VISUALIZATION OF ENERGY WITH ZERO CARBON FOOTPRINT USING VOSVIEWER
VOSviewerを用いたゼロカーボンフットプリントエネルギー研究の可視化 (AI 翻訳)
GELMANOVA ZOYA SALIKHOVNA, FAYEZ WAZANI ABDUL WALID
🤖 gxceed AI 要約
日本語
本研究は、2020～2025年のWeb of Science文献19,450件を対象に、VOSviewerを用いてゼロカーボンエネルギー研究の構造と発展を分析。キーワード共起ネットワークから、再生可能エネルギー、エネルギー移行、デジタル技術（AI・機械学習）などの主要テーマと知識ギャップを特定した。
English
This bibliometric study analyzes 19,450 publications (2020-2025) using VOSviewer to map zero-carbon energy research. Findings reveal key themes: renewable energy, energy transition, digital tech (AI/ML), and sustainability, highlighting interdisciplinary linkages and emerging knowledge gaps.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本でもカーボンニュートラル実現に向けた研究の俯瞰が重要だが、本論文は特定の制度（GXリーグ、SSBJ等）との接点はなく、一般的な研究動向の整理に留まる。
In the global GX context
While the paper provides a useful overview for researchers entering the field, it lacks policy-specific insights (e.g., ISSB, TCFD) and offers limited novelty for global GX practitioners already familiar with broad energy transition themes.
👥 読者別の含意
🔬研究者:Useful as a starting point for literature review in zero-carbon energy, but offers no novel methodology or dataset.
📄 Abstract（原文）
This study examines the structure and development of zero-carbon energy research through bibliometric analysis and scientific visualization. A dataset of 19,450 publications from the Web of Science (2020–2025) was analyzed using VOSviewer to construct keyword co-occurrence networks, thematic clusters, and research linkages. The results identify key research areas, including renewable energy, energy transition, energy efficiency, decarbonization, sustainability, and carbon footprint reduction. The findings reveal a highly interdisciplinary field, combining insights from engineering, environmental science, economics, and data analytics. Network visualization highlights the relationships among major themes and uncovers emerging trends, particularly the growing role of digital technologies such as artificial intelligence and machine learning in optimizing energy systems. The study also identifies knowledge gaps and evolving research directions that are critical for future investigation. This research provides a clear and systematic mapping of the zero-carbon energy domain, offering valuable insights for researchers, policymakers, and industry stakeholders working to accelerate the transition toward sustainable and carbon-neutral energy systems.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.5281/zenodo.19712400first seen 2026-05-15 17:15:51
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gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。