Spectral Deconvolution

Spectral Deconvolution is a computational analytical technique used in spectroscopic analysis that resolves an overlapping composite spectrum into its constituent individual spectral components by applying mathematical models to separate convoluted signals originating from multiple sources or transitions.

1.2K

Publications

70K

Citations

3.4K

Authors

1.2K

Institutions

Publications per year

2017–2026

213

Authors

3.4K

  1. GA
    Gareth A. Morris

    University of Manchester, United Kingdom

    13 publications · 771 citations

    13

    h-index

  2. MG
    Marc Garland

    Institute of Chemical and Engineering Sciences, Singapore

    9 publications · 207 citations

    9

    h-index

  3. ZZ
    Zhaoli Zhang

    Central China Normal University, China

    9 publications · 411 citations

    9

    h-index

  4. GK
    G. Kitis

    Aristotle University of Thessaloniki, Greece

    8 publications · 662 citations

    8

    h-index

  5. MN
    Mathias Nilsson

    University of Manchester, United Kingdom

    7 publications · 439 citations

    7

    h-index

1–5 of 3.4K

Venues

  1. Applied Spectroscopy

    75 publications · 4K citations

    33

    h-index

  2. Analytical Chemistry

    44 publications · 2.2K citations

    26

    h-index

  3. Journal of Magnetic Resonance (1969)

    33 publications · 2.4K citations

    21

    h-index

  4. Applied Optics

    24 publications · 972 citations

    17

    h-index

  5. Journal of Magnetic Resonance

    JMR · 26 publications · 685 citations

    17

    h-index

1–5