The conjugate gradient method also uses the first derivatives of the potential energy. But instead of local gradient for downhill as in the steepest descent method, the conjugate gradient technique define the new gradient direction for each iteration by using information from previous gradient directions to determine the optimum direction for the line search. It is considered to select a successive search direction in order to eliminate repeated minimization along the same direction. What can one expect from molecular dynamics simulations of lipid systems, given the general possibilities and limitations of molecular dynamics described in the previous section? Obviously, it is important to know at which time and length scale the processes occur. A brief overview is given here, and a more elaborate account can be found in. Apart from the fundamental considerations of time and length scale that have to be taken into account when planning a simulation, there are a number of technical choices to be made. The most important technical choices are treated briefly below.