0
Research Papers

Modification of Nóse–Hoover Thermostat to Improve Temperature Response in Molecular Simulations

[+] Author and Article Information
Ashley Guy

The Robotics, Biomechanics, and
Dynamic Systems Laboratory,
Department of Mechanical and
Aerospace Engineering,
University of Texas at Arlington,
Arlington, TX 76019
e-mail: ashley.guy@mavs.uta.edu

Alan Bowling

Mem. ASME
Associate Professor
The Robotics, Biomechanics, and
Dynamic Systems Laboratory,
Department of Mechanical and
Aerospace Engineering,
University of Texas at Arlington,
Arlington, TX 76019
e-mail: bowling@uta.edu

Contributed by the Design Engineering Division of ASME for publication in the JOURNAL OF COMPUTATIONAL AND NONLINEAR DYNAMICS. Manuscript received September 23, 2015; final manuscript received October 24, 2016; published online January 16, 2017. Assoc. Editor: Dan Negrut.

J. Comput. Nonlinear Dynam 12(3), 031019 (Jan 16, 2017) (6 pages) Paper No: CND-15-1302; doi: 10.1115/1.4035191 History: Received September 23, 2015; Revised October 24, 2016

This work investigates the modification of the Nóse–Hoover thermostat, a well-known tool for controlling system temperature in nanoscale dynamical simulations. Nóse–Hoover response is characterized by a mean temperature converging to a target temperature. However, oscillations in the actual system temperature consistently appear over time. To reduce these oscillations, the Nóse–Hoover control law is modified to resemble a proportional–derivative controller. The modified thermostat is compared to the standard and shown to significantly reduce deviations. Gains are varied and compared to show effects on response and simulation time. Work–energy calculations show the modified dynamics drive the system to a low-energy state significantly faster than the standard. The behavior of the modified thermostat is illustrated using a simulation of a molten salt solution.

FIGURES IN THIS ARTICLE
<>
Copyright © 2017 by ASME
Your Session has timed out. Please sign back in to continue.

References

Figures

Grahic Jump Location
Fig. 1

Mechanical model: sodium, potassium, and nitrate ions represented by spherical particles

Grahic Jump Location
Fig. 2

Time evolution of system. Cations (small) and anions (medium) are shown here interacting with a silicon dioxide nanoparticle (large). Ionic radii are enlarged for viewing.

Grahic Jump Location
Fig. 3

Temperature response using standard thermostat for fixed and stepped target temperatures. Brownian motion disabled.

Grahic Jump Location
Fig. 4

Temperature response using modified thermostat for fixed and stepped target temperatures. Brownian motion disabled.

Grahic Jump Location
Fig. 5

Brownian motion enabled

Grahic Jump Location
Fig. 6

Brownian motion enabled

Grahic Jump Location
Fig. 7

Effect of varying gains on response. (a) O(Q) = 1, (b) O(Q) = 10, (c) O(Q) = 100, and (d) O(Q) = 1000. The inset shows the order of the derivative gain.

Grahic Jump Location
Fig. 8

Effect of varying gains on simulation time

Grahic Jump Location
Fig. 9

System energy and thermostat work. (a) Standard thermostat, (b) modified thermostat, and (c) comparison of total system energy from (a) and (b).

Tables

Errata

Discussions

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In