Optical n(p, T_90) measurement suite 1: He, Ar, and N_2
Supplemental material to the article "Optical n(p, T_90) measurement suite 1: He, Ar, and N_2" by PF Egan and Y Yang in International Journal of Thermophysics 2023.The archive file contains research data and analysis scripts as follows:* The n(p, T_90) dataset for helium. A Python script analyzes the data to produce the estimate of temperature-dependent compressibility, and reproduces Fig. 2 from the article.* The n(p, T_90) dataset for argon. A Python script analyzes the data to determine T - T_90, and reproduces Fig. 3 from the article. Additionally, the output data T - T_90 (Table 2 in the article) are included in a separate text file, together with the estimated uncertainty in the determination. The Python script includes the further analysis undertaken on the nonlinear terms B and C to reproduce Fig. 6.* The n(p, T_90) dataset for nitrogen. A Python script analyzes the data to reveal the temperature-dependence of polarizability, and reproduce Fig. 4. The script includes the further analysis undertaken on the nonlinear terms B and C to reproduce Fig. 7.* A Python script uses argon and nitrogen results from the present work to reproduce Fig. 5, a graphical depiction of difference with literature for the second density virial coefficient B_p.
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| accessLevel | public |
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| description | Supplemental material to the article "Optical n(p, T_90) measurement suite 1: He, Ar, and N_2" by PF Egan and Y Yang in International Journal of Thermophysics 2023.The archive file contains research data and analysis scripts as follows:* The n(p, T_90) dataset for helium. A Python script analyzes the data to produce the estimate of temperature-dependent compressibility, and reproduces Fig. 2 from the article.* The n(p, T_90) dataset for argon. A Python script analyzes the data to determine T - T_90, and reproduces Fig. 3 from the article. Additionally, the output data T - T_90 (Table 2 in the article) are included in a separate text file, together with the estimated uncertainty in the determination. The Python script includes the further analysis undertaken on the nonlinear terms B and C to reproduce Fig. 6.* The n(p, T_90) dataset for nitrogen. A Python script analyzes the data to reveal the temperature-dependence of polarizability, and reproduce Fig. 4. The script includes the further analysis undertaken on the nonlinear terms B and C to reproduce Fig. 7.* A Python script uses argon and nitrogen results from the present work to reproduce Fig. 5, a graphical depiction of difference with literature for the second density virial coefficient B_p. |
| distribution |
[
{
"title": "Supplemental material to article",
"mediaType": "application/x-zip-compressed",
"description": "The n(p,T_90) datasets for helium, argon, and nitrogen, plus the analysis scripts",
"downloadURL": "https://data.nist.gov/od/ds/mds2-3106/egan-npT-supp.zip"
},
{
"title": "egan-npT-supp",
"mediaType": "application/zip",
"downloadURL": "https://data.nist.gov/od/ds/mds2-3054/egan-npT-supp.zip"
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| identifier | ark:/88434/mds2-3054 |
| issued | 2023-08-31 |
| keyword |
[
"Refractometry",
"interferometry",
"polarizability",
"thermodynamic metrology"
]
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| landingPage | https://data.nist.gov/od/id/mds2-3054 |
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| license | https://www.nist.gov/open/license |
| modified | 2023-08-01 00:00:00 |
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"name": "National Institute of Standards and Technology",
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| replaces | ark:/88434/mds2-3054 |
| theme |
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"Metrology:Thermometry metrology"
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|
| title | Optical n(p, T_90) measurement suite 1: He, Ar, and N_2 |
