Third, computational cost is a serious challenge as we move from small molecules (e.g. one aromatic ring) to the medium-sized molecules that are so important in organic, pharmaceutical, and biological chemistry. The accurate methods are based on coupled-cluster calculations (e.g. CCSD(T)), where the cost of computing the energy at a single molecular geometry scales roughly as the number of electrons to the 7 th power. So for example computing the energy of a dimer (or a monomer + monomer Transition State) is about 2 7 = 128 times slower than computing its monomer. But as molecules get larger they also have more conformations, and so more geometries that need to be computed. Often many of the conformers correspond to the gauche-gauche'-trans arrangements around single bonds; there are about 3 Nrotors of those conformers. So if a monomer has 6 rotatable single bonds, it will have about 3 6 = 729 conformers, and its dimer with 12 rotatable single bonds will have about 3 12 = 531,441 conformers, i.e. about 729 times as many conformers as the monomer. If one were to attempt to compute the energies of each conformer at the same high (e.g. CCSD(T)) level the CPU time to compute the dimer (or monomer + monomer TS) would be about 128*729 = 93,312 times longer than computing the monomer at the same level of theory. So although it may be practical to very accurately compute the properties of the monomer, it might be infeasible to compute the dimer or the monomer + monomer TS. There has been a lot of excellent work to find methods with near CCSD(T) accuracy but better scaling, but more work is needed on methods for handling conformers/rotors accurately and efficiently, particularly conformers of transition states.