Supplementary material for the publication "Thermodynamically consistent derivation of excess Raman spectra "
datacite.FundingReference.funderName | Deutsche Forschungsgemeinschaft | |
Contributing person | Bräuer, Andreas Siegfried (orcid: https://orcid.org/0000-0002-7816-4027) | |
Documentation of the data | Resource Type: Data: Raman spectra as .txt files Methods: Raman spectroscopy Modell: model for calculation of molar (excess) raman spectra as Python file | |
Description of the data | The supplementary material includes the raw spectra as .txt files as well as the Python code for data evaluation and visualization. A description on how the code works can be found in the 'Read me' file. | |
Type of the data | Dataset | |
Type of the data | Model | |
Total size of the dataset | 1342556 | |
Author | Bräuer, Andreas | |
Author | Willger, Miriam | |
Upload date | 2023-12-12T14:44:13Z | |
Upload date | 2026-06-08T12:24:01Z | |
Publication date | 2023-12-12T14:44:13Z | |
Publication date | 2026-06-08T12:24:01Z | |
Data of data creation | 2023 | |
Publication date | 2023-12-12 | |
Abstract of the dataset | The supplementary material includes all raw data used for the publication. These are the recorded mixture Raman spectra for the binary mixtures acetone-water, acetone-n-heptane, acetone-n-hexane, acetone-cyclohexane and acetone-ethanol at 25°C as .txt files. The files are located in the subfolders of the respective mixture name in the 'Data' folder. The 'Data' folder also contains the raman shift ('ramanshift' ,.txt) for all spectra. In addition, the literature data for the mixture densities and refractive indices can be found in the .xlsx file 'refractive_index_density'. The python code used for the evaluation, which is also used to generate the figures shown in the publication, can be found in the 'Code' folder. A description on how the code works can be found in the 'Read me' file. | |
Public reference to this page | https://opara.zih.tu-dresden.de/handle/123456789/2580 | |
Public reference to this page | https://doi.org/10.25532/OPARA-274 | |
dc.language | eng | |
Publisher | Technische Universität Bergakademie Freiberg | |
Licence | Attribution 4.0 International | |
URI of the licence text | http://creativecommons.org/licenses/by/4.0/ | |
Specification of the discipline(s) | 4 | |
Title of the dataset | Supplementary material for the publication "Thermodynamically consistent derivation of excess Raman spectra " | |
Research instruments | Cobolt Samba,532 nm, 1 W | |
Research instruments | Ocean Optics QE Pro | |
Software | Python (Version 3.9) | |
Project abstract | Excess properties of mixtures quantify the difference of the property of a real and an ideal mixture at identical temperature, pressure and composition. According to the “state-of-the-art” the excess Gibbs energy of a mixture can be extracted via partial least squares regression (PLSR) from the excess absorption spectrum of the same mixture. The correlations of excess properties of mixtures feature two disadvantages: (i) they are a function of the mixture compounds. Thus, mixtures of various “families”, such as ketone/alkane or ketone/alcohol, cannot be reflected with one and the same correlation. (ii) The desired activity coefficients can be obtained having fitted gE models to the gE values that resulted from the correlations. These disadvantages can be circumvented, if partial excess properties of the mixture compounds are regarded instead of excess properties of mixtures. Therefore, this project aims at correlating the partial excess Raman spectrum of the mixture compounds with their activity coefficients. The proposed correlation of partial excess properties of mixture compounds features two advantages compared to the “state-of-the-art”: (i) As partial excess properties are regarded, the identified correlations are supposed to be more independent from the mixture family. The degree of independence from the mixture family depends on the correlation method, because of which machine learning methods will be made use of that can regard linear (partial least squares regression) as well as non-linear (convolutional neural networks) relations. (ii) The desired activity coefficients result directly from the identified correlations and do not have to be obtained by fitting first the interaction parameters of gE models. The identified correlations of partial excess properties will enable the experimental Raman spectroscopic determination of activity coefficients of the compounds in a mixture without the need of measuring phase equilibria. | |
Project title | DFG- BR 3766/27-1: Determination of activity coefficients from partial excess Raman spectra |
Files
Original bundle
- Name:
- refractive_index_density.xlsx
- Size:
- 15.85 KB
- Format:
- Microsoft Excel XML
- Description:
- 03 Refracive_index_density
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