• Title of article

    Chemical class information in ion mobility spectra at low and elevated temperatures

  • Author/Authors

    Eiceman، G.A. نويسنده , , Nazarov، E.G. نويسنده , , Rodriguez، J.E. نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2001
  • Pages
    -52
  • From page
    53
  • To page
    0
  • Abstract
    Modified subcritical water is proposed as an extractant for the development of a liquid-liquid extraction method for the demetalisation of used industrial oils. The two immiscible liquid phases (the used oil and water modified with 4% (v/v) HNO3+0.1M KCl) enter into contact in an approach designed by the authors, consisting of an extraction coil in stainless steel located into an electrically heated oven. After close contact between the two immiscible phases for proper mass transfer, the oil-water segments leave the oven through the restrictor, then are cooled by passage through a coil located in a bath at room temperature. Spontaneous separation of both phases takes place in the collection flask at the end of the cooling coil. The metals (Cu, V, Pb, Ni, Cd and Cr) extracted into the aqueous phase are determined by graphite furnace atomic absorption spectrometry. An in-depth study of variables affecting the demetalisation-extraction step as well as those concerning the hydrodynamic variables was performed. The method was validated using a Certified Reference Material (C.R.M. 1086a; Wear Metals in Oil, N.I.S.T., Gaithersburg, MA) and applied to five different used industrial oils. A residence time of 270s provides oil samples purified to 75, 85, 95, 90, 98 and 90% (with respect to the initial concentration of each metal in the oil) for Cu, V, Pb, Cd, Cr and Ni, respectively. While the extraction time was 270s, the complete method was achieved in about 40min. The proposed approach proves to be cheap, quick and avoids handling the organic samples.
  • Keywords
    Mobility spectra , Fragment ion , Atmospheric pressure chemical ionization , Ion mobility spectrometry , Spectral library , Neural networks
  • Journal title
    Analytica Chimica Acta
  • Serial Year
    2001
  • Journal title
    Analytica Chimica Acta
  • Record number

    49275