arXiv subjects

Seungheon Shin

Publications and source records attributed to Seungheon Shin.

12 recordsLinked to original sources

arXiv2026

AlN Gate Interlayer for UWBG AlGaN Transistors with Breakdown Field >6.9 MV/cm and PFOM >1.8 GW/cm2

We report the demonstration of regrown epitaxial AlN gate interlayers with ultra-wide bandgap (UWBG) AlGaN polarization-graded field effect transistors (PolFETs). The introduction of the epitaxial AlN gate interlayer enables significant improvement in breakdown strength, with average breakdown field exceeding 6.94 MV/cm, which represents state-of-the-art for lateral field effect transistors, while maintaining excellent on-state current density exceeding 1 A/mm. The integration of epitaxial AlN enables state-of-the-art power-switching figure of merit exceeding 1.87 GW/cm2 at a breakdown voltage exceeding 1.45 kV. This work shows the potential of UWBG AlGaN for next-generation high-power switching and RF applications with enhanced device performance established by a high-quality epitaxially regrown AlN gate interlayer.

physics.app-ph↗

arXiv2026

High Breakdown Field Multi-kV UWBG AlGaN Transistors

We demonstrate high-performance UWBG AlGaN PolFETs exhibiting a state-of-the-art combination of nearly 1 A/mm on-state current (~ 960 mA/mm) and large breakdown field (> 4.8 MV/cm) in high carrier density (1.15 x 1013 cm-2). Multi-kV robustness is successfully demonstrated exhibiting 1.28 and 2.17 kV by utilizing a gate-connected field plate structures in 3.9 and 6.8 {\mu}m LGD, corresponding to the extremely low specific on-resistance of 1.25 and 2.86 m{\Omega}cm2, respectively. High RF performance is also achieved, providing fT and fMAX, of 8.5 and 15 GHz, respectively, for 3.9 {\mu}m LGD. These results highlight UWBG AlGaN as a platform for both high-voltage RF and power applications.

physics.app-ph↗

arXiv2026

Extremely Low Thermal Resistance Architectures for AlxGaN1-x Semiconductor Devices

Next-generation high-power radio-frequency (RF) devices increasingly demand transistors that operate efficiently with high gain at high frequencies. High-aluminum-content ultra-wide-bandgap (UWBG) AlGaN alloys have shown great potential for enabling such high-frequency RF technologies. However, the widespread adoption of AlGaN-based RF devices is limited by thermal-management challenges arising from the intrinsically low thermal conductivity of AlGaN, which leads to higher device thermal resistance for a given geometry compared to GaN RF devices. As a result, these next-generation devices are highly susceptible to self-heating. This study investigates the thermal behavior of UWBG AlGaN devices, focusing on the effects of AlGaN channel thickness, substrate technology, and high-k material integration on reducing device thermal resistance to enable high-power operation. Experimental results demonstrate a record-low thermal resistance of 3.96 mm$\cdot$K/W when an AlN substrate is employed and the AlGaN channel thickness is reduced to 5 nm. These findings provide valuable insights into mitigating thermal limitations in UWBG devices through device-level engineering and the strategic integration of high-k materials.

physics.app-ph↗

arXiv2025

Ultra-Wide Bandgap AlGaN Heterostructure Field Effect Transistors with Current Gain Cutoff Frequency Above 85 GHz

We report the design and demonstration of ultra-wide-bandgap (UWBG) AlGaN polarization-graded field-effect transistors (PolFETs) that achieve a current-gain cutoff frequency above 85 GHz and a current density exceeding 1.3 A/mm. Ultra-thin channel and buffer layers were grown epitaxially on AlN substrates, and a reverse-graded AlGaN contact layer was incorporated to reduce the contact resistance to below 1 ohm.mm. With aggressively scaled device dimensions, the AlGaN PolFETs exhibit state-of-the-art high-frequency performance for UWBG transistors. Small-signal modeling reveals both parasitic and transit delays, confirming the benefits of reduced access resistance and enhanced intrinsic transconductance. These results establish a new performance benchmark for UWBG AlGaN devices and demonstrate their strong potential for next-generation millimeter-wave electronics.

physics.app-ph↗

arXiv2025

Scaled Ultra-Wide Bandgap AlGaN Polarization-Graded FET with Ultra-thin Buffer Layer

We report on the design and demonstration of ultra-wide bandgap AlGaN polarization-graded field effect transistors with ultra-thin channels to enable excellent current density and high-frequency performance while significantly reducing thermal resistance. We use polarization-graded AlGaN layers and ultra-thin pseudomorphic AlGaN buffer layers to enable low thermal resistance and excellent structural quality. The polarization-graded field effect transistors (PolFETs) demonstrated here show Imax over 800mA/mm and current/power gain cutoff frequency (fT/fmax) of 26/28 GHz. Small signal modeling and analysis were used to determine parasitic/transit delays, and gate-resistance thermometry was implemented to thermally characterize AlGaN PolFET and benchmark against state-of-the-art AlGaN HEMTs. The ultra-thin AlGaN PolFET showed thermal resistance of 12 K.mm/W, representing a significant reduction from typical AlGaN transistors. These results show state-of-art combination of high current density, excellent fT-LG product for ultra-wide bandgap AlGaN transistors, and superior thermal performance, and highlight the promise of AlGaN transistors for future RF and mm-wave applications.

physics.app-ph↗

arXiv2025

Barrier Electrostatics and Contact Engineering for Ultra-Wide Bandgap AlGaN HFETs

We report ultra-wide bandgap (UWBG) AlGaN heterostructure field-effect transistors (HFETs) exhibiting a high breakdown field (> 5.3 MV/cm) and a low contact resistance (~1.55 {\Omega}mm), tailored for high-power radiofrequency applications. A split-doped barrier architecture, employing two distinct doping concentrations, is shown to enhance both the breakdown field and contact resistance. This design enables a state-of-the-art combination of maximum drain current (487 mA/mm) and breakdown field, along with a high cutoff frequency of 7.2 GHz. These results demonstrate a viable pathway to push device performance toward the material limits while minimizing contact resistance in UWBG AlGaN HFETs, paving the way for next-generation high-power, high-frequency applications.

cond-mat.mtrl-sci↗

arXiv2025

Energy Bands and Breakdown Characteristics in Al2O3/UWBG AlGaN Heterostructures

We report on energy bands and breakdown characteristics of Al2O3 dielectrics on ultra-wide bandgap (UWBG) AlGaN heterostructures. Metal-dielectric-semiconductor structures are important to sustain high fields needed for future high-performance UWBG transistors. Using systematic experiments, we determined the fixed charge density (> 1013 cm-2), the dielectric/interface, and electric fields in the oxide of under flat-band conditions in the semiconductor. Low gate-to-drain leakage current of up to 5 x 10-7 A/cm2 were obtained in the metal-oxide-semiconductor structures. In lateral metal-semiconductor-insulator test structures, breakdown voltage exceeding 1 kV was obtained with a channel sheet charge density of 1.27 x 1013 cm-2. The effective peak electric field and average breakdown field were estimated to be > 4.27 MV/cm and 1.99 MV/cm, respectively. These findings demonstrate the potential of Al2O2 integration for enhancing the breakdown performance of UWBG AlGaN HEMTs.

cond-mat.mtrl-sci↗

arXiv2025

High Breakdown Electric Field (> 5 MV/cm) in UWBG AlGaN Transistors

We report on the design and demonstration of ultra-wide bandgap (UWBG) AlGaN-channel metal-insulator heterostructure field effect transistors (HEFTs) for high-power, high-frequency applications. We find that the integration of gate dielectrics and field plates greatly improves the breakdown field in these devices, with state-of-art average breakdown field of 5.3 MV/cm (breakdown voltage > 260 V) with an associated maximum current density of 342 mA/mm, and cut-off frequency of 9.1 GHz. Furthermore, low trap-related impact was observed from minimal gate and drain lag estimated from pulsed I-V characteristics. The reported results provide the potential of UWBG AlGaN HEFTs for the next generation high-power radio frequency applications.

cond-mat.mtrl-sci↗

arXiv2025

Topology Optimization for Multi-Axis Additive Manufacturing Considering Overhang and Anisotropy

Topology optimization produces designs with intricate geometries and complex topologies that require advanced manufacturing techniques such as additive manufacturing (AM). However, insufficient consideration of manufacturability during the optimization process often results in design modifications that compromise the optimality of the design. While multi-axis AM enhances manufacturability by enabling flexible material deposition in multiple orientations, challenges remain in addressing overhang structures, potential collisions, and material anisotropy caused by varying build orientations. To overcome these limitations, this study proposes a novel space-time topology optimization framework for multi-axis AM. The framework employs a pseudo-time field as a design variable to represent the fabrication sequence, simultaneously optimizing the density distribution and build orientations. This approach ensures that the overhang angles remain within manufacturable limits while also mitigating collisions. Moreover, by incorporating material anisotropy induced by diverse build orientations into the design process, the framework can take the scan path-dependent structural behaviors into account during the design optimization. Numerical examples demonstrate that the proposed framework effectively derives feasible and optimal designs that account for the manufacturing characteristics of multi-axis AM.

cs.CE↗

arXiv2024

1/2$^-$ $α$ cluster resonances of $^{13}$C studied by the analytic continuation in the coupling constant

The 1/2$^-$ resonant states in $^{13}{\rm C}$ are investigated to search for the Hoyle-analog state. In order to treat the resonance states located around the 3$α+n$ threshold, the analytic continuation in the coupling constant (ACCC) has been combined with the real-time evolution method (REM). The properties of the 1/2$^-$ resonance states such as the radii and monopole transition probabilities are calculated. We show the 1/2$^-_3$ and 1/2$^-_4$ states are well-developed $α$ cluster states, and the 1/2$^-_4$ state is a candidate of the Hoyle-analog state.

nucl-th↗

arXiv2022

Simple Baseline for Weather Forecasting Using Spatiotemporal Context Aggregation Network

Traditional weather forecasting relies on domain expertise and computationally intensive numerical simulation systems. Recently, with the development of a data-driven approach, weather forecasting based on deep learning has been receiving attention. Deep learning-based weather forecasting has made stunning progress, from various backbone studies using CNN, RNN, and Transformer to training strategies using weather observations datasets with auxiliary inputs. All of this progress has contributed to the field of weather forecasting; however, many elements and complex structures of deep learning models prevent us from reaching physical interpretations. This paper proposes a SImple baseline with a spatiotemporal context Aggregation Network (SIANet) that achieved state-of-the-art in 4 parts of 5 benchmarks of W4C22. This simple but efficient structure uses only satellite images and CNNs in an end-to-end fashion without using a multi-model ensemble or fine-tuning. This simplicity of SIANet can be used as a solid baseline that can be easily applied in weather forecasting using deep learning.

cs.CV↗

arXiv2022

Domain Generalization Strategy to Train Classifiers Robust to Spatial-Temporal Shift

Deep learning-based weather prediction models have advanced significantly in recent years. However, data-driven models based on deep learning are difficult to apply to real-world applications because they are vulnerable to spatial-temporal shifts. A weather prediction task is especially susceptible to spatial-temporal shifts when the model is overfitted to locality and seasonality. In this paper, we propose a training strategy to make the weather prediction model robust to spatial-temporal shifts. We first analyze the effect of hyperparameters and augmentations of the existing training strategy on the spatial-temporal shift robustness of the model. Next, we propose an optimal combination of hyperparameters and augmentation based on the analysis results and a test-time augmentation. We performed all experiments on the W4C22 Transfer dataset and achieved the 1st performance.

cs.CV↗