arXiv subjects

Zifeng Huang

Publications and source records attributed to Zifeng Huang.

8 recordsLinked to original sources

arXiv2026

Active Passivation Tunes Hotspot Locations in GaN Transistors with In Situ Thermal Mechanical Visualization

Efficient thermal dissipation has become critical in emerging electronic devices. However, most existing studies have primarily focused on engineering heat dissipation pathways, largely overlooking the intrinsic behavior of the heat source itself. We demonstrate an active passivation technology that proactively tunes hotspot locations in GaN transistors. By adjusting the active passivation layer length, the hotspot is shifted from the gate edge to the drain-side AP edge, establishing a clear one-to-one spatial correlation. In-situ thermal-mechanical visualization via micro-Raman thermography, combined with multi-physics electro-thermal-mechanical simulations, directly captures the spatial redistribution of both temperature and thermal stress profiles. Electrical analysis confirms that this hotspot migration is driven by the spatial shift of the peak electric field and localized Joule heating. This proactive heat-source tuning strategy provides critical design guidelines for power electronics.

physics.app-ph↗

arXiv2026

Upper Generalization Bounds for Neural Oscillators

Neural oscillators that originate from second-order ordinary differential equations (ODEs) have shown competitive performance in learning mappings between dynamic loads and responses of complex nonlinear structural systems. Despite this empirical success, theoretically quantifying the generalization capacities of their neural network architectures remains undeveloped. In this study, the neural oscillator consisting of a second-order ODE followed by a multilayer perceptron (MLP) is considered. Its upper probably approximately correct (PAC) generalization bound for approximating causal and uniformly continuous operators between continuous temporal function spaces and that for approximating the uniformly asymptotically incrementally stable second-order dynamical systems are derived by leveraging the Rademacher complexity framework. These bounds are further extended to the squared Wasserstein-1 distances between the probability measures of quantities of interest calculated from target causal operators and the corresponding learned neural oscillators. The theoretical results show that the estimation errors grow polynomially with respect to both MLP sizes and the time length, thereby avoiding the curse of parametric complexity. Furthermore, the derived error bounds demonstrate that constraining the Lipschitz constants of the MLPs via loss function regularization can improve the generalization ability of the neural oscillator. Numerical studies considering a Bouc-Wen nonlinear system under stochastic seismic excitation validates the theoretically predicted power laws of the estimation errors with respect to the sample size and time length, and confirms the effectiveness of constraining MLPs' matrix and vector norms in enhancing the performance of the neural oscillator under limited training data.

cs.LG↗

arXiv2026

High Thermal Conductivity in Back-End-of-Line Compatible AlN Thin Films

With thermal issues becoming a major challenge to the development of integrated circuits (ICs), high-thermal-conductivity (high-TC) materials are gaining interest from both the industry and academia, especially for high-density back-end-of-line (BEOL) structures. Aluminum nitride (AlN) is an insulating material with high TC, suitable for thermal management in electronic devices. Furthermore, polycrystalline AlN thin films can be deposited at BEOL-compatible low temperatures (lower than 400 C) while retaining relatively high TC, rendering AlN a promising candidate for BEOL heat dissipation. Still, AlN deposition should aim at achieving high TC on a variety of substrates used in IC processes. In this work, we obtained 600- and 1200-nm BEOL-compatible AlN thin film samples on Si, SiO, SiN, and Al2O3 substrates for structural and thermal characterizations. Specifically, time-domain thermoreflectance (TDTR) measurements revealed consistently high TC (higher than 45 W m-1 K-1) on different substrates. Moreover, finite element analysis (FEA) simulations of AlN capped on top of an indium-tin-oxide (ITO) transistor showed a reduction of up to 44% in peak device temperature. Our work provided experimental and calculational evidence for the practicality of leveraging AlN as a high-TC, BEOL-compatible heat spreader material.

cond-mat.mtrl-sci↗

arXiv2026

Ion Implantation Enhanced Nucleation Facilitates Heat Transport across Atomically-Sharp Semiconductor Interfaces

Overheating is a critical bottleneck limiting the performance and reliability of next-generation high-power and high-frequency electronics. Interfacial thermal resistance constitutes a significant portion of the total thermal resistance. In this study, we report an ultrahigh thermal boundary conductance (TBC) of approximately 800 MW/m2-K at the atomically-sharp AlN-SiC interface, achieved through an ion implantation-enhanced nucleation epitaxy technique. This value is among the highest TBC values reported for semiconductor interfaces, confirmed by structural characterizations which show an ultrahigh-quality interface. Atomistic Green Function calculations reveal that elastic phonon transmission dominates the interface, with nearly half of the acoustic modes (0-15 THz) exhibiting near-unity transmission due to the atomically sharp structure. Furthermore, using high-energy-resolution electron energy loss spectroscopy, we probe vibrational properties with nanometer spatial resolution and identify unique interfacial phonon modes connecting the mismatched phonon spectra, confirmed by molecular dynamics simulations. The ultrahigh TBC is attributed to both the high elastic phonon transmission due to the high quality interfaces and the inelastic phonon scattering channel due to interfacial phonon modes. These findings not only advance the fundamental understanding of interfacial thermal transport but also provide a pathway for effective thermal management in emerging electronic devices.

cond-mat.mes-hall↗

arXiv2025

Upper Approximation Bounds for Neural Oscillators

Neural oscillators, originating from second-order ordinary differential equations (ODEs), have demonstrated strong performance in stably learning causal mappings between long-term sequences or continuous temporal functions, as well as in accurately approximating physical systems. However, theoretically quantifying the capacities of their neural network architectures remains a significant challenge. In this study, the neural oscillator consisting of a second-order ODE followed by a multilayer perceptron (MLP) is considered. Its upper approximation bound for approximating causal and uniformly continuous operators between continuous temporal function spaces and that for approximating uniformly asymptotically incrementally stable second-order dynamical systems are derived. The established proof method of the approximation bound for approximating the causal continuous operators can also be directly applied to state-space models consisting of a linear time-continuous complex recurrent neural network followed by an MLP. Theoretical results reveal that the approximation error of the neural oscillator for approximating the second-order dynamical systems scales polynomially with the reciprocals of the widths of two utilized MLPs, thus overcoming the curse of parametric complexity. The convergence rates of two established approximation error bounds are validated through four numerical cases. These results provide a robust theoretical foundation for the effective application of the neural oscillator in science and engineering.

cs.LG↗

arXiv2025

Experimental Observation of Extremely Strong Defect-Phonon Scatterings in Semiconductor Single Crystals

The role of doping in tailoring thermal transport in semiconductors is critical for efficient thermal management in electronic devices. While the effects of doping have been extensively studied to tune electrical properties, its impact on thermal transport has not yet been thoroughly explored, particularly with respect to experimental investigations into exceptionally strong non-Rayleigh defect-phonon scattering phenomena. Herein, by combining the high-quality growth and advanced characterizations of cubic silicon carbide single crystals with well controlled boron doping, we experimentally observe anomalous strong defect-phonon scatterings, among the strongest reported in common semiconductors, that exceeds the predictions of the classic mass difference model by tens of times in magnitude. The measured thermal conductivity of doped 3C SiC match excellently with those predicted by first principle calculations in which resonant scattering of low frequency phonon is considered. Our findings not only shed light on the fundamental understanding of defect-phonon interactions and will also impact applications such as thermal management of electronics.

cond-mat.mtrl-sci↗

arXiv2024

Thermal Conductivity of Cubic Silicon Carbide Single Crystals Heavily Doped by Nitrogen

High-purity cubic silicon carbide possesses the second-highest thermal conductivity among large-scale crystals, surpassed only by diamond, making it crucial for practical applications of thermal management. Recent theoretical studies predict that heavy doping reduces the thermal conductivity of 3C-SiC via phonon-defect and phonon-electron scattering. However, experimental evidence has been limited. In this work, we report the thermal conductivity of heavily nitrogen doped 3C SiC single crystals, grown using the top-seeded solution growth method, measured via time domain thermoreflectance. Our results show that a significant reduction (up to 30%) in thermal conductivity is observed with nitrogen doping concentrations around 1020 cm-3. A comparison with theoretical calculations indicates less intensive scatterings are observed in the measured thermal conductivity. We speculate that the electron-phonon scattering may have a smaller impact than previously anticipated or the distribution of defects are nonuniform which leads to less intensive scatterings. These findings shed light on understanding the doping effects on thermal transport in semiconductors and support further exploration of 3C SiC for thermal management in electronics.

cond-mat.mtrl-sci↗

arXiv2024

Interfacial reaction boosts thermal conductance of room-temperature integrated semiconductor interfaces stable up to 1100 C

Overheating has emerged as a primary challenge constraining the reliability and performance of next-generation high-performance electronics, such as chiplets and (ultra)wide bandgap electronics. Advanced heterogeneous integration not only constitutes a pivotal technique for fabricating these electronics but also offers potential solutions for thermal management. This study presents the integration of high thermal conductivity semiconductors, specifically, 3C-SiC thin films and diamond substrates, through a room-temperature surface-activated bonding technique. Notably, the thermal conductivity of the 3C-SiC films is among the highest for all semiconductor films which can be integrated near room temperature with similar thicknesses. Furthermore, following annealing, the interfaces between 3C-SiC and diamond demonstrate a remarkable enhancement in thermal boundary conductance (TBC), reaching up to approximately 300%, surpassing all other grown and bonded heterointerfaces. This enhancement is attributed to interfacial reactions, specifically the transformation of amorphous silicon into SiC upon interaction with diamond, which is further corroborated by picosecond ultrasonics measurements. Subsequent to annealing at 1100 C, the achieved TBC (150 MW/m2-K) is record-high among all bonded diamond interfaces. Additionally, the visualization of large-area TBC, facilitated by femtosecond laser-based time-domain thermoreflectance measurements, shows the uniformity of the interfaces which are capable of withstanding temperatures as high as 1100 C. Our research marks a significant advancement in the realm of thermally conductive heterogeneous integration, which is promising for enhanced cooling of next-generation electronics.

cond-mat.mes-hall↗