A Curated Dataset of Low-Temperature Plasma Literature (2000–2025)

Overview This dataset presents a curated collection of 23,389 peer-reviewed research publications related to low-temperature plasma (LTP) science, covering the period 2000–2025. It provides structured bibliographic metadata to support systematic literature discovery, bibliometric analysis, scientific knowledge extraction, research trend identification, and data-driven studies in plasma science. The dataset was compiled from approximately 25 domain-expert-recommended scientific journals using the Crossref Metadata API. It was developed following the FAIR (Findable, Accessible, Interoperable, and Reusable) data principles to facilitate scientific data discovery, interoperability, and reuse. The released dataset contains bibliographic metadata only. Article abstracts and full-text content are not included. Data Collection and Curation The dataset was developed through a multi-stage collection and curation pipeline: Data Collection: Bibliographic metadata were retrieved through the Crossref Metadata API for journal articles published between 2000 and 2025 in approximately 25 expert-selected scientific journals relevant to plasma research. Data Cleaning and Preprocessing: Retrieved records underwent metadata normalization, deduplication, text cleaning, incomplete-record filtering, and English-language screening to improve data consistency and quality. LLM-Based Relevance Filtering: Large language model (LLM)-assisted relevance classification was applied to identify research publications associated with low-temperature plasma science and exclude unrelated publications. Metadata Organization: The selected publications were organized into a standardized tabular structure with unique dataset identifiers and essential bibliographic attributes. FAIR-Oriented Data Preparation: The curated dataset was prepared for repository deposition with a documented data schema, collection methodology, provenance information, licensing terms, and persistent identification. Dataset Description The final dataset comprises 23,389 publication records, organized in CSV format with the following seven attributes: ID: Unique numerical identifier assigned to each dataset record. Title: Title of the original research publication. DOI: Digital Object Identifier providing a persistent reference to the original publication. Authors: Names of the publication authors. Authors Affiliation: Institutional affiliations of the authors, where available. Journal Name: Name of the journal in which the research article was published. Published Year: Year of publication. The dataset contains bibliographic information only and does not include article abstracts, full texts, figures, or supplementary research content. The CSV format enables straightforward integration with commonly used programming languages, data analysis libraries, bibliometric tools, and scientific information retrieval systems. Research Applications The dataset is intended to support multiple research applications, including: Bibliometric analysis and temporal mapping of LTP research. Identification of emerging topics, research trends, and scientific developments. Analysis of publication patterns, journal contributions, and research collaborations. Scientific literature discovery and publication classification. Development of bibliographic knowledge graphs and citation-linked research databases. Metadata-driven information retrieval and AI-assisted scientific literature analysis. Identification of research directions relevant to plasma-assisted energy technologies, environmental sustainability, and advanced manufacturing. FAIR Data Principles The dataset has been organized to support the following FAIR principles: Findable: Structured descriptive metadata, standardized publication identifiers, relevant keywords, and a persistent Zenodo DOI upon publication. Accessible: Repository-based metadata discovery and dataset file access according to the configured Zenodo access permissions. Interoperable: Machine-readable CSV representation, consistently defined bibliographic attributes, standardized publication DOIs, and accompanying schema documentation. Reusable: Documented data collection and preprocessing procedures, provenance information, a data dictionary, version information, and declared licensing conditions. The accompanying documentation supports dataset interpretation, provenance tracking, reproducibility, and responsible reuse. Data Source and Attribution Primary metadata source: Crossref Metadata API (https://www.crossref.org/). The dataset was compiled from bibliographic information associated with publications in selected scientific journals. Each publication DOI provides a persistent link to the corresponding original scholarly work. The original research publications remain attributable to their respective authors and publishers. License and Reuse The dataset compilation and original accompanying documentation are made available under the Creative Commons Attribution 4.0 International (CC BY 4.0) license, to the extent that the dataset creators hold the applicable rights. License: https://creativecommons.org/licenses/by/4.0/ Users may share and adapt the licensed material, including for research and commercial purposes, provided that appropriate attribution is given, the license is referenced, and modifications are indicated. This license does not supersede any independently applicable third-party rights in the underlying publication metadata or original scholarly works. Intended Impact This dataset aims to provide a structured and reusable bibliographic resource for the low-temperature plasma research community. By consolidating publication metadata across approximately 25 scientific journals over a 26-year period, it facilitates systematic investigation of research developments, publication patterns, and evolving scientific interests. The dataset provides a foundation for reproducible bibliometric studies, automated literature discovery, scientific knowledge organization, and AI-assisted research analysis. Its broader objective is to improve the discoverability and reuse of LTP research information, supporting scientific innovation in plasma-based technologies relevant to clean energy, sustainable manufacturing, environmental protection, and resource-efficient industrial processes.