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Kinetic rates at different temperatures and the associated Arrhenius parameters, whenever Arrhenius law is obeyed, are efficiently estimated by applying maximum likelihood analysis to waiting times collected using the temperature programmed molecular dynamics method. When transitions involving many activated pathways are available in the dataset, their rates may be calculated using the same collection of waiting times. Arrhenius behaviour is ascertained by comparing rates at the sampled temperatures with ones from the Arrhenius expression. Three prototype systems with corrugated energy landscapes, namely, solvated alanine dipeptide, diffusion at the metal-solvent interphase, and lithium diffusion in silicon, are studied to highlight various aspects of the method. The method becomes particularly appealing when the Arrhenius parameters can be used to find rates at low temperatures where transitions are rare. Systematic coarse-graining of states can further extend the time scales accessible to the method. Good estimates for the rate parameters are obtained with 500-1000 waiting times. Published by AIP Publishing.

Several studies in the past have generated Markov State Models (MSMs), i.e., kinetic models, of biomolecular systems by post-analyzing long standard molecular dynamics (MD) calculations at the temperature of interest and focusing on the maximally ergodic subset of states. Questions related to goodness of these models, namely, importance of the missing states and kinetic pathways, and the time for which the kinetic model is valid, are generally left unanswered. We show that similar questions arise when we generate a room-temperature MSM (denoted MSM-A) for solvated alanine dipeptide using state-constrained MD calculations at higher temperatures and Arrhenius relation - the main advantage of such a procedure being a speed-up of several thousand times over standard MD-based MSM building procedures. Bounds for rate constants calculated using probability theory from state-constrained MD at room temperature help validate MSM-A. However, bounds for pathways possibly missing in MSM-A show that alternate kinetic models exist that produce the same dynamical behaviour at short time scales as MSM-A but diverge later. Even in the worst case scenario, MSM-A is found to be valid longer than the time required to generate it. Concepts introduced here can be straightforwardly extended to other MSM building techniques. (C) 2015 AIP Publishing LLC.

We present a hierarchical coarse-grained simulation technique called the temperature programmed molecular dynamics (TPMD) method for accelerating molecular dynamics (MD) simulations of rare events. The method is targeted towards materials where a system visits many times a collection of energy basins in the potential energy surface, called a superbasin, via low-barrier moves before escaping to a new superbasin via a high-barrier move. The superbasin escape events are rare at the MD time scales. The low-barrier moves become accessible to MD by employing a temperature program, i.e., the MD temperature changes during the simulation. Once a superbasin is detected, transitions within the superbasin are ignored, in effect causing coarse-graining of basins. The temperature program enables the system to escape from the superbasin with reduced computational cost thereby overcoming the "low-barrier" problem. The main advantage of our approach is that the superbasin-to-superbasin transitions are accurately obtained at the original temperature with a reasonable computational cost. We study surface diffusion in Ag/Ag(001) system and demonstrate the ability of the TPMD method to span a wide-range of timescales. (C) 2014 AIP Publishing LLC.