In the EigenFollowing geometry optimization method, the geometry is changed on each cycle; if the ΔHf decreases, the cycle is completed. If it does not drop, the step-size is reduced, and the ΔHf recalculated. Only when the ΔHf decreases, compared to the previous cycle, is the current cycle considered to be successful. During the calculation, the confidence level or trust radius is continuously checked. If this becomes too small, the calculation will be stopped. This can readily happen if (a) the geometry was already almost optimized; (b) a reaction path or grid calculation is being performed; (c) if the geometry is in internal coordinates and "big rings" are involved; or (d) if the gradients are not correctly calculated (in a complicated C.I., for example).
For cases (a) and (b), add LET and DDMIN=0. In case (c) use either mixed coordinates or entirely Cartesian coordinates. Case (d) is difficult--if nothing else works, add NOANCI; this will always cause the derivatives to be correctly calculated, but will also use a lot of time.
Adding LET and DDMIN=0 is often very effective, particularly when reaction paths are being calculated. The first geometry optimization might take more cycles, but the resulting Hessian matrix is better tempered, and subsequent steps are generally more efficient.