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Energetics and possible stable structures of CO2–Arn (n = 1–21) clusters are investigated by performing molecular-dynamics simulations. The pairwise-additive approximation is tested to construct the potential energy function for describing the non-rigid particle interactions in the system. A potential model by Pariseau et al. (Journal of Chemical Physics, Vol. 42, p. 2335, 1965) is used for the internal motion of the CO2 molecule and the Billing form potential (Chemical Physics, Vol. 185, p. 199, 1994) is used for all other pair interactions. The stable configurations are determined for the ground state of CO2–Arn clusters, and the growing pattern process of the clusters is determined via rearrangement collisions. Ar atoms tend to surround the CO2 molecule, and the clusters prefer to form three-dimensional compact structures. Obtained structures and energetics are in quantitative agreement with previous results (Journal of Chemical Physics, Vol. 109, p. 1343, 1998) that have used split-repulsion and ab initio potentials in which the molecule was treated as rigid.Key words: argon, CO2, cluster, potential energy function, molecular dynamics.

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Um algoritmo geral para resolver problemas inversos lineares e não lineares, baseado em redes neurais recursivas, é discutido neste trabalho. O procedimento será aplicado a problemas físico-químicos modelados por equações integrais, diferenciais e de autovalor. As aplicações são discutidas em espectroscopia de aniquilação de pósitrons, cinética química e espectroscopia vibracional. O método é robusto com relação a erros nas condições iniciais ou em dados experimentais. A presente abordagem é simples, numericamente estável e tem uma grande aplicabilidade.A general algorithm to solve linear and nonlinear inverse problems, based on recursive neural networks, is discussed in this work. The procedure will be applied to physical chemical problems modeled by integral, differential and eigenvalue equations. Representative applications discussed are in positron lifetime spectroscopy, chemical kinetics and vibrational spectroscopy. The method is robust with respect to errors in the initial condition or in the experimental data. The present approach is simple, numerically stable and has a broad range of applicability.

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