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Dataset related to publication: Nanoporous Film Layers to Enhance the Performance of Passive Radiative Cooling Paint Mixtures

<p>Dataset related to the publication:</p> <p><em>Giuseppe Emanuele Lio,</em><em>&nbsp;Sara Levorin</em><em>, Atakan Erdoğan</em><em>, J&eacute;r&eacute;my Werl&eacute;</em><em>, Alain J. Corso</em><em>, Luca&nbsp;</em><em>Schenato</em><em>, Diederik S. Wiersma</em><em>, Marco Santagiustina</em><em>, Lorenzo Pattelli</em><em>, Maria Guglielmina Pelizzo.&nbsp;</em><em>Nanoporous Film Layers to Enhance the Performance of Passive Radiative Cooling Paint Mixtures, accepted and in publishing on International Journal of Thermophysics. </em>DOI: 10.1007/s10765-024-03439-8</p> <p>The repository contains the temperature, relative humidity, irradiance, sky temperature and net cooling power measurements in the file named "DATA_IJT_Nanoporous_Film_ Layer.txt" and the python script (Data_analizer.py) to analyze them as done in the paper.</p> <p>&nbsp;</p> <p>The repository also contain the Matlab workspace (IJT_data.mat)and code (Data_R_ATR_analyzer)to evaluate all the sample reflectance and FTIR measurements. Moreover, the extra measurements performed on the Celgard thin film are available in the workspace "Celgard_UV_VIS_NIR_T.mat" and "R_Celgard.mat". Moreover in Version 2 all the used data for Reflectance and Transmittance are also available in "txt" format for a simple and fast usage.&nbsp;</p> <p>&nbsp;</p> <h2>Notes (English)</h2> <div> <table> <tbody> <tr> <td> <p>This work was partly supported by</p> <ul> <li>European Project 21GRD03 PaRaMetriC, which received funding from the European Partnership on Metrology, co-financed by the European Union's Horizon Europe Research and Innovation Programme, and from the Participating States.</li> <li>European Union - PON Research and Innovation 2014-2020 in accordance with Article 24, paragraph 3a), of Law No. 240 of December 30, 2010, as amended, and Ministerial Decree No. 1062 of August 10, 2021</li> </ul> </td> </tr> </tbody> </table> </div>

ShareScore

44/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
8
Harmonization
4
Access
20
Reuse readiness
8
Engagement
4

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