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May 20, 2026
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cemff: A force field database for cementitious materials including validations, applications and opportunities

Cement and Concrete Research. 2017. Vol. 102. P. 68–89.
Mishra R. K., Kunhi Mohamed A., Geissbühler D., Manzano H., Jamil T., Shahsavari R., Kalinichev Andrey G, Galmarini S., Tao L., Heinz H., Pellenq R., van Duin A. C., Parker S. C., Flatt R. J., Bowen P.

This paper reviews atomistic force field parameterizations for molecular simulations of cementitious minerals, such as tricalcium silicate (C3S), portlandite (CH), tobermorites (model C-S-H). Computational techniques applied to these materials include classical molecular simulations, density functional theory and energy minimization. Such simulations hold promise to capture the nanoscale mechanisms operating in cementitious materials and guide in performance optimization. Many force fields have been developed, such as Born–Mayer–Huggins, InterfaceFF (IFF), ClayFF, CSH-FF, CementFF, GULP, ReaxFF, and UFF. The benefits and limitations of these approaches are discussed and a database is introduced, accessible via a web-link (http://cemff.epfl.ch). The database provides information on the different force fields, energy expressions, and model validations using systematic comparisons of computed data with benchmarks from experiment and from ab-initio calculations. The cemff database aims at helping researchers to evaluate and choose suitable potentials for specific systems. New force fields can be added to the database.

Research target: Computer Science Construction Mechanics and Mechanical Engineering Effective Natural Resource Management Physics
Priority areas: IT and mathematics engineering science
Language: English
DOI
Text on another site
Keywords: наноструктурананоматериалымолекулярное моделированиеmolecular modelingatomistic modelingатомистическое моделированиеnanomaterialsNanostructured materialscementцемент
Publication based on the results of:
­­­Atomistic multiscale modeling of properties and processes in materials and living systems; analysis of efficiency of new supercomputer technologies (2018)
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