Abstract: Provided is a method for generating a digital representation of a chemical substance. This may involve training aspects of neural networks to represent chemical sub-stances. Provided further relates to applications of the digital representation including a computer program product, a database search engine for identifying chemical sub-stances, apparatuses for generating measurement data associated with chemical substances and control data associated with synthesis specifications for chemical substances.

Abstract: A method for characterizing a chemical substance in a predetermined multimodal representation having a predetermined plurality of modalities, comprises: receiving (S12) multimodal substance data (2, 12) comprising a first set of modalities of the chemical substance; encoding (S13) said multimodal data (2, 12) using a data driven model (3, 10) of the chemical substance for generating encoded substance data; and generating multimodal substance data comprising a second set of modalities of the chemical substance by decoding said encoded substance data using the data driven model (3, 10), wherein the multimodal substance data is indicative of a physicochemical property of the chemical substance, a composition of the chemical substance and/or an identifier of the chemical substance. The data driven model (3, 10) is implemented to map input data (2, 12) to encoded output data (6), input data being a multimodal representation (2, 12) of the chemical substance.