A novel machine learning workflow to optimize cooling devices grounded in solid-state physics.
- DOI
- 10.1038/s41598-024-80212-9
- Published
- 2024 Nov 18
- Container
- Scientific reports
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1038/s41598-024-80212-9,
title = {A novel machine learning workflow to optimize cooling devices grounded in solid-state physics.},
author = {Fernandez JG and Etesse G and Seoane N and Comesaña E and Hirakawa K and Garcia-Loureiro A and Bescond M},
year = {2024},
journal = {Scientific reports},
doi = {10.1038/s41598-024-80212-9},
url = {https://doi.org/10.1038/s41598-024-80212-9}
}RIS
TY - JOUR TI - A novel machine learning workflow to optimize cooling devices grounded in solid-state physics. AU - Fernandez JG AU - Etesse G AU - Seoane N AU - Comesaña E AU - Hirakawa K AU - Garcia-Loureiro A AU - Bescond M PY - 2024 JO - Scientific reports DO - 10.1038/s41598-024-80212-9 UR - https://doi.org/10.1038/s41598-024-80212-9 ER -
APA
JG, F., G, E., N, S., E, C., K, H., A, G., & M, B. (2024). A novel machine learning workflow to optimize cooling devices grounded in solid-state physics.. Scientific reports. https://doi.org/10.1038/s41598-024-80212-9
Source records
- pubmed · retrieved 2026-09-25T22:17:46.200Z