Research ArticleJournal of Scientometric ResearchVol. 7 | Issue 2 | 2018 | pp. 79–83Open access
Data-Mining the Foundational Patents of Photovoltaic Materials: An Application of Patent Citation Spectroscopy
- 1,
- 2*
- 1 Social and Behavioral Sciences Department, The MITRE Corporation, McLean, VA, UNITED STATES.
- 2 Amsterdam School of Communication Research (ASCoR), University of Amsterdam, PO Box 15793, 1001 NG Amsterdam, NETHERLANDS.
Published in Journal of Scientometric Research
Correspondence: Loet Leydesdorff
Amsterdam School of Communication Research (ASCoR), University of Amsterdam, PO Box 15793, 1001 NG Amsterdam, NETHERLANDS.
Email: loet@leydesdorff.net
Copyright: © 2018 Manuscript Technomedia. This is an open access article.
- Published:
- Aug 1, 2018
- Received:
- Apr 9, 2018
- Accepted:
- Jul 17, 2018
How to cite
Comins, J. A., & Leydesdorff, L. (2018). Data-Mining the Foundational Patents of Photovoltaic Materials: An Application of Patent Citation Spectroscopy. Journal of Scientometric Research, 7(2), 79–83. https://doi.org/10.5530/jscires.7.2.13
Abstract
Patents branch out in tree-like structures along trajectories. The historical root or seminal, patent can be followed using sequences of patent citations. The algorithmic method of PCS presented in this study provides a solution to the problem where to begin the analysis of a technological development. PCS enables the user to retrieve the fundamental patent in any technological domain using a topical search. This application thus orients the user strategically. To illustrate the value of PCS, we provide the results of a search for the seminal patents of the nine CPC subclasses pertaining to photovoltaic solar cells, a key area of technological innovation. Research and development (R&D) in photovoltaic devices continues to yield greater efficiencies, offering the potential to lower the cost of solar energy.[1] As these advances in solar technology become primed for penetrating the global energy system, an understanding of the key patents and inventors in photovoltaic materials will assist decision-makers in understanding the R&D landscape.[2] We demonstrate that such searches are easily completed via PCS in each of the nine CPC subclasses. Searches of scholarly article databases validated the results obtained through PCS in five of the nine classes.
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Article metadata
| Title | Data-Mining the Foundational Patents of Photovoltaic Materials: An Application of Patent Citation Spectroscopy |
|---|---|
| Authors | Jordan A Comins; Loet Leydesdorff |
| Affiliations | Social and Behavioral Sciences Department, The MITRE Corporation, McLean, VA, UNITED STATES.; Amsterdam School of Communication Research (ASCoR), University of Amsterdam, PO Box 15793, 1001 NG Amsterdam, NETHERLANDS. |
| Corresponding author | loet@leydesdorff.net |
| Journal | Journal of Scientometric Research |
| Volume / Issue | Vol. 7, Issue 2 (2018) |
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