Activated Carbon Materials for Hydrogen Storage - University of Nottingham
水素貯蔵用活性炭材料 - ノッティンガム大学 (AI 翻訳)
University of Nottingham, Nanolayers
🤖 gxceed AI 要約
日本語
本データセットは、237種類の超多孔質活性炭サンプルの組成、実験条件、特性測定値を含む。機械学習モデルの入力と出力として使用可能で、水素吸蔵性能の予測に貢献する。
English
This dataset includes 237 ultraporous activated carbon samples with composition, conditions, and characterization data. It supports machine learning models for predicting hydrogen uptake, crucial for hydrogen storage material discovery.
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
水素貯蔵は日本の水素基本戦略の重要課題。本データセットは活性炭材料の特性と水素吸蔵性能の関係を機械学習で解析する基盤を提供し、材料開発の効率化に寄与する可能性がある。
In the global GX context
Hydrogen storage is critical for the global hydrogen economy. This dataset enables machine-learning-driven discovery of activated carbon materials, accelerating the development of efficient storage solutions.
👥 読者別の含意
🔬研究者:Provides a curated dataset of activated carbon properties and hydrogen uptake measurements for developing predictive models.
🏢実務担当者:Useful for materials scientists screening hydrogen storage candidates using ML.
📄 Abstract（原文）
This datasets includes 237 ultraporous activated carbon samples fom University of Nottingham. The first 188 samples are collected from previous research available in scientific literature, while the last 49 were generated during the MAST3RBoost project. Each row describes one sample, and the column provide composition information, experimental conditions, and characterisation measurements. Column headers are mostly self-explanatory. Additionally, each header is prefixed by “[input]” if the column describes the precursor mixture composition such as elemental ratios or reaction conditions such as reactiontemperature and duration. Conversely, the “[output]” is prepended to columns that provide characterisation quantities for the resulting AC material. These labels also indicate which quantities are supposed to be used as input for machine-learning models, and which are sensible performance metrics they should predict in their output. The output columns can be grouped into two categories. The first group lists the analysis results of nitrogen adsorption isotherms, including details of the isotherm fitting results, and pore size and volume estimates. The latter group provides the actual gravimetric and volumetric hydrogen uptake measurements. Samples from literature do not have H uptake characterisation since it was not done at the time. While H uptake is the true performance metric of interest for these materials, it was found during the project that pore surface area (ABET) estimated from N adsorption correlates strongly with H uptake and it can thus be used as a proxy parameter for the performance of these samples.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.5281/zenodo.20772298first seen 2026-07-14 04:45:17
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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。