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Weak Hydrogen Bonds Dethrone Copper's Stability, Opening a New Path for Ion Selection
Copper has been knocked off the top of a stability ranking it had dominated for decades. Without altering the atoms directly bonded to the metal, a KAIST research team reversed the longstanding trend in which copper generally forms the most stable complexes by tuning only the weak hydrogen bonds in its surrounding environment. The findings could open new avenues for selective metal separation and recognition, as well as catalyst design.
KAIST (President Choongsik Bae) announced on September 6 that a research team led by Professor Yunjung Baek of the Department of Chemistry developed a "metal complex"—a structure in which several molecules surround and bond to a central metal— using a ligand based on the flavin framework found in vitamin B2. By tuning the hydrogen bonding around the metal, the team achieved a stability trend that runs opposite to the widely accepted Irving–Williams series.
The Irving–Williams series is an empirical rule that ranks how stably transition metals—such as iron, nickel, and copper, which bond with other substances in a variety of ways—bind to surrounding molecules. Among manganese (Mn), iron (Fe), cobalt (Co), nickel (Ni), copper (Cu), and zinc (Zn), stability is generally known to increase moving from manganese toward copper, with copper forming particularly stable bonds.
This difference has been understood to arise from each metal's electronic structure, meaning how its electrons are arranged. In other words, which metal forms the more stable complex has long been considered largely determined by the metal's own inherent properties.
Until now, changing this order typically required either designing a new ligand, the molecule that directly grips the metal, or altering the coordination structure, the way the metal bonds with surrounding molecules.
The research team instead focused on hydrogen bonding, a force that acts outside the direct metal bonding region. Hydrogen bonds are relatively weak forces between molecules that help hold the surrounding structure in a fixed shape.
Using flavin derivatives, versions of flavin with part of their chemical structure modified, the team incorporated different metals ranging from manganese to zinc, while ensuring that all the metals shared the same basic coordination geometry. By keeping the basic conditions around each metal identical, the researchers were able to examine what difference hydrogen bonding alone made to each metal's stability.
The results showed that hydrogen bonding specifically blocks the structural change copper needs to become stable. Copper has a distinctive tendency to slightly reshape its surrounding bonding structure into a form that favors its own stability, much like a person shifting slightly to find the most comfortable posture.
In the structure developed by the team, however, the surrounding hydrogen-bonded framework constrained the geometry around copper, preventing it from adopting its preferred distorted structure. As a result, copper lost much of the additional stabilization it would normally gain through structural distortion, producing what the researchers describe as an anti–Irving–Williams trend.
What matters most is not simply that copper was displaced from the top of the ranking, but that the study demonstrated the relative stability of metal complexes, long regarded as being largely determined by the intrinsic properties of each metal, can be adjusted by changing the surrounding environment. For example, if a desired metal can be made to bond more strongly while others bond more weakly within a mixture, the principle could provide a basis for developing systems that selectively extract or recover target metals.
This principle could also be applied to catalyst design, where the surrounding environment is tuned so that a desired metal performs more effectively. Just as proteins and enzymes in the human body select the metal they need from among iron, copper, zinc, and others, the approach is also expected to offer a new method for designing biomimetic systems that replicate the operating principles of living organisms to achieve a desired function.
Professor Yunjung Baek said, "The key point of this study is not simply that we lowered copper's stability, but that we showed the order of bonding stability, long regarded as an inherent property of each metal, can be changed through the surrounding environment." She added that the approach is expected to be used to design new chemical systems that selectively capture or react with a desired metal.
The research also drew attention at the International Conference on Coordination Chemistry (ICCC), held in Denmark. Haneul Im, a combined master's and PhD student in KAIST's Department of Chemistry and the study's first author, presented the work as a poster and was the only Korean student to receive a Best Poster Award. The study, with Haneul Im as first author, was published in the Journal of the American Chemical Society (JACS) on September 3. JACS published by the American Chemical Society (ACS).
Paper title: When Copper Falls: Overriding the Irving–Williams Stability Trend through Outer-Sphere Hydrogen Bonding,
DOI: 10.1021/jacs.6c10430
Author information: Haneul Im (KAIST, first author), Neetu Singh (KAIST, joint second author), Seogyeon Kwon (IBS, joint second author), Changhyeon Seo (KAIST, third author), Nak-Kwan Chung (KRISS, fourth author), and Yunjung Baek (KAIST, corresponding author). Six authors in total.
This work was supported by the Young Scientist Grants program of the Ministry of Science and ICT (MSIT).
2026.09.07 View 448 -
KAIST Develops Smartphone-Based Technology to Detect Hidden Cameras
A smartphone can now be transformed into a “hidden-camera detector.” KAIST researchers have developed an AI technology that can detect hidden cameras using only a smartphone and a low-cost LED device. This new security technology enables users to protect their privacy more easily and is expected to help prevent illegal filming in everyday spaces such as hotels and short-term rentals.
KAIST (President Choongsik Bae) announced on August 30 that a research team led by Professor Jun Han of the School of Computing, in collaboration with the National University of Singapore and Singapore Management University, has developed “SweepLED,” a technology that detects hidden cameras by attaching an LED case to a smartphone.
As hidden cameras are increasingly being installed in everyday spaces such as hotels, short-term rentals, and restrooms, the need is growing for detection technology that everyday users can easily use. However, existing portable detectors require users to visually identify bright reflective spots, which can lead to false positives by mistaking reflections from metal, glass, or glossy plastic surfaces for camera lenses.
SweepLED works by keeping the smartphone camera fixed while changing only the direction of the LED illumination, then analyzing the patterns of reflected light that appear on object surfaces. Reflections from ordinary glossy objects tend to move or disappear depending on the direction of the light. In contrast, camera lenses show distinctive deformation patterns in their reflections due to their internal lens, aperture, and sensor structures.
The research team uses deep learning-based analysis to distinguish these differences in temporal reflection patterns. While conventional detection methods rely on the user’s eyes to simply look for “bright spots,” SweepLED is different in that it analyzes both the movement and shape changes of reflections across multiple lighting angles.
This enables more reliable detection of hidden camera lenses inside various everyday objects commonly found in lodging spaces, such as chargers, clocks, remote controls, and everyday objects.
The research team evaluated SweepLED on 30 objects that may be found in real-world environments and found that it achieved approximately 94% detection accuracy. It also took less than five seconds to inspect a single object.
In addition, the core components of the LED case attached to the smartphone cost less than USD 7, or about KRW 10,000, demonstrating the potential for this technology to be developed into an affordable detection tool that general users can easily access.
Professor Jun Han said, “Hidden cameras pose a serious threat to personal safety and privacy in everyday spaces,” adding, “This research is meaningful in that it combines low-cost smartphone-based hardware with AI analysis to present the possibility of a practical detection technology that even non-experts can use.”
This paper, with KAIST doctoral student Jonghyuk Yun as first author, was presented on June 20 at ACM MobiSys 2026, one of the leading international conferences in the field of mobile computing.
Paper title: Hide-and-Sweep: Detecting Concealed Cameras via LED Illumination Sweeps
https://doi.org/10.1145/3812835.3814866
Author information: Jonghyuk Yun (first author), Jaeyoung Moon, Yunseo Park, Sean Rui Xiang Tan, Byunghyun Kim, Rajesh Krishna Balan, and Professor Jun Han (corresponding author)
This research was supported by the STEAM Global Convergence Research Support Program and the Mid-Career Researcher Program of the Ministry of Science and ICT and the National Research Foundation of Korea.
2026.08.31 View 6048 -
KAIST Shapes a " Templates a ‘Gas Lattice’ in Porous Materials”: The Moment Gas Forms a Crystal-like Lattice
Capturing carbon or storing hydrogen to combat global warming requires compressing gases into sponge-like porous materials. Until now, gas molecules were thought to adsorb in a disordered manner throughout the pores. But what if invisible gas molecules could be lined up in regular order — like ice crystals or LEGO bricks?
KAIST (President Choongsik Bae) announced on August 11 that a research team led by Professor Jihan Kim of the Department of Chemical and Biomolecular Engineering has developed a computational framework that combines large-scale screening of metal–organic frameworks (MOFs)* with machine-learning-guided inverse design. Focusing on the “gas lattice”—a crystal-like ordered state formed by gas molecules under confinement—the framework enables researchers to explore a vast range of MOF structures and design candidate porous materials capable of stabilizing desired gas arrangements.
*Metal–organic framework (MOF): a material built from metal ions or clusters connected by organic linkers to create countless microscopic pores; MOFs are promising eco-friendly materials used to store or separate gases.
Using xenon (Xe), a monatomic noble gas, as a model system, the research team identified a specific cobalt-based porous material — Co-CAU-36 — that stabilizes xenon in a regular lattice. Computer simulations (GCMC) confirmed that xenon inside this material does not spread out randomly, but instead lines up in a body-centered cubic (BCC) lattice, a well-defined, crystal-like arrangement. This is a breakthrough because gas crystallization was achieved within the pores without the extreme bulk pressures normally required by using the pore structure as a ‘template’.
Striking results also emerged when the team examined the separation of xenon (Xe) and krypton (Kr), a gas mixture of industrial importance. Inside the framework, xenon preferentially occupies an ordered shell region, displacing krypton toward the pore core — a separation behavior that had not been reported before.
To show that the phenomenon could be deliberately designed rather than occurring incidentally, the researchers combined machine learning with a genetic algorithm and used inverse design to identify candidate porous structures targeting BCC- and FCC-like lattices.
The findings may have applications in advanced energy and environmental technologies that depend on precise control of molecular arrangement, including carbon capture and separation, selective catalytic reactions, and gas storage.
"This research is the first demonstration of a gas forming a crystal-like ordered state inside a porous material," said Professor Jihan Kim. He added that the work's significance lies in moving beyond conventional approaches focused primarily on increasing adsorption capacity, toward treating the arrangement of gas molecules itself as a design target.
"If this approach can be extended to more complex molecules, such as carbon dioxide or water, it could become an important starting point for designing tailored materials for gas separation and storage," Professor Kim added.
Younghun Kim and Dohoon Kim, PhD candidates in KAIST's Department of Chemical and Biomolecular Engineering, are co-first authors, with Seungwoo Kim, a master's candidate, and Yunsung Lim, a PhD, serving as co-authors. The findings were published online on June 23 in the international academic journal Nature Communications.
Paper title: Framework-templated gas lattices in metal-organic frameworks
DOI: 10.1038/s41467-026-74776-5This work was supported by grants from the National Research Foundation of Korea (NRF), funded by the Ministry of Science and ICT (Project Numbers RS-2024-00451160 and RS-2024-00435493).
2026.08.11 View 953 -
KAIST Held Inauguration Ceremony for 18th President Choongsik Bae, Unveiling Vision of "Fundamentals First, Innovation Forward"
KAIST announced that it held an inauguration ceremony for its 18th president, Choongsik Bae, at the KAIST Auditorium on Monday, August 10. At the ceremony, the university unveiled "Fundamentals First, Innovation Forward" as its new vision.
The ceremony officially presented President Bae's philosophy on university governance and his vision for KAIST's future to the KAIST community and the public. Departing from the conventional format of a formal inaugural address, President Bae personally explained his vision and the strategies for implementing it. Professor Yiyun Kang of the Department of Industrial Design directed the stage production, bringing KAIST's future vision to life through an intuitive and immersive presentation.
The event built on the innovation advanced under KAIST's 17th president, Kwang Hyung Lee, while introducing new leadership and development strategies that will guide the university toward its 60th anniversary. Distinguished guests from Korea and abroad attended, including Deputy Prime Minister and Minister of Science and ICT Kyung Hoon Bae, former KAIST President Kwang Hyung Lee, and ambassadors to Korea from key countries.
In his inaugural address, President Bae presented "Continuity & Innovation" as the central philosophy of his administration. He aimed to preserve the values KAIST has cultivated over the past 55 years -- Creativity, Challenge, and Caring -- while pursuing innovation across education, research, entrepreneurship, and administration in response to AI-driven transformation and intensifying global competition for technological leadership.
The new vision, "Fundamentals First, Innovation Forward," rests on two foundational principles: people strongly grounded in fundamental disciplines, humanistic insight, and AI capabilities; and an organization characterized by autonomy, accountability, and efficiency. On these foundations, KAIST aims to achieve world-class excellence in education, research, entrepreneurship, and internationalization.
To realize this vision, KAIST will pursue the following five development strategies, collectively called the Beyond Series:
Beyond AI – AI for Everyone: Create a leading environment for education and research that moves beyond today's AI toward Humanistic AI, Democratic AI, and Agentic AI.
Beyond Laboratory – Innovative Research and Entrepreneurship: Move beyond the laboratory to advance deep-tech innovation in partnership with industry and society and build a global startup ecosystem.
Beyond Barriers – An Efficient and Open University: Remove barriers so that members can devote themselves to research and education, underpinned by transparent governance and a culture and systems built on trust.
Beyond Carbon – Sustainability and a Greener Future: Strengthen research to address the climate crisis and create an environmentally responsible, carbon-neutral campus grounded in ESG and the UN Sustainable Development Goals.
Beyond KAIST – Toward the World and the Future through Global Connect: Connect global talent, universities, research institutions, companies, and local communities; foster a more international campus; expand international joint research; and strengthen global and regional partnerships.
KAIST plans to make AI not merely a technology for specific disciplines or specialists, but a common language and general-purpose tool across all fields. By strengthening foundational education and interdisciplinary AI education, KAIST aims to push beyond merely using AI effectively toward leading AI innovation.
KAIST will also expand research in physical AI, AI that operates in the real world, including robotics, autonomous driving, and advanced manufacturing, as well as in strategic technologies such as quantum science, climate technology, and energy technology. Building on world-class basic research, KAIST will expand industry collaboration, technology commercialization, and global entrepreneurship, creating a cycle in which research outcomes drive innovation in industry and society.
KAIST will expand the establishment of corporate satellite laboratories and collaborative research centers. It will also support joint research and development with companies by building AI Autonomous Labs that integrate AI into the R&D process, creating a new research environment in which AI designs and conducts experiments and analyzes the results. The university will introduce specialized entrepreneurship education for newly admitted students and establish a model that combines classroom instruction with hands-on training, involving alumni entrepreneurs and industry professionals.
The inauguration also featured case studies of KAIST alumni using AI to drive innovation in industry and research. Dr. Hyeon-Sook Yoon from Korea Shipbuilding & Offshore Engineering (KSOE) presented the use of digital twins in the shipbuilding and maritime industries, while Dr. Ji-Yong Shin from Samsung Electronics' Semiconductor R&D Center discussed the use of AI in semiconductor manufacturing. Professor Joonsik Hwang of KAIST then discussed the development and applications of physical AI in automobiles, mobility, robotics, and other fields.
KAIST plans to build an AI Native Campus that organically connects AI Interactive Education in education, AI Autonomous Labs in research, AI Agent Administration in administration, and AI Energy Convergence in infrastructure.
KAIST will also build an AI-based digital administration system to streamline or eliminate unnecessary regulations and procedures so that faculty and students can focus more fully on education and research. The campus will also become a living lab where climate and energy technologies are developed and validated, while global cooperation will be strengthened by recruiting outstanding international students and faculty, expanding international joint research, and broadening dual-degree programs.
In his address, President Bae said, “We will carry forward the proud tradition we have inherited: our vision of becoming a Global Value-Creative Leading University and our C-Cube core values of Creativity, Challenge, and Caring. Building on this foundation, we will pursue the innovation needed to move toward our new goal, Fundamentals First, Innovation Forward.” He added, “Grounded in strong fundamentals across both our people and our institution, we will advance five strategic priorities—AI, global entrepreneurship, a stronger focus on education and research, sustainable growth, and internationalization—and further establish KAIST as a world-leading university.”
He also emphasized, “I will listen with an open mind and act with determination. As both a facilitator and a servant leader, I will empower every member of the KAIST community to pursue their aspirations with confidence and fulfillment. Together, we will take KAIST beyond innovation—establishing it as a university that sets new standards and a national innovation platform shaping the future of science and technology in Korea.”
President Bae is an internationally recognized mechanical engineer and energy scientist specializing in carbon-neutral transportation power systems and sustainable mobility technologies. He earned his bachelor’s and master’s degrees in aerospace engineering from Seoul National University and a Ph.D. in mechanical engineering from Imperial College London. Since joining KAIST in 1998, he has served in leadership roles including Chair of the Department of Mechanical Engineering, Dean of the College of Engineering, and Director of the Mobile Clinic Module Project during the COVID-19 pandemic, gaining broad experience in education, research, and university administration.
He has also contributed to energy and carbon-neutrality research and to national science and technology policy as chair of the International Energy Agency's Technology Collaboration Programme on Sustainable Combustion, chair of the Climate Division of the Ministry of Foreign Affairs' Science and Technology Diplomacy Advisory Committee, and chair of the Society of Carbon-Neutral Fuel Technology. He was the first Korean researcher in the powertrain field to be elected an SAE Fellow and has received honors including a Presidential Commendation and a Merit Award from the National Assembly of the Republic of Korea.
KAIST presented the inauguration as a ceremony marking the start of a new presidency and as a forum for sharing the university's future vision and implementation strategies. The occasion marked KAIST's move beyond "a KAIST that embraces challenges" toward "a KAIST that sets the next standard for innovation," as it pursues its goal of becoming a world-leading university for innovation.
2026.08.10 View 1891 -
Twelve Years Later, KAIST’s Undergraduate Research Program Continues to Shape World-Class Talent
KAIST’s undergraduate research programs have helped launch the careers of professors at world-leading universities and experts in global industry in just over a decade. Three students featured as undergraduate researchers in 2014 have since built distinguished careers: two are now professors at leading universities in the United States, while the third works as an open innovation expert at a global pharmaceutical company. Their career paths demonstrate the lasting impact of KAIST’s Undergraduate Research Participation Program (URP) on talent development.
KAIST (President Choongsik Bae) announced on Aug 9 that its Undergraduate Research Participation Program (URP), which enables undergraduate students to formulate their own research questions and experience the entire research process in faculty laboratories, has become a cornerstone of the Institute’s efforts to develop world-class researchers and science and technology professionals.
URP is one of KAIST’s flagship research education programs. It allows undergraduate students to conduct actual research projects in faculty laboratories and directly experience the entire research process, from developing research ideas to conducting experiments, analyzing data, and writing papers. Operated with support from the Ministry of Science and ICT, the program has conducted a total of 679 research projects over the past five years. Through these projects, students have generated a wide range of research outcomes, including publications in international academic journals, patent applications, and awards at international conferences.
“KAIST has steadily expanded research-centered education so that undergraduate students can formulate their own questions and create new knowledge in a world-class research environment,” said President Choongsik Bae. “We will continue to provide strong support through URP and other research programs enabling students to take on challenges without fear of failure and grow into science and technology leaders who drive innovation at universities and in industry around the world.”
A notable example can be found in the laboratory of Professor YongKeun Park in the Department of Physics. In 2014, KAIST highlighted the achievements of undergraduate researchers in Professor Park’s laboratory in an article titled “Professor YongKeun Park Produces Undergraduate Students with International Achievements.” The three students featured at the time have since grown into world-class researchers and professionals, each pursuing a different career in academia or industry.
Sangyeon Cho began working in a laboratory during his first year at KAIST and completed more than 30 credits of research courses by the time he graduated. One of the two first-author papers he published as an undergraduate, his review article on optical imaging techniques for malaria was featured on the cover of Trends in Biotechnology in 2012. He later earned his Ph.D. through the Harvard-MIT Health Sciences and Technology program and served as an assistant professor at Harvard Medical School before joining Rice University as an assistant professor in July 2026. He currently studies technologies that use the world’s smallest nanolasers to track individual cancer cells and therapeutic cells over extended periods.
YoungJu Jo began conducting research combining microscopy and artificial intelligence as an undergraduate, building an interdisciplinary foundation early in his career. His research at the time on virtual staining and diagnosis was published in journals including Nature Cell Biology and Science Advances. He later conducted neuroscience research at Stanford University and published a first-author paper that was featured on the cover of Cell in 2022. In July 2026, Jo joined UC Berkeley as an assistant professor, where he is developing next-generation brain-computer interface (BCI) technologies capable of delivering complex information to the brain.
Seoeun Lee carried the research mindset she developed as an undergraduate into a career in industry. After earning her Ph.D. from Columbia University and working at Boston Consulting Group, she joined global pharmaceutical company Eli Lilly. She currently leads External Innovation activities in the company’s neuroscience division, identifying and pursuing collaborations with promising biotechnology companies through mergers and acquisitions, licensing, partnerships, and other arrangements. Her career demonstrates that undergraduate research experience can lead not only to traditional research careers but also to roles in strategy and collaboration within science- and technology-based industries.
Although the three alumni ultimately pursued careers in different settings—universities and industry—their journeys began in much the same way. During their first or second year as undergraduates, they independently sought out opportunities in laboratories and experienced research that began with questions they were personally curious about rather than merely executing assigned experiments. As an undergraduate, Sangyeon Cho conceived an idea for a super-resolution microscope after seeing a streetlight turn on while walking back to his dormitory late at night. Together with Professor Park, he developed this initial curiosity into a scientific question and ultimately into a research paper.
This undergraduate research culture continues at KAIST today. In 2023, research on GOBI, a methodology for estimating causal relationships in time-series data, involving undergraduate Seho Park as first author, was published in Nature Communications.
In 2024, undergraduate Taesik Youn, serving as first author, conducted the world’s first total synthesis of the natural product securinine G, which has potential applications in cancer treatment and drug development. In 2025, two studies involving undergraduate Minjae Kim were published. His co-first-authored research on a wearable carbon dioxide sensor for real-time breath monitoring appeared in Device, a Cell Press journal, while his lead-author study on OLED displays was published in Nature Communications. Undergraduate Jaehong Cho received both the Best Paper Award and the Distinguished Artifact Award at an IEEE international conference based on his URP research. Through URP, undergraduate-led, world-class research achievements continue to emerge across diverse fields, including drug development, wearable devices, displays, and artificial intelligence. These students are not only publishing in internationally recognized journals and receiving awards at international conferences but also developing advanced research capabilities early in their academic careers.
“These students did not become outstanding researchers through mentorship alone,” said Professor YongKeun Park. “I am grateful that KAIST has created an environment in which faculty members can conduct research alongside such exceptional students. A professor’s role, I believe, is to help students further develop the tremendous potential they already possess.”
“Research is about discovering something new, which means that undergraduate and graduate students begin from the same starting point,” he added. “What ultimately shapes a researcher is the depth of their engagement, their persistence in the face of setbacks, and their ability to formulate questions independently and seek out answers.”Questions first explored in undergraduate laboratories 12 years ago are now driving new research and innovation at universities and companies around the world. KAIST will continue to expand research opportunities through URP so that students can pursue their own questions and create new knowledge.
2026.08.10 View 1281 -
KAIST Develops ‘Chameleon AI Semiconductor’ with Programmable Response Speeds
AI semiconductors are becoming more programmable. KAIST researchers have developed a device whose response characteristics can be programmed to process data changing at different speeds. The technology reduced prediction errors for time-varying data by up to 40-fold and is expected to enhance real-time AI performance in autonomous vehicles, robots, and wearable devices.
KAIST (President Choongsik Bae) announced on August 7 that a research team led by Chair Professor Shinhyun Choi from the School of Electrical Engineering and the Graduate School of Semiconductor Technology has developed a programmable dynamic memtransistor (PDM), a semiconductor device whose time-response characteristics can be adjusted to multiple states and retained, as well as an integrated array based on the device.
A memtransistor is a next-generation semiconductor device that combines the information-storage function of memory with the computing function of a transistor. In the developed PDM, the ability to process data while retaining previous information allows its response characteristics to be adjusted and retained for incoming data.
Today’s computers and smartphones require complex software processing to analyze data that changes over time, resulting in large computational loads and high power consumption. To address this, researchers have been studying technologies that allow semiconductor hardware itself to process data directly. However, conventional devices have had fixed response speeds that cannot be changed once the device is fabricated.
The research team overcame this limitation by introducing a dual-layer structure inside the transistor, combining a charge storage layer that accumulates and processes data with an electron trapping layer that controls the response speed in a nonvolatile manner.
In the PDM developed by the research team, incoming data is processed in the charge storage layer, while the electron trapping layer controls, across multiple levels, the recovery speed at which the semiconductor returns to its original state. In experiments, the team succeeded in tuning the current recovery time over an approximately 5-fold range and the characteristic frequency over a range of more than 10-fold.
In particular, in experiments involving the prediction of data in which fast and slow changes are intricately mixed, the PDM reduced prediction errors by as much as 40 times compared with conventional fixed-response semiconductor devices. The PDM enables accurate information processing even when handwriting or object-movement speeds vary, by using response characteristics configured to match different input timescales. Once the response characteristics are set, the device remembers them without requiring a continuous external power supply, and it does not require complex preprocessing of input data. Because it is fully compatible with materials used in widely adopted commercial semiconductor processes, it is also highly advantageous for mass production and commercialization.
The research team fabricated a PDM array and used it to predict complex data, confirming that it achieved accuracy comparable to conventional software-based systems while consuming far less energy.
“This study demonstrates an AI semiconductor whose response characteristics can be programmed to efficiently process data changing at different speeds,” said Chair Professor Choi. “We expect it to become a core technology that improves the performance of AI devices such as autonomous vehicles, robots, and wearables while reducing their power consumption.”
This research was led by KAIST Graduate School of Semiconductor Technology Ph.D. candidate Dae-won Kim as the first author, with Yoonho Cho, Seokho Seo, Yujin Kim, See-On Park, Taehwan Jang, and Chaebin Park participating as co-authors. Young Taek Oh and Fellow Jae-Duk Lee of Samsung Electronics’ Semiconductor R&D Center also participated as co-authors, and Chair Professor Shinhyun Choi served as the corresponding author. The research was published in July in the internationally renowned journal Nature Communications on July 4.
Paper title: Programmable memtransistor array with temporal dynamics modulation for efficient time-series data processing,
DOI: https://doi.org/10.1038/s41467-026-75211-5
This research was supported by the National R&D Program through the National Research Foundation of Korea funded by the Ministry of Science and ICT, the ETRI R&D Support Program of the Institute of Information & Communications Technology Planning & Evaluation, the HRD Program for Industrial Innovation of the Korea Institute for Advancement of Technology funded by the Ministry of Trade, Industry and Energy, Samsung Electronics, and others.
2026.08.07 View 1952 -
KAIST and Seoul National University Students Hold 100-Hour Robot Hackathon to Nurture Physical AI Talent
KAIST (President Choongsik Bae) announced on August 4 that RoboticUS, a joint student organization formed by students from KAIST and Seoul National University, is holding the inaugural Robot Hackathon at KAIST from August 3 to 8.
"In the era of Physical AI, we need convergence talent who can go beyond building good AI to design and implement robots and systems that move the real world based on AI," said Choongsik Bae, President of KAIST. "This hackathon, planned and run entirely by students, is a good example of KAIST's culture of challenge and collaboration, and we expect it to become a new educational model for turning future technologies into reality," he added.
The hackathon puts this educational philosophy directly into students' hands. It is Korea's first student-led Physical AI robot hackathon, planned and run by students from KAIST and Seoul National University across institutional boundaries. Participants experience the entire process of designing and building working robots, developing hands-on capabilities that integrate AI and hardware.
The event is hosted by RoboticUS, a nonprofit student organization formed jointly by MR, a robotics club in KAIST's Department of Mechanical Engineering, and Seoul National University's robotics clubs SHAPE and SIGMA. Students who share a passion for robotics from the two universities joined forces across institutional lines, handling every stage themselves — from recruiting participants to designing the mission, running the event, and setting up the presentation and judging format. KAIST's Department of Mechanical Engineering supports the event with facilities and operational assistance so that the students' initiative can translate into genuine educational value.
Ten teams — 30 students total — selected from the two universities will take part. After receiving training in power circuits and robot joint control on August 3 and 4, participants will begin building their robots when the mission is unveiled on the morning of August 5 and continue working until 4 p.m. on August 8. Starting from an idea, they will go through design, assembly, programming, and repeated testing to complete a working robot — experiencing the full roughly 100-hour cycle themselves.
Each team will be provided with Angel Robotics' "phact" actuator, which serves as the robot's joints and muscles, and NVIDIA's Jetson AGX, which functions as the robot's brain. Taejin Technology Co., Ltd will provide training on circuits and electronic components for supplying stable power to the robots, and Angel Robotics will support hands-on training in using the actuators and controlling the robots.
Participants will not simply assemble a finished kit — they will design the robot's shape and movement from the ground up and build it themselves.
For fairness, the mission will be revealed only at the start of the hackathon on August 5. There is no single correct answer or predetermined robot form. Each team will interpret the same mission differently, combining mechanical structure, circuitry, AI, and control software into a single robot. One of the highlights will be seeing the different solutions the ten teams develop in response to the same mission.
The final day, August 8, will be an open Physical AI festival that welcomes the general public. A public conference at the KI Building (E4) Fusion Hall will introduce the current state of Physical AI in an accessible and engaging way — from robotic skin that lets robots feel touch like humans, to humanoid robots that can see and hear people, to a quadrupedal robot that has completed a marathon.
Professors Jung Kim, Yong-Hwa Park, and Jemin Hwangbo of the Department of Mechanical Engineering, along with Joon-Ha Kim, CEO of Diden Robotics, will each give a talk on robotic skin and haptics, multimodal perception in humanoid robots, the quadrupedal robot Raibo, and the journey of developing Physical AI for industrial use, respectively.
After the conference, an open demo day for the ten participating teams will run from 4 to 5 p.m. at KAIST's Culture Complex (E9), 3rd floor. Members of the public will be able to visit each team's booth, watch the robots the students built over 100 hours in action, and submit their own evaluations via QR code.
Judging criteria include mission achievement, technical execution, creativity, and presentation and demonstration. The final score will weight faculty advisor evaluation at 30%, peer evaluation among hackathon participants at 30%, sponsor judging panel evaluation at 30%, and pre-registered public attendee evaluation at 10%.
Angel Robotics and Taejin Technology are taking part as core technology partners, providing equipment and training. Faculty members and industry experts are providing education and technical guidance so that students can safely handle equipment used in real research and industrial settings.
"Physical AI's competitiveness comes not just from software but from hardware and control technology," said Kyoungchul Kong, Professor from Mechanical Engineering at KAIST and Head of the Future Technology Institute at Angel Robotics. "This hackathon will show that with high-performance robot components and the right development environment in place, even undergraduates can turn their imagination into a working robot in 100 hours," he added.
"This hackathon is about learning and building together, rather than competing between schools," said Yeonsu An, President of RoboticUS (and President of MR, KAIST's robotics club). "We hope the general public will get to experience the robots students have built firsthand and take part in the judging, coming away with the sense that Physical AI is a technology anyone can understand and enjoy — not just something for experts," she added.
“Although we do not yet know what the challenge will be, I am most looking forward to gathering in one place and developing robots together,” said Hyeontae Jeon, a participating student from Seoul National University. “It will be even more meaningful to work through challenges across university boundaries and present the robots we built ourselves to the public.”
The public conference is open to anyone through pre-registration. Pre-registered attendees can watch the lectures, view the open demo day, and take part in on-site judging. Registration is available on the RoboticUS official website or on Event-us, under "First Robot Hackathon – Robot & AI Public Conference (KAIST × SNU)." Registration closes August 6.
2026.08.04 View 1831 -
KAIST Develops AI That Avoids Hallucinating Even at Night or in Smoke
Multimodal large language models (MLLMs), which process multiple types of sensory information such as text, images, and audio at the same time, are rapidly expanding the range of applications for artificial intelligence (AI). However, in real-world environments, these models can misinterpret the physical characteristics of sensors, mistakenly identify objects, or claim to hear sounds that are not actually present simply because a certain object appears in a video. These errors are known as hallucinations. A KAIST research team has developed a new technology that corrects such information confusion and physical misperceptions in AI.
KAIST (President Choongsik Bae) announced on the 31st of July that a research team led by Professor Yong Man Ro from the School of Electrical Engineering has developed two core technologies that overcome the tendency of existing large language models to rely too heavily on ordinary camera (RGB) images and enable AI to suppress cross-modal hallucinations that occur when different sensory inputs become mixed.
The first technology developed by the research team is the Diverse Negative Attributes (DNA) optimization method, which helps AI accurately understand the physical characteristics of special camera sensors such as thermal, depth, and X-ray sensors. Existing AI models often failed to understand the physical meaning of such images, for example by mistaking bright areas in thermal images for simple light reflection.
The research team built VS-TDX, the first comprehensive benchmark for evaluating diverse vision sensors, and used the types of wrong answers that AI frequently produces as learning signals to help the model internalize the characteristics of each sensor. As a result, the AI gained a “new eye” that allows it to accurately infer the state of objects even in darkness or smoke.
The second technology is Modality-Adaptive Decoding (MAD), a control method that blocks hallucinations caused by confusion between visual and auditory information at the source. This technology prevents AI from mistakenly claiming that it hears a sound that does not actually exist simply because a certain object appears in a video.
MAD works by having the AI self-assess whether vision or audio is more important for a given task, and then increasing the weight of the more relevant modality in real time. A key advantage of this technology is that it can immediately suppress hallucination errors without costly model retraining, as it is training-free.
Instead of retraining AI models at large scale with massive computing resources, the research team maximized cost efficiency by introducing the DNA method, which enables fine adjustment with only a small amount of data, and the
MAD plug-in approach, which requires no additional training at all.
These technologies can be applied to autonomous vehicles operating at night or in bad weather, robots performing missions in smoke-filled environments, and unmanned aerial vehicles using thermal cameras. They are also expected to be useful in fields that process multiple types of sensor information together, such as airport X-ray security screening and medical image analysis.
Professor Yong Man Ro said, “This research is significant because it reduces AI’s sensory bias and misperceptions without large-scale retraining,” adding, “It will serve as a foundation for building multimodal AI that can be trusted in real-life and industrial settings.”
This achievement was notable for its continuity, with Sangyun Chung, a doctoral student in KAIST’s School of Electrical Engineering, participating as first author in both studies. Dr. Youngjun Yoo also participated as co-first author in the DNA study.
Among the related papers, the MAD study was presented in June at the Conference on Computer Vision and Pattern Recognition (CVPR), the world’s leading international conference in AI and computer vision. The DNA study was published in IEEE Transactions on Image Processing, a leading international journal in the field of image processing.
Paper title: Enhanced Vision-Language Models for Diverse Sensor Understanding: Cost-Efficient Optimization and Benchmarking,
DOI: 10.48550/arXiv.2412.20750 Author information: Sangyun Chung (KAIST, co-first author), Youngjun Yoo (KAIST, co-first author), Se Yeon Kim (KAIST, third author), Youngchae Chee (KAIST, fourth author), Yong Man Ro (KAIST, corresponding author)
Paper title: MAD: Modality-Adaptive Decoding for Mitigating Cross-Modal Hallucinations in Multimodal Large Language Models,
DOI: 10.48550/arXiv.2601.21181
Author information: Sangyun Chung (KAIST, first author), Se Yeon Kim (KAIST, second author), Youngchae Chee (KAIST, third author), Yong Man Ro (KAIST, corresponding author)
Related demo video: https://youtu.be/VuP9i6Vfk8o
This research was supported by the Institute of Information & Communications Technology Planning & Evaluation’s (IITP’s) Human-Centered AI Core Technology Development Program and by a Center for Applied Research in Artificial Intelligence (CARAI) grant funded by the Defense Acquisition Program Administration (DAPA) and the Agency for Defense Development (ADD).
2026.08.03 View 1350 -
KAIST Develops Ultra-Precise Inspection Technology to Prevent Electric Vehicle Battery Fires
An ultra-precise inspection technology that could help prevent electric vehicle battery fires and improve battery safety has been developed. A KAIST research team has developed a method capable of detecting minute variations in battery electrode thickness that can contribute to thermal runaway with a precision equivalent to approximately one ten-thousandth the diameter of a human hair, all without disassembling or damaging the battery. The technology is expected to improve battery safety and quality by identifying invisible defects during the manufacturing process.
KAIST (President Choongsik Bae) announced on 23rd of July that a research team led by Professor Young-Jin Kim from the Department of Mechanical Engineering has developed a technology that measures the thickness of lithium-ion battery electrodes in a non-contact and non-destructive manner.
The technology combines terahertz waves (electromagnetic waves in the spectral region between light and radio waves) to obtain information from inside battery electrodes with an optical frequency comb, which divides the frequency of light into evenly spaced intervals like the markings on a ruler and serves as a reference for ultra-precise measurements.
The electrodes in lithium-ion batteries, which are widely used in electric vehicles, are essential components through which electric current flows. Even a slight variation in electrode thickness can cause current to become concentrated in certain areas when charging and discharging, generating heat. If the heat continues to accumulate, it may lead to thermal runaway, a phenomenon in which the internal temperature of a battery rises rapidly and can result in a fire or explosion. Maintaining uniform electrode thickness is therefore critically important during battery manufacturing.
Existing inspection technologies, however, have limitations when applied to production environments. X-ray computed tomography can provide detailed images of internal structures, but its relatively long inspection time makes it difficult to use on high-speed production lines. Ultrasonic acoustic microscopy requires direct contact with a liquid medium, while laser displacement sensors can perform rapid measurements but have difficulty precisely analyzing structures inside an electrode.
The research team overcame these limitations by combining optical frequency comb and terahertz technologies. The researchers first directed terahertz waves at a battery electrode and collected signals generated as the waves were repeatedly reflected within the electrode. They then used an optical frequency comb as a reference to analyze the signals with exceptionally high precision and calculate the electrode thickness. This enabled nanometer-scale measurements of the electrode’s internal structure without damaging the battery.
At the core of the technology is Fabry–Pérot interference, a regularly spaced interference pattern produced as terahertz waves repeatedly travel back and forth between the front and rear surfaces of an electrode. Much like measuring length by reading the markings on a ruler, the researchers precisely analyzed the interference pattern using the optical frequency comb as a reference to determine the electrode thickness.
As a result, the team successfully measured both the electrode thickness and its complex refractive index (a material’s optical property indicating how strongly it transmits and absorbs electromagnetic waves) in a single measurement without requiring a separate calibration process.
The researchers validated the technology using battery electrodes measuring between 50 and 150 micrometers in thickness, comparable to the diameter of a human hair. With a measurement time of just 0.2 seconds, the system detected thickness differences as small as 70.1 nanometers in the anode (approximately one fourteen-hundredth the diameter of a human hair) and 465.5 nanometers in the cathode. This measurement speed is considered sufficient for use on rapidly moving battery production lines.
When the measurement time was increased to 25.6 seconds, the precision improved further. The system distinguished differences as small as 7.8 nanometers in the anode (approximately one ten-thousandth the diameter of a human hair) and 25.2 nanometers in the cathode. This represents up to a 100-fold improvement in precision compared with conventional time-domain analysis methods, enabling the detection of thickness variations that are completely invisible to the naked eye.
The technology is not limited to measuring thickness at a single point. It can generate a three-dimensional map of thickness across an entire electrode and track gradual thickness variations in real time during production. The researchers also confirmed that the system could accurately measure an electrode tilted at an angle of approximately 45 degrees, demonstrating its potential for application to fast-moving, real-world battery manufacturing lines.
The study is significant because it presents a new inspection technology capable of identifying invisible microscopic defects during production without disassembling or damaging batteries. In addition to lithium-ion batteries, the technology is expected to serve as a key quality-control tool for manufacturing next-generation all-solid-state batteries, which use solid electrolytes instead of liquid electrolytes. By detecting defects at an early stage, the technology could improve battery safety and quality while enabling more stable manufacturing processes.
“This technology is an integrated metrology platform that can simultaneously measure electrode thickness and material properties without requiring a separate calibration process,” said Professor Kim. “We expect it to become a key technology for the real-time quality control of production lines for next-generation lithium-ion batteries and all-solid-state batteries.”
The study was led by Dr. Guseon Kang from the KAIST Department of Mechanical Engineering, currently with the Korea Institute of Industrial Technology, as the first author, with Professor Young-Jin Kim serving as the corresponding author. The research findings were published in the international journal Nature Communications on June 10.
Paper title: Nanometre-precision terahertz interferometry for battery electrode metrology
DOI: https://doi.org/10.1038/s41467-026-74193-8
This work was financially supported by the National Research Foundation of Korea (NRF) (RS-2024-00401786, RS-2025-00523273, RS-2025-25455397, RS-2026-25540567, and NRF-2022M1A3C2069728) and from the Korean government’s Defense Acquisition Program Administration (DAPA) (KRIT-CT-22-040).
2026.07.23 View 1856 -
KAIST Develops a Molecular Platform for the Selective Control of Oxygen Reaction Pathways
Controlling how oxygen reacts is important for improving technologies such as batteries, fuel cells, and environmentally sustainable chemical processes. A KAIST research team has developed a new molecular system that can selectively switch the pathway through which electrons are transferred during oxygen activation. The findings are expected to provide a fundamental design principle for next-generation catalysts and energy-conversion technologies.
KAIST (President Choongsik Bae) announced on the 22nd of July that a research team led by Professor Seung Jun Hwang from the Department of Chemistry has developed a molecular system capable of directing oxygen activation along a selected electron-transfer pathway. By combining germanium with a molecular framework that can store and transfer electrons, the team established a design principle for selectively switching oxygen activation between two- and four-electron pathways.
Catalysts for controlling oxygen reactions have traditionally been developed around transition-metal centers such as iron, cobalt, and nickel. Germanium, by contrast, is a main-group element in the same group of the periodic table as silicon and has generally been considered less suitable for reactions requiring the coordinated transfer of several electrons.
To overcome this limitation, the research team combined germanium with a redox-active ligand, a molecular framework capable of storing, accepting, and transferring electrons. The ligand serves as an electron reservoir and cooperates with the germanium center, allowing the entire molecular structure to participate in multielectron reactions.
When oxygen reacts, the products and reaction outcomes depend on whether two or four electrons are transferred. In general, two-electron oxygen reduction produces hydrogen peroxide, while four-electron reduction produces water. Selectively controlling these pathways is therefore an important challenge in the development of batteries, fuel cells, and greener chemical catalysts.
The study presents a rare example of a main-group molecular system in which two- and four-electron reactivity can be selectively accessed within the same underlying molecular framework. This approach broadens the range of elements that may be considered in catalyst design and provides an alternative strategy to relying exclusively on transition metals.
The team also succeeded in isolating and analyzing a germanium compound representing the two-electron stage of the reaction, which they stabilized by attaching a methyl group to the germanium complex. Remarkably, the germanium atom in this compound could both donate and accept electrons, providing an important clue to how the system controls different reaction pathways.
The team also confirmed the practical potential of the new system. Under mild, light-free conditions, the germanium complex removed halogen atoms such as bromine and chlorine from organic compounds and regenerated alkenes (organic compounds containing a carbon-carbon double bond), which are widely used as raw materials for pharmaceuticals, plastics, and other chemical products. These results suggest that useful chemical feedstocks could be produced through simpler and potentially more energy-efficient processes.
“We expect these findings to inform the development of next-generation catalysts for energy conversion and to contribute to more selective and efficient chemical processes.” said Professor Hwang.
The study was conducted by Sung Gyu Kim and Jinrok Oh, currently postdoctoral researchers in the KAIST Department of Chemistry, and Dae Eui Choi, a student in the combined master’s and doctoral program in the Department of Chemistry at POSTECH. The results were published online in the international journal Chem on July 6.
Paper title: Germanium Ligand Redox Cooperativity: A Key to Ambiphilicity and Switchable Two- and Four-Electron Transfer
DOI: 10.1016/j.chempr.2026.103127
This work was supported by National Research Foundation of Korea grants funded by the Korean government through the Ministry of Science and ICT (NRF-2021R1C1C1010220 and RS-2025-02216980), and by the Samsung Science and Technology Foundation under Project No. SSTF-BA2101-09. Sung Gyu Kim received research fellowship support from the Basic Science Research Program through the National Research Foundation of Korea, funded by the Ministry of Education (RS-2024-00415390).
2026.07.22 View 1510 -
KAIST’s Solarstill Box Wins Red Dot’s Highest Honor for Producing Clean Water Using Only Sunlight
A KAIST design that produces clean drinking water using only sunlight, without electricity or fuel, has won one of the world’s most prestigious design awards. The design received high international recognition not only for its technical completeness, but also for its sustainable approach, which enables residents in regions affected by water scarcity and water pollution to produce and manage clean water on their own.
KAIST (President Choongsik Bae) announced on the 17th of July that “Solarstill Box,” a solar-powered water purification and desalination device developed by a research team led by Professor Sangmin Bae from the Department of Industrial Design, has won the “Red Dot: Best of the Best” award in the Social Impact category at the Red Dot Award: Design Concept 2026, a globally renowned design competition.
The Red Dot Design Award is considered one of the world’s three major design awards, along with Germany’s iF Design Award and the United States’ IDEA (International Design Excellence Awards). Among them, the “Best of the Best” is the highest distinction, awarded to works that demonstrate the greatest innovation and completeness in each category.
This award is significant because it goes beyond recognition of product design excellence. It represents international acknowledgment that design can help address the shared human challenge of clean water access and create sustainable social value.
Solarstill Box is a low-cost water purification and desalination device that converts seawater or water containing salt and pollutants into drinking water through solar distillation. It was developed for coastal areas, saline regions, and off-grid communities that rely on contaminated water sources. The device is designed to produce clean water using only solar energy, without electricity, fuel, or separate filters.
The stepped trays inside the device increase the surface area for evaporation, improving the efficiency of solar distillation. As evaporated water vapor condenses on the transparent cover, contaminants such as salt, heavy metals, and bacteria are naturally separated, allowing only clean water to be collected.
Solarstill Box is also made of flat components based on Plaveneer sheets, allowing it to be produced and transported in a flat-pack format. Anyone can assemble it locally in about 20 minutes, and maintenance costs are reduced because only damaged parts need to be replaced. Another key feature is that it moves beyond the one-time delivery of relief supplies and instead creates a sustainable drinking water system that local residents can install and manage themselves.
Solarstill Box was developed as part of the “SEED Project,” a social contribution design research project by ID+IM Design Lab, led by Professor Sangmin Bae of the Department of Industrial Design, in collaboration with World Vision. Following this award, the research team plans to work with World Vision to pursue product commercialization and establish local distribution models. In the long term, the team aims to expand the project into a cooperative-based operating model in which local residents directly participate in manufacturing, distribution, and maintenance, thereby supporting both clean water access and sustainable community development.
The project aimed to improve access to clean drinking water in low-resource regions where water scarcity and pollution make it difficult to secure safe water. The design development was carried out by Professor Sangmin Bae, doctoral student Jungwoo Kim, master’s student Minsu Kim, and undergraduate student Seunghee Han.
Professor Sangmin Bae said, “Design should go beyond creating beautiful products; it should serve as a tool for solving social problems and changing people’s lives,” adding, “We hope Solarstill Box will provide practical help to communities in need of clean water and spread as a sustainable drinking water system that residents can operate on their own.”
Solarstill Box will be introduced to a global audience through the official award ceremony and exhibition of the Red Dot Award: Design Concept 2026, which will be held in October.
2026.07.20 View 1221 -
KAIST Study Finds Politically Salient Immigration Issues Can Lead to Higher Industrial Pollution
When immigration or refugee issues become heated political topics, nearby factories may end up releasing more toxic substances. Although the two phenomena may appear unrelated, a KAIST-led international research team has found that they are in fact connected through the government’s limited administrative and fiscal resources.
KAIST (President Choongsik Bae) announced on the 10th of July that a joint research team led by Professor Narae Lee from The School of Business and Technology Management at KAIST, in collaboration with Professor Heli Wang from Singapore Management University (SMU), analyzed immigration-related legislation and environmental data across the United States and found that when immigration becomes a central political agenda, government environmental oversight weakens and firms’ toxic chemical releases increase. The research team describes this phenomenon as “institutional crowding.”
Government administrative capacity and budgets are not unlimited. When a new political issue emerges, government attention and resources become concentrated in that area. In the process, enforcement in relatively less visible policy areas, such as environmental oversight, may weaken. Although the research team analyzed immigration as a case study, they explain that this phenomenon is not limited to a specific issue. Rather, it represents a general mechanism that can arise when political agendas compete for limited government resources.
The research team combined data from the U.S. Environmental Protection Agency’s Toxics Release Inventory (TRI) with immigration-related legislative data from U.S. states. By analyzing a total of 82,377 observations collected from 14,390 manufacturing facilities across the United States between 2010 and 2018, the team found that each additional immigration-related bill was associated with an average increase of about 1% in toxic chemical releases per manufacturing facility. This is equivalent to approximately 25 kilograms, or 56 pounds, of additional toxic emissions per facility.
The researchers found that this increase was not caused by a relaxation of environmental regulatory standards. Rather, it occurred because firms reduced costly efforts to cut pollution and treat toxic waste as government environmental oversight became relatively less effective.
This pattern was especially pronounced in states facing fiscal constraints. In states with high debt or heavy fiscal burdens, environmental oversight weakened further when political attention shifted to new issues.This suggests that when government budgets are tight, resources are more likely to be allocated first to politically urgent issues, while environmental monitoring may be pushed down the priority list.
Professor Narae Lee said, “This study does not argue that immigration causes environmental pollution. Rather, it shows that shifts in the political agenda item can weaken environmental oversight and thereby increase corporate pollution,” adding, “Even when limited government resources are concentrated on a particular issue, environmental oversight needs to be institutionally protected so that it remains stable.”
The study is significant in that it empirically identifies how competition among political agendas can affect firms’ environmental pollution management. It also offers new implications for public policy and for advancing environmental justice, so that the burden of environmental pollution does not fall disproportionately on socially vulnerable groups.
The research was published online on May 29 in the Journal of Management, a leading international journal in the field of management, with Professor Narae Lee as the first author.
An earlier version of the paper received the POSCO Corporate Citizenship Research Award, the Robert J. Litschert Award from the Academy of Management, and the Best Paper with Practical Implications Award from the Strategic Management Society, recognizing the excellence and practical significance of the research.
※ Paper title: There’s More Than Meets the Eye: Assessing the Impact of Immigrants on Firm Environmental Performance, DOI: https://doi.org/10.1177/01492063261442451
2026.07.10 View 1439