Editing Molecular dynamics (section)

== History ==
MD was originally developed in the early 1950s, following earlier successes with [[Monte Carlo simulation]]s{{Em dash}}which themselves date back to the eighteenth century, in the [[Buffon's needle problem]] for example{{Em dash}}but was popularized for [[statistical mechanics]] at [[Los Alamos National Laboratory]] by [[Marshall Rosenbluth]] and [[Nicholas Metropolis]] in what is known today as the [[Metropolis–Hastings algorithm]]. Interest in the time evolution of [[N-body problem|N-body systems]] dates much earlier to the seventeenth century, beginning with [[Isaac Newton]], and continued into the following century largely with a focus on [[celestial mechanics]] and issues such as the [[Stability of the Solar System|stability of the Solar System]]. Many of the numerical methods used today were developed during this time period, which predates the use of computers; for example, the most common integration algorithm used today, the [[Verlet integration]] algorithm, was used as early as 1791 by [[Jean Baptiste Joseph Delambre]]. Numerical calculations with these algorithms can be considered to be MD done "by hand".

As early as 1941, integration of the many-body equations of motion was carried out with [[Analog computer|analog computers]]. Some undertook the labor-intensive work of modeling atomic motion by constructing physical models, e.g., using macroscopic spheres. The aim was to arrange them in such a way as to replicate the structure of a liquid and use this to examine its behavior. [[J.D. Bernal]] describes this process in 1962, writing:<ref>{{cite journal |title=The Bakerian Lecture, 1962 The structure of liquids |journal=Proceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences |date=January 1997 |volume=280 |issue=1382 |pages=299–322 |doi=10.1098/rspa.1964.0147 |bibcode=1964RSPSA.280..299B | vauthors = Bernal JD |s2cid=178710030 }}</ref><blockquote>... I took a number of rubber balls and stuck them together with rods of a selection of different lengths ranging from 2.75 to 4 inches. I tried to do this in the first place as casually as possible, working in my own office, being interrupted every five minutes or so and not remembering what I had done before the interruption.</blockquote>Following the discovery of microscopic particles and the development of computers, interest expanded beyond the proving ground of gravitational systems to the statistical properties of matter. In an attempt to understand the origin of [[irreversibility]], [[Enrico Fermi]] proposed in 1953, and published in 1955,<ref name=fput>Fermi E., Pasta J., Ulam S., Los Alamos report LA-1940 (1955).</ref> the use of the early computer [[MANIAC I]], also at [[Los Alamos National Laboratory]], to solve the time evolution of the equations of motion for a many-body system subject to several choices of force laws. Today, this seminal work is known as the [[Fermi–Pasta–Ulam–Tsingou problem]]. The time evolution of the energy from the original work is shown in the figure to the right.

[[File:Time evolution of energy for FPUT N-body dynamics.jpg|thumb|upright=1.35|One of the earliest simulations of an N-body system was carried out on the MANIAC-I by Fermi and coworkers to understand the origins of irreversibility in nature. Shown here is the energy versus time for a 64-particle system.]]
In 1957, [[Berni Alder]] and Thomas Wainwright used an [[IBM 704]] computer to simulate perfectly [[Elastic collision|elastic collisions]] between [[hard spheres]].<ref name="a&w">{{cite journal |vauthors=Alder BJ, Wainwright T |date=August 1959 |title=Studies in Molecular Dynamics. I. General Method |journal=The Journal of Chemical Physics |volume=31 |issue=2 |pages=459–466 |bibcode=1959JChPh..31..459A |doi=10.1063/1.1730376}}</ref> In 1960, in perhaps the first realistic simulation of matter, J.B. Gibson ''et al''. simulated radiation damage of [[Native copper|solid copper]] by using a [[Born–Mayer equation|Born–Mayer]] type of repulsive interaction along with a [[Cohesion (chemistry)|cohesive]] surface force.<ref>{{cite journal |vauthors=Gibson JB, Goland AN, Milgram M, Vineyard G |year=1960 |title=Dynamics of Radiation Damage |journal=Phys. Rev. |volume=120 |issue=4 |pages=1229–1253 |doi=10.1103/PhysRev.120.1229 |bibcode=1960PhRv..120.1229G}}</ref> In 1964, [[Aneesur Rahman]] published simulations of liquid [[argon]] that used a [[Lennard-Jones potential]]; calculations of system properties, such as the coefficient of [[self-diffusion]], compared well with experimental data.<ref name="a.rahman">{{cite journal |author-link1=Aneesur Rahman |vauthors=Rahman A |date=19 October 1964 |title=Correlations in the Motion of Atoms in Liquid Argon |journal=Physical Review |volume=136 |issue=2A |pages=A405–A411 |bibcode=1964PhRv..136..405R |doi=10.1103/PhysRev.136.A405}}</ref> Today, the Lennard-Jones potential is still one of the most frequently used [[Interatomic potential|intermolecular potentials]].<ref>{{cite journal |vauthors=Stephan S, Thol M, Vrabec J, Hasse H |title=Thermophysical Properties of the Lennard-Jones Fluid: Database and Data Assessment |journal=Journal of Chemical Information and Modeling |volume=59 |issue=10 |pages=4248–4265 |date=October 2019 |pmid=31609113 |doi=10.1021/acs.jcim.9b00620 |s2cid=204545481 |url=https://depositonce.tu-berlin.de/handle/11303/10447}}</ref><ref>{{cite journal |vauthors=Wang X, Ramírez-Hinestrosa S, Dobnikar J, Frenkel D |title=The Lennard-Jones potential: when (not) to use it |journal=Physical Chemistry Chemical Physics |volume=22 |issue=19 |pages=10624–10633 |date=May 2020 |pmid=31681941 |doi=10.1039/C9CP05445F |arxiv=1910.05746 |s2cid=204512243 |bibcode=2020PCCP...2210624W}}</ref> It is used for describing simple substances (a.k.a. [[Lennard-Jones potential|Lennard-Jonesium]]<ref>{{Cite journal |vauthors=Mick J, Hailat E, Russo V, Rushaidat K, Schwiebert L, Potoff J |date=December 2013 |title=GPU-accelerated Gibbs ensemble Monte Carlo simulations of Lennard-Jonesium |journal=Computer Physics Communications |language=en |volume=184 |issue=12 |pages=2662–2669 |doi=10.1016/j.cpc.2013.06.020 |bibcode=2013CoPhC.184.2662M}}</ref><ref>{{Cite journal |vauthors=Chapela GA, Scriven LE, Davis HT |date=October 1989 |title=Molecular dynamics for discontinuous potential. IV. Lennard-Jonesium |url=http://aip.scitation.org/doi/10.1063/1.456811 |journal=The Journal of Chemical Physics |language=en |volume=91 |issue=7 |pages=4307–4313 |doi=10.1063/1.456811 |bibcode=1989JChPh..91.4307C |issn=0021-9606}}</ref><ref>{{cite journal | vauthors = Lenhard J, Stephan S, Hasse H | title = A child of prediction. On the History, Ontology, and Computation of the Lennard-Jonesium | journal = Studies in History and Philosophy of Science | volume = 103 | pages = 105–113 | date = February 2024 | pmid = 38128443 | doi = 10.1016/j.shpsa.2023.11.007 | s2cid = 266440296 }}</ref>) for conceptual and model studies and as a building block in many [[Force field (chemistry)|force fields]] of real substances.<ref>{{Cite journal |vauthors=Eggimann BL, Sunnarborg AJ, Stern HD, Bliss AP, Siepmann JI |date=2013-12-24 |title=An online parameter and property database for the TraPPE force field |journal=Molecular Simulation |volume=40 |issue=1–3 |pages=101–105 |doi=10.1080/08927022.2013.842994 |s2cid=95716947 |issn=0892-7022}}</ref><ref>{{Cite journal |vauthors=Stephan S, Horsch MT, Vrabec J, Hasse H |date=2019-07-03 |title=MolMod – an open access database of force fields for molecular simulations of fluids |journal=Molecular Simulation |language=en |volume=45 |issue=10 |pages=806–814 |doi=10.1080/08927022.2019.1601191 |s2cid=119199372 |issn=0892-7022|url=https://osf.io/m87cy/ |arxiv=1904.05206 }}</ref>