9. Molecular Dynamics Simulations in Biology, Chemistry and Physics

Abstract

Abstract. We review recent progress in understanding fundamental processes in biology, chemistry and physics on the basis of ab initio and molecular dynamics simulations. The first step of the visual process involving the excitation of bovine rhodopsin after absorption of light is taken as an example from biochemistry to demonstrate what is nowadays possible to simulate numerically. The act of freezing of water has recently been simulated, for the first time successfully, by scientists from chemistry. Martensitic transformation in bulk and nanophase materials, a typical and hitherto not completely solved problem from solid state physics, is used to illustrate the achievements of multimillion atoms simulations. Molecular Dynamics as a Multidisciplinary Numerical ToolMolecular dynamics (MD) has proved to be an optimum numerical recipe applicable to problems with many degrees of freedom from quite different fields of science. The knowledge of the energy or potential landscape of interacting particles, like electrons and atoms, enables one to calculate the forces acting on the particles and to study the evolution of the system with time. As long as classical mechanics is appropriate to describe the dynamics of the individual constituents (i.e. atoms or molecules), the Newtonian equations of motion can be related to the statistical mechanics of the (classical) particles by using the equipartition theorem, i.e. by combining the equationsfor i = 1 . . . N particles. Although the equipartition theorem holds only for classical particles, to the authors' knowledge the combination of classical and statistical physics has also been used to simulate small molecules at low temperatures without critically discussing so far the limitations of 9.1 and 9.2 when applying to very small quantum mechanical systems. The forces in 9.1 are then simply related to the gradients of the potential energy surface (PES) of either the classical or the quantum mechanical N -particle system. For pedagogical reasons let us recall the classical constant-temperature case. Omitting the statistical average in 9.2 means that the temperature is a measure

Computer simulation of strain-induced phase transformations in thin Fe films

“…Secondly, the Meyer-Entel potential has a relatively simple EAM form; compared with the bond-order potential by Müller et al [38], the Meyer-Entel potential allows for a ten times faster calculation speed. Thirdly, the α-γ phase transition in Fe has been studied successfully in simulations, not only for bulk Fe [41,44,45], but also for Fe nanoparticles [46]. Finally, this potential has also been used to study thin-film systems [47,48] and phase transitions in iron nanowires [26][27][28].…”

Solid–solid phase transitions in Fe nanowires induced by axial strain

“…We perform molecular-dynamics simulations using the embedded-atom method (EAM) potential for iron proposed by Meyer and Entel [16], which reproduces qualitatively the bcc-fcc phase transition [17], with good results even for nanoparticles [18]. Recently we studied the role of the wire diameter in solid-solid phase transitions in Fe nanowires [15].…”

Martensitic and austenitic phase transformations in Fe–C nanowires

“…However, atomistic simulation methods have up to now rarely been used to study phase transitions in the Fe-C system. The majority of atomistic studies focused on transitions in pure iron [19][20][21][24][25][26][27][28][29][30][31][32] or in iron-metal alloys [33][34][35].…”