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Flexible Routes to Liquid Fuels from CO2 by Advanced Catalysis and Engineering

通过先进的催化和工程将二氧化碳转化为液体燃料的灵活途径

基本信息

批准号：
EP/N010531/1
负责人：
Matthew Rosseinsky
金额：
$ 229.9万
依托单位：
University of Liverpool
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2016
资助国家：
英国
起止时间：
2016 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=EP%2FN010531%2F1
关键词：
Flexible Routes Liquid Fuels CO2

项目摘要

There is an urgent need to address the accelerating increase in global CO2 emissions and atmospheric CO2 levels while providing fuels to meet growing energy needs. The UK government has targeted an 80% reduction in emissions (from 1990 levels) by 2050 with an interim target of 34% reduction by 2020. Increasingly, it is becoming clear that a key approach to storage of variable sustainable energy sources such as solar or wind power is in the form of stored chemical energy, and that this is likely to be as a form of hydrogen. However, although hydrogen itself has excellent enthalpy content per unit weight, it is a low density gas, has storage difficulties, and requires relatively high compression energy. The present proposal is focused on the conversion of sustainably produced hydrogen to high energy density liquid fuels including methanol, DME and hydrocarbons which are more easily transported and are compatible with existing fuel distribution networks. These fuels are low in sulfur and flexible in their contribution to future low carbon-intensity fuel scenarios by displacing fossil sources from the liquid fuels pool. They can be used for transport fuels (where they are likely to remain the focus for some time to come), as blending components, as seasonal storage candidates (exploiting their permanence and energy density), for distributed power production or for local heating.The synthesis of these liquid fuels will be achieved using CO2 as a vector to react with hydrogen from solar or wind inputs. We therefore aim to develop new technology to reduce the atmospheric CO2 burden by utilising only water as a source of this hydrogen, avoiding highly endothermic thermocatalytic steam reforming. The annual CO2 emissions from UK electricity generation (around 150x10^6 tonnes) is sufficient, in principle, to supply the UK requirement for liquid transportation fuels, or three times the amount required for the world annual production of methanol (around 45x10^6 tonnes). There are a number of possible attractive concentrated point sources of this CO2, including CO2 prepared for sequestration or from ammonia plants, which could be used to make liquid fuels in the medium term provided efficient catalytic technologies could be developed. Thus we will develop new catalytic technology for the production of synthesis gas (CO/H2) and simple fuel organics, ultimately driven by solar energy using CO2 and H2 sustainably produced from water. We will explore integration of hydrogen and syngas generation with production of syngas from biogenic sources such as waste or biomass to provide additional feed flexibility. Part of our work will develop novel and targeted catalysts for the thermocatalytic production of 'green' fuels from syngas with variable CO2, H2 and water content, focused by process systems engineering considerations that specifically address low-carbon aspects such as intermittency of primary renewable power in process design. Industry partners have endorsed the approach and will provide key input into the form of point source CO2 supply, catalyst manufacture, liquid fuel synthesis, electrolyser manufacture, sustainable hydrogen generation and technology integration, life cycle analysis and industrial fuel usage.The proposal adopts a multidisciplinary catalyst discovery, deployment and process engineering approach to develop, evaluate and optimise thermal, photo- and electro-catalysed routes to liquid fuels from CO2 and water using solar energy (and, indirectly, wind or marine power). Direct thermal and solar-assisted paths to methanol and DME will be compared with stepwise solar/electrochemical syngas generation plus thermal DME or Fischer-Tropsch hydrocarbon synthesis paths. The novel catalyst chemistries enabling each route will be integrated on the basis of process systems modelling and analysis to identify optimised schemes that will be benchmarked by input from industry partners with key roles in potential supply chains.

迫切需要解决全球二氧化碳排放量和大气二氧化碳水平加速增加的问题，同时提供燃料以满足日益增长的能源需求。英国政府的目标是到2050年减排80%（从1990年的水平），中期目标是到2020年减排34%。越来越清楚的是，储存诸如太阳能或风能等可变可持续能源的关键方法是储存化学能的形式，并且这可能是氢的形式。然而，尽管氢本身具有优异的每单位重量焓含量，但它是低密度气体，具有存储困难，并且需要相对高的压缩能量。本提案的重点是将可持续生产的氢气转化为高能量密度液体燃料，包括甲醇、二甲醚和碳氢化合物，这些燃料更容易运输，并与现有的燃料分配网络兼容。这些燃料硫含量低，通过从液体燃料库中取代化石燃料，对未来低碳强度燃料情景的贡献灵活。它们可用于运输燃料（在未来一段时间内，它们可能仍然是焦点），作为混合成分，作为季节性储存候选者（利用其持久性和能量密度），用于分布式发电或局部供暖，这些液体燃料的合成将利用CO2作为载体与来自太阳能或风能输入的氢反应来实现。因此，我们的目标是开发新的技术，以减少大气中的二氧化碳负担，仅利用水作为这种氢的来源，避免高度吸热的热催化蒸汽重整。英国发电产生的二氧化碳年排放量（约150x10^6吨）原则上足以满足英国对液体运输燃料的需求，或者是世界甲醇年产量（约45x10^6吨）的三倍。这种CO2有一些可能的有吸引力的浓缩点源，包括为封存而准备的CO2或来自氨厂的CO2，如果能够开发出有效的催化技术，这些CO2可在中期内用于制造液体燃料。因此，我们将开发新的催化技术，用于生产合成气（CO/H2）和简单的燃料有机物，最终由太阳能驱动，使用从水中可持续生产的CO2和H2。我们将探索氢气和合成气生产与从生物来源（如废物或生物质）生产合成气的整合，以提供额外的进料灵活性。我们的部分工作将开发新型和有针对性的催化剂，用于从具有可变CO2，H2和水含量的合成气热催化生产“绿色”燃料，重点关注工艺系统工程考虑，特别是解决低碳方面，如工艺设计中主要可再生能源的不稳定性。行业合作伙伴已经认可了该方法，并将提供关键输入点源CO2供应，催化剂制造，液体燃料合成，电解槽制造，可持续制氢和技术集成，生命周期分析和工业燃料使用的形式。该提案采用多学科催化剂发现，部署和工艺工程方法，以开发，评估和优化热，利用太阳能（以及间接的风能或海洋能）从二氧化碳和水转化为液体燃料的光催化和电催化路线。将对甲醇和二甲醚的直接热能和太阳能辅助路径与逐步太阳能/电化学合成气发电加上热能二甲醚或费托碳氢化合物合成路径进行比较。将在工艺系统建模和分析的基础上整合实现每种路线的新型催化剂化学，以确定优化方案，这些方案将由在潜在供应链中发挥关键作用的行业合作伙伴提供基准。

项目成果

期刊论文数量（10）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

High-throughput discovery of Hf promotion on the stabilisation of hcp Co and Fischer-Tropsch activity

DOI：
10.1016/j.jcat.2021.02.022
发表时间：
2021-04
期刊：
Journal of Catalysis
影响因子：
7.3
作者：
Luis Alvarado Rupflin;H. van Rensburg;M. Zanella;Elliot J. Carrington;Rebecca Vismara;A. Grigoropoulos;T. Manning;J. Claridge;A. Katsoulidis;R. Tooze;M. Rosseinsky
通讯作者：
Luis Alvarado Rupflin;H. van Rensburg;M. Zanella;Elliot J. Carrington;Rebecca Vismara;A. Grigoropoulos;T. Manning;J. Claridge;A. Katsoulidis;R. Tooze;M. Rosseinsky

Kinetic Model Discrimination for Methanol and DME Synthesis using Bayesian Estimation

使用贝叶斯估计进行甲醇和 DME 合成的动力学模型判别