Another analysis of the FP& NMP projects shows the achievements (PDF version, 2.58MB) that can NOT be achieved experimentally. It is hoped that this can convince experimentalists of the value of modelling!
Models explained the reasons for previously observed, yet so far very poorly understood phenomena (material properties and behaviour, manufacturing process parameters) and the models help clarify underlying processes and they help make accurate interpretations of observed materials phenomena.
Models explain the role played by certain phenomena and explain the connection between them.
Models have even predicted phenomena which were only later on experimentally verified. Understanding of biomaterials is hampered by the limits on experiments in-vivo and here models provide insight that even post-mortem analysis can not give.
Modelling is able to predict phenomena at any point within the (composite) material structure while these are extremely difficult to measure and modelling is therefore complementary to experimental evaluation. Computational modelling, in particular on the electron or atomistic scale, allows the investigation of processes beyond the experimental scale. People often speak of the “computer microscope” that allows to monitor the motion of a single atom.
The model guides the definition of the optimum composition of candidate materials and optimal configuration of devices and manufacturing processes. The theory can pre-identify interesting materials and in-service behaviour prior to the actual synthesis and experiments. The calculations pointed out samples that were until then simply not considered. Models suggest routes for device design that should eliminate or reduce reliability problems.