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A guide to writing articles in energy science

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  • Weiss, Martin
  • Newman, Alexandra M.

Abstract

Energy science addresses key questions of sustainable development. This suggests that energy scientists should communicate their research effectively with readers both from within and outside of the scientific community. In the communication of energy science, however, scientific writing potentially presents a weak link. Here, we address this problem by clarifying the principle conventions for writing articles in energy science. We propose a top-down approach to writing that begins with structuring the article into sections. Each section should, in turn, be structured in and of itself so that readers can: (i) comprehend the scientific context; (ii) grasp the research questions addressed; (iii) verify methods and results; and (iv) understand the significance of the results. Subsequently, authors should ensure clarity of their scientific arguments by: (i) presenting existing information at the beginning of a sentence and new information at the sentence’s end; (ii) articulating action with appropriate verbs, preferably in active voice; (iii) placing statements in positive form; and (iv) using consistent technical terminology. Substantial text revisions constitute an indispensable part of scientific writing and enable authors to make their exposition concise. Following the conventions outlined in this article can make writing easier, more efficient, and enables energy scientists to communicate their research effectively with a wide audience.

Suggested Citation

  • Weiss, Martin & Newman, Alexandra M., 2011. "A guide to writing articles in energy science," Applied Energy, Elsevier, vol. 88(11), pages 3941-3948.
  • Handle: RePEc:eee:appene:v:88:y:2011:i:11:p:3941-3948
    DOI: 10.1016/j.apenergy.2011.04.007
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    1. Joanna Poyago-Theotoky & John Beath & Donald S. Siegel, 2002. "Universities and Fundamental Research: Reflections on the Growth of University--Industry Partnerships," Oxford Review of Economic Policy, Oxford University Press, vol. 18(1), pages 10-21, Spring.
    2. Meyer-Krahmer, Frieder & Schmoch, Ulrich, 1998. "Science-based technologies: university-industry interactions in four fields," Research Policy, Elsevier, vol. 27(8), pages 835-851, December.
    3. Caloghirou, Yannis & Tsakanikas, Aggelos & Vonortas, Nicholas S, 2001. "Univeristy-Industry Cooperation in the Context of the European Framework Programmes," The Journal of Technology Transfer, Springer, vol. 26(1-2), pages 153-161, January.
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    1. Christos Alexakis & Michael Dowling & Konstantinos Eleftheriou & Michael Polemis, 2021. "Textual Machine Learning: An Application to Computational Economics Research," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 369-385, January.

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