Virtual screening of materials using neuro-genetic approach: Concepts and implementation

We describe the concepts and an implementation of a quantitative structure activity relationship methodology for the discovery of solid materials. The paper focuses on virtual screening methodologies. We have investigated the integration of artificial neural network with genetic algorithm in order to accelerate the search of optima. The learning model monitors the optimization process while it is updated in the course of the screening. The optimization is performed on the basis of catalytic data collected in a large high throughput experimentation campaign. The implementation is carried out in a free software (OptiCat).