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The control of charge transport on a polymer chain by impurity molecules working as switches is studied. Charge propagation is estimated using a backpropagation neural network approach. The supervised learning is accomplished using theoretical results in which the chain is modeled by a tight-binding Hamiltonian extended to include the effects of an external electric field. The charge transport through the sites that work like a switch is analyzed by the numerical integration of the equations of motion. For a donor]acceptor pair of impurities, we found that the chain offers a wide range of devices, from simple switches to perfect molecular rectifiers. The influence of the parameters of the molecules on the charge transport, the role of the length of separation between the sites where the impurity molecules bond, as well as the changes they must undergo to characterize each kind of molecular switch are determined. Q 1999 John Wiley & Sons, Inc. J Comput Chem 20: 1060]1066, 1999

Investigating charge transport in molecular switches with neural networks