Paesani Research Group

Laboratory for Theoretical and Computational Chemistry at UC San Diego  


© Paesani Research Group. All rights reserved.

Building upon the demonstrated accuracy of the MB-pol potential energy function (PEF) for water, we developed a theoretical and computational framework, MB-nrg, which enable the development of data-driven many-body PEFs for generic molecules [1-8].

MB-nrg PEFs representing the interactions between halide and alkali metal ions with water achieve chemical accuracy and accurately predict the properties of ionic aqueous systems from gas-phase clusters to solutions, outperforming both nonpolarizable and polarizable force fields as well as DFT models [9-20]. When employed in computer simulations, the MB-nrg PEFs enabled the identification of tunneling pathways and splittings in halide-water dimers [12] and halide-dihydrate complexes [13-14], the characterization of isomeric equilibria and vibrational spectra of small ion-water complexes [15-17], and the characterization of the hydration structure and EXAFS spectra of ions in solution [18-21].

Similarly, MB-nrg PEFs for small molecules accurately reproduce CCSD(T) reference energies as well as structural and thermodynamic properties of molecular fluids, such as neat CO2 and CH4, and binary CO2/H2O [3,22] and CH4/H2O [4,23] mixtures.

The MB-nrg theoretical and computational framework has recently been extended to generic molecules. The resulting

MB-nrg PEFs accurately reproduce both energetics and structures of arbitrarily long alkanes [5] as well as the properties of dinitrogen pentoxide (N2O5) and N-metylacetamide in both gas phase and solution [6-8].

The MB-nrg PEFs for halide and alkali metal ions, molecular fluids, and other molecules are available in MBX, an open-access many-body energy and force calculator for data-driven many-body simulations. MBX is interfaced to common simulation packages such as LAMMPS and i-PI. MBX can also be used as a standalone software and provides interfaces written in Fortran and Python that can be seamlessly used in combination with third-party software. MBX can be downloaded from our GitHub page.

How to use the MB-nrg PEFs

MB-nrg PEFs for generic molecules can be developed with MB-Fit [24], an integrated software infrastructure that prrovides a complete array of 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 MB-nrg PEFs, and 4) generate the associated codes that are directly exported to MBX.


1)   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).    

2)   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).

3)   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).

4)   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).

5)   E.F. Bull-Vulpe, M. Riera, S.L. Bore, F. Paesani, Data-driven many-body potential energy functions for generic

      molecules: Linear alkanes as a proof-of-concept application, J. Chem. Theory Comput. ASAP (2023).

6)   V.W.D. Cruzeiro, E. Lambros, M. Riera, R. Roy, F. Paesani, A.W. Götz, Highly accurate many-body potentials for

      simulations of N2O5 in water: Benchmarks, development, and validation, J. Chem. Theory Comput. 17, 3931 (2021).

7)   V.W.D. Cruzeiro, M. Galib, D.T. Limmer, A.W. Götz, Uptake of N2O5 by aqueous aerosol unveiled using chemically

      accurate many-body potentials, Nat. Commun. 13, 1266 (2022).

6)   R. Zhou, M. Riera, F. Paesani, Towards data-driven many-body simulations of biomolecules in solution: N-methyl

      acetamide as a proxy for the protein backbone, J. Chem. Theory Comput. In press (2023).

7)   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).

8)   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, J. Chem. Theory Comput. 16, 3055 (2020).

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

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

10)  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).

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

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

12)  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).

13)  M. Riera, J.J. Talbot, R.P. Steele, F. Paesani, Infrared signatures of isomer selectivity and symmetry breaking in the

       Cs+(H2O)3 complex using many-body potential energy functions, J. Chem. Phys. 153, 044306 (2020).

14)  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).

15)  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).

16)  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).

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

       from clusters to bulk, J. Chem. Phys. 155, 064502 (2021).

18)  A. Caruso, X. Zhu, J. L. Fulton, F. Paesani, Accurate modeling of bromide and iodide hydration with data-driven

       many-body potentials, J. Phys. Chem. B 126, 8266 (2022).

19)  D. Zhuang, M. Riera, R. Zhou, A. Deary, F. Paesani, Hydration structure of Na+ and K+ ions in solution predicted by

       data-driven many-body potentials, J. Phys. Chem. B 126, 9349 (2022).

20)  S. Yue, M. Riera, R. Ghosh, A.Z. Panagiotopoulos, F. Paesani, Transferability of data-driven many-body models

       for CO2 simulations in the vapor and liquid phases, J. Chem. Phys. 156, 104503 (2022).

21)  V. Naden Robinson, R. Ghosh, C.K. Egan, M. Riera, C. Knight, F. Paesani, A. Hassanali, The behavior of       

       methane-water mixtures under elevated pressures using many-body potentials, J. Chem. Phys. 156, 194504


22)  E.F. Bull-Vulpe, M. Riera, A.W. Götz, F. Paesani, MB-Fit: Software infrastructure for data-driven many-body

       potential energy functions, J. Chem. Phys. 155, 124801 (2021).