About

Dr. Yao Fu is an Associate Professor in the Kevin T. Crofton Department of Aerospace and Ocean Engineering at Virginia Tech, having joined the department in 2021. She holds a Ph.D. in mechanical engineering from the University of Pittsburgh and has conducted postdoctoral studies at the University of South Carolina, University of Colorado Boulder, and Oak Ridge National Laboratory. Her research focuses on the computationally guided prediction and evaluation of materials degradation in high-temperature and corrosive environments, as well as innovative materials design and manufacturing. Dr. Fu's expertise includes materials behaviors under harsh conditions, multiphysics simulation of materials behaviors, and the development of advanced materials for demanding applications. She is actively involved in professional societies such as the International Association for Computational Mechanics, the United States Association for Computational Mechanics, and the Minerals, Metals & Materials Society. Her contributions have been recognized with awards including the NSF CAREER Award in 2021, the ONR Young Investigator Award in 2021, and the Outstanding New Assistant Professor award from Virginia Tech's College of Engineering in 2022.

Research topics

• Composite material
• Materials science
• Thermodynamics
• Nanotechnology
• Physics

Selected publications

• Laser defocus regulates melt pool stability and performance in laser powder bed fused 316 L stainless steels

  Materials Today Communications · 2026-03-01

  articleOpen accessSenior author
  PublisherDOI

• Evaluation of Chronic Disease Management Services in Primary Healthcare Institutions in Huili City: A Cross-Sectional Study Based on the ACIC Scale

  Research Square · 2025-10-08

  preprintOpen access
  PublisherOA PDFDOI

• The highly specific fluorescence visualization of mitochondrial peroxynitrite <i>via</i> a naphthalimide probe

  Analytical Methods · 2025-01-01 · 2 citations

  article

  A concise naphthalimide fluorescent probe was rationally designed and synthesized for specifically tracking mitochondrial peroxynitrite.

  PublisherDOI

• Nuclear power system based on open Brayton cycle for Mars base: configuration comparison and performance assessment

  Applied Thermal Engineering · 2025-08-10 · 3 citations

  article
  PublisherDOI

• Effect of defocus distance and energy density on melt pool morphology, surface roughness, and grain orientation of 70/30 copper-nickel alloy in laser powder bed fusion

  Materials Characterization · 2025-10-04 · 1 citations

  articleSenior authorCorresponding
  PublisherDOI

• Investigation the thermodynamic performance of closed Brayton cycle with CO2-based binary mixtures for hypersonic vehicle power generation systems under finite cold source

  Thermal Science and Engineering Progress · 2025-05-28 · 3 citations

  article
  PublisherDOI

• The Intrinsic Mechanism and Enhancement Pathways of Online Social Science Popularization Effectiveness

  Scientific and Social Research · 2025-06-06

  articleOpen accessSenior author

  In recent years, social philosophy has emphasized that the popularization of social sciences is a crucial means to enhance citizens’ social scientific literacy and ideological-moral standards, promoting comprehensive individual development and the progress of social civilization. As an important channel for such efforts, online social science dissemination plays a significant role in advancing its reach. However, the current effectiveness of online dissemination still faces numerous challenges. Therefore, this study analyzes the weight of factors influencing online social science popularization based on questionnaire data and identified issues. Furthermore, drawing on DeFleur’s Interactive Process Model, a closed-loop framework is constructed, encompassing subject encoding, channel communication, audience decoding, and feedback regulation. This model reveals the interaction among subject control, channel algorithm optimization, and audience demand responsiveness. Based on the findings, solutions are proposed through three pathways: internal dynamics, external dynamics, and feedback regulation mechanisms. These include expanding the scope of popularization subjects via policy incentives, enabling targeted content delivery through technological empowerment, and establishing digital feedback mechanisms. The study aims to provide decision-making support for governments in optimizing resource allocation for social science popularization and setting technical standards for online dissemination, thereby contributing to rural revitalization and the improvement of citizens’ scientific literacy.

  PublisherOA PDFDOI

• Corrosion evaluation and microstructural characteristics of 70/30 copper-nickel alloy fabricated by laser powder bed fusion

  Journal of Alloys and Metallurgical Systems · 2025-01-14 · 4 citations

  articleOpen accessSenior authorCorresponding

  This study explored the fabrication of 70/30 Cu-Ni via LPBF technique and investigated its corrosion and microstructure properties. Samples were fabricated with varied parameters, including power, scan rate, and hatch spacing, and compared with wrought Cu-Ni alloy. Corrosion behaviour was conducted using cyclic polarization and EIS in 3.5 wt% NaCl. Optical microscopy and EBSD techniques were employed for microstructure evaluation. The results revealed that the examined LPBF samples had surface porosities below 1 %, indicating superior density and minimal voids, with larger grain sizes displaying elongated grain. Additionally, LPBF samples exhibited delayed breakdown passive layer potential, superior repassivation abilities compared to the wrought specimen. EIS analysis revealed corrosion resistance of as-fabricated samples was slightly higher than conventional ones, peaking at 58–73 kΩ.cm 2 with hatch spacing between 125 and 200 μm and P/V ratio between 1.7 and 2 J/mm. However, deviation in parameters led to a decrease in corrosion resistance.

  PublisherDOI

• A Fine-Grained Aircraft Target Recognition Algorithm for Remote Sensing Images Based on YOLOV8

  IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · 2025-01-01 · 6 citations

  articleOpen access

  Fine-grained recognition plays a pivotal role in the field of remote sensing image analysis, particularly in critical applications such as reconnaissance and early warning, intelligence analysis, and intelligent interpretation. However, the extensive coverage of remote sensing images, the low pixel ratio of targets, and the subtlety of features pose significant challenges for finegrained recognition of aircraft targets. This article addresses the issues of missed and false detections in existing aircraft target fine-grained recognition algorithms for remote sensing images by proposing an improved algorithm based on YOLOv8, called FDYOLOv8 (Focus Detail-YOLOv8). Initially, this article designs a Local Detail Feature Module (LDFM) to tackle the problem of information loss in shallow networks. This module enhances the capture of semantic information while extracting shallow features, thereby preserving more fine-grained features and improving the network's feature extraction capability. Subsequently, a Focus Modulation Mechanism (FMM) is employed to enhance the network's interactive understanding of local and global features, thereby improving the recognition accuracy for small and challenging targets. Finally, a Multi-Type Feature Fusion (MTFF) is designed, which optimizes the generation of feature maps by integrating local features, high-level semantic information, and low-level texture information, enhancing the accuracy of finegrained target recognition. Experiments conducted on the public remote sensing image dataset FAIR1M demonstrated that the YOLOv8n algorithm achieved a mean Average Precision (mAP) of 81.8% for aircraft category recognition tasks. In contrast, FDYOLOv8 exhibited superor performance, with an mAP of 85.0%, indicating a significant advantage in fine-grained recognition.

  PublisherDOI

• Phase Field Numerical Model for Simulating the Diffusion Controlled Stress Corrosion Cracking Phenomena in Anisotropic Material

  ECS Meeting Abstracts · 2025-07-11

  articleSenior author

  In this study, we develop a phase field numerical model to simulate diffusion-controlled stress corrosion cracking (SCC) in anisotropic materials. Our model is based on multiphysics model involving the electrochemical process, the mechanical response of the material, and the coupling between them. The corrosion system consists of a metallic solid phase immersed in an electrolyte, initially protected by a passive film. The model captures the breakdown of this film, leading to localized pitting corrosion, which subsequently evolves into stress corrosion cracking under the influence of mechanical stress. We employ the Allen-Cahn equation to describe the evolution of the non-conserved phase field variable, representing the metal-electrolyte interface, and the Cahn-Hilliard equation to account for the concentration field dynamics, ensuring volume conservation. The mechanical behavior of the anisotropic material is modeled using crystal plasticity, which accounts for the elastic and plastic deformation of the material, with the degradation due to corrosion incorporated into the stress-strain relationship. We analyze the transition from pitting to cracking in single crystalline, bi-crystalline, and polycrystalline structures. The results demonstrate the capability of the model to capture the complex interactions between electrochemical corrosion and mechanical deformation, providing insights into the pit-to-crack transition in anisotropic materials. The developed phase field numerical model presents a significant advancement in understanding and simulating SCC phenomena, with potential applications in various engineering fields where corrosion is a critical concern.

  PublisherDOI

Recent grants

• Fundamental Mechanisms in Stress-Aided Variant Selection of Nanoscale Precipitation

  NSF · $425k · 2021–2026

• CDS&E/Collaborative Research: In-Situ Monitoring-Enabled Multiscale Modeling and Optimization for Environmental and Mechanical Performance of Advanced Manufactured Materials

  NSF · $369k · 2023–2027

• CAREER: Understanding the Corrosion Fatigue Behavior of Additively Processed Metals through an Integrated Experimental and Computational Approach

  NSF · $627k · 2021–2026

Frequent coauthors

• Xiaonan Jiang

  Market Matters

  16 shared

• Albert C. To

  University of Pittsburgh

  16 shared

• Chengrui Yu

  Changchun Institute of Optics, Fine Mechanics and Physics

  12 shared

• Haçène Serrai

  12 shared

• Xiangzhi Li

  12 shared

• Jeong‐Hoon Song

  University of Colorado Boulder

  10 shared

• Qing‐Xiang Guo

  10 shared

• Jie Song

  Collaborative Innovation Center of Advanced Microstructures

  9 shared

Education

• PhD, Mechanical Engineering

  University of Pittsburgh

  2013

• MS

  Institute of Metal Research Chinese Academy of Sciences

  2009

Awards & honors

• Outstanding New Assistant Professor, College of Engineering,…
• ONR Young Investigator Award, Office of Naval Research (2021…
• CAREER Award, National Science Foundation (2021)