Transition metal oxide complexes as molecular catalysts for selective methane to methanol transformation: any prospects or time to retire?

甲醇 催化作用 氧化物 甲烷 化学 过渡金属 金属 反应性(心理学) 无机化学 有机化学 医学 替代医学 病理
作者
Emily E. Claveau,Safaa Sader,Benjamin A. Jackson,Shahriar N. Khan,Evangelos Miliordos
出处
期刊:Physical Chemistry Chemical Physics [The Royal Society of Chemistry]
卷期号:25 (7): 5313-5326 被引量:14
标识
DOI:10.1039/d2cp05480a
摘要

Transition metal oxides have been extensively used in the literature for the conversion of methane to methanol. Despite the progress made over the past decades, no method with satisfactory performance or economic viability has been detected. The main bottleneck is that the produced methanol oxidizes further due to its weaker C-H bond than that of methane. Every improvement in the efficiency of a catalyst to activate methane leads to reduction of the selectivity towards methanol. Is it therefore prudent to keep studying (both theoretically and experimentally) metal oxides as catalysts for the quantitative conversion of methane to methanol? This perspective focuses on molecular metal oxide complexes and suggests strategies to bypass the current bottlenecks with higher weight on the computational chemistry side. We first discuss the electronic structure of metal oxides, followed by assessing the role of the ligands in the reactivity of the catalysts. For better selectivity, we propose that metal oxide anionic complexes should be explored further, while hydrophylic cavities in the vicinity of the metal oxide can perturb the transition-state structure for methanol increasing appreciably the activation barrier for methanol. We also emphasize that computational studies should target the activation reaction of methanol (and not only methane), the study of complete catalytic cycles (including the recombination and oxidation steps), and the use of molecular oxygen as an oxidant. The titled chemical conversion is an excellent challenge for theory and we believe that computational studies should lead the field in the future. It is finally shown that bottom-up approaches offer a systematic way for exploration of the chemical space and should still be applied in parallel with the recently popular machine learning techniques. To answer the question of the title, we believe that metal oxides should still be considered provided that we change our focus and perform more systematic investigations on the activation of methanol.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
浮游应助科研通管家采纳,获得10
1秒前
浮游应助科研通管家采纳,获得10
1秒前
1秒前
远山等故归完成签到,获得积分10
1秒前
Hedy应助科研通管家采纳,获得10
1秒前
1秒前
小米发布了新的文献求助10
1秒前
ccnnzzz完成签到,获得积分10
1秒前
小马甲应助科研通管家采纳,获得10
2秒前
浮游应助科研通管家采纳,获得10
2秒前
2秒前
2秒前
2秒前
英姑应助luobeimin采纳,获得10
2秒前
cici完成签到,获得积分10
3秒前
CipherSage应助Carpediem采纳,获得10
3秒前
脑洞疼应助3587采纳,获得10
4秒前
叶迎发布了新的文献求助10
4秒前
眼睛大的芹菜完成签到 ,获得积分10
4秒前
煎炒焖煮炸培根完成签到,获得积分10
4秒前
吐个泡泡完成签到,获得积分10
4秒前
6秒前
clariom完成签到,获得积分20
6秒前
柴先生完成签到,获得积分10
7秒前
李爱国应助Zola采纳,获得10
7秒前
7秒前
稳中的豆沙包完成签到,获得积分10
7秒前
8秒前
ffq完成签到 ,获得积分10
8秒前
柯夫子完成签到,获得积分10
8秒前
hackfeng应助吐个泡泡采纳,获得30
9秒前
科研通AI2S应助ww采纳,获得10
10秒前
量子星尘发布了新的文献求助10
11秒前
layzhj完成签到,获得积分10
11秒前
咸鱼王完成签到,获得积分10
11秒前
12秒前
planto发布了新的文献求助10
12秒前
典雅的俊驰应助ni采纳,获得30
12秒前
顾矜应助T拐拐采纳,获得10
12秒前
13秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Iron toxicity and hematopoietic cell transplantation: do we understand why iron affects transplant outcome? 2000
Teacher Wellbeing: Noticing, Nurturing, Sustaining, and Flourishing in Schools 1200
List of 1,091 Public Pension Profiles by Region 1021
A Technologist’s Guide to Performing Sleep Studies 500
EEG in Childhood Epilepsy: Initial Presentation & Long-Term Follow-Up 500
Latent Class and Latent Transition Analysis: With Applications in the Social, Behavioral, and Health Sciences 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 物理化学 基因 遗传学 催化作用 冶金 量子力学 光电子学
热门帖子
关注 科研通微信公众号,转发送积分 5483942
求助须知:如何正确求助?哪些是违规求助? 4584399
关于积分的说明 14397356
捐赠科研通 4514299
什么是DOI,文献DOI怎么找? 2473912
邀请新用户注册赠送积分活动 1459930
关于科研通互助平台的介绍 1433260