1. 2016
  2. Peak deconvolution to correctly assess the band broadening of chromatographic columns

    Vanderheyden, Y., Broeckhoven, K. & Desmet, G. 23 Sep 2016 In : Journal of Chromatography A. 1465, p. 126-142 16 p.

    Research output: Research - peer-reviewArticle

  3. Electrochemical characterisation of a microfluidic reactor for cogeneration of chemicals and electricity

    Wouters, B., Hereijgers, J., De Malsche, W., Breugelmans, T. & Hubin, A. 20 Aug 2016 In : Electrochimica Acta. 210, p. 337-345

    Research output: Research - peer-reviewArticle

  4. Effect of reference conditions on flow rate, modifier fraction and retention in supercritical fluid chromatography

    De Pauw, R., Choikhet, K., Desmet, G. & Broeckhoven, K. 12 Aug 2016 In : Journal of Chromatography A. 1459, p. 129-135 7 p.

    Research output: Research - peer-reviewArticle

  5. A robust multistage mesoflow reactor for liquid-liquid extraction for the separation of Co/Ni with cyanex 272

    Vandermeersch, T., Gevers, L. & De Malsche, W. 10 Aug 2016 In : Separation and Purification Technology. 168, p. 32-38 7 p.

    Research output: Research - peer-reviewArticle

  6. Geometry influence on corrosion in dynamic thin film electrolytes

    Simillion, H., Van den Steen, N., Terryn, H. & Deconinck, J. 10 Aug 2016 In : Electrochimica Acta. 209, p. 149-158

    Research output: Research - peer-reviewArticle

  7. Theoretical study of the effect of trickle phase conditions on competitive adsorption in packed bed adsorption columns

    De Schepper, P. R. & Denayer, J. 1 Aug 2016 In : Chemical Engineering Journal. 297, p. 35-44 10 p.

    Research output: Research - peer-reviewArticle

  8. Cathode flow field design for nitric oxide/hydrogen fuel cell in cogeneration of hydroxylamine and electricity

    De Schepper, P. R., Danilov, V. & Denayer, J. Aug 2016 In : International Journal of Energy research. 40, 10, p. 1355-1366 12 p.

    Research output: Research - peer-reviewArticle

  9. Towards a chromatographic similarity index to establish localized QSRR models for retention prediction: use of retention time ratio

    Tyteca, E., Talebi, M., Amos, R., Park, S. H., Taraji, M., Haddad, P. & Szucs, R. Aug 2016

    Research output: ResearchPoster

ID: 20154