WeChat Mini Program
Old Version Features

Preparation and Characterization of Ni–SiO2 Composite Coating on Pipeline Inner Surface

JOURNAL OF MATERIALS SCIENCE(2024)

Henan Institute of Science and Technology

Cited 1|Views4
Abstract
A novel Ni–SiO2 composite deposition layer was created in the inner wall of the pipe adopting a new type of brush plating device, and the properties of the deposition layer were characterized; experimental results show that the nanocomposite deposition layer significantly improves the mechanical properties and corrosion resistance of the inner wall of the pipe. Firstly, under the conditions of nanoparticle addition (40 mL/L, 60 mL/L, 80 mL/L), working voltage (12 V, 14 V, 16 V) and pH (5, 7, 9), the hardness value and surface morphology of deposited layer were investigated through orthogonal experiments, and the optimal process variables were preliminarily determined. Orthogonal experiment results show that when the addition of nanoparticles is 80 mL/L, the voltage is 14 V, and the pH value is 7, the Ni–SiO2 nanocomposite deposition layer has high microhardness (618.6 HV) and good microscopic morphology. According to the analysis of the results of the orthogonal experiment, the addition amounts of nanoparticles is the main influencing factor, so the control variable method is utilized to investigate the effect of the addition amounts of nanoparticles on the properties of the deposited layer. The results show that when the amounts of nanoparticles added is 80 mL/L, the surface of deposited layer is smoother, denser and less defective. Moreover, the deposited layer has excellent mechanical property and corrosion resistance. In a solution of 3.5
More
Translated text
Key words
Nano-composites,Nanostructured Coatings
求助PDF
上传PDF
Bibtex
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
  • Pretraining has recently greatly promoted the development of natural language processing (NLP)
  • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
  • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
  • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
  • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined