Performance Analysis of IPMC Electrode Based on the Densest Packing Principle
Journal of materials research/Pratt's guide to venture capital sources（2021）
Xi’an Jiaotong University
Abstract
Based on the deposition and permeation of metal particles during the formation of IPMC electrode, the microstructure of the electrode was analyzed. In combination with the principle of the most compact packing, the electrode is modeled by the face-centered cubic most compact packing and the hexagonal crystal system. Finally, the model is verified by experiments. The results show that the predicted values are in good agreement with the experimental data, and the relative error is small. The influences of packing density, coincidence ratio, electrode thickness and particle radius on the resistance and capacitance of IPMC are discussed. By controlling these parameters effectively, the electric properties of IPMC electrodes can be designed, the ideal actuators and sensors can be prepared, and the potential application range of IPMC can be expanded.
MoreTranslated text
Key words
Composite,Modeling,Polymer,Electrical properties
求助PDF
上传PDF
View via Publisher
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