Department of Electrical Engineering

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

This fall, recognition for the UNIST community spans creative practice, international leadership, cybersecurity, data science, and semiconductor engineering. The honors bring together faculty and students at different stages of their careers, highlighting work that is gaining attention across fields. Ayoung Kim | TIME100 AI 2026 Invited Professor Ayoung Kim has been named to TIME100 AI 2026 in the Thinkers category for her work exploring the relationship between artificial intelligence and human experience. Through multimedia works including Delivery Dancer , Kim examines how algorithms shape movement, labor, and everyday life—using art to probe the growing influence of AI on the world around us. Full Story ➤ Jae-Yon Lee | Global Leadership in Digital Humanities Associate Professor Jae-Yon Lee of the School of Liberal Arts has been elected President-Elect of the Constituent Organizations Board of the Alliance of Digital Humanities Organizations (ADHO). He will assume the presidency in 2027, bringing to the role research that connects Korean literature with computational approaches including network and corpus analysis, word embeddings, and AI language models. Full Story ➤ Seongil Wi's Team | Korea's First Internet Defense Prize A browser-security system developed by Professor Seongil Wi's team received the Internet Defense Prize at the 2026 USENIX Security Symposium, marking the first time a Korean institution has received the Meta-funded award. Their browser-security system, BUIzz, uncovered 35 security bugs across six major browsers by testing vulnerabilities that can emerge through ordinary browsing behavior. The paper also received runner-up recognition for the symposium's Distinguished Paper Award. Full Story ➤ Industrial Engineering | Two Honors in Data Science Two student teams from UNIST's Department of Industrial Engineering received honors at the 2026 K-DATA SCIENCE Conference. Junhyeong Lee and Sangjin Jin received the Deputy Prime Minister and Minister of Science and ICT Award for research on decision-focused learning, while Inwoo Tae and Kangmin Kim received the Creative Research Award for work on preserving temporal relationships in sequential synthetic data. Full Story ➤ Electrical Engineering | Two Honors in Circuit Research Students from Professor Heein Yoon's laboratory received two honors for advances in semiconductor circuit automation. SungJin Kim received an Outstanding Paper Award from Samsung Electronics' Device Solutions Division for AI-assisted circuit design, while HyeonJun Nam, Hyogyoung An, and ChangMin An received the IITP President's Award at ICT Challenge 2026 for a clock generator that recalibrates itself as operating conditions change. Full Story ➤

The rapid growth of generative AI and large language models is pushing up both computing demand and power consumption. A new UNIST project will explore whether more of that computation can be performed with light, reducing the energy required for data movement and signal processing in conventional electronic AI hardware. Led by Professor Il-Sug Chung of the Department of Electrical Engineering, with Professors Jongeun Lee and Heein Yoon as co-investigators, the project has received KRW 9 billion in government funding for research from 2026 through 2030. UNIST will lead the project in collaboration with Lambda Innovation. The team will integrate lasers, photonic integrated circuits (PICs), and electronic integrated circuits (EICs) into a single photonic-electronic computing system. Directly modulated vertical-cavity surface-emitting lasers (VCSELs) will generate high-speed optical signals, while optical interference will perform core neural network computations with less reliance on energy-intensive electronic data movement. To scale the architecture, the researchers will combine time-division multiplexing with optical signal distribution, allowing a limited number of physical optical channels to process larger numbers of inputs and weights. The project will also address one of the central challenges in photonic neural networks: nonlinear activation. Optical systems can perform linear operations such as matrix multiplication efficiently, but nonlinear operations often require electronic post-processing. The team will instead exploit nonlinear effects arising from coherent optical interference and detection, reducing the need to move between optical and electronic processing. The researchers aim to demonstrate an integrated system with approximately 100 optical channels and an energy efficiency of 100 trillion operations per second per watt (100 TOPS/W) at the optical computing core. Light sources, PICs, EICs, packaging, system boards, and AI algorithms will be co-designed to support larger AI workloads. “Meeting the computational demands of generative AI will require new approaches that move beyond the energy-efficiency limits of conventional electronic processors,” said Professor Chung. “By integrating lasers, photonic circuits, and electronic circuits, we aim to establish core technologies for the next generation of AI computing hardware.” The project extends Chung's work in heterogeneous photonic-electronic integration. Since 2025, his team has led a separate KRW 11 billion national project to develop an all-in-one frequency-modulated continuous-wave (FMCW) LiDAR chip and system, integrating lasers, silicon photonics, electronic circuits, and optical transmit-and-receive components. While the LiDAR project applies photonic-electronic integration to 3D sensing, the new project extends the technology to AI computing. The two efforts will provide a technology base spanning sensing and computation, with potential applications in autonomous systems, robotics, physical AI, aerospace, and defense.

Two student projects from Professor Heein Yoon's lab are advancing circuit automation at different stages of the chip lifecycle—using AI to optimize analog circuit design and enabling clock circuits to recalibrate themselves as operating conditions change. The work, conducted in the Department of Electrical Engineering, received separate honors from Samsung Electronics and the Institute for Information & Communications Technology Planning & Evaluation (IITP) in August 2026. SungJin Kim, a Combined MS-Ph.D. student in the Department of Electrical Engineering, received an outstanding paper award from Samsung Electronics' Device Solutions (DS) Division on August 19. His research automates the design of LC voltage-controlled oscillators (LC-VCOs), key circuits for generating precise reference frequencies in wireless communications and AI chips. LC-VCO design requires engineers to balance tightly coupled parameters affecting frequency, power consumption, and noise. Changes in fabrication technology or target frequency can therefore require extensive simulation and redesign, making the process difficult to automate. His framework combines reinforcement learning to optimize circuit parameters with a gradient-based algorithm for physical layout. By integrating circuit and layout optimization into a single workflow, the approach reduces the manual effort involved in adapting designs to different semiconductor technologies and frequency ranges. The approach achieved strong figures of merit (FoM) across multiple technology nodes and frequency bands. The researchers expect it to shorten development cycles and facilitate the migration of analog and RF circuits to new semiconductor processes. “I continued working on circuit design automation because I enjoyed the research itself, even when progress was difficult to see,” said SungJin Kim. “I'm glad the work has attracted interest from designers, and I hope to continue contributing to the field.” A second project from Professor Yoon's lab tackles automation after a circuit is already operating. On August 26, Combined MS-Ph.D. students HyeonJun Nam, Hyogyoung An, and ChangMin An, competing as team ACELAB , received the IITP President's Award at ICT Challenge 2026 for an injection-locked clock generator that automatically adjusts its operation to suppress unwanted reference spurs. Injection locking offers an energy-efficient way to generate the precise clock signals that coordinate operations within a chip. But injecting an external reference signal can introduce spurs around the target frequency, degrading signal quality. The ACELAB design addresses that problem by allowing the circuit to find the injection timing that minimizes spurs. If changes in fabrication process, supply voltage, or temperature shift the optimum, an on-chip calibration circuit searches for a new operating point and adjusts accordingly. This reduces both reference spurs and clock jitter without relying on complex external control. Such self-calibration could benefit AI accelerators, high-speed communications hardware, and next-generation systems-on-chip (SoCs), where clock quality directly affects system performance. The team plans to develop the technology into reusable clock IP for different semiconductor processes and operating frequencies. Meanwhile, the ICT Challenge 2026 drew 206 teams from 84 research centers at 39 universities. Of the 32 teams that advanced from the preliminary round, five—including ACELAB—received the IITP President's Award. Projects were evaluated for technical performance as well as market and commercialization potential. “We are pleased that the technical merit and potential of our research were recognized,” the ACELAB team said. “We hope to continue developing semiconductor technologies with practical applications in industry.”

Abstract Achieving the theoretical performance of 2D molybdenum disulfide (MoS2) electronics is currently bottlenecked by interfacial contamination derived from lithographic processing. A critical, yet often overlooked, mechanism is the interaction between photoresist (PR) and plasma, which chemically alters the interface. In this work, we elucidate the atomistic origin of this degradation: theoretical calculations based on molecular dynamics (MD) and density functional theory (DFT) reveal that plasma exposure functionalizes the PR with oxygen, drastically increasing its adsorption energy on the MoS2 surface from −1.15 to −2.36 eV. This doubling of adsorption energy creates thermodynamically stable, hardened residues that resist conventional removal methods. To overcome this fundamental limitation, we introduce a universal prevention-first strategy: Sacrificial Metal Mask Lithography. By utilizing a sacrificial layer to physically isolate the channel, we shield the MoS2 from reactive plasma species, preventing the formation of hardened residue entirely. This strategy results in a ten-fold reduction in contact resistance (RC) from 2.59 × 106 Ω·µm to 2.58 × 105 Ω·µm and an order-of-magnitude enhancement in on-current. Crucially, we demonstrate the universality of this method by successfully applying it to top-gated transistor arrays, electron-beam lithography (EBL), and atomic layer deposition (ALD)-synthesized films. Two-dimensional (2D) semiconductors, such as molybdenum disulfide (MoS2) hold promise for smaller, thinner electronics, but their extreme thinness also makes them particularly vulnerable to contamination during fabrication. Even small amounts of residue can interfere with electrical performance. A research team, led by Professor Myung-Soo Kim of the Department of Electrical Engineering and Professor Byoung Jo Kim of the Graduate School of Semiconductor Materials and Devices Engineering at UNIST, has developed a fabrication method that protects MoS2 from photoresist (PR) residue. The approach uses a thin, removable metal layer to keep the residue from reaching the semiconductor surface. PR is a light-sensitive material used to pattern circuits during semiconductor fabrication. When exposed to plasma, however, it can leave residue on MoS2 that conventional solvents struggle to remove. More aggressive cleaning can damage or even detach the atomically thin material from its substrate. Rather than removing the residue after it forms, the researchers prevent it from reaching the MoS2 in the first place. They place a 5-nanometer-thick metal layer over the semiconductor before patterning. Once fabrication is complete, the metal is dissolved, carrying the accumulated residue with it. Transistors made with the new process had a contact resistance of 2.58 × 10⁵ Ω·μm, about one-tenth that of devices made conventionally. Their on-current, or the current flowing when the transistor is switched on, increased by roughly tenfold. The researchers also found no clear damage to the crystal structure of MoS2 after the metal layer was removed. The team also uncovered why the residue is so difficult to remove. Molecular-level calculations showed that plasma exposure introduces oxygen into the PR, changing its chemistry and causing it to bind much more strongly to MoS2. The calculated adsorption energy shifted from −1.15 to −2.36 eV, roughly doubling the strength of the interaction. “This process can be used not only with conventional semiconductor patterning, but also with electron-beam lithography for finer features,” said Dahyun Kim, first author of the study. “We also found that it works with MoS2 produced by different synthesis methods.” The researchers tested the method with top-gated transistor arrays, electron-beam lithography, and MoS2 films grown by atomic layer deposition, showing that it can be used across different device structures and fabrication methods. “MoS2 is a promising material for making semiconductor devices, such as transistors smaller and thinner,” said Professor Myung-Soo Kim. “By addressing process contamination that has limited device performance, this work could help advance highly integrated logic and memory devices based on 2D semiconductors.” The study was published online in Small on August 11, 2026. The research was supported by the Ministry of Science and ICT (MSIT), National Research Foundation of Korea (NRF), Institute of Information & Communications Technology Planning & Evaluation (IITP), InnoCORE program, Ministry of Trade, Industry and Energy (MOTIE), and Korea Institute for Advancement of Technology (KIAT). Journal Reference Dahyeon Kim, Yanfeng Zhao, Sungyeon Kim, et al ., “Preventing Plasma-Induced Resist Hardening in Molybdenum Disulfide Transistors via Sacrificial Metal Mask Lithography,” Small, (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

Abstract This paper presents a wireless power transfer (WPT) system that maintains high efficiency and low output voltage ripple under large variations in coupling and load conditions. To address these variations, the proposed system employs an adaptive mode switching scheme with coupling-insensitive sensing. This is implemented using a fixed-reference sensor topology with filtered integrated sensor outputs and synchronization of RX 0X-to-1X transitions with TX 0X-to-1X mode transitions. For stable output regulation, a voltage-racing hysteretic controller is introduced to achieve low output voltage ripple, which is difficult to obtain with conventional analog feedback- or comparator-based hysteretic controllers. In addition, an on-chip load detector enables automatic detection of heavy- and light-load conditions. Fabricated in a 0.18- μ m BCD process, the proposed system was measured with coil distances from 7 to 20 mm, corresponding to coupling coefficient (k) variations from 0.42 to 0.08. The system supports an output power range from 2.6 mW to 147 mW while achieving a low ripple voltage of 18 mV and achieves a peak end-to-end efficiency of 69.1%. Implantable medical devices must continue operating reliably despite the body's constant movement—from walking and breathing to simply changing position during sleep. But those everyday movements can disrupt wireless charging by altering the alignment between the external charger and the implanted device. Researchers at UNIST have developed a wireless power transfer system that adapts to changes in body movement and device power demand. By maintaining stable power delivery while reducing unnecessary energy loss and heat generation, the system could make long-term wireless powering of implantable medical devices more practical. Many implantable medical devices alternate between active treatment and standby modes, causing their power requirements to change over time. At the same time, body movement can shift the distance or alignment between the transmitter and receiver coils, reducing wireless charging efficiency. Together, these challenges make it difficult to deliver stable power when and where it is needed. Led by Professor Franklin Bien of the Department of Electrical Engineering, the team designed the system to distinguish changes in device power demand from changes in coil alignment caused by body movement. Rather than relying solely on signal strength, it detects characteristic changes in communication between the transmitter and receiver, allowing it to switch reliably between high- and low-power modes as charging conditions change. The researchers also developed a new Voltage-Racing Hysteretic Controller (VRHC) to stabilize the receiver's output voltage. Instead of comparing voltages directly, the new controller detects voltage changes by measuring tiny differences in signal propagation time within the circuit. This allows it to respond more quickly and keep the output voltage remarkably stable. In laboratory tests, the system remained stable across transmission distances ranging from 7 mm to 20 mm. Even when the implanted device's operating current increased sharply from 6 mA to 16 mA, it maintained a constant 3.3 V output with a voltage ripple of only 18 mV. The system achieved a peak end-to-end power transfer efficiency of 69.1%, representing an improvement of up to 51.3 percentage points over a comparable design without the adaptive mode-switching technology. “Wireless charging systems need to adapt as conditions change, whether because a patient moves or a device's power demand shifts,” said Professor Bien. "By continuously adjusting power delivery in real time, our system improves both efficiency and stability. We hope it will help make implantable medical devices more practical for long-term use." The study was co-first authored by Sungmin Shin and Seongbin Kwon of UNIST. The research was supported by the Ministry of Science and ICT (MSIT) and the Institute for Information & Communications Technology Planning & Evaluation (IITP), and published in IEEE Transactions on Circuits and Systems I: Regular Papers (IEEE TCAS-I) on June 19, 2026. Journal Reference Sungmin Shin, Seongbin Kwon, Kiju Lee, et al ., "A Wireless Power Transfer System With Adaptive Mode-Switching Insensitive to Coupling Variations Achieving Low Ripple and High Efficiency," IEEE TCAS-I, (2026).

Abstract Data-centric applications continue to be limited by the memory wall. Logic-in-Memory (LiM) architectures based on non-volatile memories (NVMs), such as memristors, offer a promising solution by enabling in-memory computation and eliminating costly data movement. While several approaches leveraging memristor-aided logic (MAGIC) operations have been proposed, many fail to fully exploit the parallelism and spatial efficiency of memristor crossbars, especially under physical design constraints. In this paper, we propose a parallelism-driven, area-aware look-up table (LUT)-based mapping framework of arbitrary logic circuits into a memristor crossbar using MAGIC operations. We present a crossbar-aware floorplanning strategy that leverages topological LUT information to enable two-directional parallel computation (ie, HNOR and VNOR), thereby maximizing computational LUTs with minimal execution cycles. We formulate an integer linear programming (ILP) approach to define the placement of each LUT and its fanin locations, improving routability while preserving parallelism. Moreover, we introduce our novel A∗-search-based fan-in routing method with Hanan grid that fully utilizes the aligned fans and intermediate results. Experimental results demonstrate that the proposed framework achieves maximum parallelism and crossbar utilization, thereby reducing cycle counts by 19.6% and ensuring that all benchmarks map successfully under strict area constraints. We also confirm the scalability and practical applicability of the proposed framework for large-scale logic mapping in memristor-based LiM systems. Modern computing is increasingly limited not by processing speed, but by the time and energy required to move data between memory and processors. Researchers at UNIST have developed an automated design framework that addresses this challenge by making logic-in-memory (LiM) chips more efficient. Led by Professor Heechun Park of the Department of Electrical Engineering, the team designed a framework that automatically optimizes the placement of logic circuits and data pathways in memristor-based LiM architectures. By enabling more operations to run simultaneously while making better use of limited chip area, the approach reduced the number of computation cycles by nearly 20% compared with existing state-of-the-art methods. Unlike conventional computer chips, LiM architectures perform computation directly where data are stored, reducing costly data movement between memory and processors. This approach helps overcome the memory wall where data transfer limits overall computing performance. The framework determines where computations are performed within a memristor crossbar array and how intermediate results move to the next operation. Unlike previous approaches, it enables computations to proceed in both the horizontal and vertical directions, allowing more operations to run simultaneously while making better use of the available chip area. The framework also reorganizes intermediate data during computation, freeing unused memory cells and reducing wasted space. It then identifies efficient routes for transferring intermediate results between computational blocks, preserving parallel execution even under tight area constraints. In benchmark evaluations, chips designed using the new framework required 19.6% fewer computation cycles than those designed using existing approaches. The framework also successfully mapped every benchmark circuit, including designs that previous methods could not accommodate under the same area constraints, suggesting it can scale to larger LiM systems. “The performance of LiM computing depends not only on the memory device itself, but also on how computations are organized within the array,” said Professor Park. "By arranging operations to maximize parallel execution, our framework improves efficiency while remaning practical under realistic area constraints." The research was conducted by Ikkyum Kim and Minhong Kim as first and second authors, respectively, with Professor Heechun Park serving as the corresponding author. The findings were published online in IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (IEEE TCAD) on June 2, 2026. The research was supported by the National Research Foundation of Korea (NRF) and the Institute of Information & Communications Technology Planning & Evaluation (IITP). The EDA tool was supported by the IC Design Education Center (IDEC). Journal Reference Ikkyum Kim, Minhong Kim, and Heechun Park, “A Parallelism-Driven, Area-Aware Technology Mapping Framework for Memristive Logic-in-Memory,” IEEE TCAD , (2026).

Abstract Next-generation 6G communication requires radio-frequency components capable of operating above 100 GHz with low loss, high isolation, and zero static power—requirements that challenge complementary metal-oxide-semiconductor (CMOS) and microelectromechanical systems (MEMS) technologies. Here, we report transfer-free, large-area millimeter-wave (mmWave) switches based on solution-processed MoS2. While solution-processed 2D materials are often viewed as inferior to their crystalline counterparts due to high defect densities, we demonstrate that their edge-rich morphology is, in fact, a performance enabler. These edge defects act as intrinsic templates that confine Cu-filament pathways, enabling rapid (76 ns) and low-energy switching (1.57 nJ) with > 2000 cycles and uniform zero static-power operation, as corroborated by Kelvin probe force microscopy, conductive atomic force microscopy and low-temperature studies. The resulting switches achieve an low insertion loss ( < 0.1 dB) and high isolation ( > 35 dB) at 67 GHz. Notably, they exhibit a switching figure-of-merit (RON·COFF) of ~ 0.8 fs (fco ~ 187 THz), surpassing previously reported 2D switches. Importantly, by adopting an inverse-state operational scheme in a SHUNT architecture, we mitigate self-switching and achieve improved power handling (P0.1dB > 10 dBm) and linearity (IIP3 > 42.1 dBm). Finally, we demonstrate the platform's circuit-level viability by integrating the switches into a true-time-delay and hybrid-coupled phase shifters targeting 30 GHz mmWave applications. Researchers at UNIST have developed a high-performance radio-frequency (RF) switch using a solution-processed two-dimensional (2D) semiconductor, demonstrating stable operation at frequencies up to 67 GHz while consuming no static power. The technology could support future 6G wireless networks, satellite communications, radar systems, and other high-frequency communication platforms that demand compact, energy-efficient components. Led by Professor Myungsoo Kim of the Department of Electrical Engineering, the team fabricated the device using a thin film of solution-processed molybdenum disulfide (MoS2). Unlike conventional fabrication methods that require 2D semiconductor films to be grown and transferred onto a substrate, the new approach forms the semiconductor layer directly from a liquid precursor, simplifying manufacturing and making large-area production more practical. RF switches are fundamental components in wireless communication systems. They control the flow of high-frequency signals in smartphones, wireless base stations, satellite communications, radar systems, and autonomous vehicles. As communication technologies move toward the millimeter-wave frequencies required for future 6G and space communications, RF switches must transmit signals with minimal loss, effectively block unwanted leakage, and operate with very low power consumption. The newly developed switch achieved all three. Operating at 67 GHz, it recorded an insertion loss below 0.1 dB and signal isolation greater than 35 dB, allowing nearly all of the incoming signal to pass while suppressing signal leakage to less than 0.03%. The device also requires no standby power. Once switched on or off, it maintains its operating state even after power is removed, reducing unnecessary energy consumption. The researchers attribute the device's durability to the characteristics of the solution-processed MoS2 film. During fabrication, naturally occurring sulfur vacuums help guide the movement of copper ions that create the conductive pathways responsible for switching. Rather than reducing performance, these defects stabilize the switching process. Devices fabricated using solution-processed films continued to operate reliably after more than 2,000 switching cycles, whereas comparable devices fabricated from mechanically exfoliated MoS2 showed a lifetime of only about 100 cycles. To evaluate its practical potential, the team integrated the switch into communication circuits used for high-frequency signal control, including a transmit/receive switch and a beam-steering phase shifter. Both operated successfully, demonstrating that the technology can be incorporated into circuits used in satellite communications, radar, defense systems, and future wireless networks. Beam-steering phase shifters electronically direct radio waves without physically moving the antenna, enabling fast and precise tracking of moving targets such as satellites and drones. “By using solution-processed 2D semiconductor materials, we developed an RF switch that combines low signal loss with excellent isolation in the millimeter-wave band without requiring complex transfer processes,” said Professor Kim. “Because the switch retains its operating state even when power is removed, it consumes no standby power and could contribute to smaller, more energy-efficient communication systems for 6G, satellite communications, radar, and defense applications.” The findings were published online in Nature Communications on June 18, 2026. The research was supported by the National Research Foundation of Korea (NRF) and the Institute of Information & Communications Technology Planning & Evaluation (IITP), including the Space-K BIG Project and the InnoCORE Program of the Ministry of Science and ICT (MSIT). Journal Reference Changwoo Pyo, Sungmoon Park, Seungchan Lee, et al ., "Sub-femtosecond figure-of-merit millimeter-wave switches via solution-processed MoS2 for 6G radio-frequency front-ends," Nat. Commun ., (2026).

Abstract A proposed chest patch device and its interface IC are configured to allow detection of multi-domain signals in the form of optical, electrical, acoustic, and chemical signals at a single body spot. The IC integrates on-chip classification capabilities for cardiovascular diseases (CVDs) based on photo-plethysmogram (PPG) and electrocardiogram (ECG), along with hazardous gas analysis. For low-power multimodal sensing, an ECG R-peak_triggered PPG window (RPT-PW) is proposed as an inter-sensor scheme to reduce activity on the PPG channel, which is the dominant energy consumer. Additionally, the PPG and ECG readout channels incorporate analog peak detection to enable normalized on-chip extraction of pulse arrival time (PAT) and RR interval (RRI). For minimal computation and communication power, a multi-domain convolutional neural network (MD-CNN) processes both analog and digital inputs, and a reconfigurable analog ternary/binarized neural network (a-TNN/BNN) provides additional computation capability for multi-domain applications. The IC was fabricated in an 180-nm BCD process and integrated into a chest patch device prototype with an in-house adhesive meta patch. The RPT-PW demonstrated adaptive operation with an effective LED duty cycle (EDC) as low as 0.02%. The on-chip computation achieved average sensitivity and specificity of 90.87%/95.38% for three-label hypertension, 92.80%/96.36% for three-label arrhythmia, and 92.46%/97.50% for four-label gas mixture classification. Continuous wearable monitoring often requires transmitting large volumes of sensor data to external devices for analysis, increasing power consumption and limiting operating time. A joint research team, led by Professor Jae Joon Kim of Electrical Engineering and Professor Hoon Eui Jeong of Mechanical Engineering, has developed a wearable chest patch that analyzes physiological and environmental signals directly on the device, reducing both communication and sensing power while enabling continuous real-time monitoring. The wearable integrates optical, electrical, acoustic, and chemical sensing into a single device capable of simultaneously monitoring cardiovascular signals and hazardous gases. Rather than transmitting raw sensor data, it processes the information using an on-chip AI processor and sends only the analysis results via Bluetooth. This reduces communication overhead while allowing multiple users to be monitored remotely. To extend battery life, the researchers introduced an adaptive sensing scheme that selectively activates the optical sensor—the most power-intensive component of the device. By synchronizing optical measurements with ECG signals, the system reduced power consumption in the optical sensing channel by approximately 83%, enabling longer operation on a single charge. The device achieved more than 90% sensitivity and specificity in classifying hypertension and cardiac arrhythmias. It also classified hazardous gas mixtures with 92.46% accuracy, demonstrating its ability to monitor both physiological conditions and environmental hazards using a single wearable platform. The chest patch incorporates a microstructured adhesive interface that conforms securely to rough skin while allowing clean removal without leaving residue, making it better suited for long-term wear. “This work brings multimodal sensing and AI inference together on a single wearable platform,” said Professor Kim. “By processing information directly on the device, the system reduces communication demands while enabling continuous monitoring of both health conditions and environmental hazards.” The study has been participated by Sanghyeon Cho and Hyunjoong Kim as co-first authors. Their findings will appear in the July 2026 issue of the IEEE Journal of Solid-State Circuits (JSSC) , one of the leading journals in integrated circuit design. The technology has been licensed to Anvix Lab, a startup co-founded by the research team, which is pursuing commercialization of next-generation bioelectronic patch platform based on on-chip AI. The research was supported by the Ministry of Trade, Industry and Energy (MOTIE), the Ministry of Education (ME), and the Ministry of Science and ICT (MSIT). Journal Reference Sanghyeon Cho, Hyunjoong Kim, Dong Kwan Kang, et. al., “An Energy-Efficient Chest Patch Interface With Inter-Sensor PPG Windowing and Multi-Domain On-Chip Analog Computing,” JSSC , (2026).