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Research 2026년 09월 02일 수요일

New Process Shields 2D Semiconductors from Fabrication Residue

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).

Research 2026년 09월 01일 화요일

Rethinking What Matters

《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

Research 2026년 08월 11일 화요일

Adaptive Wireless Charging for Implantable Medical Devices

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).

Research 2026년 08월 06일 목요일

Smarter Design Method Improves Efficiency of In-Memory Computing Chips

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).

Research 2026년 08월 03일 월요일

Solution-Processed Semiconductor Enables High-Performance RF Switches for 6G and Satellite Communications

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).

Research 2026년 07월 14일 화요일

New Wearable Patch Combines Multimodal Sensing with On-Chip AI

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).

Research 2026년 07월 02일 목요일

New Semiconductor Device Brings Communication and AI Computing onto a Single Chip

Abstract Next-generation 6G communication systems necessitate hardware that simultaneously manages high-frequency signal routing and massive matrix-level computations under extreme constraints. However, conventional digital architectures suffer from high power dissipation and area overhead. Here, we report an oxidized molybdenum disulfide (MoS2)-based memristive platform that integrates nonvolatile radio-frequency (RF) switching and energy-efficient vector–matrix multiplication. By implementing a controlled thermal oxidation process, we achieve stable resistive switching with low switching energy and zero-static power consumption, while maintaining a high cutoff frequency of 33.2 THz, outperforming existing phase-change and microelectromechanical systems (MEMS) technologies. Using system-level simulations, we demonstrate the robustness of this hardware through successful 1024-quadrature amplitude modulation (1024-QAM) demodulation, spectral analysis, and multiple-input multiple-output (MIMO) signal reconstruction, even when accounting for intrinsic device non-idealities. This monolithic integration of high-frequency switching and analog computing provides a scalable solution for energy-efficient deployment of intelligent wireless systems. Future 6G networks and satellite communication systems will require hardware that can process growing amounts of data while operating under strict power and space constraints. Professor Myungsoo Kim and his research team from the Department of Electrical Engineering at UNIST introduced a new semiconductor device that combines high-frequency signal switching and computation on a single platform, offering a more compact and energy-efficient approach to next-generation wireless systems. At the heart of the platform is a multifunctional memristor based on oxidized molybdenum disulfide (MoS2), a two-dimensional semiconductor. The device functions as both a radio-frequency (RF) switch and hardware for in-memory matrix operations, bringing communication and computation onto a single chip. Conventional communication systems typically separate these functions, requiring signals to move between switching circuits and processors. This data movement increases power consumption, processing delays, and chip size. By integrating both functions into a single device, the new platform simplifies signal processing while improving energy efficiency. The memristor also operates without standby power. Once switched between its ON and OFF states, it retains that state even after power is removed, making it particularly well suited to energy-constrained applications such as satellite communications and future 6G infrastructure. The device demonstrated a switching energy of just 140 picojoules per operation and switching power below one milliwatt. It maintained stable operation for more than 40,000 seconds and over 1,000 switching cycles, while achieving a calculated cutoff frequency of 33.2 THz. Experimental measurements verified high-frequency switching up to 67 GHz. To evaluate its computing capability, the researchers performed system-level simulations of wireless communication tasks. The device successfully carried out 1024-quadrature amplitude modulation (1024-QAM) demodulation and multiple-input multiple-output (MIMO) signal reconstruction, demonstrating that a single hardware platform can efficiently support both communication and signal processing. "Commercial RF switches continuously consume standby power and often suffer signal loss at high frequencies," said Juhyo Son, the study's first author. "Our device addresses these limitations while remaining competitive with existing phase-change memory and MEMS technologies in energy efficiency, operating speed, and scalability." Professor Kim added, "Our study demonstrates that oxidized MoS₂ memristors can function not only as high-performance RF switches but also as hardware for the in-memory matrix operations required for next-generation wireless communications. By combining nonvolatile operation, low power consumption, and high-frequency performance, this platform could contribute to more compact and energy-efficient systems for satellite communications, radar, defense electronics, and future 6G RF front ends." The research was supported by the National Research Foundation of Korea (NRF) through the Ministry of Science and ICT (MSIT), the Institute for Information & Communications Technology Planning & Evaluation (IITP), the Space-K BIG Project, and a regional talent development program. The findings were published online in Advanced Functional Materials on June 6, 2026. Journal Reference Juho Son, Changwoo Pyo, Sungmoon Park, et al., “ Oxidized MoS2-Based Multifunctional Memristive Hardware for Energy-Efficient mmWave Signal Processing and In-Memory Matrix Multiplication ,” Adv. Funct. Mater., (2026).

News 2026년 06월 09일 화요일

UNIST Selected to Lead National Space-K BIG Project for Very Low Earth Orbit Satellites

UNIST has been selected to lead a major national research project aimed at developing core technologies for very low Earth orbit (VLEO) satellite platforms, reinforcing Korea's efforts to strengthen its space technology capabilities. The project is part of the 2026 Space-K BIG Project, an initiative of the Korea AeroSpace Administration (KASA) that designs leading university research centers to advance foundational space technologies while training the next generation of space professionals. Under the program, the Department of Electrical Engineering at UNIST will receive KRW 5.7 billion in government funding through December 2030. The project, led by Professor Gangil Byun from the Department of Electrical Engineering , brings together Professors Myungsoo Kim, Hoon Lee, Jinseok Park, Minho Choi, Dongyun Kam, Kawon Han, and Jaeyong Jeong in a multidisciplinary effort. Titled "Mission-Oriented Convergent Platform Technologies for Very Low Earth Orbit Satellites and Global Talent Development," the project will develop key technologies for future satellite missions, including space-qualified RF devices, AI semiconductors, and optoelectronic components. Researchers will also advance domestically developed commercial off-the-shelf (COTS) technologies for satellite applications and establish an integrated VLEO satellite platform for future mission deployment. Education and workforce development form another major component of the initiative. UNIST will collaborate with industry, government research institutes, and international partners to provide students with hands-on research experience through joint projects and specialized training, creating an integrated environment that connects education with advanced space research. “This project provides an important opportunity for UNIST to lead research on core technologies for very low Earth orbit satellites while cultivating globally competitive talent in space engineering,” said Professor Gangil Byun, the project's principal investigator. “By combining the expertise of our faculty with the innovative capabilities of our industry partners, we aim to deliver technologies that will contribute to the future growth of Korea’s space industry.”

Community 2026년 06월 05일 금요일

Professor Sung Whan Yoon Receives MSIT Commendation for Digital Talent Development

Professor Sung Whan Yoon of the Graduate School of Artificial Intelligence (AIGS) and Department of Electrical Engineering at UNIST has been honored with a Ministerial Commendation from the Ministry of Science and ICT (MSIT) for his contributions to digital talent development. The award recognizes his efforts to advance reliable AI technologies, while connecting AI education with real-world manufacturing challenges. A major challenge in applying AI to factories is the gap between the lab and the field. Data collected from actual equipment often differs from the data used to train a model. Changes in materials, machine conditions, operating methods, or data quality can all weaken model performance. In manufacturing, those errors can lead directly to production losses or safety risks. Professor Yoon has worked to address that problem through robust AI algorithms. Robust AI refers to machine learning systems that continue to perform reliably even when conditions change. Rather than pursuing high accuracy only under fixed conditions, his work focuses on AI that can make dependable decisions in real industrial environments. His research has also drawn international recognition. At the International Conference on Learning Representations (ICLR) 2025, one of the world’s leading AI conferences, his work on improving the stability of reinforcement learning models was selected for an oral presentation. Oral presentations at ICLR are typically reserved for roughly the top 2 percent of submitted papers. Reinforcement learning allows AI systems to improve decisions through trial and error. In manufacturing, it can help optimize equipment settings and production processes. But factories leave little room for unstable decisions, since one wrong choice can create cost and safety risks. Professor Yoon’s research showed how reinforcement learning models can become more stable under uncertain or changing field conditions, moving the technology closer to industrial use. Beyond research, Professor Yoon has also brought those advances into AI education for manufacturing professionals. Since joining UNIST, Professor Yoon has helped design and run AI programs for industry workers in Ulsan and the southeastern region. The programs are built around problems participants face in their own factories, turning actual production issues into hands-on AI projects. His team has applied reinforcement learning-based optimization methods to manufacturing and processing facilities. The work aims to improve equipment operations while maintaining process stability and safety. This link between AI training and workplace change was a key reason for the commendation. Professor Yoon currently serves as a project leader in the national AI Star Fellowship program. In partnership with SK Energy, he is developing core technologies for robust manufacturing AI that can be used in complex process industries, including petrochemicals. “High performance alone is not enough for AI to succeed in industry,” Professor Yoon said. “AI systems must remain stable even when conditions change. We will continue developing robust AI technologies and connecting them to manufacturing solutions and digital talent development.”

Research 2026년 06월 05일 금요일

New High-Efficiency Wireless Charging for Implantable Medical Devices

Abstract This article presents a single-input–dual-output (SIDO) wireless power transfer (WPT) system that maintains high link efficiency across both heavy and light load conditions. Conventional SIDO architectures employ a fixed matching network, which leads to significant efficiency degradation when the load changes. To address this limitation, the proposed system classifies the two outputs into heavy-load and light-load domains and employs dedicated matching networks optimized for each operating condition, thereby maximizing link efficiency during charging of either load. To minimize the power overhead of mode switching while enabling single-stage AC–DC regulation, a charging-phase controller, a full/half-window mode controller, and an adaptive window generator are employed. Furthermore, an active rectifier with a slowdown unit cell (SUC)-based on/off controller (SOOC) is proposed to improve power conversion efficiency (PCE). In addition, an early turn-on switching (ETS) is implemented to achieve higher PCE compared to conventional zero-voltage switching (ZVS). Fabricated in a 0.18- μ m BCD process, the system is implemented as two chips, a standalone rectifier for accurate PCE measurement and a SIDO integrating the same rectifier. The SIDO demonstrates stable full/half-window operation without multiple pulsing. Measured link efficiency reaches 94.4% at 3mA and 92.7% at 30mA at a coupling coefficient k = 0.2, confirming the effectiveness of the load-optimized matching. The rectifier achieves 94.5% peak PCE and maintains above 92.3% PCE across a 2.5–5.0V input range. A new wireless charging technology promises to enhance the safety and longevity of implantable medical devices, such as pacemakers and neural stimulators. Led by Professor Franklin Bien of the Department of Electrical Engineering, the research team developed a system that employs load-specific matching networks and adaptive control to optimize power delivery. Implantable devices often incorporate circuits with varying power demands—high-current circuits for stimulation and low-current circuits for data processing. Traditional wireless chargers rely on fixed configurations, which can lead to inefficiencies and heat buildup, potentially damaging surrounding tissue. The new system detects changes in load and switches between dedicated matching networks tailored for high and low power conditions, thereby optimizing energy transfer. Furthermore, the team improved the efficiency of the rectifier circuit that converts received alternating current (AC) into direct current (DC). By precisely controlling switching points during power conversion, they minimized energy loss and enhanced overall performance. Experimental results demonstrated a link efficiency of 94.4% at a low load of 3mA and 92.7% at a high load of 30mA. The active rectifier achieved a peak power conversion efficiency of up to 94.5%, maintaining above 92% even as input voltage varied from 2.5V to 5V. The research team anticipates that this technology will extend the operational lifespan of implantable devices, reducing the need for frequent surgical replacements and associated risks. It also holds promise for application in wearable electronics and compact Internet of Things (IoT) devices that require reliable, low-loss wireless power. The findings of this research were published online in the IEEE Transactions on Very Large Scale Integration (VLSI) Systems on April 29, 2026. The study has been s upported by the Ministry of Science and ICT (MSIT) and the Institute for Information & Communications Technology Planning & Evaluation (IITP). Journal Reference Sungmin Shin, Seongbin Kwon, Geonwoo Baek, et al ., “A Single-Input Dual-Output Wireless Power Transfer System With Load-Optimized Matching Network,” IEEE TVLSI. , (2026).

Research 2026년 06월 01일 월요일

Breakthrough Chameleon MXene Promises Advanced 6G Communication and Next-Gen Batteries

Abstract Device-level performance in MXenes is dictated by architecture—planar nanosheets are optimal for electromagnetic interference (EMI) shielding, while scrolled structures enhance ion transport for energy storage—particularly when morphology is programmed at synthesis. Whether such architectures can be deterministically encoded through precursor stoichiometry remains unresolved. Here, we demonstrate that precise carbon stoichiometry control in Ti3AlCxO2-x MAX phases tunes internal lattice strain and thereby directs the emergent MXene architecture. Carbon-rich precursors (x = 1.94) yield strain-relieved, high-crystalline nanosheets with metallic conductivity (∼23 300 S cm−1), enabling ultrathin films with record-high EMI shielding performances across 8 µm) and robust W-band retention after 5,000 bending cycles (r = 2.5 mm). In contrast, carbon-deficient precursors (x = 1.71) introduce lattice compression and oxygen substitution, triggering spontaneous scrolling upon delamination. The resulting nanoscrolls offer exceptional ion accessibility, achieving 657 F g−1 at 2 mV s−1 with 99.4% retention over 12 000 cycles. This stoichiometry-programmed approach establishes a synthesis-stage lever linking MAX chemistry to MXene architecture and function, enabling application-specific architecture design within established MAX/MXene synthesis and solution-processing workflows for next-generation electronics and energy storage. Researchers at UNIST have discovered a simple way to control MXene's structure by adjusting the carbon content in its precursor. This breakthrough enables the creation of tailored MXene materials optimized for high-frequency electromagnetic interference (EMI) shielding and rapid energy storage. MXene, a two-dimensional material composed of metal and carbon layers, is celebrated for its excellent electrical conductivity and adaptability. Its potential spans batteries, sensors, and flexible electronics. With the rise of 6G technology and advanced radar systems, shielding devices against high-frequency interference has become critical. At the same time, the demand for quick, reliable energy storage continues to grow. Led by Professor Soon-Yong Kwon from the Graduate School of Semiconductor Materials and Devices Engineering and Professor EunMi Choi from the Department of Electrical Engineering, the team showed that changing the carbon content in MAX precursors influences how MXene forms during synthesis. This control method results in two distinctly different structures. When using carbon-rich precursors, the process yields flat, highly crystalline nanosheets that exhibit excellent electrical conductivity, effective electromagnetic shielding at 100 GHz, and maintain flexibility and durability under repeated bending. Conversely, employing carbon-deficient precursors induces the spontaneous formation of nanoscrolls, which significantly enhance ion transport. These nanoscroll structures enable high-capacity energy storage, achieving a capacitance of 657 F/g and a cycle life exceeding 12,000 cycles. This work confirms that simple adjustments to precursor composition can produce MXene structures tailored for specific applications—flat sheets for shielding and scrolls for energy storage—within a streamlined process. First author Jaeeun Park explains, “We showed that flat MXene sheets are ideal for electromagnetic shielding, while scroll structures are better suited for energy storage. By controlling the precursor, we can design the material for different functions without changing the synthesis method.” Professor Kwon adds, "Last year, we enhanced MXene's conductivity and broadband shielding through nitrogen doping. Now, we've demonstrated how to design the material's shape from the start. The ultra-thin, flexible MXene performs well at 100 GHz and withstands bending, making it a promising lightweight, flexible shield for future 6G and radar systems." Supported by the Ministry of Science and ICT (MSIT) and the National Research Foundation of Korea (NRF), the study was published in Advanced Materials on May 18, 2026. Journal Reference Jaeeun Park, Ju-Hyoung Han, Yujin Chae, et al ., “Stoichiometry-Programmed MXenes via Precursor Engineering for High-Performance EMI Shielding and Energy Storage,” Adv. Mater ., (2026).

Research 2026년 05월 12일 화요일

Revolutionizing Semiconductor Design: AI Cuts Development Time from Months to Just One Day

Abstract Artificial Intelligence (AI) has been increasingly utilized across various fields, including communications, healthcare, and Computer-Aided Design (CAD). However, AI has shown relatively limited advances in analog and RF circuit design, which are critical for modern communication systems such as 5G due to their higher complexity and nonlinear characteristics. For example, the Inductor-Capacitor Voltage-Controlled Oscillator (LC-VCO) is a crucial component in frequency synthesizers, determining the performance of RF systems, including high data transmission rates and wide bandwidth. In fact, LC-VCO design is challenging due to the high parameter variability and complex interactions between design variables, making it challenging to optimize parameters to meet target specifications. Thus, this study proposes a comprehensive LC-VCO design methodology compatible across multiple process nodes and supports optimization down to the layout level. We use Reinforcement Learning (RL) to navigate the nonlinear design space efficiently for schematic optimization and apply an algorithm from Gradient Descent to optimize the design at the physical layout level. We highlight that the versatility of our methodology is demonstrated by producing optimized Figures of Merit (FoM) across various technology nodes and frequency ranges, showcasing its potential as a universal design tool accessible to all users. A team of researchers from UNIST and Kyungpook National University (KNU) has unveiled a pioneering AI system capable of completing the complex design of high-performance semiconductor circuits in just one day—an achievement that drastically reduces the traditional development timeline, which can take several months. Led by Professor Heein Yoon of UNIST’s Department of Electrical Engineering and Professor Taigon Song of KNU, the team developed an integrated AI platform that automates the entire process—from schematic design to physical chip layout. This breakthrough technology streamlines a typically multi-stage, resource-intensive task, offering faster, more efficient, and highly optimized circuit design solutions. The initial focus was on the design of the Inductor-Capacitor Voltage-Controlled Oscillator (LC-VCO), a critical component in 5G and emerging 6G communication systems. LC-VCOs generate the carrier signals essential for high-speed data transmission. Designing these circuits involves balancing numerous variables—such as inductor and transistor sizes—to minimize noise and power consumption. However, translating schematic designs into physical layouts often introduces parasitic effects that can impair performance. The new model integrates circuit schematic optimization with physical layout design, addressing these challenges holistically. During the schematic phase, reinforcement learning algorithms explore various parameter configurations to meet specific frequency and performance targets. Subsequently, in the layout phase, the system employs gradient descent methods to iteratively refine physical design parameters—such as wire widths and spacing—to enhance overall circuit performance. Gradient descent, a well-established optimization technique, incrementally adjusts design variables by following the gradient of the objective function toward an optimal solution. This integrated approach drastically accelerates the design process. Tasks that previously required up to 119 hours can now be completed in approximately 28.5 hours—reducing the overall time by over 76%. Moreover, the system’s adaptability across different semiconductor process nodes is enabled by transfer learning. Models trained on one technology node (e.g., 65nm) can be efficiently adapted to others (such as 40nm or 28nm), using just around 10% additional data. This AI-driven methodology not only shortens development cycles and reduces costs but also addresses the industry’s growing need for efficient design automation amid a global talent shortage. By ensuring high performance while minimizing manual effort, this technology is poised to significantly impact the production of next-generation communication and AI chips. The researchers anticipate expanding this framework beyond LC-VCOs to automate various analog and RF circuit designs, further accelerating innovation in semiconductor technology. The research was led by Sungjin Kim of UNIST and Hyunsoo Lee of KNU, who served as co-first authors, with additional contributions from Hong Seong-min of KNU. The findings of this research have been published online in the IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD) on April 3, 2026. The study has been supported by the Ministry of Science and ICT (MSIT), the National Research Foundation of Korea (NRF), the Ministry of Education (BK21 Four), the Ministry of Trade, Industry and Energy (MOTIE), the Semiconductor Design Education Center (IDEC), Samsung Electronics, Axion Co., Ltd., and the Institute for Information & Communications Technology Planning & Evaluation (IITP). Journal Reference Sungjin Kim, Hyunsoo Lee, Seongmin Hong, et al., "A Framework of Automated LC-VCO Design with Physical Layout Based on Reinforcement Learning, IEEE TCAD, (2026).