The Kinetic Monte Carlo Method as a Way To Solve the Master Equation for Interstellar Grain Chemistry

Cuppen, H. M.; Karssemeijer, Leendertjan; Lamberts, Thanja

doi:10.1021/cr400234a

Cited by 84 publications

(93 citation statements)

References 176 publications

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“…Thus, the reaction routes investigated in this study can be used to extend already-existing astrochemical simulations. In this respect, the lattice-gas kinetic Monte Carlo simulations are the most promising, as they account for the specific lattice position for each of the intermediate radicals required to form COMs with two, three, and more carbon atoms (Cuppen et al 2013;Vasyunin & Herbst 2013a;Chang & Herbst 2016;Garrod et al 2017). However, the direct implications of the formation routes presented in Figure 1 require better knowledge of branching ratios and the activation barriers of various H-atom addition and abstraction reactions.…”

Section: Conclusion and Astronomical Relevancementioning

confidence: 99%

Formation of Glycerol through Hydrogenation of CO Ice under Prestellar Core Conditions

Fedoseev

Chuang

Ioppolo

et al. 2017

ApJ

102

111

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Observational studies reveal that complex organic molecules (COMs) can be found in various objects associated with different star formation stages. The identification of COMs in prestellar cores, i.e., cold environments in which thermally induced chemistry can be excluded and radiolysis is limited by cosmic rays and cosmic-rayinduced UV photons, is particularly important as this stage sets up the initial chemical composition from which ultimately stars and planets evolve. Recent laboratory results demonstrate that molecules as complex as glycolaldehyde and ethylene glycol are efficiently formed on icy dust grains via nonenergetic atom addition reactions between accreting H atoms and CO molecules, a process that dominates surface chemistry during the "CO freeze-out stage" in dense cores. In the present study we demonstrate that a similar mechanism results in the formation of the biologically relevant molecule glycerol-HOCH 2 CH(OH)CH 2 OH-a three-carbon-bearing sugar alcohol necessary for the formation of membranes of modern living cells and organelles. Our experimental results are fully consistent with a suggested reaction scheme in which glycerol is formed along a chain of radical-radical and radical-molecule interactions between various reactive intermediates produced upon hydrogenation of CO ice or its hydrogenation products. The tentative identification of the chemically related simple sugar glyceraldehyde-HOCH 2 CH(OH)CHO-is discussed as well. These new laboratory findings indicate that the proposed reaction mechanism holds much potential to form even more complex sugar alcohols and simple sugars.

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Section: Conclusion and Astronomical Relevancementioning

confidence: 99%

Formation of Glycerol through Hydrogenation of CO Ice under Prestellar Core Conditions

Fedoseev

Chuang

Ioppolo

et al. 2017

ApJ

102

111

View full text Add to dashboard Cite

show abstract

“…Kinetic Monte Carlo algorithms are widely used in condensed matter physics, chemistry and biophysics to describe processes as diverse as antibiotic translocation through proteins, the chemistry of interstellar dust grains or graphene growth (Ceccarelli et al 2012; Cuppen et al 2013; Lloyd-Williams et al 2012). The type of KMC used here is commonly referred to as ‘rejection-free’ (rfKMC), and the basic ideas behind it are depicted in Figure 2a.…”

Section: Methodsmentioning

confidence: 99%

A radiobiological model of radiotherapy response and its correlation with prognostic imaging variables

et al. 2017

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Radiobiological models of tumour control probability (TCP) can be personalized using imaging data. We propose an extension to a voxel-level radiobiological TCP model in order to describe patient-specific differences and intra-tumour heterogeneity. In the proposed model, tumour shrinkage is described by means of a novel kinetic Monte Carlo method for inter-voxel cell migration and tumour deformation. The model captures the spatiotemporal evolution of the tumour at the voxel level, and is designed to take imaging data as input. To test the performance of the model, three image-derived variables found to be predictive of outcome in the literature have been identified and calculated using the model’s own parameters. Simulating multiple tumours with different initial conditions makes it possible to perform an in silico study of the correlation of these variables with the dose for 50% tumour control (TCD50) calculated by the model. We find that the three simulated variables correlate with the calculated TCD50. In addition, we find that different variables have different levels of sensitivity to the spatial distribution of hypoxia within the tumour, as well as to the dynamics of the migration mechanism. Finally, based on our results, we observe that an adequate combination of the variables may potentially result in higher predictive power.

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“…[26][27][28][29][30] The one presented here is categorized as rejection-free kMC originated from the "first-reaction" method by Gillespie. 26 Considering a system currently in state i, all the N possible transitions to other j states have the associated rate constants k i,j .…”

Section: A Kinetic Monte Carlomentioning

confidence: 99%

Generic parameters of trajectory-extending kinetic Monte Carlo for calculating diffusion coefficients

Tien

Chiu

2018

AIP Advances

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One of the challenging applications of molecular dynamics (MD) simulations is to determine the dynamic properties such as the diffusion coefficient of the molecule of interest, particularly slow dynamic systems such as hydrogels and polymer melts. Recently, Neyertz et al. proposed a trajectory- extending kinetic Monte Carlo (TEKMC) algorithm combining both MD and kinetic Monte Carlo to probe the penetrant diffusion within the glassy polymer systems (S. Neyertz and D. Brown, Macromolecules 43, 9210, 2010). Yet, the original TEKMC relies on the manual adjustments of the key parameters of the sampling interval τ and the discretizing grid size rgrid, which limits its applicability to systems with unknown kinetic properties. Here, we reviewed the theoretical background of kinetic Monte Carlo to establish the generic criteria for selecting TEKMC parameters. Also, we modified and expanded the TEKMC algorithm for bulk fluid systems. The modified TEKMC algorithm were applied to systems with various kinetic properties, including Lennard Jones liquid, bulk water, Li+ liquid electrolyte, and Li+ polymer electrolyte. The diffusion coefficients obtained from the modified TEKMC and the generic parameter selections were promising and robust compared with the conventional MD results. With the proposed TEKMC approach, one can extend the MD trajectories to unambiguously characterize the diffusion behavior in the long-time diffusive regime.

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The Kinetic Monte Carlo Method as a Way To Solve the Master Equation for Interstellar Grain Chemistry

Cited by 84 publications

References 176 publications

Formation of Glycerol through Hydrogenation of CO Ice under Prestellar Core Conditions

Formation of Glycerol through Hydrogenation of CO Ice under Prestellar Core Conditions

A radiobiological model of radiotherapy response and its correlation with prognostic imaging variables

Generic parameters of trajectory-extending kinetic Monte Carlo for calculating diffusion coefficients

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