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| 001 | 889302 | ||
| 005 | 20210623133421.0 | ||
| 024 | 7 | _ | |2 doi |a 10.1016/j.techfore.2020.120505 |
| 024 | 7 | _ | |2 Handle |a 2128/27224 |
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| 100 | 1 | _ | |0 P:(DE-HGF)0 |a Baumann, Manuel |b 0 |e Corresponding author |
| 245 | _ | _ | |a Comparative patent analysis for the identification of global research trends for the case of battery storage, hydrogen and bioenergy |
| 260 | _ | _ | |a Amsterdam [u.a.] |b Elsevier Science |c 2021 |
| 336 | 7 | _ | |2 DRIVER |a article |
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| 336 | 7 | _ | |0 PUB:(DE-HGF)16 |2 PUB:(DE-HGF) |a Journal Article |b journal |m journal |s 1614073064_8335 |
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| 520 | _ | _ | |a Patent documents provide knowledge about which countries are investing in certain technologies and make it possible to identify potential innovation trends. The aim of this article is to analyze trends in patenting that might result in innovations for three energy technologies: thermochemical conversion of biomass (Bioenergy), lithium-ion battery storage, and hydrogen production by alkaline water electrolysis. Based on different patent indicators, the most active countries are compared to provide insights into the global market position of a country, particularly Germany which is used as a reference here. In line with this, a freely available patent analysis software tool was developed directly using the European Patent Office database through their Open Patent Services. The results for named technologies show that patenting activity of Germany is low in comparison to other countries such as Japan, China, and the US. Whereas the position of Germany for batteries and hydrogen is comparable, bioenergy shows different results regarding the identified countries and the number of patents found. However, a broader context beyond patenting is suggested for consideration to make robust statements about particular technology trends. The presented tool and methodology in this study can serve as a blueprint for explorative assessments in any technological domain. |
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| 700 | 1 | _ | |0 P:(DE-HGF)0 |a Domnik, Tobias |b 1 |
| 700 | 1 | _ | |0 P:(DE-HGF)0 |a Haase, Martina |b 2 |
| 700 | 1 | _ | |0 P:(DE-Juel1)168163 |a Wulf, Christina |b 3 |u fzj |
| 700 | 1 | _ | |0 P:(DE-HGF)0 |a Emmerich, Philip |b 4 |
| 700 | 1 | _ | |0 P:(DE-HGF)0 |a Rösch, Christine |b 5 |
| 700 | 1 | _ | |0 P:(DE-Juel1)130493 |a Zapp, Petra |b 6 |u fzj |
| 700 | 1 | _ | |0 P:(DE-HGF)0 |a Naegler, Tobias |b 7 |
| 700 | 1 | _ | |0 P:(DE-HGF)0 |a Weil, Marcel |b 8 |
| 773 | _ | _ | |0 PERI:(DE-600)2015184-6 |a 10.1016/j.techfore.2020.120505 |p 120505 |t Technological forecasting and social change |v 165 |x 0040-1625 |y 2021 |
| 856 | 4 | _ | |u https://juser.fz-juelich.de/record/889302/files/1-s2.0-S0040162520313317-main.pdf |y OpenAccess |
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