Innovative Models

Published models can be applied by everyone: everyone can get the same results.

Since reality is by far too complex for a computation the solution to a given problem must be found with a model. The validity of this model depends on the reliability of the experimental data that are to be understood.

A model consists of

• a hypothesis on the physical/chemical/biological phenomenon measured
• idea on how the measurement reflects the phenomenon
• assumptions on the type of molecular/ensemble properties relevant to the phenomenon
• selection of appropriate theoretical methods to compute these properties
• consistent scheme for the steps to reach the models result (procedure)
• mathematical correlation between theoretical and experimental data

and gives reliable answers only within the limits of validity of all assumptions.

Thus only a question that really can be answered can be answered.

Often time is crucial for the theoretical study to be faster than the synthesis of the compounds. Thus, the model has to be as efficient as possible. This makes a judicious choice of the basic assumptions even more important. Experience counts.

It is necessary to develop new automated procedures even if the computational methods are available. Thus, the adequate solution to a given problem within a novel model may require to adjust and enhance the software in use. We implement and test new models within our own software MOBY.

Our experience in developing and implementing makes our innovative models unique.