. 2023 Feb 17;18(1):18. doi: 10.1186/s11671-023-03792-x

Table 4.

Most commonly employed simulation techniques for nanoparticles

Simulation type	Representatives	Force field	Time scale	Spatial-scale	Advantages	Disadvantages	Applications
Quantum mechanical (QM) Calculations	Density functional theory (DFT) [261]		10^–15 s	$10^{3}$ atoms	Most accurate and detailed molecular method	Limited spatio-temporal scales	Structure, stability, and electronic properties of a nanomaterial
	QM/molecular mechanical(MM) method [262, 263]		10^–15 s	$10^{3}$ atoms	Most accurate and detailed molecular method	Limited spatio-temporal scales
All-atom molecular simulation	Atomistic Monte Carlo (MC) [264]		10^–9 s	1–10 nm	The atoms are explicitly modeled Parameters are obtained based on experimental and QM calculations	Limited spatio-temporal scales Lack of suitable parameters for NPs	Adsorption, etc. Compatibility studies, molecular diffusion, interface chemistry, etc
All-atom molecular simulation	Atomistic molecular dynamics (AMD) simulation [265]	GROMOS [266]; CHARMM [267]; OPLS [268]; AMBER [269]	10^–9 s	1–10 nm
Coarse-grained molecular simulation	Coarse-grained (CG) molecular dynamics (MD)	MARTINI [270]; L–J [271]	10^–9–10^–6 s	10–100 nm	Increase of spatio-temporal scales upto 2 orders $O (2)$ of magnitudes as compared to AMD	Does not provide atomic level resolution Implementation is not straight-forward Beads can cross -over each other	Membrane Fusion Processes [272], Phase separation, self-assembled structure, cell membrane, etc
Coarse-grained molecular simulation	Dissipative particle dynamics (DPD) [273]	Soft-Potentials	10^–9–10^–6 s	10–100 nm