Recent progress of thermoelectric applications for cooling/heating, power generation, heat flux sensor and potential prospect of their integrated applications

Huang, Liuyijie; Zheng, Yihua; Xing, Luyi; Hou, Benzhi

doi:10.1016/j.tsep.2023.102064

Cited by 13 publications

(2 citation statements)

References 130 publications

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“…The sensing principle of a thermoelectric tactile sensor ( Figure 4 a) is mainly based on thermoelectric effect [ 50 ]. The thermoelectric effect refers to the electrons in the object moving from the hotter region to the colder region due to the temperature difference, thereby generating current [ 50 ]. Thermal energy is one of the most commonly used types of clean energy, but thermoelectric tactile sensors have not been widely used thus far.…”

Section: Classification Of Self-powered Tactile Sensorsmentioning

confidence: 99%

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Recent Advances in Self-Powered Tactile Sensing for Wearable Electronics

Liu,

Li,

Lai

et al. 2024

Materials

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With the arrival of the Internet of Things era, the demand for tactile sensors continues to grow. However, traditional sensors mostly require an external power supply to meet real-time monitoring, which brings many drawbacks such as short service life, environmental pollution, and difficulty in replacement, which greatly limits their practical applications. Therefore, the development of a passive self-power supply of tactile sensors has become a research hotspot in academia and the industry. In this review, the development of self-powered tactile sensors in the past several years is introduced and discussed. First, the sensing principle of self-powered tactile sensors is introduced. After that, the main performance parameters of the tactile sensors are briefly discussed. Finally, the potential application prospects of the tactile sensors are discussed in detail.

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Section: Classification Of Self-powered Tactile Sensorsmentioning

confidence: 99%

Section: Classification Of Self-powered Tactile Sensorsmentioning

confidence: 99%

Recent Advances in Self-Powered Tactile Sensing for Wearable Electronics

Liu,

Li,

Lai

et al. 2024

Materials

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Predicting High‐Performance Thermoelectric Materials With StarryData2

Parse,

Recatala‐Gomez,

Zhu

et al. 2024

Advcd Theory and Sims

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In recent years, machine learning (ML) has emerged as a potential tool in the exploration of thermoelectric (TE) materials. This study exploits the StarryData2 public database to construct an ML model for predicting the figure‐of‐merit ZT of TE materials. The original dataset from StarryData2 (372,480 datapoints) underwent systematic cleaning, resulting in a refined dataset of 18,126 instances with 2,761 unique compounds. The cleaned data is employed to train an XGBoost regressor model, utilizing chemical formulas of TE compounds as features to predict ZT at given temperatures. The XGBoost regressor exhibited high prediction accuracy, achieving the coefficient of determination (R2) scores of 0.815 and mean absolute error (MAE) of 0.103 for the test set, further evaluated through cross‐validation across 5 folds. The learning curve analysis demonstrated improved model performance with increased training data. Furthermore, the contributions of different chemical descriptors to ZT are analyzed based on feature importance analysis. Beyond conventional TE families in the training set, the trained model is applied to predict ZT for promising unexplored TE materials and estimate optimal doping concentrations. This comprehensive study shows the impact of ML on TE material research, offering valuable insights and accelerating the discovery of materials with enhanced TE properties.

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Low thermal conductivity and high thermoelectric performance in Cu2Se/CuAgSe composite materials

Yu,

Fu,

et al. 2024

J Mater Sci: Mater Electron

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Recent progress of thermoelectric applications for cooling/heating, power generation, heat flux sensor and potential prospect of their integrated applications

Cited by 13 publications

References 130 publications

Recent Advances in Self-Powered Tactile Sensing for Wearable Electronics

Recent Advances in Self-Powered Tactile Sensing for Wearable Electronics

Predicting High‐Performance Thermoelectric Materials With StarryData2

Low thermal conductivity and high thermoelectric performance in Cu2Se/CuAgSe composite materials

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