Historically, nanotechnology faces the same challenges of every new, emerging and science-based industry. The transfer of viable knowledge from science to market needs to be better bridged. To enhance this transfer, a methodology is designed which integrates engineering design and subject-actionobject (SAO) text mining. The methodology is used to find, select and evaluate appropriate nanotechnologies for solving industrial problems using scientific abstracts. A case study is conducted whereby engineering design methods are used to structure a technical innovation problem in the manufacturing industry. 1.2 million abstracts from nanotechnology related articles are retrieved from the Web of Science and indexed using SAOparsing of the title and abstract. The performance of this novel methodology is measured using precision and recall, an approach common to the field of information retrieval. The methodology is further evaluated on the basis of structured interviews conducted with two engineering managers. The results demonstrate that the SAO methodology is a valuable assist to innovation and design within the firm. Significant challenges which are addressed in this article-for example knowledge loss due to SAO-parsing, and also the phenomena of information stickiness.