Radiation Chemistry of Liquid Water with Heavy Ions: Monte Carlo Simulation Studies 373
the rst to use Monte Carlo simulations to derive computer-plot representations of the chemical evo-
lution of a few keV electron tracks in liquid water at times between ∼10
−12
and 10
−7
s (Turner et al.,
1981, 1983, 1988). Following this pioneering work, stochastic simulation codes employing Monte
Carlo procedures were used with success by a number of investigators to study the relationship
between the initial track structure and the ensuing chemical processes that occur in the radiolysis
of both pure water and water-containing solutes (for reviews, see, e.g., Ballarini et al., 2000; Uehara
and Nikjoo, 2006; Kreipl et al., 2009). Two main approaches have been widely used: (1) the “step-
by-step” (or random ights Monte Carlo simulation) method, in which the trajectories of the dif-
fusing species of the system are modeled by time-discretized random ights and in which reaction
occurs when reactants undergo pairwise encounters, and (2) the “independent reaction times” (IRT)
method (Clifford et al., 1986; Pimblott et al., 1991; Pimblott and Green, 1995), which allows the cal-
culation of reaction times without having to follow the trajectories of the diffusing species. Among
the stochastic approaches, the most reliable is certainly the full random ights simulation, which
is generally considered as a measure of reality. However, this method can be exceedingly consum-
ing in computer time when large systems (such as complete radiation tracks or track segments) are
studied. The IRT method was devised to achieve much faster realizations than are possible with the
full Monte Carlo model. In essence, it relies on the approximation that the distances between pairs
of reactants evolve independently of each other, and, therefore, the reaction times of the various
potentially reactive pairs are independent of the presence of other reactants in the system. For every
pair, a reaction time is stochastically sampled according to the time-dependent survival function
(Green et al., 1990; Goulet and Jay-Gerin, 1992; Frongillo et al., 1998) that is appropriate for the
type of reaction considered. This function depends on the initial (or zero-time) distance separating
the species, their diffusion coefcients, their Coulomb interaction, their reaction radius, and the
probability of reaction during one of their encounters. The rst reaction time is found by taking
the minimum of the resulting ensemble of reaction times and allowing the corresponding pair of
species to react at this time. This procedure for modeling reaction is continued either until all reac-
tions are completed or until a predened cut-off time is reached. The IRT simulation technique also
allows one to incorporate, in a simple way, pseudo rst-order reactions of the radiolytic products
with various scavengers that are homogeneously distributed in the medium (such as H
+
, OH
−
, and
H
2
O itself, or more generally any solutes for which the relevant reaction rates are known). The abil-
ity of the IRT method to give accurate time-dependent chemical yields has been well validated by
comparison with full random ight Monte Carlo simulations that do follow the reactant trajectories
in
detail (Pimblott et al., 1991; Goulet et al., 1998; Plante, 2009).
14.5.1 the ionlyS-irt SiMulation code
In a program begun in the summer of 1988 in collaboration with Jean Paul Patau (Université Paul-
Sabatier, Toulouse, France) and Christiane Ferradini (Université René-Descartes, Paris, France), the
Sherbrooke group has developed and progressively rened, with very high levels of detail, several
Monte Carlo codes that simulate the track structure of ionizing particles in water, the production of
the various ionized and excited species, and the subsequent reactions of these species in time with
one another or with available solutes (Cobut, 1993; Cobut et al., 1998; Frongillo et al., 1998; Hervé
du Penhoat et al., 2000; Meesungnoen et al., 2001, 2003; Meesungnoen and Jay-Gerin, 2005a,b,
2009; Muroya et al., 2002, 2006; Plante et al., 2005; Autsavapromporn et al., 2007; Guzonas et al.,
2009). A most recent version of the Sherbrooke codes, called IONLYS-IRT (Meesungnoen and Jay-
Gerin,
2005a,b), is used in the present work.
Briey,
the IONLYS step-by-step simulation program models all the events of the physical
and physicochemical stages in the track development. To take into account the effects of multiple
ionizations under high-LET heavy-ion impact, the model incorporates double-, triple-, and qua-
druple ionization processes in single ion–water collisions (see above). The double ionization of
water is assumed to lead to the production of
through the intervention of oxygen atoms