Introduction:

This repository contains the key raw data analysed and discussed in the manuscript:

Estimation of semiconductor-like pigment concentrations in paint mixtures and their differentiation from paint layers using first-derivative reflectance spectra
Anuradha R. Pallipurath, Jonathan M. Skelton, Paola Ricciardi and Stephen R. Elliott
Talanta 154, 63-72 (2016)
DOI: 10.1016/j.talanta.2016.03.052

General:

This repository contains the complete set of fibre-optic reflectance spectra (FORS spectra) collected from the paint samples prepared for the work referenced above, together with the optimised structures and electronic density-of-states and band-dispersion curves obtained from the complementary modelling studies. Readers are referred to the manuscript for details of the study, the methodology used, and the results obtained. Any data from the paper or SI which is not available in this repository may be requested from the authors.

If you use the data in this repository for e.g. further analysis, testing processing algorithms, etc., please cite the following references:

•	A. R. Pallipurath, J. M. Skelton, P. Ricciardi and S. R. Elliott, Talanta 154, 63-72 (2016), DOI: 10.1016/j.talanta.2016.03.052

•	A. R. Pallipurath, J. M. Skelton, P. Ricciardi and S. R. Elliott, Data for “Estimation of semiconductor-like pigment concentrations in paint mixtures and their differentiation from paint layers using first-derivative reflectance spectra” (2016), DOI: 10.15125/BATH-00183

Available data:

The reflectance spectra and modelling results have been bundled into two GZip-compressed TAR-format archives for convenience, the contents of which are detailed below. The archives can be unpacked with the “tar” utility on Mac and Linux systems, and the free PeaZip software on Windows (http://www.peazip.org/; accessed 22/03/2016).
1. Reflectance-Spectra.tar.gz
This archive contains the complete set of FORS spectra recorded from the model paint films. The data are stored in a simple tab-separated plain-text format, which can be viewed in a text editor and easily imported into most data-analysis software (e.g. Microsoft Excel).

The spectra are organised into subfolders, one for each sample, named according to the convention:

“<Pigment(s)>_<SampleType>”

The “Pigment(s)” field lists the pigments used to make up the paint film, using the abbreviations employed in the article: “LW” - lead white, “LTY” - lead-tin yellow, “RL” - red lead, “VRM” - vermillion. The “SampleType” field lists the pigment composition, and may be one of “Pure”, “Glaze”, or the proportions of two pigments in wt. %.

Some illustrative examples:
•	“RL_Pure” - a paint made up with pure RL.
•	“LW-LTY_66.7-33.3” - a tint of LTY made up of 66.7 wt. % LW and 33.3 wt. % LTY.
•	“RL-VRM_Glaze” - a RL glaze on an underlayer of VRM.

Note that, in the case of glaze samples, the pigments are identified with the top-layer one first (e.g. “RL-VRM_Glaze” indicates a RL glaze on an underlayer of VRM, whereas “VRM-RL_Glaze” indicates the opposite).

Within the subfolders, the spectra are named according to the following convention:

“<Pigment(s)>_<SampleType>_Spectrum<SpectrumNumber>.<FileExtension>”

The first two fields are the same as in the subfolder names. “SpectrumNumber” is a sequential identifier, with each spectrum having been recorded from a different spot on the paint film. “FileExtension” identifies the type of the data, and is one of the following:

•	“.asd.sco.txt” - wavelength/reflectance data.
•	“.asd.sco.dv1.txt” - wavelength/first-derivative reflectance data.

As noted in the data-access statement in the manuscript, spectra recorded from the manuscript samples are not included in this archive. Readers who would like this data should contact the authors.
2. Computational-Modelling.tar.gz
This archive contains four data files for each of the three systems on which computational modelling was carried out, viz. SnPb2O4 (lead-tin yellow), tetragonal Pb3O4 (“Tet-Pb3O4”, red lead) and -HgS (“aHgS”, vermillion).

For each system, the following data is provided:

•	“*_OptimisedStructure.vasp”

These files contain the atomic coordinates and unit-cell parameters of the optimised structure in the POSCAR format used by the Vienna Ab initio Simulation Package (VASP) code, described at http://cms.mpi.univie.ac.at/vasp/guide/node59.html (accessed 27/03/2016). The structures can be visualised using a number of programs, including the free VESTA software (http://jp-minerals.org/vesta/en/; accessed 27/03/2016), which also has some file-conversion capability.

•	“*_TotalDOS.csv”

These files contain the calculated total electronic density-of-states (DoS) curves for each of the models, obtained at the PBEsol generalized-gradient approximation (GGA) level of theory, in the comma-separated values (CSV) format. The three columns contain the energy (referenced to the calculated Fermi energy, EF) and the number of states in the histogram bins, plus the cumulative integrated DoS (“IDoS”). CSV is a plain-text format, and the files can be viewed using a text editor or readily imported into data-analysis software such as Microsoft Excel.

•	“*_KPoints.csv” and “*_BandEnergies.csv”

These files contain the data from the electronic band-dispersion calculations, calculated, as for the DoS curves, at the PBEsol level of theory. This data is also stored in plain-text CSV-format files. The first file contains the index and coordinates (kx, ky, kz) of the k-points along the band path, together with the band indices, energies and occupations of the valence and conduction bands, and also the calculated direct bandgap, at each. The second file lists the energies and occupations of all the bands at each of the k-points; the k-points are labelled by indices corresponding to the entries in the matching “KPoints” file. As with the DoS data, all band energies are referenced to the Fermi energy.

As noted above, full technical details of these calculations can be found in the manuscript and electronic supporting information.