Carbon-Based Printed Thermoelectric Generator on Paper for Cold-Chain Monitoring
2023 Smart Systems Integration Conference and Exhibition (SSI)(2023)
Instituto de Microelectrónica de Barcelona. IMB-CNM (CSIC)
Abstract
Many essential goods need to be stored at specific temperatures throughout the production and distribution chain. Therefore, it becomes necessary to be able to continuously monitor the storage temperature of such products, possibly through inexpensive and environmentally friendly sensors. Here, we propose a self-powered sensor based on thermoelectric power generation. The thermoelectric generator, based on carbon materials, is in contact with the environment on one side and with a phase change material on the other. This allows the generation of a transient temperature difference whenever the sensor is exposed to an inappropriate temperature, which results in the generation of electrical energy that can be exploited to detect and report the exposure to such environment.
MoreTranslated text
Key words
self-powered sensor,flexible thermoelectric generator,cold-chain monitoring,carbon materials,carbon nanotubes,phase change material
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