Several research efforts are being carried out in molecular electronics; both theory and experiment claim extraordinary findings for molecular devices. However, before practical molecular circuits can be implemented, we need to develop scenarios for information coding and transfer in molecular circuits able to operate at integration densities and speeds orders of magnitude higher than current ICs do. Initial attempts have been already proposed; however,a simple adaptation to methods being used in current microelectronics devices does not offer much hope at the atomistic and nanoscopic levels due to the large dissipation energy densities that would be generated. We have proposed two new paradigms to process and transmit information in molecular circuits that can defeat the heat dissipation problem. One is based on the characteristic vibrational behavior of molecules and clusters, and the other is based on the molecular electrostatic potentials. It is suggested that these two scenarios can be used for molecular signal processing and transfer in molecular circuits; a theoretical demonstration using computational techniques is presented for these two paradigms.

Molecular electronics can be developed if we are able to program a random arrangement of molecules or a field-programmable molecular random array. The ansatz that small molecules can be programmed needs to be demonstrated; this means characterizing the smallest molecular system with programmable features. We demonstrate that even two molecules in a series conformation can have multivalued responses and, thus, is able to be programmed; we also indicate how to extend this programmability to other molecular circuit conformations. Current programs for the calculation of current-voltage characteristics of electronic circuits, needed for such demonstrations, are only capable of predicting single-valued characteristics. We present results from our ab initio procedures that couple the molecular approaches with a practical analysis of molecular circuits having strong nonlinearities.