gxceed
← 論文一覧に戻る

Ab Initio Kinetics for H‐atom Abstraction Reactions From Low‐Carbon Alcohols and Ethers by NH <sub>2</sub> Radical

低炭素アルコールとエーテルからのNH2ラジカルによるH原子引き抜き反応の第一原理速度論 (AI 翻訳)

Zimu Wang, Yueying Liang, Liang Yu, Xingcai Lu

International Journal of Chemical Kinetics📚 査読済 / ジャーナル2026-05-11#エネルギー転換Origin: CN
DOI: 10.1002/kin.70077
原典: https://doi.org/10.1002/kin.70077

🤖 gxceed AI 要約

日本語

本研究は、C1-C4アルコールおよびエーテルからNH2ラジカルによるH原子引き抜き反応の速度論を系統的に調査した。量子化学計算を用いて速度定数を算出し、文献値と良い一致を示した。位置選択性パターンが明らかになり、炭素鎖長や分岐構造の影響も解明された。この結果はアンモニア/アルコールおよびアンモニア/エーテル燃焼反応機構の構築に理論的支援を提供する。

English

This study systematically investigates the kinetics of H-atom abstraction from C1-C4 alcohols and ethers by NH2 radicals using quantum chemical calculations at the QCISD(T)/CBS level. Rate constants were computed over 300-2000 K and agree with literature. Regioselectivity patterns (e.g., k_tertiary > k_secondary > k_primary) and effects of chain length/branching were identified. The data supports construction of accurate reaction mechanisms for ammonia/alcohol and ammonia/ether combustion, aiding engine simulation and sustainable fuel design.

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

日本はアンモニア混焼や水素・アンモニア燃料の利用を推進しており、本研究はアンモニアと低炭素アルコール・エーテルの混合燃焼における速度論的データを提供する。これにより、日本が目指すアンモニア燃料エンジンの開発や排出制御に理論的基盤を与える。

In the global GX context

Ammonia is being explored globally as a carbon-free fuel, often blended with reactive fuels like alcohols. This kinetic study provides essential rate constants for accurate combustion modeling, supporting the development of sustainable fuel formulations and emission reduction strategies worldwide.

👥 読者別の含意

🔬研究者:Provides high-level ab initio kinetic data for NH2 radical reactions with low-carbon alcohols and ethers, useful for combustion mechanism development.

🏢実務担当者:Engineers designing ammonia co-firing engines can use these rate constants to simulate fuel blends and optimize combustion.

📄 Abstract(原文)

ABSTRACT Alcohols and ethers serve as promising reactive green fuels as additives to blend with ammonia for modern engines. The H‐atom abstraction reactions by NH 2 radicals from fuels are crucial in the combustion process of ammonia and fuel mixtures. In this work, the kinetics of H‐atom abstraction reaction by NH 2 radicals from C 1 –C 4 alcohols and ethers are systematically studied. Quantum chemical calculations at the QCISD(T)/CBS//M06‐2X/6‐311++G(d,p) level were performed to optimize geometries and compute vibrational frequencies for all relevant species. Single‐point energy was determined using QCISD(T)/cc‐pVDZ, and QCISD(T)/cc‐pVTZ level of theories, with basis set corrections using MP2/cc‐pVDZ, MP2/cc‐pVTZ, and MP2/cc‐pVQZ methods. One‐dimensional hindered rotor potentials were obtained with 10° increment using M06‐2X/cc‐pVTZ method. High‐pressure limit rate constants for all reaction channels were calculated by using Master Equation System Solver with conventional transition state theory over a range of temperature (300–2000 K). The computed rate constants exhibit good agreement with the data available in the literature. Moreover, key regioselectivity patterns emerge: for alcohols, k tertiary &gt; k secondary &gt; k primary , and k α &gt; k γ &gt; k β ; for ethers: k tertiary &gt; k secondary &gt; k primary , and k α &gt; k β. The impact of the carbon chain length and branched structure on the rate constants has also been investigated. Substituent effects reveal that branching in the carbon chain consistently decreases rate constants at identical abstraction sites across both alcohol and ether systems. This study provided theoretical support for the accurate construction of the ammonia/alcohol and ammonia/ether reaction kinetic mechanism, and to develop a comprehensive database to support practical applications in engine simulation, emission control, and sustainable fuel formulation strategies.

🔗 Provenance — このレコードを発見したソース

🔔 こうした論文の新着を逃したくない方は キーワードアラート に登録(無料・3キーワードまで)。

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。