arXiv subjects

Chuanjian Yao

Publications and source records attributed to Chuanjian Yao.

4 recordsLinked to original sources

arXiv2026

Unveiling Nanoscale Surface Damage Dynamics in Swift Heavy Ion Irradiated Gallium Nitride

This work systematically unveils the nanoscale surface damage dynamics in gallium nitride by investigating the atomistic mechanisms of hillock formation. The results identify two distinct hillock morphologies dependent on electronic energy loss (Se) values. Bell-shaped hillocks form under 18.2 keV/nm Kr irradiation, whereas crater-rim hillocks with central holes emerge under 40.2 keV/nm Ta irradiation. Microstructural analysis reveals that Ga-rich hillocks are accompanied by the generation of metastable zincblende nanodomains. These nanodomains preferentially aggregate around the periphery or sidewalls of the hillocks and exhibit a high spatial correlation with screw dislocations. Further temperature-dependent studies indicate that elevated temperatures significantly enlarge the overall dimensions of the hillock structures without altering their fundamental morphologies. Notably, under Ta irradiation above 1200 K, the high temperatures drastically reduce the viscosity and surface tension of liquid gallium. This enhanced fluidity of the transient molten phase promotes the formation of penetrating nanochannels.

cond-mat.mtrl-sci↗

arXiv2026

Atomistic Mechanisms of Temperature-Dependent Ion Track Formation in Gallium Nitride under Swift Heavy Ion Irradiation

The radiation tolerance of gallium nitride under extreme conditions is critical for its deployment in next-generation electronic and optoelectronic devices, yet the microscopic mechanisms governing swift heavy ion induced damage at elevated temperatures remain poorly understood. Therefore, this study employs a coupled approach including the two-temperature model and molecular dynamics simulations to resolve the entire processes of ion track generation induced by swift heavy ions irradiation across a wide temperature range. A temperature-driven morphological transition of ion tracks, evolving from discontinuous segments to continuous tracks composed of isolated nanobubbles, and ultimately to fully continuous channels is observed. Under lower electronic stopping loss of 430 MeV Kr irradiation, increasing temperature significantly enhances track visibility, enlarges track radii and promotes nanobubble formation. For higher electronic stopping conditions of 1171 MeV Ta irradiation, continuous ion tracks consisting of discontinuous nanobubbles (~1.5 nm radius) emerge already at 300 K, followed by a thermally activated transition into continuous channels with further radial expansion. At the atomic scale, SHI irradiation induces decomposition of wurtzite GaN into Ga clusters and N2 molecules along the ion trajectory, with Ga-rich regions and recrystallized wurtzite phases accumulating near bubble interfaces, while N2 preferentially segregates within bubble cores. Additionally, zincblende nanodomains nucleate around ion tracks and exhibit strong spatial correlation with radiation-induced dislocation networks, particularly screw dislocations, providing potential pathways for leakage current and increased susceptibility to single-event burnout.

cond-mat.mtrl-sci↗

arXiv2024

FedDCT: A Dynamic Cross-Tier Federated Learning Framework in Wireless Networks

Federated Learning (FL), as a privacy-preserving machine learning paradigm, trains a global model across devices without exposing local data. However, resource heterogeneity and inevitable stragglers in wireless networks severely impact the efficiency and accuracy of FL training. In this paper, we propose a novel Dynamic Cross-Tier Federated Learning framework (FedDCT). Firstly, we design a dynamic tiering strategy that dynamically partitions devices into different tiers based on their response times and assigns specific timeout thresholds to each tier to reduce single-round training time. Then, we propose a cross-tier device selection algorithm that selects devices that respond quickly and are conducive to model convergence to improve convergence efficiency and accuracy. Experimental results demonstrate that the proposed approach under wireless networks outperforms the baseline approach, with an average reduction of 54.7\% in convergence time and an average improvement of 1.83\% in convergence accuracy.

cs.DC↗

arXiv2023

A Trustworthy and Consistent Blockchain Oracle Scheme for Industrial Internet of Things

Blockchain provides decentralization and trustlessness features for the Industrial Internet of Things (IIoT), which expands the application scenarios of IIoT. To address the problem that the blockchain cannot actively obtain off-chain data, the blockchain oracle is proposed as a bridge between the blockchain and external data. However, the existing oracle schemes are difficult to solve the problem of low quality of service caused by frequent data changes and heterogeneous devices in IIoT, and the current oracle node selection schemes are difficult to balance security and quality of service. To tackle these problems, this paper proposes a secure and reliable oracle scheme that can obtain high-quality off-chain data. Specifically, we first design an oracle node selection algorithm based on Verifiable Random Function (VRF) and reputation mechanism to securely select high-quality nodes. Second, we propose a data filtering algorithm based on a sliding window to further improve the consistency of the collected data. We verify the security of the proposed scheme through security analysis. The experimental results show that the proposed scheme can effectively improve the service quality of the oracle.

cs.CR↗