Thermodynamic properties of molecules and clusters
The prediction of thermodynamic properties of molecules and molecular clusters is an active research area in our group (also see "Aerosolized environmental nanoparticles" above). This line of endeavor arose from postdoctoral research under Donald Truhlar (U. Minnesota) and David Freeman (U. Rhode Island). Current work includes collaboration with Mark Tuckerman (New York U).
(1) E. Schneider, L. Dai, R.Q. Topper, C. Drechsel-Grau, and M.E. Tuckerman, Stochastic neural network approach for learning high-dimensional free energy surfaces, Physical Review Letters, accepted (2017).
(1) R.Q. Topper, D.L. Freeman, D. Bergin* and K. LaMarche**, Computational techniques and strategies for Monte Carlo thermodynamic calculations with applications to nanoclusters, invited book chapter, Reviews in Computational Chemistry, Vol. 19, pp. 1-41, K.B. Lipkowitz, R. Larter and T.R. Cundari, Eds., Wiley-VCH/John Wiley and Sons, New York (2003). ISBN 0-471-23585-7. PDF
(2) R.Q. Topper, Adaptive path-integral Monte Carlo methods for accurate computation of molecular thermodynamic properties, invited book chapter, Monte Carlo Methods in Chemical Physics, Advances in Chemical Physics105, Chapter 5, pp. 117-170, D. Ferguson, I. Siepmann, and D.G. Truhlar, Eds., John Wiley & Sons, Inc., New York (1999).
(3) R.Q. Topper, Q. Zhang, Y.-P. Liu, and D.G. Truhlar, Quantum steam tables. Free energy calculations for H2O,D2O, H2S, and H2Se by adaptively optimized Fourier path integrals, Journal of Chemical Physics98, 4991 (1993). PDF
(5) R.Q. Topper and D.G. Truhlar, Quantum free-energy calculations: Optimized Fourier path-integral Monte Carlo computation of coupled vibrational partition functions,Journal of Chemical Physics97, 3648 (1992). PDF
* = Undergraduate / graduate student researcher.
**=Undergraduate student researcher.