Cooling Performance Prediction of Particle-Based Radiative Cooling Film Considering Particle Size Distribution
Here, we present a novel protocol concept for quantifying the cooling performance of particle-based radiative cooling (PBRC). PBRC, known for its high flexibility and scalability, emerges as a promising method for practical applications. The cooling power, one of the cooling performance indexes, is...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-02-01
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| Series: | Micromachines |
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| Online Access: | https://www.mdpi.com/2072-666X/15/3/292 |
| _version_ | 1797240005295341568 |
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| author | Jaehyun Lim Junbo Jung Jinsung Rho Joong Bae Kim |
| author_facet | Jaehyun Lim Junbo Jung Jinsung Rho Joong Bae Kim |
| author_sort | Jaehyun Lim |
| collection | DOAJ |
| description | Here, we present a novel protocol concept for quantifying the cooling performance of particle-based radiative cooling (PBRC). PBRC, known for its high flexibility and scalability, emerges as a promising method for practical applications. The cooling power, one of the cooling performance indexes, is the typical quantitative performance index, representing its cooling capability at the surface. One of the primary obstacles to predicting cooling power is the difficulty of simulating the non-uniform size and shape of micro-nanoparticles in the PBRC film. The present work aims to develop an accurate protocol for predicting the cooling power of PBRC film using image processing and regression analysis techniques. Specifically, the protocol considers the particle size distribution through circle object detection on SEM images and determines the probability density function based on a chi-square test. To validate the proposed protocol, a PBRC structure with PDMS/Al<sub>2</sub>O<sub>3</sub> micro-nanoparticles is fabricated, and the proposed protocol precisely predicts the measured cooling power with a 7.8% error. Through this validation, the proposed protocol proves its potential and reliability for the design of PBRC. |
| first_indexed | 2024-04-24T18:00:33Z |
| format | Article |
| id | doaj.art-7fb4e07ccf004bd79c421b128503293c |
| institution | Directory Open Access Journal |
| issn | 2072-666X |
| language | English |
| last_indexed | 2024-04-24T18:00:33Z |
| publishDate | 2024-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Micromachines |
| spelling | doaj.art-7fb4e07ccf004bd79c421b128503293c2024-03-27T13:54:55ZengMDPI AGMicromachines2072-666X2024-02-0115329210.3390/mi15030292Cooling Performance Prediction of Particle-Based Radiative Cooling Film Considering Particle Size DistributionJaehyun Lim0Junbo Jung1Jinsung Rho2Joong Bae Kim3Department of Mechanical Engineering, Kongju National University, Cheonan 31080, Republic of KoreaDepartment of Mechanical Engineering, Kongju National University, Cheonan 31080, Republic of KoreaDepartment of Mechanical Engineering, Hanbat National University, Daejeon 34158, Republic of KoreaDepartment of Mechanical and Automotive Engineering, Kongju National University, Cheonan 31080, Republic of KoreaHere, we present a novel protocol concept for quantifying the cooling performance of particle-based radiative cooling (PBRC). PBRC, known for its high flexibility and scalability, emerges as a promising method for practical applications. The cooling power, one of the cooling performance indexes, is the typical quantitative performance index, representing its cooling capability at the surface. One of the primary obstacles to predicting cooling power is the difficulty of simulating the non-uniform size and shape of micro-nanoparticles in the PBRC film. The present work aims to develop an accurate protocol for predicting the cooling power of PBRC film using image processing and regression analysis techniques. Specifically, the protocol considers the particle size distribution through circle object detection on SEM images and determines the probability density function based on a chi-square test. To validate the proposed protocol, a PBRC structure with PDMS/Al<sub>2</sub>O<sub>3</sub> micro-nanoparticles is fabricated, and the proposed protocol precisely predicts the measured cooling power with a 7.8% error. Through this validation, the proposed protocol proves its potential and reliability for the design of PBRC.https://www.mdpi.com/2072-666X/15/3/292radiative coolingmicro-nanoparticleregression analysisimage processingchi-square test |
| spellingShingle | Jaehyun Lim Junbo Jung Jinsung Rho Joong Bae Kim Cooling Performance Prediction of Particle-Based Radiative Cooling Film Considering Particle Size Distribution Micromachines radiative cooling micro-nanoparticle regression analysis image processing chi-square test |
| title | Cooling Performance Prediction of Particle-Based Radiative Cooling Film Considering Particle Size Distribution |
| title_full | Cooling Performance Prediction of Particle-Based Radiative Cooling Film Considering Particle Size Distribution |
| title_fullStr | Cooling Performance Prediction of Particle-Based Radiative Cooling Film Considering Particle Size Distribution |
| title_full_unstemmed | Cooling Performance Prediction of Particle-Based Radiative Cooling Film Considering Particle Size Distribution |
| title_short | Cooling Performance Prediction of Particle-Based Radiative Cooling Film Considering Particle Size Distribution |
| title_sort | cooling performance prediction of particle based radiative cooling film considering particle size distribution |
| topic | radiative cooling micro-nanoparticle regression analysis image processing chi-square test |
| url | https://www.mdpi.com/2072-666X/15/3/292 |
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