6. ReaxFF Models

6.1. Introduction

The Reactive Force Field (ReaxFF) replaces fixed bond topologies of classical force fields with the concept of bond order to simulate bond breaking/formation of chemical reactions. Originally conceived for hydrocarbons in the gas phase [1], ReaxFF has been extended to a wide range of applications [2].

Danger

Just because a ReaxFF potential is available with the atoms for your intented application, it DOES NOT mean it is transferable if the training set did not include configurations similar to your intented application. For example, there are many potentials with C/H/O/N atoms but not all have the pi-bond parameters trained so a benzene molecule might behave in a completely unphysical manner. You need to consult the original journal article (doi links below) together with the supplementary materials to confirm the transferability of a given ReaxFF potential to your application.

The Potential Energy Surface (PES) is an insanely immense mathematical object. PES of a system with N atoms doesn’t have N points, it has 3N dimensions! The odds are infinitesimal that someone else visited the same tiny slice of subspace you’re interested in and made a Machine-Learning Inter-Atomic-Potential (ML-IAP) or a Reax Force Field (FF) for you already. Stop looking for potentials from somewhere else, except to practice and learn to maybe get close to what you’re doing. For original research there’s no way around having to generate your own DFT and/or experimental data to train a new MLIAP or FF. This is the purpose of FitSNAP-ReaxFF.

ReaxFF in LAMMPS [3] supports three charge equilibration methods to represent the dynamics of electron density:

• Charge Equilibration (QEq) [4][5]

• Atom-Condensed Kohn-Sham DFT to second order (ACKS2) [6][7]

• Charge Transfer and Polarization in Equilibrium (QTPIE) [8]

while fixed partial charges in classical force fields (eg. CHARMM) do not. FitSNAP-ReaxFF enables retraining of legacy ReaxFF QEq potentials for ACKS2 and QTPIE, including optimization of the bond_softness, chi, eta, gamma, bcut_acks2, and gauss_exp parameters.

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6.2. ReaxFF functional form

The ReaxFF overall system energy is expressed as the sum:

\[\begin{split}E_{system} & = E_{bond} + E_{lp} + E_{over} + E_{under} + E_{val} + E_{pen} + E_{coa} + E_{C2}\\[.6em] & \qquad + E_{triple} + E_{tors} + E_{conj} + E_{Hbond} + E_{vdWaals} + E_{Coulomb}\end{split}\]

Details for each term:

• Bond order/energy

• Lone pair energy

• Overcoordination

• Undercoordination

• Valence Terms (Angle energy, Penalty energy, Three-body conjugation term)

• Correction for C2

• Triple bond energy correction

• Torsion Terms (Torsion rotation barriers, Four body conjugation term)

• Hydrogen bond interactions

• Nonbonded interactions (van der Waals, Coulomb)

are presented in the Supporting Information of A ReaxFF Reactive Force Field for Molecular Dynamics Simulations of Hydrocarbon Oxidation by Chenoweth, van Duin, Goddard (2008).

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6.3. ReaxFF LAMMPS commands

• pair_style reaxff (/kk)

• fix qeq/reaxff (/kk)

• fix acks2/reaxff (/kk)

• fix qtpie/reaxff (/kk)

• compute reaxff/bonds (/kk)

• compute reaxff/species (/kk)

• compute reaxff/atom (/kk)

where (/kk) denotes LAMMPS commands available in KOKKOS package.

Note

KOKKOS version of ReaxFF with -k on t 1 -sf kk is always used by FitSNAP-ReaxFF.

“IMO anyone and everyone should be using the KOKKOS version of ReaxFF. Not only is it more memory robust and will never have these hbondchk errors, it is also faster on CPUs, at least in most cases that I’ve benchmarked, or same speed at the very least.”

– Stan Moore (2024/10) on MatSci.org:

Lammps hbondchk failed.

https://matsci.org/t/lammps-hbondchk-failed/58230/6

“I highly suggest using the KOKKOS package for ReaxFF, works in serial for CPUs too.”

– Stan Moore (2024/10) on MatSci.org:

Segmentation fault: address not mapped to object at address 0xc2cfb87c.

https://matsci.org/t/segmentation-fault-address-not-mapped-to-object-at-address-0xc2cfb87c/58493/5

“You could also try the KOKKOS version which doesn’t use the safezone, mincap, and minhbonds factors which can bloat the memory if you set them too high.”

– Stan Moore (2025/01) on MatSci.org:

Possible memory problem with Reaxff when the total atom number increased.

https://matsci.org/t/possible-memory-problem-with-reaxff-when-the-total-atom-number-increased/60431/2

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6.4. Fitting ReaxFF parameters

If a ReaxFF potential is not available for your intented application, then you can fit new parameters with FitSNAP-ReaxFF from DFT training data. FitSNAP-ReaxFF is based on the Covariance Matrix Adaptation Evolution Strategy (CMAES) optimization algorithm as implemented by the pycma python package. CMAES finds a minimum \(x \in \mathbb{R}^n\) of an objective function \(f(x)\). In FitSNAP-ReaxFF, the objective function minimized is the Sum of Squared Errors (SSE) between DFT reference data and predicted energy/forces given current values of parameters to be optimized.

The FitSNAP-ReaxFF workflow is fundamentally different than FitSNAP but relies on the same underlying infrastructure:

FitSNAP (SNAP/PACE/…)

Two separate phases after scraping data: (i) process_configs() to calculate descriptors and (ii) perform_fit() to solve for optimal coefficients.

FitSNAP-ReaxFF

One integrated phase: perform_fit() consists of a loop where process_configs() runs in parallel at each step of the fitting algorithm. During this loop, a population of popsize candidate parameters is refined until the CMAES algorithm meets a termination criteria.

You can start a FitSNAP-ReaxFF optimization with a potential file from reaxff/potentials/reaxff-<AUTHOR><YEAR>.ff (see below for full list bundled with FitSNAP-ReaxFF). You can also start with any other valid ReaxFF potential file (with the exception of eReaxFF and LG dispersion correction), or FIXME: restart from a previously optimized potential.

N2_ReaxFF example

Let’s start with a simple example related to the nitrogen molecule example of INQ, a modern clean-slate C++/CUDA open source (TD)DFT package from LLNL. DFT reference data can also be obtained from Quantum Espresso (QE), Vienna Ab initio Simulation Package (VASP), literature, online databases,…

First, training data is computed using INQ with PBE functional and saved to JSON/N2/N2*.json:

examples/N2_ReaxFF/N2_ReaxFF-bond-scan.py

from fitsnap3lib.parallel_tools import ParallelTools
from fitsnap3lib.io.input import Config
from fitsnap3lib.calculators.inq import INQ
import json
import numpy as np

bond_scan = [{
    "Positions":[[-d/2,0.0,0.0], [d/2,0.0,0.0]], 
    "AtomTypes":['N','N']
    } for d in np.arange(0.9,1.51,.05)]

settings = { "CALCULATOR": {
    "calculator": "INQ", "energy": 1, "force": 1, "dipole": 1 
}}

pt = ParallelTools()
config = Config(pt, settings)
inq = INQ('inq', pt, config)
inq.process_configs(bond_scan)

for i, b in enumerate(bond_scan):
    with open(f'JSON/N2/N2_{i}.json', 'w') as json_file:
        json.dump({"Dataset": {"Data": b}}, json_file)

Second, a FitSNAP-ReaxFF optimization with input scripts N2_ReaxFF-<CHARGE_FIX>.in:

QEQACKS2QTPIE

examples/N2_ReaxFF/N2_ReaxFF-qeq.in

[REAXFF]
potential      = reaxff-wood2014.ff
parameters     = BND.N.N.p_bo1 BND.N.N.p_bo2 BND.N.N.p_bo3 BND.N.N.p_bo4 BND.N.N.p_bo5 BND.N.N.p_bo6
                 BND.N.N.p_be1 BND.N.N.p_be2 
                 BND.N.N.De_s BND.N.N.De_p BND.N.N.De_pp
                 BND.N.N.p_ovun1

[CALCULATOR]
calculator     = LAMMPSREAXFF
charge_fix     = fix 1 all qeq/reaxff 1 0.0 10.0 1.0e-6 reaxff maxiter 500
energy         = .5
force          = 0
dipole         = .5

[SOLVER]
solver         = CMAES
popsize        = 10
sigma          = 0.1

[SCRAPER]
scraper        = JSON

[PATH]
dataPath       = JSON

[OUTFILE]
potential      = reaxff-n2-qeq.ff

[GROUPS]
group_sections = name training_size
group_types    = str float
N2-PBE         = 1.0

Third, potential energy computed along the bond scan \(\text{N}\!\equiv\!\text{N}\) by running LAMMPS with potentials

• reaxff-wood2014.ff

• reaxff-N2_ReaxFF-qeq.ff

• reaxff-N2_ReaxFF-acks2.ff

• reaxff-N2_ReaxFF-qtpie.ff

is compared to QM training data with matplotlib and saved to N2_ReaxFF.png:

6.4.1. FitSNAP-ReaxFF input script

Compared to linear and nonlinear models, the input script for ReaxFF models needs:

• [REAXFF] section instead of [BISPECTRUM] or [ACE] section

• calculator = LAMMPSREAXFF instead of LAMMPSSNAP, LAMMPSPACE, …

• solver = CMAES instead of eg. SVD, PYTORCH, …

[REAXFF] section

• potential path of initial ReaxFF potential file

• parameters strings separated by spaces with format <BLOCK>.<ATOM_1>...<ATOM_N>.<NAME>:

  • GEN.name for atom parameters

  • ATM.C.name for atom parameters

  • BND.C.H.name for bond parameters

  • OFD.C.H.name for off-diagonal parameters

  • ANG.C.H.O.name for angle parameters

  • TOR.C.H.O.N.name for torsion parameters

  • HBD.C.H.O.name for hydrogen-bond parameters

  where name is LAMMPS implementation parameter name (which might be different than other ReaxFF implementations commonly seen in comments of potential files)

Block	Position	Name	Description	Category	Eq. [15]
GEN	R1	p_boc1	Overcoordination parameter	Expert	4c
GEN	R2	p_boc2	Overcoordination parameter	Expert	4d
GEN	R3	p_coa2	Valency angle conjugation parameter	Expert	15
GEN	R4	p_trip4	Triple bond stabilization parameter	Expert	20
GEN	R5	p_trip3	Triple bond stabilization parameter	Expert	20
GEN	R6	k_c2	C2-correction	Expert	19
GEN	R7	p_ovun6	Undercoordination parameter	Expert	12
GEN	R8	p_trip2	Triple bond stabilization parameter	Expert	20
GEN	R9	p_ovun7	Undercoordination parameter	Expert	12
GEN	R10	p_ovun8	Undercoordination parameter	Expert	12
GEN	R11	p_trip1	Triple bond stabilization energy	Expert	20
GEN	R12	nonb_low,swa	Lower Taper-radius	DoNotOptimize	21
GEN	R13	R_cut	Upper Taper-radius	DoNotOptimize	21
GEN	R14	p_fe1	Fe dimer correction	DoNotOptimize	6a
GEN	R15	p_val6	Valency undercoordination	Expert	13c
GEN	R16	p_lp1	Valency angle/lone pair parameter	Expert	8
GEN	R17	p_val9	Valency angle parameter	Expert	13f
GEN	R18	p_val10	Valency angle parameter	Expert	13g
GEN	R19	p_fe2	Fe dimer correction	DoNotOptimize	6a
GEN	R20	p_pen2	Double bond/angle parameter	Expert	14a
GEN	R21	p_pen3	Double bond/angle parameter: overcoord	Expert	14b
GEN	R22	p_pen4	Double bond/angle parameter: overcoord	Expert	14b
GEN	R23	p_fe3	Fe dimer correction	DoNotOptimize	6a
GEN	R24	p_tor2	Torsion/BO parameter	Expert	16b
GEN	R25	p_tor3	Torsion overcoordination	Expert	16c
GEN	R26	p_tor4	Torsion overcoordination	Expert	16c
GEN	R28	p_cot2	Conjugation	Expert	17b
GEN	R29	p_vdW1	VdW shielding	Expert	23b
GEN	R30	cutoff*100	Cutoff for bond order (* 100)	Expert	3a,b
GEN	R31	p_coa4	Valency angle conjugation parameter	Expert	15
GEN	R32	p_ovun4	Overcoordination parameter	Expert	11b
GEN	R33	p_ovun3	Overcoordination parameter	Expert	11b
GEN	R34	p_val8	Valency/lone pair parameter	Expert	13d
GEN	R35	X_soft	ACKS2 softness parameter	Expert	25
GEN	R39	p_coa3	Valency angle conjugation parameter	Expert	15
ATM	R1C1	r_s	σ-bond covalent radius	Standard	2
ATM	R1C2	valency	Valency	DoNotOptimize	3a,4b,5,9a
ATM	R1C3	mass	Atomic mass	DoNotOptimize	9a
ATM	R1C4	r_vdw	van der Waals radius	Expert	23a
ATM	R1C5	epsilon	van der Waals dissociation energy	Expert	23a
ATM	R1C6	gamma	Valence orbital exponent (QEQ, ACKS2, QTPIE)	Expert	24
ATM	R1C7	r_pi	π-bond covalent radius	Standard	2
ATM	R1C8	valency_e	Number of valence electrons	DoNotOptimize	7,8,9
ATM	R2C1	alpha	van der Waals parameter	Expert	23b
ATM	R2C2	gamma_w	van der Waals shielding	Expert	23b
ATM	R2C3	valency_boc	Valency for 1, 3-BO correction	DoNotOptimize	16c,13c
ATM	R2C4	p_ovun5	Undercoordination energy	Expert	12
ATM	R2C5	gauss_exp	Gaussian orbital exponent (QTPIE)	Expert	26
ATM	R2C6	chi	Electronegativity [always eV] (QEQ, ACKS2, QTPIE)	Expert	24,25
ATM	R2C7	eta	Atomic hardness [always eV] (QEQ, ACKS2, QTPIE)	Expert	24,25
ATM	R2C8	p_hbond	Donor or acceptor switch in H-bonds	DoNotOptimize	n/a
ATM	R3C1	r_pi_pi	π-π-bond covalent radius	Standard	2
ATM	R3C2	p_lp2	Lone pair energy	Expert	10
ATM	R3C3	n/a	Atomic heat of formation	DoNotOptimize	n/a
ATM	R3C4	b_o_131	Bond order correction	Expert	4e,f
ATM	R3C5	b_o_132	Bond order correction	Expert	4e,f
ATM	R3C6	b_o_133	Bond order correction	Expert	4e,f
ATM	R3C7	bcut_acks2	Atomic softness cutoff parameter (ACKS2)	Expert	25
ATM	R4C1	p_ovun2	Valence angle parameter	Expert	12
ATM	R4C2	p_val3	Valence angle parameter	Expert	13b,13a
ATM	R4C4	valency_val	Number of lone pairs	DoNotOptimize	3b
ATM	R4C5	p_val5	Valence angle parameter	Expert	13b
ATM	R4C6	rcore2	Inner wall vdW repulsion parameter	Expert	23c
ATM	R4C7	ecore2	Inner wall vdW repulsion parameter	Expert	23c
ATM	R4C8	acore2	Inner wall vdW repulsion parameter	Expert	23c
BND	R1C1	De_s	σ-bond dissociation energy	Standard	6,11a
BND	R1C2	De_p	π-bond dissociation energy	Standard	6
BND	R1C3	De_pp	π-π-bond dissociation energy	Standard	6
BND	R1C4	p_be1	Bond energy parameter coefficient	Standard	6
BND	R1C5	p_bo5	π-π-bond parameter coefficient	Standard	2
BND	R1C6	v13cor	1,3-Bond order correction	DoNotOptimize	3b
BND	R1C7	p_bo6	π-π-bond order exponent	Standard	2
BND	R1C8	p_ovun1	Overcoordination penalty	Standard	11a
BND	R2C1	p_be2	Bond energy parameter exponent	Standard	6
BND	R2C2	p_bo3	π-bond order parameter coefficient	Standard	2
BND	R2C3	p_bo4	π-bond order parameter exponent	Standard	2
BND	R2C5	p_bo1	σ-bond order coefficient	Standard	2
BND	R2C6	p_bo2	σ-bond order exponent	Standard	2
BND	R2C7	ovc	Uncorrected BO overcoordination	DoNotOptimize	3a
OFD	R1C1	D	VdW energy	Expert	23a
OFD	R1C2	r_vdW	VdW radius	Expert	23a
OFD	R1C3	alpha	VdW parameter	Expert	23a
OFD	R1C4	r_s	σ-bond length	Standard	2
OFD	R1C5	r_p	π-bond length	Standard	2
OFD	R1C6	r_pp	π-π-bond length	Standard	2
ANG	R1C1	theta_00	180o-(equilibrium angle)	Standard	13g
ANG	R1C2	p_val1	Valence angle parameter	Standard	13a
ANG	R1C3	p_val2	Valence angle parameter	Standard	13a
ANG	R1C4	p_coa1	Valence conjugation	Expert	15
ANG	R1C5	p_val7	Undercoordination	Expert	13c
ANG	R1C6	p_pen1	Penalty energy	Expert	14b,14a
ANG	R1C7	p_val4	Valence angle parameter	Expert	13b
TOR	R1C1	V1	V1-torsion barrier	Standard	16a
TOR	R1C2	V2	V2-torsion barrier	Standard	16a
TOR	R1C3	V3	V3-torsion barrier	Standard	16a
TOR	R1C4	p_tor1	Torsion angle parameter	Standard	16a
TOR	R1C5	p_cot1	Conjugation energy	Expert	17a
HBD	R1C1	r0_hb	Hydrogen bond equilibrium distance	Standard	18
HBD	R1C2	p_hb1	Hydrogen bond energy	Standard	18
HBD	R1C3	p_hb2	Hydrogen bond/bond order	Expert	18
HBD	R1C4	p_hb3	Hydrogen bond parameter	Expert	18

Note

reaxff/tools/reaxff-format-ff.py properly reformats a ReaxFF potential file (eg. copy/pasted from journal articles) together with LAMMPS implementation parameter names in comment fields.

[CALCULATOR] section

• calculator must be LAMMPSREAXFF for FitSNAP-ReaxFF

• charge_fix charge equilibration fix command, eg:

  • (a) fix 1 all qeq/reaxff 1 0.0 10.0 1.0e-6 reaxff

  • (b) fix 1 all acks2/reaxff 1 0.0 10.0 1.0e-6 reaxff maxiter 500

  • (c) fix 1 all qtpie/reaxff 1 0.0 10.0 1.0e-6 reaxff exp.qtpie

  • fix ID (1 in examples a-c), can only contain alphanumeric characters and underscores to be valid in LAMMPS

• energy turn on 1 or off 0 energy fitting

• force turn on 1 or off 0 force fitting

• stress ignored in FitSNAP-ReaxFF

• dipole turn on 1 or off 0 dipole fitting

Note

Stress fitting is not supported in FitSNAP-ReaxFF, only energy = 1 and force = 1 are available.

[SOLVER] section

• solver must be CMAES for FitSNAP-ReaxFF

• popsize population size setting of CMAES algorithm, with default \(4+3*log(|P|)\) where \(|P|\) is the number of parameters to be optimized. [detailed discussion with the author of the pycma python package]

• sigma sigma setting of CMAES algorithm, with default 0.1

[SCRAPER] section

• same as FitSNAP

[PATH] section

• same as FitSNAP

[OUTFILE] section

• potential path of optimized ReaxFF potential file

• output_style not applicable because output_style=REAXFF implied by REAXFF section

[REFERENCE] section

• not applicable in FitSNAP-ReaxFF

Note

FitSNAP-ReaxFF only supports units real and atom_style charge.

[GROUPS] section

• same as FitSNAP

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6.5. Available ReaxFF potentials

Historical serial Fortran 77 force fields (no longer compatible and not available)

Branch	Atoms	Filename	Source
combustion	C / H	n/a	van Duin et al.[1]

6.5.1. Combustion Branch

Available COMBUSTION force fields in LAMMPS

Branch	Atoms	Filename (LAMMPS)	Filename (SCM)	Source
combustion	Au/S/C/H	reaxff-jarvi2011.ff	AuSCH_2011.ff	Järvi et al.[9]
combustion	C	reaxff-srinivasan2015.ff	C.ff	Srinivasan et al.[10]
combustion	C/H	reaxff-mao2017.ff	CH_aromatics.ff	Mao et al.[11]
combustion	C/H/B/N	reaxff-pai2016.ff	CBN.ff	Pai et al.[12]
combustion	C/H/Na	reaxff-hjertenaes2016.ff	CHNa.ff	Hjertenæs et al.[13]
combustion	C/H/O	reaxff-ashraf2017.ff	CHO-2016.ff	Ashraf and Van Duin[14]
combustion	C/H/O	reaxff-chenoweth2008a.ff	CHO.ff	Chenoweth et al.[15]
combustion	C/H/O/Ba/Zr/Y	reaxff-vanduin2008.ff	BaYZrCHO.ff	Van Duin et al.[16]
combustion	C/H/O/N	reaxff-strachan2003.ff	n/a	Strachan et al.[17]
FIXME	C/H/O/N	reaxff-budzien2009.ff	n/a	Budzien et al.[18]
FIXME	C/H/O/N/S	reaxff-mattsson2010.ff	n/a	Mattsson et al.[19]
FIXME	C/H/O/N/S/F/Pt/Cl/Ni/X	reaxff-singh2013.ff	n/a	Singh et al.[20]
combustion	C/H/O/N/S/Si	reaxff-liu2011.ff	dispersion/CHONSSi-lg.ff	Liu et al.[21]
combustion	C/H/O/N/S/Si	reaxff-zhang2009.ff	HE2.ff	Zhang et al.[22]
combustion	C/H/O/N/S/Si/Ge	reaxff-psofogiannakis2016.ff	CHONSSiGe.ff	Psofogiannakis and Van Duin[23]
combustion	C/H/O/N/S/Si/Na/P	reaxff-zhang2014.ff	CHONSSiNaP.ff	Zhang et al.[24]
combustion	C/H/O/N/S/Si/Pt/Zr/Ni/Cu/Co	reaxff-nielson2005.ff	CHONSSiPtZrNiCuCo.ff	Nielson et al.[25]
combustion	C/H/O/N/S/Si/Pt/Ni/Cu/Co/Zr/Y/Ba	reaxff-merinov2014.ff	CHONSSiPtNiCuCoZrYBa.ff	Merinov et al.[26]
combustion	C/H/O/N/S/Si/Pt/Zr/Ni/ Cu/Co/He/Ne/Ar/Kr/Xe	reaxff-kamat2010.ff	CHONSSiPtZrNiCuCoHeNeArKrXe.ff	Kamat et al.[27]
combustion	C/H/O/N/Si/S	reaxff-kulkarni2013.ff	SiONH.ff	Kulkarni et al.[28]
combustion	C/H/O/S	reaxff-mueller2016.ff	Mue2016.ff	Müller and Hartke[29]
combustion	C/H/O/S	reaxff-komissarov2021.ff	n/a	Komissarov et al.[30]
combustion	C/H/O/S/F/Cl/N	reaxff-wood2014.ff	CHOSFClN.ff	Wood et al.[31]
combustion	C/H/Pt	reaxff-sanz2008.ff	PtCH.ff	Sanz-Navarro et al.[32]
combustion	C/H/O/Si	reaxff-chenoweth2005.ff	PDMSDecomp.ff	Chenoweth et al.[33]
FIXME	H/O/Au	reaxff-joshi2010.ff	n/a	Joshi et al.[34]
combustion	Co	reaxff-zhang2014b.ff	Co.ff	Zhang et al.[35]
combustion	H/O/N/B	reaxff-weismiller2010.ff	Ab.ff	Weismiller et al.[36]
combustion	Li/S	reaxff-islam2015.ff	LiS.ff	Islam et al.[37]
combustion	Ni/C/H	reaxff-mueller2010.ff	NiCH.ff	Mueller et al.[38]
combustion	O/Pt	reaxff-fantauzzi2014.ff	OPt.ff	Fantauzzi et al.[39]
combustion	Pd/H	reaxff-senftle2014.ff	PdH.ff	Senftle et al.[40]
combustion	Si/C/O/H/N/S	reaxff-newsome2012.ff	SiC.ff	Newsome et al.[41]
combustion	V/O/C/H	reaxff-chenoweth2008b.ff	VOCH.ff	Chenoweth et al.[42]

6.5.2. Independent Branch

Available INDEPENDENT force fields in LAMMPS

Branch	Atoms	Filename (LAMMPS)	Filename (SCM)	Source
independent	C/H/Ar/He/Ne/Kr	reaxff-yoon2016.ff	CHArHeNeKr.ff	Yoon et al.[43]
independent	C/H/Fe	reaxff-islam2016.ff	CHFe.ff	Islam et al.[44]
independent	C/H/Ga C/H/In	reaxff-rajabpour2021a.ff reaxff-rajabpour2021b.ff	GaCH-2020.ff InCH-2020.ff	Rajabpour et al.[45]
independent	C/H/O/Ge	reaxff-nayir2018.ff	CHOGe.ff	Nayir et al.[46]
independent	C/H/O/Li/Al/Ti/P	reaxff-shin2018.ff	CHOLiAlTiP.ff	Shin et al.[47]
independent	C/H/O/N/B/Al/Si/Cl	reaxff-uene2024.ff	CHONBAlSiCl.ff	Uene et al.[48]
independent	C/H/O/N/S/Mg/P/Na/Cu/Cl/Ti/X	reaxff-hou2022.ff	CHONSMgPNaCuClTi.ff	Hou et al.[49]
independent	C/H/O/N/S/Si	reaxff-soria2018.ff	CHONSSi.ff	Soria et al.[50]
independent	C/H/O/N/S/Si/Ge/Ga/Ag	reaxff-niefind2024.ff	CHONSSiGeGaAg.ff	Niefind et al.[51]
independent	C/H/O/N/S/Zr	reaxff-dwivedi2020.ff	CHONSZr.ff	Dwivedi et al.[52]
independent	C/H/O/N/Si	reaxff-wang2020.ff	CHONSi.ff	Wang et al.[53]
independent	C/H/O/S/Cu/Cl/X	reaxff-yeon2018.ff	CuSCH.ff	Yeon et al.[54]
independent	C/H/O/S/Mo/Ni/Au/Ti	reaxff-mao2022.ff	CHOSMoNiAuTi.ff	Mao et al.[55]
independent	Cu/Zr	reaxff-huang2019.ff	CuZr.ff	Huang et al.[56]
independent	H/O/N/Si/F	reaxff-kim2021.ff	HONSiF.ff	Kim et al.[57]
independent	H/O/Si/Al/Li	reaxff-ostadhossein2016.ff	HOSiAlLi.ff	Ostadhossein et al.[58]
independent	H/S/Mo	reaxff-ostadhossein2017.ff	HSMo.ff	Ostadhossein et al.[59]
independent	I/Br/Pb/Cs	reaxff-pols2024.ff	IBrPbCs.ff	Pols et al.[60]
independent	I/Pb/Cs/X	reaxff-pols2021.ff	CsPbI.ff	Pols et al.[61]
independent	Li/Si/C	reaxff-olou2023.ff	LiSiC.ff	Olou’ou Guifo et al.[62]
independent	Mg/O	reaxff-fiesinger2023.ff	MgO.ff	Fiesinger et al.[63]
independent	Ni/Al	reaxff-du2023.ff	NiAl.ff	Du et al.[64]
independent	Ni/Cr	reaxff-shin2021.ff	NiCr.ff	Shin et al.[65]
independent	Ru/H	reaxff-onwudinanti2022.ff	RuH.ff	Onwudinanti et al.[66]
independent	Ru/N/H	reaxff-kim2018.ff	RuNH.ff	Kim et al.[67]
independent	Si/Al/Mg/O	reaxff-yeon2021.ff	SiAlMgO.ff	Yeon et al.[68]
independent	Si/O/H	reaxff-nayir2019.ff	SiOHv2.ff	Nayir et al.[69]
independent	W/S/H/Al/O	reaxff-nayir2021.ff	WSHAlO.ff	Nayir et al.[70]
independent	Zr/Y/O/H	reaxff-mayernick2010.ff	ZrYOHVac.ff	Mayernick et al.[71]
independent	Zr/Y/O/Ni/H	reaxff-liu2019.ff	ZrYONiH.ff	Liu et al.[72]

6.5.3. Water Branch

Available WATER force fields in LAMMPS

Branch	Atoms	Filename (LAMMPS)	Filename (SCM)	Source
water	Al/C/H/O	reaxff-hong2016.ff	AlCHO.ff	Hong and Van Duin[73]
water	C/H/O/Al/Ge/X	reaxff-zheng2017.ff	CHOAlGeX.ff	Zheng et al.[74]
water	C/H/O/Ca/Si/X	reaxff-manzano2012.ff	CaSiOH.ff	Manzano et al.[75]
water	C/H/O/Cs/K/Na/Cl/I/F/Li	reaxff-fedkin2019.ff	CHOCsKNaClIFLi.ff	Fedkin et al.[76]
water	C/H/O/Fe	reaxff-aryanpour2010.ff	FeOCHCl.ff	Aryanpour et al.[77]
water	C/H/O/Fe/Al/Ni/Cu/S/Cr	reaxff-shin2015.ff	CHOFeAlNiCuSCr.ff	Shin et al.[78]
water	C/H/O/Fe/Al/Ni/Cu/S/Cr	reaxff-tavazza2015.ff	CHOFeAlNiCuSCr_v3.ff	Tavazza et al.[79]
water	C/H/O/N	reaxff-rahaman2011.ff	Glycine.ff	Rahaman et al.[80]
water	C/H/O/N	reaxff-trnka2018.ff	n/a	Trnka et al.[81]
water	C/H/O/N	reaxff-kowalik2019.ff	CHON-2019.ff	Kowalik et al.[82]
water	C/H/O/N/S/Fe	reaxff-moerman2021.ff	CHONSFe.ff	Moerman et al.[83]
water	C/H/O/N/S/Mg/P/Na/Cu	reaxff-huang2013.ff	CuBTC.ff	Huang et al.[84]
water	C/H/O/N/S/Mg/P/Na/Cu/Cl	reaxff-monti2013a.ff	CHONSMgPNaCuCl.ff	Monti et al.[85]
water	C/H/O/N/S/Mg/P/Na/Cu/Cl	reaxff-monti2013b.ff	CHONSMgPNaCuCl_v2.ff	Monti et al.[86]
water	C/H/O/N/S/Mg/P/Na/Cu/Cl/X	reaxff-zhang2018.ff	CHON2017_weak.ff	Zhang and Van Duin[87]
water	C/H/O/N/S/Mg/P/Na/Ti/Cl/F	reaxff-huygh2014.ff	CHONSMgPNaTiClF.ff	Huygh et al.[88]
water	C/H/O/N/S/Mg/P/Na/Ti/Cl/F	reaxff-kim2013a.ff	TiOCHNCl.ff	Kim et al.[89]
water	C/H/O/N/S/Mg/P/Na/Ti/Cl/F	reaxff-kim2013b.ff	TiClOH.ff	Kim and van Duin[90]
water	C/H/O/N/S/Mg/P/Na/Ti/Cl/F/Au	reaxff-monti2016.ff	CHONSMgPNaTiClFAu.ff	Monti et al.[91]
water	C/H/O/N/S/Mg/P/Na/Ti/Cl/F/K/Li	reaxff-ganeshan2020.ff	CHONSMgPNaTiClFKLi.ff	Ganeshan et al.[92]
water	C/H/O/N/Si/Cu/Ag/Zn	reaxff-lloyd2016.ff	AgZnO.ff	Lloyd et al.[93]
water	C/H/O/N/S/Si/Ca/Cs/K/Sr/Na/Mg/Al/Cu	reaxff-psofogiannakis2015.ff	CHONSSiCaCsKSrNaMgAlCu.ff	Psofogiannakis et al.[94]
water	C/H/O/N/S/Si/Na/Al	reaxff-bai2012.ff	CHONSSiNaAl.ff	Bai et al.[95]
water	C/H/O/S/Mo/Ni/Li/B/F/P/N	reaxff-liu2021.ff	CHOSMoNiLiBFPN-2.ff	Liu et al.[96]
water	C/H/O/Si/Na	reaxff-hahn2018.ff	CHOSiNa.ff	Hahn et al.[97]
water	C/H/O/Zn	reaxff-han2010.ff	CHOZn.ff	Han et al.[98]
water	H/O/Si/Al/Li	reaxff-narayanan2011.ff	SiOAlLi.ff	Narayanan et al.[99]
water	H/O/X	reaxff-zhang2017.ff	Water2017.ff	Zhang and Van Duin[100]
water	Zn/O/H	reaxff-raymand2010.ff	ZnOH.ff	Raymand et al.[101]

---

6.6. ReaxFF Bibliography

download reaxff.bib

[1] (1,2)

Adri C. T. van Duin, Siddharth Dasgupta, Francois Lorant, and William A. Goddard. Reaxff: a reactive force field for hydrocarbons. The Journal of Physical Chemistry A, 105(41):9396–9409, 2001. URL: https://doi.org/10.1021/jp004368u.

[2]

Thomas P Senftle, Sungwook Hong, Md Mahbubul Islam, Sudhir B Kylasa, Yuanxia Zheng, Yun Kyung Shin, Chad Junkermeier, Roman Engel-Herbert, Michael J Janik, Hasan Metin Aktulga, and others. The reaxff reactive force-field: development, applications and future directions. npj Computational Materials, 2(1):1–14, 2016. URL: https://doi.org/10.1038/npjcompumats.2015.11.

[3]

Hasan Metin Aktulga, Joseph C Fogarty, Sagar A Pandit, and Ananth Y Grama. Parallel reactive molecular dynamics: numerical methods and algorithmic techniques. parallel computing, 38(4-5):245–259, 2012. URL: https://doi.org/10.1016/j.parco.2011.08.005.

[4]

Anthony K Rappe and William A Goddard III. Charge equilibration for molecular dynamics simulations. The Journal of Physical Chemistry, 95(8):3358–3363, 1991. URL: https://doi.org/10.1021/j100161a070.

[5]

Aiichiro Nakano. Parallel multilevel preconditioned conjugate-gradient approach to variable-charge molecular dynamics. Computer Physics Communications, 104(1-3):59–69, 1997. URL: https://doi.org/10.1016/S0010-4655(97)00041-6.

[6]

Toon Verstraelen, PW Ayers, Veronique Van Speybroeck, and Michel Waroquier. Acks2: atom-condensed kohn-sham dft approximated to second order. The Journal of chemical physics, 2013. URL: https://doi.org/10.1063/1.4791569.

[7]

Kurt A O’Hearn, Abdullah Alperen, and Hasan Metin Aktulga. Fast solvers for charge distribution models on shared memory platforms. SIAM Journal on Scientific Computing, 42(1):C1–C22, 2020. URL: https://doi.org/10.1137/18M1224684.

[8]

Jiahao Chen and Todd J Martínez. Qtpie: charge transfer with polarization current equalization. a fluctuating charge model with correct asymptotics. Chemical physics letters, 438(4-6):315–320, 2007. URL: https://doi.org/10.1016/j.cplett.2007.02.065.

[9]

Tommi T Järvi, Adri CT Van Duin, Kai Nordlund, and William A Goddard III. Development of interatomic reaxff potentials for au–s–c–h systems. The Journal of Physical Chemistry A, 115(37):10315–10322, 2011. URL: https://doi.org/10.1021/jp201496x.

[10]

Sriram Goverapet Srinivasan, Adri CT Van Duin, and Panchapakesan Ganesh. Development of a reaxff potential for carbon condensed phases and its application to the thermal fragmentation of a large fullerene. The Journal of Physical Chemistry A, 119(4):571–580, 2015. URL: https://doi.org/10.1021/jp510274e.

[11]

Qian Mao, Yihua Ren, KH Luo, and Adri CT Van Duin. Dynamics and kinetics of reversible homo-molecular dimerization of polycyclic aromatic hydrocarbons. The Journal of Chemical Physics, 2017. URL: https://doi.org/10.1063/1.5000534.

[12]

Sung Jin Pai, Byung Chul Yeo, and Sang Soo Han. Development of the reaxff cbn reactive force field for the improved design of liquid cbn hydrogen storage materials. Physical Chemistry Chemical Physics, 18(3):1818–1827, 2016. URL: https://doi.org/10.1039/C5CP05486A.

[13]

Eirik Hjertenæs, Anh Quynh Nguyen, and Henrik Koch. A reaxff force field for sodium intrusion in graphitic cathodes. Physical Chemistry Chemical Physics, 18(46):31431–31440, 2016. URL: https://doi.org/10.1039/C6CP06774C.

[14]

Chowdhury Ashraf and Adri CT Van Duin. Extension of the reaxff combustion force field toward syngas combustion and initial oxidation kinetics. The Journal of Physical Chemistry A, 121(5):1051–1068, 2017. URL: https://doi.org/10.1021/acs.jpca.6b12429.

[15]

Kimberly Chenoweth, Adri CT Van Duin, and William A Goddard. Reaxff reactive force field for molecular dynamics simulations of hydrocarbon oxidation. The Journal of Physical Chemistry A, 112(5):1040–1053, 2008. URL: https://doi.org/10.1021/jp709896w.

[16]

Adri CT Van Duin, Boris V Merinov, Seung Soon Jang, and William A Goddard. Reaxff reactive force field for solid oxide fuel cell systems with application to oxygen ion transport in yttria-stabilized zirconia. The Journal of Physical Chemistry A, 112(14):3133–3140, 2008. URL: https://doi.org/10.1021/jp076775c.

[17]

Alejandro Strachan, Adri CT van Duin, Debashis Chakraborty, Siddharth Dasgupta, and William A Goddard III. Shock waves in high-energy materials: the initial chemical events in nitramine rdx. Physical Review Letters, 91(9):098301, 2003. URL: https://doi.org/10.1103/PhysRevLett.91.098301.

[18]

Joanne Budzien, Aidan P Thompson, and Sergey V Zybin. Reactive molecular dynamics simulations of shock through a single crystal of pentaerythritol tetranitrate. The Journal of Physical Chemistry B, 113(40):13142–13151, 2009. URL: https://doi.org/10.1021/jp9016695.

[19]

Thomas R Mattsson, J Matthew D Lane, Kyle R Cochrane, Michael P Desjarlais, Aidan P Thompson, Flint Pierce, and Gary S Grest. First-principles and classical molecular dynamics simulation of shocked polymers. Physical Review B—Condensed Matter and Materials Physics, 81(5):054103, 2010. URL: https://doi.org/10.1103/PhysRevB.81.054103.

[20]

Sandeep Kumar Singh, S Goverapet Srinivasan, M Neek-Amal, Sebastian Costamagna, Adri CT Van Duin, and FM Peeters. Thermal properties of fluorinated graphene. Physical Review B—Condensed Matter and Materials Physics, 87(10):104114, 2013. URL: https://doi.org/10.1103/PhysRevB.87.104114.

[21]

Lianchi Liu, Yi Liu, Sergey V Zybin, Huai Sun, and William A Goddard III. Reaxff-lg: correction of the reaxff reactive force field for london dispersion, with applications to the equations of state for energetic materials. The Journal of Physical Chemistry A, 115(40):11016–11022, 2011. URL: https://doi.org/10.1021/jp201599t.

[22]

Luzheng Zhang, Sergey V Zybin, Adri CT Van Duin, Siddharth Dasgupta, William A Goddard III, and Edward M Kober. Carbon cluster formation during thermal decomposition of octahydro-1, 3, 5, 7-tetranitro-1, 3, 5, 7-tetrazocine and 1, 3, 5-triamino-2, 4, 6-trinitrobenzene high explosives from reaxff reactive molecular dynamics simulations. The Journal of Physical Chemistry A, 113(40):10619–10640, 2009. URL: https://doi.org/10.1021/jp901353a.

[23]

George Psofogiannakis and Adri CT Van Duin. Development of a reaxff reactive force field for si/ge/h systems and application to atomic hydrogen bombardment of si, ge, and sige (100) surfaces. Surface Science, 646:253–260, 2016. URL: https://doi.org/10.1016/j.susc.2015.08.019.

[24]

Bo Zhang, Adri CT Van Duin, and J Karl Johnson. Development of a reaxff reactive force field for tetrabutylphosphonium glycinate/co2 mixtures. The Journal of Physical Chemistry B, 118(41):12008–12016, 2014. URL: https://doi.org/10.1021/jp5054277.

[25]

Kevin D Nielson, Adri CT Van Duin, Jonas Oxgaard, Wei-Qiao Deng, and William A Goddard. Development of the reaxff reactive force field for describing transition metal catalyzed reactions, with application to the initial stages of the catalytic formation of carbon nanotubes. The Journal of Physical Chemistry A, 109(3):493–499, 2005. URL: https://doi.org/10.1021/jp046244d.

[26]

Boris V Merinov, Jonathan E Mueller, Adri CT Van Duin, Qi An, and William A Goddard III. Reaxff reactive force-field modeling of the triple-phase boundary in a solid oxide fuel cell. The journal of physical chemistry letters, 5(22):4039–4043, 2014. URL: https://doi.org/10.1021/jz501891y.

[27]

Amar M Kamat, Adri CT Van Duin, and Alexei Yakovlev. Molecular dynamics simulations of laser-induced incandescence of soot using an extended reaxff reactive force field. The Journal of Physical Chemistry A, 114(48):12561–12572, 2010. URL: https://doi.org/10.1021/jp1080302.

[28]

Anant D Kulkarni, Donald G Truhlar, Sriram Goverapet Srinivasan, Adri CT Van Duin, Paul Norman, and Thomas E Schwartzentruber. Oxygen interactions with silica surfaces: coupled cluster and density functional investigation and the development of a new reaxff potential. The Journal of Physical Chemistry C, 117(1):258–269, 2013. URL: https://doi.org/10.1021/jp3086649.

[29]

Julian Müller and Bernd Hartke. Reaxff reactive force field for disulfide mechanochemistry, fitted to multireference ab initio data. Journal of chemical theory and computation, 12(8):3913–3925, 2016. URL: https://doi.org/10.1021/acs.jctc.6b00461.

[30]

Leonid Komissarov, Robert Ruger, Matti Hellstrom, and Toon Verstraelen. Params: parameter optimization for atomistic and molecular simulations. Journal of Chemical Information and Modeling, 61(8):3737–3743, 2021. URL: https://doi.org/10.1021/acs.jcim.1c00333.

[31]

Mitchell A Wood, Adri CT Van Duin, and Alejandro Strachan. Coupled thermal and electromagnetic induced decomposition in the molecular explosive alpha-hmx; a reactive molecular dynamics study. The Journal of Physical Chemistry A, 118(5):885–895, 2014. URL: https://doi.org/10.1021/jp406248m.

[32]

Carlos F Sanz-Navarro, Per-Olof Åstrand, De Chen, Magnus Rønning, Adri CT Van Duin, Timo Jacob, and William A Goddard. Molecular dynamics simulations of the interactions between platinum clusters and carbon platelets. The Journal of Physical Chemistry A, 112(7):1392–1402, 2008. URL: https://doi.org/10.1021/jp074806y.

[33]

Kimberly Chenoweth, Sam Cheung, Adri CT Van Duin, William A Goddard, and Edward M Kober. Simulations on the thermal decomposition of a poly (dimethylsiloxane) polymer using the reaxff reactive force field. Journal of the American Chemical Society, 127(19):7192–7202, 2005. URL: https://doi.org/10.1021/ja050980t.

[34]

Kaushik Joshi, Adri CT van Duin, and Timo Jacob. Development of a reaxff description of gold oxides and initial application to cold welding of partially oxidized gold surfaces. Journal of Materials Chemistry, 20(46):10431–10437, 2010. URL: https://doi.org/10.1039/C0JM01556C.

[35]

Xue-Qing Zhang, Eldhose Iype, Silvia V Nedea, Antonius PJ Jansen, Bartłomiej M Szyja, Emiel JM Hensen, and Rutger A van Santen. Site stability on cobalt nanoparticles: a molecular dynamics reaxff reactive force field study. The Journal of Physical Chemistry C, 118(13):6882–6886, 2014. URL: https://doi.org/10.1021/jp500053u.

[36]

Michael R Weismiller, Adri CT Van Duin, Jongguen Lee, and Richard A Yetter. Reaxff reactive force field development and applications for molecular dynamics simulations of ammonia borane dehydrogenation and combustion. The Journal of Physical Chemistry A, 114(17):5485–5492, 2010. URL: https://doi.org/10.1021/jp100136c.

[37]

Md Mahbubul Islam, Alireza Ostadhossein, Oleg Borodin, A Todd Yeates, William W Tipton, Richard G Hennig, Nitin Kumar, and Adri CT Van Duin. Reaxff molecular dynamics simulations on lithiated sulfur cathode materials. Physical Chemistry Chemical Physics, 17(5):3383–3393, 2015. URL: https://doi.org/10.1039/C4CP04532G.

[38]

Jonathan E Mueller, Adri CT Van Duin, and William A Goddard III. Development and validation of reaxff reactive force field for hydrocarbon chemistry catalyzed by nickel. The Journal of Physical Chemistry C, 114(11):4939–4949, 2010. URL: https://doi.org/10.1021/jp9035056.

[39]

Donato Fantauzzi, Jochen Bandlow, Lehel Sabo, Jonathan E Mueller, Adri CT van Duin, and Timo Jacob. Development of a reaxff potential for pt–o systems describing the energetics and dynamics of pt-oxide formation. Physical Chemistry Chemical Physics, 16(42):23118–23133, 2014. URL: https://doi.org/10.1039/C4CP03111C.

[40]

Thomas P Senftle, Michael J Janik, and Adri CT Van Duin. A reaxff investigation of hydride formation in palladium nanoclusters via monte carlo and molecular dynamics simulations. The Journal of Physical Chemistry C, 118(9):4967–4981, 2014. URL: https://doi.org/10.1021/jp411015a.

[41]

David A Newsome, Debasis Sengupta, Hosein Foroutan, Michael F Russo, and Adri CT Van Duin. Oxidation of silicon carbide by o2 and h2o: a reaxff reactive molecular dynamics study, part i. The Journal of Physical Chemistry C, 116(30):16111–16121, 2012. URL: https://doi.org/10.1021/jp306391p.

[42]

Kimberly Chenoweth, Adri CT Van Duin, Petter Persson, Mu-Jeng Cheng, Jonas Oxgaard, and William A Goddard Iii. Development and application of a reaxff reactive force field for oxidative dehydrogenation on vanadium oxide catalysts. The Journal of Physical Chemistry C, 112(37):14645–14654, 2008. URL: https://doi.org/10.1021/jp806988b.

[43]

Kichul Yoon, Ali Rahnamoun, Jacob L Swett, Vighter Iberi, David A Cullen, Ivan V Vlassiouk, Alex Belianinov, Stephen Jesse, Xiahan Sang, Olga S Ovchinnikova, and others. Atomistic-scale simulations of defect formation in graphene under noble gas ion irradiation. ACS nano, 10(9):8376–8384, 2016. URL: https://doi.org/10.1021/acsnano.6b03036.

[44]

Md Mahbubul Islam, Chenyu Zou, Adri CT Van Duin, and Sumathy Raman. Interactions of hydrogen with the iron and iron carbide interfaces: a reaxff molecular dynamics study. Physical Chemistry Chemical Physics, 18(2):761–771, 2016. URL: https://doi.org/10.1039/C5CP06108C.

[45]

Siavash Rajabpour, Qian Mao, Nadire Nayir, Joshua A Robinson, and Adri CT Van Duin. Development and applications of reaxff reactive force fields for group-iii gas-phase precursors and surface reactions with graphene in metal–organic chemical vapor deposition synthesis. The Journal of Physical Chemistry C, 125(19):10747–10758, 2021. URL: https://doi.org/10.1021/acs.jpcc.1c01965.

[46]

Nadire Nayir, Adri CT Van Duin, and Sakir Erkoc. Development of a reaxff reactive force field for interstitial oxygen in germanium and its application to geo2/ge interfaces. The Journal of Physical Chemistry C, 123(2):1208–1218, 2018. URL: https://doi.org/10.1021/acs.jpcc.8b08862.

[47]

Yun Kyung Shin, Mert Y Sengul, ASM Jonayat, Wonho Lee, Enrique D Gomez, Clive A Randall, and Adri CT Van Duin. Development of a reaxff reactive force field for lithium ion conducting solid electrolyte li 1+ x al x ti 2- x (po 4) 3 (latp). Physical Chemistry Chemical Physics, 20(34):22134–22147, 2018. URL: https://doi.org/10.1039/C8CP03586E.

[48]

Naoya Uene, Takuya Mabuchi, Masaru Zaitsu, Shigeo Yasuhara, Adri CT van Duin, and Takashi Tokumasu. Reactive force field molecular dynamics studies of the initial growth of boron nitride using bcl3 and nh3 by atomic layer deposition. The Journal of Physical Chemistry C, 128(3):1075–1086, 2024. URL: https://doi.org/10.1021/acs.jpcc.3c06704.

[49]

Dingyu Hou, Muye Feng, Jili Wei, Yi Wang, Adri CT van Duin, and Kai H Luo. A reactive force field molecular dynamics study on the inception mechanism of titanium tetraisopropoxide (ttip) conversion to titanium clusters. Chemical Engineering Science, 252:117496, 2022. URL: https://doi.org/10.1016/j.ces.2022.117496.

[50]

Federico A Soria, Weiwei Zhang, Patricia A Paredes-Olivera, Adri CT Van Duin, and Eduardo M Patrito. Si/c/h reaxff reactive potential for silicon surfaces grafted with organic molecules. The Journal of Physical Chemistry C, 122(41):23515–23527, 2018. URL: https://doi.org/10.1021/acs.jpcc.8b07075.

[51]

Falk Niefind, Qian Mao, Nadire Nayir, Malgorzata Kowalik, Jung-Joon Ahn, Andrew J Winchester, Chengye Dong, Rinu A Maniyara, Joshua A Robinson, Adri CT van Duin, and others. Watching (de) intercalation of 2d metals in epitaxial graphene: insight into the role of defects. Small, 20(11):2306554, 2024. URL: https://doi.org/10.1002/smll.202306554.

[52]

Swarit Dwivedi, Malgorzata Kowalik, Nilton Rosenbach, Dalal S Alqarni, Yun Kyung Shin, Yongjian Yang, John C Mauro, Akshat Tanksale, Alan L Chaffee, and Adri CT Van Duin. Atomistic mechanisms of thermal transformation in a zr-metal organic framework, mil-140c. The Journal of Physical Chemistry Letters, 12(1):177–184, 2020. URL: https://doi.org/10.1021/acs.jpclett.0c02930.

[53]

Yang Wang, Yuqing Shi, Qiang Sun, Kang Lu, Momoji Kubo, and Jingxiang Xu. Development of a transferable reaxff parameter set for carbon-and silicon-based solid systems. The Journal of Physical Chemistry C, 124(18):10007–10015, 2020. URL: https://doi.org/10.1021/acs.jpcc.0c01645.

[54]

Jejoon Yeon, Heather L Adams, Chad E Junkermeier, Adri CT Van Duin, Wilfred T Tysoe, and Ashlie Martini. Development of a reaxff force field for cu/s/c/h and reactive md simulations of methyl thiolate decomposition on cu (100). The Journal of Physical Chemistry B, 122(2):888–896, 2018. URL: https://doi.org/10.1021/acs.jpcb.7b06976.

[55]

Qian Mao, Yuwei Zhang, Malgorzata Kowalik, Nadire Nayir, Michael Chandross, and Adri CT van Duin. Oxidation and hydrogenation of monolayer mos2 with compositing agent under environmental exposure: the reaxff mo/ti/au/o/s/h force field development and applications. Frontiers in Nanotechnology, 4:1034795, 2022. URL: https://doi.org/10.3389/fnano.2022.1034795.

[56]

HS Huang, LQ Ai, ACT Van Duin, M Chen, and YJ Lü. Reaxff reactive force field for molecular dynamics simulations of liquid cu and zr metals. The Journal of Chemical Physics, 2019. URL: https://doi.org/10.1063/1.5112794.

[57]

Dong Hyun Kim, Seung Jae Kwak, Jae Hun Jeong, Suyoung Yoo, Sang Ki Nam, YongJoo Kim, and Won Bo Lee. Molecular dynamics simulation of silicon dioxide etching by hydrogen fluoride using the reactive force field. ACS omega, 6(24):16009–16015, 2021. URL: https://doi.org/10.1021/acsomega.1c01824.

[58]

Alireza Ostadhossein, Sung-Yup Kim, Ekin D Cubuk, Yue Qi, and Adri CT Van Duin. Atomic insight into the lithium storage and diffusion mechanism of sio2/al2o3 electrodes of lithium ion batteries: reaxff reactive force field modeling. The Journal of Physical Chemistry A, 120(13):2114–2127, 2016. URL: https://doi.org/10.1021/acs.jpca.5b11908.

[59]

Alireza Ostadhossein, Ali Rahnamoun, Yuanxi Wang, Peng Zhao, Sulin Zhang, Vincent H Crespi, and Adri CT Van Duin. Reaxff reactive force-field study of molybdenum disulfide (mos2). The journal of physical chemistry letters, 8(3):631–640, 2017. URL: https://doi.org/10.1021/acs.jpclett.6b02902.

[60]

Mike Pols, Adri CT van Duin, Sofía Calero, and Shuxia Tao. Mixing i and br in inorganic perovskites: atomistic insights from reactive molecular dynamics simulations. The Journal of Physical Chemistry C, 128(9):4111–4118, 2024. URL: https://doi.org/10.1021/acs.jpcc.4c00563.

[61]

Mike Pols, José Manuel Vicent-Luna, Ivo Filot, Adri CT Van Duin, and Shuxia Tao. Atomistic insights into the degradation of inorganic halide perovskite cspbi3: a reactive force field molecular dynamics study. The journal of physical chemistry letters, 12(23):5519–5525, 2021. URL: https://doi.org/10.1021/acs.jpclett.1c01192.

[62]

Stéphane B Olou’ou Guifo, Jonathan E Mueller, Diana van Duin, Mahdi K Talkhoncheh, Adri CT van Duin, David Henriques, and Torsten Markus. Development and validation of a reaxff reactive force field for modeling silicon–carbon composite anode materials in lithium-ion batteries. The Journal of Physical Chemistry C, 127(6):2818–2834, 2023. URL: https://doi.org/10.1021/acs.jpcc.2c07773.

[63]

Florian Fiesinger, Daniel Gaissmaier, Matthias van den Borg, Julian Beßner, Adri CT van Duin, and Timo Jacob. Development of a mg/o reaxff potential to describe the passivation processes in magnesium-ion batteries. ChemSusChem, 16(3):e202201821, 2023. URL: https://doi.org/10.1002/cssc.202201821.

[64]

Wan Du, Xue Fan, Hui Li, Dong Zhai, and Yi Liu. Development of a ni–al reactive force field for ni-based superalloy: revealing electrostatic effects on mechanical deformation. Journal of Materials Research and Technology, 24:4454–4467, 2023. URL: https://doi.org/10.1016/j.jmrt.2023.04.038.

[65]

Yun Kyung Shin, Yawei Gao, Dongwon Shin, and Adri CT van Duin. Impact of three-body interactions in a reaxff force field for ni and cr transition metals and their alloys on the prediction of thermal and mechanical properties. Computational Materials Science, 197:110602, 2021. URL: https://doi.org/10.1016/j.commatsci.2021.110602.

[66]

Chidozie Onwudinanti, Mike Pols, Geert Brocks, Vianney Koelman, Adri CT Van Duin, Thomas Morgan, and Shuxia Tao. A reaxff molecular dynamics study of hydrogen diffusion in ruthenium–the role of grain boundaries. The Journal of Physical Chemistry C, 126(13):5950–5959, 2022. URL: https://doi.org/10.1021/acs.jpcc.1c08776.

[67]

Sung-Yup Kim, Hong Woo Lee, Sung Jin Pai, and Sang Soo Han. Activity, selectivity, and durability of ruthenium nanoparticle catalysts for ammonia synthesis by reactive molecular dynamics simulation: the size effect. ACS applied materials & interfaces, 10(31):26188–26194, 2018. URL: https://doi.org/10.1021/acsami.8b05070.

[68]

Jejoon Yeon, Sanjib C Chowdhury, Chaitanya M Daksha, and John W Gillespie Jr. Development of mg/al/si/o reaxff parameters for magnesium aluminosilicate glass using an artificial neural network-assisted genetic algorithm. The Journal of Physical Chemistry C, 125(33):18380–18394, 2021. URL: https://doi.org/10.1021/acs.jpcc.1c01190.

[69]

Nadire Nayir, Adri CT Van Duin, and Sakir Erkoc. Development of the reaxff reactive force field for inherent point defects in the si/silica system. The Journal of Physical Chemistry A, 123(19):4303–4313, 2019. URL: https://doi.org/10.1021/acs.jpca.9b01481.

[70]

Nadire Nayir, Yun Kyung Shin, Yuanxi Wang, Mert Y Sengul, Danielle Reifsnyder Hickey, Mikhail Chubarov, Tanushree H Choudhury, Nasim Alem, Joan Redwing, Vincent H Crespi, and others. A reaxff force field for 2d-ws2 and its interaction with sapphire. The Journal of Physical Chemistry C, 125(32):17950–17961, 2021. URL: https://doi.org/10.1021/acs.jpcc.1c03605.

[71]

Adam D Mayernick, Matthias Batzill, Adri CT Van Duin, and Michael J Janik. A reactive force-field (reaxff) monte carlo study of surface enrichment and step structure on yttria-stabilized zirconia. Surface science, 604(17-18):1438–1444, 2010. URL: https://doi.org/10.1016/j.susc.2010.05.006.

[72]

Shu-Sheng Liu, Leton C Saha, Albert Iskandarov, Takayoshi Ishimoto, Tomokazu Yamamoto, Yoshitaka Umeno, Syo Matsumura, and Michihisa Koyama. Atomic structure observations and reaction dynamics simulations on triple phase boundaries in solid-oxide fuel cells. Communications Chemistry, 2(1):48, 2019. URL: https://doi.org/10.1038/s42004-019-0148-x.

[73]

Sungwook Hong and Adri CT Van Duin. Atomistic-scale analysis of carbon coating and its effect on the oxidation of aluminum nanoparticles by reaxff-molecular dynamics simulations. The Journal of Physical Chemistry C, 120(17):9464–9474, 2016. URL: https://doi.org/10.1021/acs.jpcc.6b00786.

[74]

Yuanxia Zheng, Sungwook Hong, George Psofogiannakis, G Bruce Rayner Jr, Suman Datta, Adri CT Van Duin, and Roman Engel-Herbert. Modeling and in situ probing of surface reactions in atomic layer deposition. ACS applied materials & interfaces, 9(18):15848–15856, 2017. URL: https://doi.org/10.1021/acsami.7b01618.

[75]

Hegoi Manzano, Roland JM Pellenq, Franz-Josef Ulm, Markus J Buehler, and Adri CT Van Duin. Hydration of calcium oxide surface predicted by reactive force field molecular dynamics. Langmuir, 28(9):4187–4197, 2012. URL: https://doi.org/10.1021/la204338m.

[76]

Mark V Fedkin, Yun Kyung Shin, Nabankur Dasgupta, Jejoon Yeon, Weiwei Zhang, Diana Van Duin, Adri CT Van Duin, Kento Mori, Atsushi Fujiwara, Masahiko Machida, and others. Development of the reaxff methodology for electrolyte–water systems. The Journal of Physical Chemistry A, 123(10):2125–2141, 2019. URL: https://doi.org/10.1021/acs.jpca.8b10453.

[77]

Masoud Aryanpour, Adri CT Van Duin, and James D Kubicki. Development of a reactive force field for iron- oxyhydroxide systems. The Journal of Physical Chemistry A, 114(21):6298–6307, 2010. URL: https://doi.org/10.1021/jp101332k.

[78]

Yun Kyung Shin, Hyunwook Kwak, Alex V Vasenkov, Debasis Sengupta, and Adri CT Van Duin. Development of a reaxff reactive force field for fe/cr/o/s and application to oxidation of butane over a pyrite-covered cr2o3 catalyst. Acs Catalysis, 5(12):7226–7236, 2015. URL: https://doi.org/10.1021/acscatal.5b01766.

[79]

Francesca Tavazza, Thomas P Senftle, Chenyu Zou, Chandler A Becker, and AC T Van Duin. Molecular dynamics investigation of the effects of tip–substrate interactions during nanoindentation. The Journal of Physical Chemistry C, 119(24):13580–13589, 2015. URL: https://doi.org/10.1021/acs.jpcc.5b01275.

[80]

Obaidur Rahaman, Adri CT Van Duin, William A Goddard III, and Douglas J Doren. Development of a reaxff reactive force field for glycine and application to solvent effect and tautomerization. The Journal of Physical Chemistry B, 115(2):249–261, 2011. URL: https://doi.org/10.1021/jp108642r.

[81]

Tomas Trnka, Igor Tvaroska, and Jaroslav Koca. Automated training of reaxff reactive force fields for energetics of enzymatic reactions. Journal of chemical theory and computation, 14(1):291–302, 2018. URL: https://doi.org/10.1021/acs.jctc.7b00870.

[82]

Malgorzata Kowalik, Chowdhury Ashraf, Behzad Damirchi, Dooman Akbarian, Siavash Rajabpour, and Adri CT Van Duin. Atomistic scale analysis of the carbonization process for c/h/o/n-based polymers with the reaxff reactive force field. The Journal of Physical Chemistry B, 123(25):5357–5367, 2019. URL: https://doi.org/10.1021/acs.jpcb.9b04298.

[83]

Evgeny Moerman, David Furman, and David J Wales. Development of reaxff reactive force field for aqueous iron–sulfur clusters with applications to stability and reactivity in water. Journal of Chemical Information and Modeling, 61(3):1204–1214, 2021. URL: https://doi.org/10.1021/acs.jcim.0c01292.

[84]

Liangliang Huang, Teresa Bandosz, Kaushik L Joshi, Adri CT Van Duin, and Keith E Gubbins. Reactive adsorption of ammonia and ammonia/water on cubtc metal-organic framework: a reaxff molecular dynamics simulation. The Journal of chemical physics, 2013. URL: https://doi.org/10.1063/1.4774332.

[85]

Susanna Monti, Cui Li, and Vincenzo Carravetta. Reactive dynamics simulation of monolayer and multilayer adsorption of glycine on cu (110). The Journal of Physical Chemistry C, 117(10):5221–5228, 2013. URL: https://doi.org/10.1021/jp312828d.

[86]

Susanna Monti, Alessandro Corozzi, Peter Fristrup, Kaushik L Joshi, Yun Kyung Shin, Peter Oelschlaeger, Adri CT Van Duin, and Vincenzo Barone. Exploring the conformational and reactive dynamics of biomolecules in solution using an extended version of the glycine reactive force field. Physical Chemistry Chemical Physics, 15(36):15062–15077, 2013. URL: https://doi.org/10.1039/C3CP51931G.

[87]

Weiwei Zhang and Adri CT Van Duin. Improvement of the reaxff description for functionalized hydrocarbon/water weak interactions in the condensed phase. The Journal of Physical Chemistry B, 122(14):4083–4092, 2018. URL: https://doi.org/10.1021/acs.jpcb.8b01127.

[88]

Stijn Huygh, Annemie Bogaerts, Adri CT Van Duin, and Erik C Neyts. Development of a reaxff reactive force field for intrinsic point defects in titanium dioxide. Computational materials science, 95:579–591, 2014. URL: https://doi.org/10.1016/j.commatsci.2014.07.056.

[89]

Sung-Yup Kim, Adri CT Van Duin, and James D Kubicki. Molecular dynamics simulations of the interactions between tio 2 nanoparticles and water with na+ and cl-, methanol, and formic acid using a reactive force field. Journal of Materials Research, 28:513–520, 2013. URL: https://doi.org/10.1557/jmr.2012.367.

[90]

Sung-Yup Kim and Adri CT van Duin. Simulation of titanium metal/titanium dioxide etching with chlorine and hydrogen chloride gases using the reaxff reactive force field. The Journal of Physical Chemistry A, 117(27):5655–5663, 2013. URL: https://doi.org/10.1021/jp4031943.

[91]

Susanna Monti, Vincenzo Carravetta, and Hans Ågren. Simulation of gold functionalization with cysteine by reactive molecular dynamics. The journal of physical chemistry letters, 7(2):272–276, 2016. URL: https://doi.org/10.1021/acs.jpclett.5b02769.

[92]

Karthik Ganeshan, Yun Kyung Shin, Naresh C Osti, Yangyunli Sun, Kaitlyn Prenger, Michael Naguib, Madhusudan Tyagi, Eugene Mamontov, De-en Jiang, and Adri CT Van Duin. Structure and dynamics of aqueous electrolytes confined in 2d-tio2/ti3c2t2 mxene heterostructures. ACS Applied Materials & Interfaces, 12(52):58378–58389, 2020. URL: https://doi.org/10.1021/acsami.0c17536.

[93]

Adam Lloyd, David Cornil, ACT Van Duin, Diana van Duin, Roger Smith, SD Kenny, Jérôme Cornil, and David Beljonne. Development of a reaxff potential for ag/zn/o and application to ag deposition on zno. Surface Science, 645:67–73, 2016. URL: https://doi.org/10.1016/j.susc.2015.11.009.

[94]

George M Psofogiannakis, John F McCleerey, Eugenio Jaramillo, and Adri CT Van Duin. Reaxff reactive molecular dynamics simulation of the hydration of cu-ssz-13 zeolite and the formation of cu dimers. The Journal of Physical Chemistry C, 119(12):6678–6686, 2015. URL: https://doi.org/10.1021/acs.jpcc.5b00699.

[95]

Chen Bai, Lianchi Liu, and Huai Sun. Molecular dynamics simulations of methanol to olefin reactions in hzsm-5 zeolite using a reaxff force field. The Journal of Physical Chemistry C, 116(12):7029–7039, 2012. URL: https://doi.org/10.1021/jp300221j.

[96]

Yue Liu, Qintao Sun, Peiping Yu, Yu Wu, Liang Xu, Hao Yang, Miao Xie, Tao Cheng, and William A Goddard III. Effects of high and low salt concentrations in electrolytes at lithium–metal anode surfaces using dft-reaxff hybrid molecular dynamics method. The Journal of Physical Chemistry Letters, 12(11):2922–2929, 2021. URL: https://doi.org/10.1021/acs.jpclett.1c00279.

[97]

Seung Ho Hahn, Jessica Rimsza, Louise Criscenti, Wei Sun, Lu Deng, Jincheng Du, Tao Liang, Susan B Sinnott, and Adri CT Van Duin. Development of a reaxff reactive force field for nasio x/water systems and its application to sodium and proton self-diffusion. The Journal of Physical Chemistry C, 122(34):19613–19624, 2018. URL: https://doi.org/10.1021/acs.jpcc.8b05852.

[98]

Sang Soo Han, Seung-Hoon Choi, and Adri CT Van Duin. Molecular dynamics simulations of stability of metal–organic frameworks against h 2 o using the reaxff reactive force field. Chemical communications, 46(31):5713–5715, 2010. URL: https://doi.org/10.1039/C0CC01132K.

[99]

Badri Narayanan, Adri CT Van Duin, Branden B Kappes, Ivar E Reimanis, and Cristian V Ciobanu. A reactive force field for lithium–aluminum silicates with applications to eucryptite phases. Modelling and Simulation in Materials Science and Engineering, 20(1):015002, 2011. URL: https://doi.org/10.1088/0965-0393/20/1/015002.

[100]

Weiwei Zhang and Adri CT Van Duin. Second-generation reaxff water force field: improvements in the description of water density and oh-anion diffusion. The Journal of Physical Chemistry B, 121(24):6021–6032, 2017. URL: https://doi.org/10.1021/acs.jpcb.7b02548.

[101]

David Raymand, Adri CT van Duin, Daniel Spångberg, William A Goddard III, and Kersti Hermansson. Water adsorption on stepped zno surfaces from md simulation. Surface science, 604(9-10):741–752, 2010. URL: https://doi.org/10.1016/j.susc.2009.12.012.