Abstract:    Basic research is an important source of technological innovation. Research on the law of knowledge transformation from basic research to technological innovation has important significance of both theory and practice. Tracing back to existing research, there are limitations of studying knowledge diffusion with the method of using citation relation among documents. In view of this, the research studies knowledge diffusion mechanism from science to technology from the perspective of content flow based on knowledge genes, a special type of knowledge unit. Taking the technology field of artificial intelligence as a research case, this paper identifies the first five basic disciplines which are cited by patents of technology field, then analyzes the knowledge relationship between the disciplines and the technology field. And the diffusion cascade network model of knowledge genes is constructed to analyze the mode of knowledge diffusion from science to technology. 
     After the research, it is found that compared with citations from patent to scientific paper, the flow of knowledge genes can reflect a more authentic knowledge diffusion relationship between the basic science discipline and technology field. The knowledge diffusion intensity represented by flow of knowledge genes from science subject to technology field which is able to filter out influencing factors such as journal influence, is positively correlated with the knowledge correlation degree between science subject and technology field. The flow of knowledge genes could also describe communication efficiency, knowledge influence characteristics and content characteristics of knowledge spreading course from science discipline to technology. It is shown that the short-term influence level of knowledge genes diffusing from science to technology is related to the science discipline source. By analyzing the network structure of diffusion cascades, it is found that the spreading course of knowledge genes from science to technology is affected by Matthew effect, which shows that the more successful the knowledge gene is, the easier it is to spread further. This result also indicates that the knowledge dissemination system from science to technology has a characteristic of self-organization. 
    Furthermore, this paper compares the transmission characteristics of knowledge genes which spread from science to technology with the general knowledge genes which spread only in technology domain, and discusses the different effects on technological innovation made by the 2 kind of knowledge genes. It is found that the cross-domain spreading knowledge genes have a better performance in diffusion scale, life span and knowledge influence, and the knowledge genes which only spread in technology domain have a better performance in diffusion speed. This result shows 2 different modes of knowledge diffusion in the process of technological innovation. Under the effect of heterogeneous knowledge combination, the knowledge genes which spread across different fields have greater innovation value and spread further. 
    By investigating how the 2 kind of knowledge genes make an influence on technological innovation, it is found that they have different dynamic characteristics. The rapid generation of general knowledge genes is one of the driving forces for the rapid development of technology. At the same time, the knowledge genes spreading from science to technology also play an important role in promoting technological innovation for they have stronger catalytic ability of innovation, though the generation speed of such knowledge genes is small. This research conclusion reveals the micro mechanism of how the scientific knowledge diffuses to technology domain and make an important impact on technological innovation. Our research provides a theoretical basis for exploring the knowledge transformation pattern from science to technology further. The conclusions made by this research could also be used in innovation prediction of emerging technology field, the layout of basic disciplines and making improvement of innovation efficiency through the optimization of science and technology policy.

Key words: science, technology, knowledge gene, knowledge diffusion