Gradient Method Optimization

Gradient Method Optimization is a systematic analytical approach within chromatographic method development that distinguishes itself by iteratively refining the solvent gradient profile to enhance resolution, minimize run time, and improve peak shape in the separation of complex mixtures.

2.3K

Publications

145.3K

Citations

6.1K

Authors

1.8K

Institutions

Publications per year

2017–2026

726

Authors

6.1K

  1. JR
    Joaquim R. R. A. Martins

    University of Michigan, United States

    15 publications · 1.6K citations

    13

    h-index

  2. JD
    J. D. Jansen

    Delft University of Technology, Netherlands

    13 publications · 874 citations

    12

    h-index

  3. KL
    Kok Lay Teo

    Curtin University, Australia

    10 publications · 352 citations

    10

    h-index

  4. AN
    Andrew Ning

    Brigham Young University, United States

    10 publications · 405 citations

    10

    h-index

  5. JT
    John T. Hwang

    University of Michigan, United States

    9 publications · 928 citations

    9

    h-index

1–5 of 6.1K

Venues

  1. arXiv (Cornell University)

    Repository · 73 publications · 4.7K citations

    33

    h-index

  2. Journal of Chromatography A

    44 publications · 1.5K citations

    24

    h-index

  3. SIAM Journal on Optimization

    25 publications · 6.5K citations

    23

    h-index

  4. AIAA Journal

    22 publications · 806 citations

    17

    h-index

  5. Inverse Problems

    17 publications · 1.1K citations

    16

    h-index

1–5