yang. “The resulting interface combines high efficiency with thermal stability, offering a promising route toward perovskite photovoltaics for environments with extreme temperature variations.” The study has been participated by Seunglok Lee and Jeewon Park of the Department of Energy and Chemical Engineering and Jingyu Yang of the Department of Materials Science and Engineering at UNIST, as co-first authors of the study. Published in Joule on August 3, the study has been supported by the Nano & Material Technology Development Program through the National Research Foundation (NRF) of Korea and the InnoCORE program of the Ministry of Science and ICT (MSIT). Journal Reference Seunglok Lee, Jinkyu Yang, Jeewon Park, et al., "Topology-governed self-assembled monolayers enable perovskite solar cells stable at −100°C to +100°C," Joule , (2026).

Abstract Organic photoelectrochemical (PEC) cells for solar water splitting typically utilize bulk heterojunction (BHJ) structures to circumvent the intrinsically short exciton diffusion lengths of organic semiconductors. However, stochastic donor/acceptor networks in BHJs often result in disordered interfacial contacts, leading to severe charge recombination. Herein, we report a pseudo-bilayer (PS-Bi) organic photoanode featuring a vertically ordered donor–acceptor configuration established via sequential deposition. Our systematic investigation reveals that this PS-Bi structure promotes selective charge transport and suppresses recombination due to its high domain purity, thereby facilitating efficient charge transfer at the interface. Consequently, the optimized PS-Bi photoanodes deliver an enhanced average photocurrent density (Jph) of 1.75 ± 0.03 mA cm−2 at 1.23 V versus the reversible hydrogen electrode for solar water oxidation, while simultaneously exhibiting a significant cathodic onset shift and extended operational stability compared to their BHJ counterparts (Jph = 1.44 ± 0.07 mA cm−2). This study demonstrates that employing the PS-Bi structure is a promising strategy for achieving high-performance and stable organic PEC systems for sustainable solar fuel production. Producing hydrogen from sunlight depends in part on how efficiently a photoelectrode can separate and move electrical charges. In organic photoelectrodes, however, the conventional practice of mixing semiconductor materials can create disordered pathways that allow those charges to recombine, reducing both performance and stability. A research team, led by Professors Han Hee Cho, Moon Kee Choi, and Myung Hoon Song of the Department of Materials Science and Engineering at UNIST, working with researchers at École Polytechnique Fédérale de Lausanne (EPFL), has developed an organic photoanode with a more ordered internal structure. The new design improved photocurrent by about 22% while extending operational stability. The team created what is known as a pseudo-bilayer (PS-Bi) structure by depositing two organic semiconductor materials in sequence. As the second layer is applied, it partially penetrates the first, forming a mixed region at the interface while preserving more distinct layers above and below. Conventional organic photoelectrodes typically use a bulk heterojunction (BHJ), in which donor and acceptor materials are mixed throughout the film. This arrangement helps generate and separate charges, but its irregular internal pathways can also bring electrons and holes back together before they contribute to the chemical reaction. The PS-Bi combines the advantages of both approaches. Charges are generated and separated in the mixed region, while the more ordered layers guide electrons and holes in different directions. This reduces recombination and allows more of the generated charge to drive water oxidation. In tests, the PS-Bi photoanodes achieved an average photocurrent density of 1.75 mA cm⁻², compared with 1.44 mA cm⁻² for conventional BHJ photoanodes, an increase of about 22%. The voltage required to initiate water oxidation also fell from 0.35 V to 0.15 V, allowing the reaction to begin with less external electrical input. The structural change also improved durability. Based on the time required for photocurrent density to fall to 0.5 mA cm⁻², the pseudo-bilayer photoanodes remained operational substantially longer than their BHJ counterparts. The researchers also found that the two structures degrade differently. In BHJ photoanodes, highly reactive holes can damage the organic semiconductor within the intermixed structure. The more ordered pseudo-bilayer reduces damage within the donor–acceptor region, helping the photoanode maintain its performance for longer. “Conventional organic photoelectrodes mix donor and acceptor materials throughout the film, which can lead to charge losses and faster degradation,” said Professor Cho. “By controlling how the two materials are arranged, we were able to improve both charge transport and operational stability.” He further added, “The lower operating voltage could also help in the development of systems that ultimately produce hydrogen using sunlight without an external electrical bias.” The study was published online in Chemical Engineering Journal on July 16, 2026. The research was supported by the National Research Foundation of Korea (NRF), funded by the Ministry of Science and ICT (MSIT), and the InnoCORE program. Journal Reference Gyu Won Chae, Seong Rae Kang, Jin Su Park, et al. , “A pseudo-bilayer organic photoanode for solar water oxidation,” Chem. Eng. J., (2026).

《Editor's Note: What does it take to make something work better? The answer may be to pare back what is unnecessary, rethink how existing parts are arranged, find another route around a constraint, or widen the frame of the problem itself. This month's UNIST research offers answers in many forms—from leaner AI systems and redesigned material structures to an unexpected route for electron transfer and a broader view of cancer drug resistance. Some of those answers run counter to what we might expect. 》 Less Can Be Enough “How much does AI really need?” AI has spent years scaling up. But recent UNIST research asks a different question—how much can be taken away while keeping what matters? At ACL 2026, researchers introduced GMoE, an architecture that shares experts across layers rather than repeatedly storing similar ones. It cut model parameters by about 63 percent, from 549 million to 204 million, while average accuracy remained virtually unchanged—39.51 percent, compared with 39.55 percent for the baseline. The next target was data. Presented at ICML 2026, CSOR removes redundant training images while preserving meaningful variation within each identity. Using roughly half the original dataset, models retained more than 95 percent of full-data performance in re-identification (ReID) tasks. A third study moved to hardware. An automated design framework for logic-in-memory (LiM) computing optimized the placement and routing of computing elements, cutting computation cycles by 19.6 percent under area constraints. ■ GMoE—Expert Sharing for Smaller AI Models (ACL 2026) ■ CSOR—Less Training Data for ReID AI (ICML 2026 ) ■ LiM—Smarter Chip Design (IEEE TCAD) Arrangement Matters “In materials, where can matter as much as what.” More iron, less corrosion. Iron (Fe) is one of magnesium's most damaging impurities, yet UNIST researchers produced a Mg alloy containing more than six times as much Fe as ultra-high-purity Mg—and it still corroded more slowly. Instead of removing the impurity, the team added scandium (Sc) to form core–shell particles that isolate Fe-rich regions from the surrounding Mg. The corrosion rate fell from 22.2 to 0.38 millimeters per year, nearly a 60-fold reduction. At the molecular scale, thermal annealing changed the packing of an organic semiconductor, more than tripling its absorption dissymmetry and even reversing its preferred handedness of circularly polarized light (CPL). The resulting near-infrared (NIR) photodetector achieved a dissymmetry factor of 0.1 at 850 nanometers. The scale shifts again in perovskite solar cells (PSCs). The same high-efficiency formulation crystallized differently depending on the buried interface beneath it. Tailoring the chloride chemistry to the inverted architecture produced a device with 26.3 percent efficiency and a fill factor (FF) of up to 86.8 percent. ■ Mg Alloy—Shielding Fe to Slow Corrosion (Science Advances) ■ NIR Photodetector—Turning Molecular Packing (Advanced Science) ■ PSCs—Why Architecture Changes Performance (Joule) Another Way Through “How spin opens a new route for electron transfer.” Conventional energetics suggested that electron transfer should be unfavorable. Yet in manganese (Mn)-doped quantum dots (QDs), spin-exchange interactions enabled transfer more than ten times faster than in undoped QDs. The mechanism could help capture energetic hot electrons before their excess energy dissipates—a longstanding challenge in photocatalysis and solar-energy conversion. ■ Hot Electrons—Spin-Enabled Transfer (Nature Communications) Beyond the Tumor “The cells helping cancer resist treatment.” Some of the cells helping breast cancer resist treatment are not part of the tumor at all. UNIST researchers found that nearby fat cells can become cancer-associated adipocytes, which release complement factor D and activate survival signaling in cancer cells. In mouse models, disrupting this TRAP1-driven communication improved the response to chemotherapy, pointing to surrounding adipocytes as potential therapeutic targets alongside the tumor itself. ■ Breast Cancer—How Nearby Fat Cells Drive Drug Resistance (STTT) Explore the latest issue and follow 『The UNIST Brief』 on LinkedIn to stay updated. Subscribe via LinkedIn