Xi Zhu

About

Xi Zhu is a doctoral candidate in Chinese at the University of Washington, specializing in early Chinese texts, early Medieval Chinese poetry, and manuscript study. He holds a Master of Arts in Asian Languages and Literature from the University of Washington, a Master of Arts in Asian Languages and Civilizations from the University of Colorado Boulder, and a Bachelor of Arts in Chinese Language and Literature from Shanghai Normal University. His research focuses on Chinese language and literature, with particular interest in early Chinese texts and manuscript studies. Xi Zhu has taught various courses including First-Year Classical Chinese, First-Year Intensive Chinese for Non-Heritage Learners, and courses on the literature and culture of China, contributing to the academic community through his teaching and research in Asian languages and literature.

Research topics

• Materials science
• Chemistry
• Nanotechnology
• Computer science
• Composite material

Selected publications

• Fully Lignocellulosic Biomass‐Based Double‐Layered Porous Hydrogel for Efficient Solar Steam Generation

  Advanced Functional Materials · 2022-10-31 · 273 citations

  article

  Abstract Solar‐driven interfacial evaporation is an important approach for solving the issue of freshwater scarcity. However, the practical application of solar steam generation is hindered by high fabrication cost and environmental concerns regarding the petroleum‐based materials. Herein, lignocellulose (cellulose‐lignin composite) hydrogel (LCG) and lignin‐derived carbon (LC) are used as the substrate and photothermal material, respectively, to construct a fully lignocellulose‐based double‐lay…

  PublisherDOI

• Eradication of tumor growth by delivering novel photothermal selenium-coated tellurium nanoheterojunctions

  Science Advances · 2020-04-08 · 167 citations

  articleOpen access

  Two-dimensional nanomaterial-based photothermal therapy (PTT) is currently under intensive investigation as a promising approach toward curative cancer treatment. However, high toxicity, moderate efficacy, and low uniformity in shape remain critical unresolved issues that hamper their clinical application. Thus, there is an urgent need for developing versatile nanomaterials to meet clinical expectations. To achieve this goal, we developed a stable, highly uniform in size, and nontoxic nanomateri…

  PublisherOA PDFDOI

• MXenes: focus on optical and electronic properties and corresponding applications

  Nanophotonics · 2020-02-01 · 162 citations

  articleOpen accessSenior authorCorresponding

  Abstract The discovery of graphene, the first two‐dimensional (2D) material, has caused an upsurge, as this kind of material revealed a tremendous potential of application in areas such as energy storage, electronics, and gas separation. MXenes are referred to as a family of 2D transition metal carbides, carbonitrides, and nitrides. After the synthesis of Ti 3 C 2 from Ti 3 AlC 2 in 2011, about 30 new compositions have been reported. These materials have been widely discussed, synthesized, and i…

  PublisherOA PDFDOI

• Deep Learning-Based Composite Iterative Reconstruction Algorithm Improves High-Resolution MRI Quality of Hippocampus: A Dual-center Study

  Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition · 2025-09-16

  article1st authorCorresponding

  Motivation: High-resolution imaging of the hippocampus is essential for diagnosing neurological conditions; however, it is often limited by long scan times and low spatial resolution. Goal(s): To validate the effectiveness of a deep learning-based composite super-resolution reconstruction algorithm combining SRGAN with denoising and sharpening modules to enhance hippocampal image quality without increasing scan time. Approach: 106 patients from two medical centers with hippocampal MRI indication…

  PublisherDOI

• Airport Express Passenger Flow Prediction Based on “Time-Feature” Cooperative Attention

  Journal of applied artificial intelligence. · 2024-10-18

  articleSenior author

  Accurate prediction of airport express passenger flow is the basis for realizing intelligent, refined and efficient management and control of the airport rail transit system, and is of great significance to improving airport service levels and operational efficiency. Due to the numerous influencing factors that overlap with each other, and the complex mechanism of factors affecting passenger flow timing, accurate prediction of airport express passenger flow is extremely challenging. This paper p…

  PublisherDOI

Frequent coauthors

• Huifeng Xu

  Inner Mongolia People's Hospital

  50 shared

• Jiagen Li

  48 shared

• Rulin Liu

  Chinese University of Hong Kong, Shenzhen

  43 shared

• Yihua Lu

  Chinese University of Hong Kong, Shenzhen

  32 shared

• Haibin Su

  Hunan Xiangdian Test Research Institute (China)

  32 shared

• Guonan Chen

  Fuzhou University

  29 shared

• Zhenyu Lin

  Fuzhou University

  28 shared

• Jiechun Liang

  Chinese University of Hong Kong, Shenzhen

  27 shared

Education

• Ph.D

  Nanyang Technological University

  2011

• Bachelor of Science, Special Class for the Gifted Young

  University of Science and Technology of China

  2006

Similar researchers at University of Washington

• Weilin Kaoh-81
• Lü, Chanh-67
• Junyoung Kimh-64