MB-Fit is an integrated software infrastructure that enables the automated development of fully transferable, data-driven many-body potential energy functions (PEFs) for generic molecules within the TTM-nrg and MB-nrg theoretical/computational frameworks.

MB-Fit provides a complete array of software tools to:

1) generate training and test sets for individual many-body energies,

2) set up and perform the required quantum mechanical calculations of the necessary training data,

3) optimize both linear and non-linear parameters entering the mathematical expressions for the TTM-nrg and MB-nrg PEFs,

4) generate the associated codes that are directly exported to the MBX many-body energy/force calculator (http://paesanigroup.ucsd.edu/software/mbx.html) that enables MD simulations with the TTM-nrg and MB-nrg PEFs using LAMMPS (https://www.lammps.org) and i-PI (http://ipi-code.org).

For details on the theoretical background and software implementation, please refer to:

E.F. Bull-Vulpe, M. Riera, A.W. Götz, F. Paesani

MB-Fit: Software infrastructure for data-driven many-bbody potential energy functions.

The current version of MB-Fit can be downloaded from https://github.com/paesanilab/MB-Fit.

For questions about MB-Fit, please refer to the MB-Fit_users group: https://groups.google.com/u/0/g/mb-fit_users.

After joining the group, users will be able to post questions/comments about MB-Fit.

Key references for TTM-nrg and MB-nrg PEFs.

MB-pol:

  -    V. Babin, C. Leforestier, F. Paesani, Development of a “first principles" water potential with flexible monomers:

       Dimer potential energy surface, VRT spectrum, and second virial coefficient, J. Chem. Theory Comput. 9, 5395,

       (2013).

  -    V. Babin, G.R. Medders, F. Paesani, Development of a “first principles" water potential with flexible monomers.

       II: Trimer potential energy surface, third virial coefficient, and small clusters, J. Chem. Theory Comput. 10, 1599

       (2014).

  -    G.R. Medders, V. Babin, F. Paesani, Development of a “first principles" water potential with flexible monomers.

       III: Liquid phase properties, J. Chem. Theory Comput. 10, 2906 (2014).

  -    S.K. Reddy, S.C. Straight, P. Bajaj, C.H. Pham, M. Riera, D.R. Moberg, M.A. Morales, C. Knight, A.W. Götz,

       F. Paesani, On the accuracy of the MB-pol many-body potential for water: Interaction energies, vibrational

       frequencies, and classical thermodynamic and dynamical properties from clusters to liquid water and ice,

       J. Chem. Phys. 145, 194504 (2016).

  -    F. Paesani, Getting the right answers for the right reasons: Toward predictive molecular simulations of water with

       many-body potential energy functions, Acc. Chem. Res. 49, 1844 (2016).

TTM-nrg and MB-nrg PEFs:

  -    D.J. Arismendi-Arrieta, M. Riera, P. Bajaj, R. Prosmiti, F. Paesani, The i-TTM model for ab initio-based ion-water

       interaction potentials. I. Halide-water potential energy functions, J. Phys. Chem. B 120, 1822 (2016).

  -   M. Riera, A.W. Götz, F. Paesani, The i-TTM model for ab initio-based ion-water interaction potentials. II. Alkali

      metal ion-water potential energy functions, Phys. Chem. Chem. Phys. 18, 30334 (2016).

  -    P. Bajaj, A.W. Götz, F. Paesani, Toward chemical accuracy in the description of ion–water interactions through

       many-body representations. I. Halide–water dimer potential energy surfaces, J. Chem. Theory Comput. 12,

       2698 (2016).    

  -    M. Riera, N. Mardirossian, P. Bajaj, A.W. Götz, F. Paesani, Toward chemical accuracy in the description of

       ion–water interactions through many-body representations. Alkali-water dimer potential energy surfaces, J. Chem.

       Phys. 147, 161715 (2017).

  -    M. Riera, S.E. Brown, F. Paesani, Isomeric equilibria, nuclear quantum effects, and vibrational spectra of

       M+(H2O)n=1–3 clusters, with M = Li, Na, K, Rb, and Cs, through many-body representations, J. Phys. Chem. A 122,

       5811 (2018).

  -    P. Bajaj, X.-G. Wang, T. Carrington, Jr., F. Paesani, Vibrational spectra of halide-water dimers: Insights on ion

       hydration from full-dimensional quantum calculations on many-body potential energy surfaces, J. Chem. Phys.

       148, 102321 (2018).

  -    P. Bajaj, J.O. Richardson, F. Paesani, Ion-mediated hydrogen-bond rearrangement through tunnelling in the

       iodide–dihydrate complex, Nat. Chem. 11, 367 (2019).

  -    P. Bajaj, D. Zhuang, F. Paesani, Specific ion effects on hydrogen-bond rearrangements in the halide–dihydrate

       complexes, J. Phys. Chem. Lett. 10, 2823 (2019).

  -    P. Bajaj, M. Riera, J.K. Lin, Y.E. Mendoza Montijo, J. Gazca, F. Paesani, Halide ion microhydration: Structure,

       energetics, and spectroscopy of small halide–water clusters, J. Phys. Chem. A 123, 2843 (2019).

  -   D. Zhuang, M. Riera, G.K. Schenter, J.L. Fulton, F. Paesani, Many-body effects determine the local hydration

       structure of Cs+ in solution, J. Phys. Chem. Lett. 10, 406 (2019).

  -   F. Paesani, P. Bajaj, M. Riera, Chemical accuracy in modeling halide ion hydration from many-body

       representations, Adv. Phys. X 4, 1631212 (2019).

  -   B.B. Bizzarro, C.K. Egan, F. Paesani, Nature of halide–water interactions: Insights from many-body

       representations and density functional theory, J. Chem. Theory Comput. 15, 2983 (2019).

  -   C.K. Egan, B.B. Bizzarro, M. Riera, F. Paesani, Nature of alkali ion–water interactions: Insights from many-body

      representations and density functional theory. II. J. Chem. Theory Comput. 16, 3055 (2020).

  -   M. Riera, E.P. Yeh, F. Paesani, Data-driven many-body models for molecular fluids: CO2/H2O mixtures

       as a case study, J. Chem. Theory Comput. 16, 2246 (2020).

  -   M. Riera, A. Hirales, R. Ghosh, F. Paesani, Data-driven many-body models with chemical accuracy for CH4/H2O

       mixtures, J. Phys. Chem. B 124, 11207 (2020).

  -   E. Lambros, S. Dasgupta, E. Palos, S. Swee, J. Hu, F. Paesani, General many-body framework for data-driven

       potentials with arbitrary quantum mechanical accuracy: Water as a case study. Under review.

  -    A. Caruso, F. Paesani, Data-driven many-body models enable a quantitative description of chloride hydration from

       clusters to bulk. Under review.

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