Gold4: Long-term stability dataset from an Aromascan A32S conducting polymer gas sensor array

Dataset overview This dataset contains raw and processed measurements acquired in a long-term repeatability and stability study of a conducting polymer gas sensor array. Measurements were obtained in 1999 using an Aromascan A32S analyser equipped with an autosampler (Aromascan plc / Osmetech plc, Crewe, UK). The instrument incorporated an array of 32 conducting polymer sensing elements, of which 18 were functional and used in the experiment. The study involved repeated measurements of n-butanol, ammonium chloride and propionic acid samples at different concentrations, together with the corresponding buffer and hydrochloric acid controls. Experimental conditions Samples were placed in 40 mL headspace vials and maintained at 22.0 ± 0.1 °C. Headspace vapour was transferred to the analyser through a heated transfer line. Following equilibration with the carrier gas, the sensor array was exposed to the sample vapour for 180 s. Sensor response was recorded as the relative change in electrical resistance (%ΔR/R) as a function of time. After sample exposure, clean carrier gas and a 1% ethanol/water vapour wash were used to remove residual analyte vapour before the next measurement. The sensor array was operated at 35.0 ± 0.05 °C. The repeated sample conditions include 0.1% and 1% n-butanol, 0.01%, 0.02% and 0.05% ammonium chloride, and propionic acid at 100, 200 and 500 ppm. Buffer and hydrochloric acid control measurements are also included. Data organization In version 2.0, the complete sensor response transients are provided directly as plain-text .txt files. The dataset contains 4,858 valid measurements, stored as read0.txt to read4857.txt. Each file contains the complete transient response for one experiment, comprising 17 sensor channels and 329 time samples. The file read4858.txt is empty and does not correspond to a valid measurement. It has been retained to preserve consistency with the original file sequence and should be ignored during analysis. The file read_label.txt contains the sample labels associated with the 4,858 valid measurements, in the same order as the numbered response files. Additional metadata are provided in wave_file_dates.csv and wave_block_dates.csv. Further information on the dataset structure and the relationship with the original data is provided in Dataset_Documentation_v2.0.pdf. Accessing the raw data Version 2.0 was created to provide direct access to the complete numerical sensor responses without requiring conversion of the original proprietary .DAT files. The plain-text format facilitates automated processing and import into common data-analysis environments such as MATLAB, Python and R. Version 1 of the dataset preserves the original .DAT files and the ARDat utility supplied with the original data. ARDat provides a graphical interface for inspecting individual measurements and allows users to select specific sensors and manually define the waveform region of interest before export. This interactive functionality is not preserved in the extracted .txt files distributed in version 2.0. Version 2.0 is more convenient for direct and automated analysis of the complete response transients, whereas version 1 remains useful when experiment-specific visual inspection or manual selection of sensors and waveform regions is required. Data source and acknowledgement The data were provided by Professor Krishna C. Persaud, Department of Chemical Engineering, The University of Manchester, United Kingdom. Suggested acknowledgement Aromascan plc A32S Conducting Polymer Dataset, courtesy Professor Krishna Persaud, University of Manchester. Publications using this dataset This dataset, or subsets of it, was used in the following publications: Padilla, M., Perera, A., Montoliu, I., Chaudry, A., Persaud, K., & Marco, S. (2010). Drift compensation of gas sensor array data by Orthogonal Signal Correction. Chemometrics and Intelligent Laboratory Systems, 100(1), 28–35. https://doi.org/10.1016/j.chemolab.2009.10.002 Ziyatdinov, A., Marco, S., Chaudry, A., Persaud, K., Caminal, P., & Perera, A. (2010). Drift compensation of gas sensor array data by common principal component analysis. Sensors and Actuators B: Chemical, 146(2), 460–465. https://doi.org/10.1016/j.snb.2009.11.034