Top-down Coarse-graining

Top-Down Coarse-Graining is a coarse-graining methodology that belongs to the class of modeling approaches which derive simplified representations by enforcing consistency with macroscopic observables or experimental data, distinguished by its imposition of global constraints to define effective interactions without explicit reference to underlying microscopic details.

10

Publications

575

Citations

32

Authors

25

Institutions

Publications per year

2017–2026

6

Authors

32

  1. PP
    Petr Plecháč

    University of Delaware, United States

    2 publications · 27 citations

    2

    h-index

  2. MA
    Markos A. Katsoulakis

    University of Massachusetts Amherst, United States

    2 publications · 27 citations

    2

    h-index

  3. WP
    Wenxiao Pan

    Pacific Northwest National Laboratory, United States

    1 publications · 26 citations

    1

    h-index

  4. AZ
    Athanassios Z. Panagiotopoulos

    Princeton University, United States

    1 publications · 87 citations

    1

    h-index

  5. AC
    Alexandros Chremos

    National Institute of Standards and Technology, United States

    1 publications · 87 citations

    1

    h-index

1–5 of 32

Venues

  1. Journal of Computational Physics

    2 publications · 53 citations

    2

    h-index

  2. Soft Matter

    1 publications · 26 citations

    1

    h-index

  3. The Journal of Chemical Physics

    1 publications · 87 citations

    1

    h-index

  4. Physical Review E

    PRE · 1 publications · 144 citations

    1

    h-index

  5. Macromolecules

    1 publications · 24 citations

    1

    h-index

1–5