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DEMO Discovery of efficient Enzyme-like Metal Organic frameworks to activate biomethane at low temperature

DEMO Discovery of efficient Enzyme-like Metal Organic frameworks to activate biomethane at low temperature
演示:发现高效的类酶金属有机框架,可在低温下激活生物甲烷
批准号:
EP/Y032799/1
负责人:
Stephen Poulston
金额:
$33.22万
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2023
资助国家:
英国
项目状态:
未结题
起止时间:
2023 至 --

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中文摘要
翻译
DEMO的主要目标是通过联合博士学位课程为13名博士候选人(DC)提供高水平的动手,计算和可转移技能培训,并培养新一代混合催化专家。DEMO以轻质(C1-C4)烷烃为例,研究将可持续分子(生物甲烷)转化为工业中的相关化学品(甲醇)。该项目结合了来自7个国家的9个世界级研究小组,化学工程,有机化学,催化,建模和光谱学专家。来自学术(3),研究中心(3),中小企业(2)和工业(1)领域的9个合作伙伴将为招募的DCs提供独特的视角,为DCs的个人研究职业生涯做好准备。DEMO将整合机器学习,有机化学,从头建模,高通量和反应器工程以及原位光谱学,以发现金属有机框架(MOF)中的酶样物质。具体而言,DEMO将遵循一种相互关联的策略来发现最佳催化剂候选物:a)通过机器学习虚拟生成MOFs中活性物种的数据集并进行筛选; B)通过实验高通量工程和建模测试大样本数据集的数据集值; c)通过原位光谱学,滴定动力学和建模了解测试输出; d)优化合成材料的方案,使之与生物学相似,并设计反应条件,以研究溶剂化现象。通过这种方式,DEMO希望通过提供高质量的混合催化培训,对科学界,欧盟工业和社会产生广泛的影响。
英文摘要
The main objective in DEMO is to provide high-level hands-on, computational and transferable skill training to 13 Doctoral Candidates (DC) through a Joint Doctorate Program and to create a new generation of experts in hybrid catalysis. DEMO uses light (C1-C4) alkanes as example to study the conversion of a sustainable molecule (biomethane) into a relevant chemical in industry (methanol). This project combines 9 world-class research groups, experts in chemical engineering, organic chemistry, catalysis, modelling and spectroscopy from 7 countries. The 9 partners in academic (3), research centre (3), SME (2) and industrial (1) fields will provide recruited DCs with unique perspectives, preparing DCs for their personal career in research with specific skillsets. DEMO will integrate machine learning, organic chemistry, ab initio modelling, high-throughput and reactor engineering and in situ spectroscopy to discover enzyme-like species in Metal Organic Frameworks (MOFs). Specifically, DEMO will follow an interconnected strategy to discover optimal catalyst candidates: a) virtually generate a dataset with active species in MOFs and screen via Machine Learning; b) test the dataset value of a large sample dataset via experimental high-throughput engineering and modelling; c) understand testing outputs through in situ spectroscopy, titration kinetics and modelling; d) optimise protocols for synthetic materials towards biological analogies and engineer reaction conditions to search solvation phenomena. This way, DEMO expects to have a broad impact on the scientific community, EU industry and society by providing high-quality training in hybrid catalysis.
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