In the last years the possibility of creating new conducting polymers exploring the concept of copolymerization (different structural monomeric units) has attracted much attention from experimental and theoretical points of view. Due to the rich carbon reactivity an almost infinite number of new structures is possible and the procedure of trial and error has been the rule. In this work we have used a methodology able of generating new structures with pre-specified properties. It combines the use of negative factor counting (NFC) technique with artificial intelligence methods (genetic algorithms - GAs). We present the results for a case study for poly(phenylenesulfide phenyleneamine) (PPSA), a copolymer formed by combination of homopolymers: polyaniline (PANI) and polyphenylenesulfide (PPS). The methodology was successfully applied to the problem of obtaining binary up to quinternary disordered polymeric alloys with a pre-specific gap value or exhibiting metallic properties. It is completely general and can be in principle adapted to the design of new classes of materials with pre-specified properties.

Quantum chemistry describes the hydrogen atom as one of the few systems that permits an exact solution of the Schrödinger equation. Students tend to consider that little can be learned from the hydrogen atom and forget that it can be used as a standard to test numerical procedures used to calculate properties of multielectronic systems. In this paper, four different numerical procedures are described in order to solve the Schrödinger equation for the hydrogen atom. The basic motivation is to identify new insights and methods that can be obtained from the application of powerful numerical techniques in a well-known system.