Haibiao Yu

ORCID: 0000-0003-1471-2730
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Research Areas
  • Catalytic Processes in Materials Science
  • Catalysis and Oxidation Reactions
  • Industrial Gas Emission Control
  • Supercapacitor Materials and Fabrication
  • Catalysis and Hydrodesulfurization Studies
  • Extraction and Separation Processes
  • Catalysis for Biomass Conversion
  • Radioactive element chemistry and processing
  • Chemical Synthesis and Characterization
  • Adsorption and biosorption for pollutant removal
  • Ammonia Synthesis and Nitrogen Reduction
  • Advancements in Battery Materials
  • Covalent Organic Framework Applications
  • Advanced battery technologies research
  • Nanomaterials for catalytic reactions
  • Electrocatalysts for Energy Conversion
  • Catalysts for Methane Reforming
  • Zeolite Catalysis and Synthesis
  • Electrochemical Analysis and Applications
  • Advanced Photocatalysis Techniques
  • Mesoporous Materials and Catalysis
  • Copper-based nanomaterials and applications
  • Advanced Cellulose Research Studies
  • Natural Fiber Reinforced Composites
  • Electrospun Nanofibers in Biomedical Applications

Liaoning University
2008-2025

Inner Mongolia Agricultural University
2018-2020

Hefei University of Technology
2019

Dalian University of Technology
2014-2018

Liaoning Shihua University
2008

Abstract Form‐stable phase change materials (PCMs) have great potential to regulate the unbalanced heat demand and supply, yet most of PCMs are in powder, plate, or bulk rigid forms, difficult adhere source target substrates. Herein, coatings based on reactive poly(ethylene glycol) (RPEG) developed for direct thermal energy exchange storage. RPEG with highly silanol groups is obtained by reaction PEG 3‐isocyanatopropyltriethoxysilane (IPTS), followed hydrolyzation weak acid. Cross‐linked...

10.1002/adfm.202108000 article EN Advanced Functional Materials 2021-11-25

10.1016/j.apcatb.2015.12.011 article EN Applied Catalysis B Environment and Energy 2015-12-12

The nonlinear characteristics of wind power series and random fluctuation resources have a harmful effect on stability prediction. This paper proposes novel hybrid short-term prediction model for improving precision Firstly, the non-stationary time is decomposed by complete ensemble empirical mode decomposition - Lempel-Ziv complexity (CEEMD-LZC). Secondly, local linear embedding (LLE) used to reduce dimension meteorological data with maintaining essential structure data. integrated...

10.1109/access.2019.2936828 article EN cc-by IEEE Access 2019-01-01
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