Dataset of Molten Metal-Catalyzed Methane Pyrolysis for Hydrogen Production under Different Operating Conditions
溶融金属触媒を用いたメタン熱分解による水素製造データセット：異なる運転条件下での性能 (AI 翻訳)
Zhong Lei, Wang Xiaobo
🤖 gxceed AI 要約
日本語
本データセットは、溶融金属触媒を用いたメタン熱分解による水素製造実験の結果をまとめたものである。反応温度、流量、入口位置など様々な運転条件がメタン転化率、水素選択性、水素収率に与える影響を記録しており、水素製造プロセスの最適化に有用な情報を提供する。
English
This dataset records experimental results on molten metal-catalyzed methane pyrolysis for hydrogen production, including key performance indicators under various operating conditions. It helps analyze effects of temperature, flow rate, and reactor geometry on methane conversion and hydrogen yield, serving as a reference for process optimization in low-carbon hydrogen production.
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
日本は水素社会の実現を目指しており、メタン熱分解は既存の天然ガスインフラを活用しつつ、固体炭素を副生するため、CO2回収コストを低減できる可能性がある。本データセットは、国内の水素製造技術開発や実証試験の条件設定に寄与する。
In the global GX context
This dataset contributes to the global hydrogen production research, particularly for methane pyrolysis with solid carbon byproduct, which is a promising low-carbon hydrogen route. It provides experimental benchmarks for reactor design and optimization, relevant for energy transition and decarbonization policies.
👥 読者別の含意
🔬研究者:Provides experimental data for validating models or optimizing reactor design in molten metal methane pyrolysis for hydrogen production.
🏢実務担当者:Useful for R&D teams in hydrogen production companies to assess potential process improvements.
📄 Abstract（原文）
The title of this dataset is "Dataset of Molten Metal Catalytic Methane Thermal Cracking for Hydrogen Production under Different Operating Conditions", mainly derived from experiments on molten metal catalyzed methane thermal cracking for hydrogen production. The experiment uses methane as the reactant gas and conducts non oxidative cracking reaction in a high-temperature molten metal system to generate hydrogen gas and solid carbon products. The dataset records key performance indicators such as methane conversion rate, hydrogen yield, and hydrogen selectivity under different reaction conditions, which can be used to analyze the effects of reaction temperature, inlet flow rate, inlet position, molten metal layer height, and gas distribution on the hydrogen production performance of methane thermal cracking. The experimental setup mainly includes a vertical tube furnace, quartz reaction tube, 316L stainless steel inlet tube, gas mass flow control system, molten metal reaction medium, and gas chromatography analysis system. During the experiment, the outlet gas composition under different operating conditions was obtained by controlling parameters such as reaction temperature, gas flow rate, and inlet position, and further results such as methane conversion rate, hydrogen selectivity, and hydrogen yield were calculated. After normalization, internal standard correction, and formula calculation, the raw gas composition data is organized into tabular data, which is then summarized, calculated, and graphically plotted using software such as Excel and Origin. The dataset does not involve large-scale geographic spatial distribution information, and its spatial information is mainly reflected in the structural parameters of the experimental reactor and reaction location parameters, such as the inner diameter of the quartz tube, the height of the molten metal layer, the height of the inlet from the molten metal liquid surface, and the aperture of the gas distributor. The main column labels include reaction temperature/℃, total inlet flow rate/mL · min ⁻¹, methane volume fraction/%, nitrogen volume fraction/%, molten metal composition, molten metal mass/g, molten metal layer height/mm, inlet height from liquid level/mm, gas distributor aperture/μ m, outlet gas composition/%, methane conversion rate/%, hydrogen selectivity/%, hydrogen yield/%, etc.
🔗 Provenance — このレコードを発見したソース
- scidb https://doi.org/10.57760/sciencedb.39867first seen 2026-07-29 11:13:43
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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。