IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i3p779-d730485.html
   My bibliography  Save this article

Machine Learning Approach for Maximizing Thermoelectric Properties of BiCuSeO and Discovering New Doping Element

Author

Listed:
  • Nuttawat Parse

    (Department of Physics, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand)

  • Chakrit Pongkitivanichkul

    (Department of Physics, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand)

  • Supree Pinitsoontorn

    (Institute of Nanomaterials Research and Innovation for Energy (IN-RIE), Khon Kaen University, Khon Kaen 40002, Thailand)

Abstract

Machine learning (ML) has increasingly received interest as a new approach to accelerating development in materials science. It has been applied to thermoelectric materials research for discovering new materials and designing experiments. Generally, the amount of data in thermoelectric materials research, especially experimental data, is very small leading to an undesirable ML model. In this work, the ML model for predicting ZT of the doped BiCuSeO was implemented. The method to improve the model was presented step-by-step. This included normalizing the experimental ZT of the doped BiCuSeO with the pristine BiCuSeO, selecting data for the BiCuSeO doped at Bi-site only, and limiting important features for the model construction. The modified model showed significant improvement, with the R 2 of 0.93, compared to the original model ( R 2 of 0.57). The model was validated and used to predict the ZT of the unknown doped BiCuSeO compounds. The predicted result was logically justified based on the thermoelectric principle. It means that the ML model can guide the experiments to improve the thermoelectric properties of BiCuSeO and can be extended to other materials.

Suggested Citation

  • Nuttawat Parse & Chakrit Pongkitivanichkul & Supree Pinitsoontorn, 2022. "Machine Learning Approach for Maximizing Thermoelectric Properties of BiCuSeO and Discovering New Doping Element," Energies, MDPI, vol. 15(3), pages 1-13, January.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:3:p:779-:d:730485
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/3/779/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/3/779/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mohamed Amine Zoui & Saïd Bentouba & John G. Stocholm & Mahmoud Bourouis, 2020. "A Review on Thermoelectric Generators: Progress and Applications," Energies, MDPI, vol. 13(14), pages 1-32, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sijing Zhu & Zheng Fan & Baoquan Feng & Runze Shi & Zexin Jiang & Ying Peng & Jie Gao & Lei Miao & Kunihito Koumoto, 2022. "Review on Wearable Thermoelectric Generators: From Devices to Applications," Energies, MDPI, vol. 15(9), pages 1-27, May.
    2. Tayfun Uyanık & Emir Ejder & Yasin Arslanoğlu & Yunus Yalman & Yacine Terriche & Chun-Lien Su & Josep M. Guerrero, 2022. "Thermoelectric Generators as an Alternative Energy Source in Shipboard Microgrids," Energies, MDPI, vol. 15(12), pages 1-14, June.
    3. Xiaoyu Liu & Chong Zhao & Hao Guo & Zhongcheng Wang, 2022. "Performance Analysis of Ship Exhaust Gas Temperature Differential Power Generation," Energies, MDPI, vol. 15(11), pages 1-17, May.
    4. Jian Li & Qingfeng Song & Ruiheng Liu & Hongliang Dong & Qihao Zhang & Xun Shi & Shengqiang Bai & Lidong Chen, 2022. "Thermoelectric Performance Optimization of n-Type La 3− x Sm x Te 4 /Ni Composites via Sm Doping," Energies, MDPI, vol. 15(7), pages 1-9, March.
    5. Zdenek Machacek & Wojciech Walendziuk & Vojtech Sotola & Zdenek Slanina & Radek Petras & Miroslav Schneider & Zdenek Masny & Adam Idzkowski & Jiri Koziorek, 2021. "An Investigation of Thermoelectric Generators Used as Energy Harvesters in a Water Consumption Meter Application," Energies, MDPI, vol. 14(13), pages 1-22, June.
    6. Mykola Moroz & Fiseha Tesfaye & Pavlo Demchenko & Myroslava Prokhorenko & Nataliya Yarema & Daniel Lindberg & Oleksandr Reshetnyak & Leena Hupa, 2021. "The Equilibrium Phase Formation and Thermodynamic Properties of Functional Tellurides in the Ag–Fe–Ge–Te System," Energies, MDPI, vol. 14(5), pages 1-15, February.
    7. Zhe Zhang & Yuqi Zhang & Xiaomei Sui & Wenbin Li & Daochun Xu, 2020. "Performance of Thermoelectric Power-Generation System for Sufficient Recovery and Reuse of Heat Accumulated at Cold Side of TEG with Water-Cooling Energy Exchange Circuit," Energies, MDPI, vol. 13(21), pages 1-18, October.
    8. Zoui, Mohamed Amine & Bentouba, Said & Velauthapillai, Dhayalan & Zioui, Nadjet & Bourouis, Mahmoud, 2022. "Design and characterization of a novel finned tubular thermoelectric generator for waste heat recovery," Energy, Elsevier, vol. 253(C).
    9. Krzysztof Sornek, 2021. "Study of Operation of the Thermoelectric Generators Dedicated to Wood-Fired Stoves," Energies, MDPI, vol. 14(19), pages 1-20, October.
    10. Daniel Sanin-Villa & Oscar Danilo Montoya & Luis Fernando Grisales-Noreña, 2023. "Material Property Characterization and Parameter Estimation of Thermoelectric Generator by Using a Master–Slave Strategy Based on Metaheuristics Techniques," Mathematics, MDPI, vol. 11(6), pages 1-19, March.
    11. Mohammed A. Qasim & Vladimir I. Velkin & Sergey E. Shcheklein, 2022. "The Experimental Investigation of a New Panel Design for Thermoelectric Power Generation to Maximize Output Power Using Solar Radiation," Energies, MDPI, vol. 15(9), pages 1-15, April.
    12. Sergii Mamykin & Roni Z. Shneck & Bohdan Dzundza & Feng Gao & Zinovi Dashevsky, 2023. "A Novel Solar System of Electricity and Heat," Energies, MDPI, vol. 16(7), pages 1-11, March.
    13. Mirosław Neska & Mirosław Mrozek & Marta Żurek-Mortka & Andrzej Majcher, 2021. "Analysis of the Parameters of the Two-Sections Hot Side Heat Exchanger of the Module with Thermoelectric Generators," Energies, MDPI, vol. 14(16), pages 1-15, August.
    14. Hegazy Rezk & Mohammed Mazen Alhato & Mujahed Al-Dhaifallah & Soufiene Bouallègue, 2021. "A Sine Cosine Algorithm-Based Fractional MPPT for Thermoelectric Generation System," Sustainability, MDPI, vol. 13(21), pages 1-17, October.
    15. Olukayode L. Ayodele & Doudou N. Luta & Mohammed T. Kahn, 2023. "A Micro-Nuclear Power Generator for Space Missions," Energies, MDPI, vol. 16(11), pages 1-18, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:15:y:2022:i:3:p:779-:d:730485. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.