Zhijun Tu

Free-Anionic Duality of Interstitial Electrons Drives Superconductivity in Electride La 3 In

Zhao Liu, Xiang Wang, Yin Yang, Pengcheng Ma et autres

In exhibit dual anionic and near-free electron characteristics. With our established effective local potential model, we trace that IAEs are located near Fermi-level states above potential barriers, forming a Fermi sea susceptible to La-derived phonon scattering, triggering superconductivity at 9.4 K. ARPES …

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One Step Diffusion-Based Super-Resolution With Time-Aware Distillation

X. He, Huaao Tang, Zhijun Tu, Junchao Zhang et autres

iffusion-based image super-resolution (SR) has shown strong potential in recovering high-fidelity details from low-resolution inputs. However, the need for tens or hundreds of sampling steps leads to substantial inference latency. Recent works attempt to accelerate this process via knowledge distillation, but often …

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Fault Diagnosis Method for Solid Oxide Fuel Cells Based on CNN-SVM

Zhuxun Li, Zhijun Tu, Ye Cao, Xiaolong Wu

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Evidence for Anion-Free-Electron Duality and Enhanced Superconducting Role of Interstitial Anionic Electrons in Electrides

Zhao Liu, X. R. Wang, Yin Yang, Peng‐Cheng Ma et autres

The discovery of superconducting electrides, characterized by interstitial anionic electrons (IAEs) residing in lattice cavities, has established a distinctive platform for investigating superconductors. Yet the superconducting origin and the fundamental role of IAEs in Cooper pairing formation remain poorly understood due to …

Pronounced orbital-selective electron-electron correlation and electron-phonon coupling in V2Se2O

Mingzhe Hu, Ziyin Song, Jingwen Cheng, Gexing Qu et autres

Orbital-selective many-body effects, in which electrons occupying different orbitals experience distinct interaction strengths, play a crucial role in correlated multiorbital materials. However, these effects usually manifest in a complex manner, obscuring their microscopic origins. Here, by combining angle-resolved photoemission spectroscopy measurements with …

Rethinking 1-bit Optimization Leveraging Pre-trained Large Language Models

Zhijun Tu, Siqi Liu, Peijun Li, Hanting Chen et autres

1-bit LLM quantization offers significant advantages in reducing storage and computational costs. However, existing methods typically train 1-bit LLMs from scratch, failing to fully leverage pre-trained models. This results in high training costs and notable accuracy degradation. We identify that the large …

Diagnosis Method for Solid Oxide Fuel Cell Using Temporal Convolutional Neural Networks and Support Vector Machines

Keye Li, Zhijun Tu, Ye Cao, Yu‐Xiao Yang et autres

Fuel depletion is one of the critical factors affecting the reliable operation of Solid Oxide Fuel Cell (SOFC). To address the issue of identifying weak faults in the system, where initial characteristics are not obvious and fault type determination is challenging, a …

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Layered Ordered Multianion Semiconductor Bi18O21.6Se1.8Cl7.2 with Low c-Axial Thermal Conductivity

Zhijun Tu, Wenju Zhou, Zhenghui Fang, Yizhe Liu et autres

Layered ordered multianion materials exhibit remarkable structural flexibility and unique chemical and physical properties, which arise from the interplay of intralayer and interlayer interactions, as well as distinct local chemical environments originating from different anionic sublattices. Here, we report a novel layered …

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RaSS: Improving Denoising Diffusion Samplers with Reinforced Active Sampling Scheduler

Xin Ding, Lei Yu, Xin Li, Zhijun Tu et autres

Recent years have witnessed the great success of denoising diffusion samplers in improving the generative capability and sampling efficiency given a pre-trained diffusion model. However, most sampling schedulers in diffusion models lack the sampling dynamics and planning capability for future generation results, …

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One-Step Diffusion-based Real-World Image Super-Resolution with Visual Perception Distillation

Xuefeng Wu, Jingwei Xin, Zhijun Tu, Jie Hu et autres

Diffusion-based models have been widely used in various visual generation tasks, showing promising results in image super-resolution (SR), while typically being limited by dozens or even hundreds of sampling steps. Although existing methods aim to accelerate the inference speed of multi-step diffusion-based …

Autoregressive Image Generation with Vision Full-view Prompt

Miaomiao Cai, Guanjie Wang, Wei Li, Zhijun Tu et autres

In autoregressive (AR) image generation, models based on the 'next-token prediction' paradigm of LLMs have shown comparable performance to diffusion models by reducing inductive biases. However, directly applying LLMs to complex image generation can struggle with reconstructing the image's structure and details, …

Superconductivity in Cubic La3Al with Interstitial Anionic Electrons

Zhijun Tu, Pei-Han Sun, Donghan Jia, Huiyang Gou et autres

Abstract We observed superconductivity in a cubic La3Al single crystal that exhibits metallic behavior in the normal state without an observable structural transition and enters the superconducting state below T c ∼ 6.32 K. Detailed characterization and analysis indicate that cubic La3Al …

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