[SY-N5] Temperature Programmed Molecular Dynamics - Accessing rare events using a combination of finite time sampling and bias potentials
Invited
Rates of physical and chemical processes often obey Arrhenius law. Recently, we developed the temperature-programmed molecular dynamics (TPMD) method1,2,3 that provides a convenient way of estimating the Arrhenius parameters of kinetic pathways even in situations where the underlying landscape is rugged. The TPMD method employs a temperature program with finite temperature MD in order to accelerate thermally activated events from a particular state of the system. Kinetic pathways are sought from a collection of states without any prior knowledge of these pathways. Since kinetic pathways are selected with a probability that is proportional to their rate constants, we find that slow pathways with small pre-exponential factors and large activation barriers are rarely sampled with TPMD. We introduce a procedure to overcome this limitation by bias potentials. This additional feature in the TPMD method dramatically improves its ability to estimate Arrhenius parameters. Examples of the variation of the TPMD method are provided for metal surface diffusion in presence of solvent.
1. V Imandi, A Chatterjee, Estimating Arrhenius parameters using temperature programmed molecular dynamics, The Journal of Chemical Physics 145, 034104, 2016.
2. S Divi, A Chatterjee, Accelerating rare events while overcoming the low-barrier problem using a temperature program, The Journal of Chemical Physics 140 (18), 184116, 2014
3. A Chatterjee, Accelerating Rare Events and Building Kinetic Monte Carlo Models Using Temperature Programmed Molecular Dynamics, Journal of Materials Research, http://dx.doi.org/10.1557/jmr.2017.460
1. V Imandi, A Chatterjee, Estimating Arrhenius parameters using temperature programmed molecular dynamics, The Journal of Chemical Physics 145, 034104, 2016.
2. S Divi, A Chatterjee, Accelerating rare events while overcoming the low-barrier problem using a temperature program, The Journal of Chemical Physics 140 (18), 184116, 2014
3. A Chatterjee, Accelerating Rare Events and Building Kinetic Monte Carlo Models Using Temperature Programmed Molecular Dynamics, Journal of Materials Research, http://dx.doi.org/10.1557/jmr.2017.460