AIM3: Additive and intelligent manufacturing of multi-functional membranes

AIM3：多功能膜的增材与智能制造

• 批准号: EP/W010011/1
• 负责人: Begum Tokay
• 金额: $ 128.53万
• 依托单位: University of Nottingham
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FW010011%2F1
• 关键词: AIM3; Additive; intelligent; manufacturing; multi

Sustainable membrane-based technologies can cut energy, operational and capital costs for energy-intensive processes such as CO2 capture from (bio)methane and removal of methane from H2, while contributing to net-zero target. These purification and separation processes account for 10-15% of the world's energy consumption and membrane technologies could save $4 billion in energy costs annually. Over 670 biogas plants are currently operational in the UK, generating nearly 12 TWh year-1 now. This means that significant amount of biogas will need to be purified because biogas contains ~15-50% CO2. These plants are already preventing 5.1 million tonnes of CO2 from being emitted each year. Moreover, the global biogas potential is expected to reach 80 Mtoe in 2040, which will contribute to a reduction in CO2 emissions, by displacing the use of more polluting fuels. In addition to this, gas and electricity companies such as National Grid, have been looking for future purification technologies to utilise on H2, which is mixed with CO2 and methane and needs to be purified.Membranes are barrier films that selectively separate molecules based on their properties e.g. size or shape. The wide-spread implementation of this technology depends on the performance of the membrane materials and their manufacturing cost. Although membranes from polymers are dominating the global membrane market their performance suffers. Therefore, new materials are required. Current efforts are directed at membranes from extremely porous materials such as zeolite imidazole framework (ZIF) and metal-organic framework (MOF) membranes. One gram of these materials contains surface areas equal to 2.5 football pitches. However, their production is expensive. Therefore, innovative techniques are required to manufacture these membranes cheaper at commercial scale. In our previous project, we increased the surface area of ZIF membranes by coating them on folded substrates via electrochemistry. However, the limited availability of flexible substrates was one of the challenges. Moreover, the existing flexible surfaces are only available in small areas (e.g., 1 cm2) and needed to be manually folded, which is not practical. We also used artificial intelligence methods (machine learning models) to reduce the number of experiments during the project. However, basic models did not work to define the membrane synthesis.Therefore, this proposal will deliver an additive manufacturing approach for manufacturing 3D folded flexible substrates. We will also define complex ZIF/MOF membrane synthesis system via complex machine learning models rather than classical approach. These will ensure scale up manufacturing of super-compacted membranes that is our original goal and enable wide-spread application of membrane-based separation technologies for a sustainable future.

可持续的基于膜的技术可以降低能源密集型过程的能源、运营和资本成本，例如从(生物)甲烷中捕获二氧化碳和从氢气中去除甲烷，同时有助于实现净零目标。这些净化和分离过程占世界能源消耗的10%-15%，膜技术每年可以节省40亿美元的能源成本。英国目前有670多家沼气厂在运营，每年产生近12太瓦时的电力。这意味着大量的沼气将需要净化，因为沼气含有大约15-50%的二氧化碳。这些工厂已经每年防止510万吨二氧化碳的排放。此外，全球沼气潜力预计将在2040年达到8000万吨，这将通过取代使用污染更严重的燃料来减少二氧化碳排放。除此之外，天然气和电力公司，如国家电网，一直在寻找未来的净化技术来利用氢气，氢气与二氧化碳和甲烷混合，需要进行净化。膜是一种阻隔膜，根据分子的性质，如大小或形状，选择性地分离分子。这项技术的广泛实施取决于膜材料的性能和制造成本。尽管聚合物膜在全球膜市场上占据主导地位，但它们的性能受到影响。因此，需要新的材料。目前的研究方向是以分子筛咪唑骨架(ZIF)和金属有机骨架(MOF)等极多孔材料为原料的膜。一克这种材料的表面积相当于2.5个足球场。然而，它们的生产成本很高。因此，需要创新技术才能以更低的价格在商业规模上制造这些膜。在我们之前的项目中，我们通过电化学将ZIF膜涂覆在折叠的衬底上来增加ZIF膜的表面积。然而，柔性衬底的可获得性有限是挑战之一。此外，现有的柔性表面只在很小的区域(如1平方厘米)可用，需要手动折叠，这是不现实的。我们还使用了人工智能方法(机器学习模型)来减少项目期间的实验次数。然而，基本模型并不能定义膜合成。因此，这一提议将为制造3D折叠柔性基板提供一种加法制造方法。我们还将通过复杂的机器学习模型而不是经典的方法来定义复杂的ZIF/MOF膜合成系统。这些将确保扩大超致密膜的制造，这是我们的最初目标，并使基于膜的分离技术能够在可持续的未来得到广泛应用。

项目成果

A bulk-surface continuum theory for fluid flows and phase segregation with finite surface thickness

• DOI: 10.1016/j.physd.2024.134055
• 发表时间: 2024-01-19
• 期刊: PHYSICA D-NONLINEAR PHENOMENA
• 影响因子: 4
• 作者: Boschman，Anne;Espath，Luis;Zee，Kristoffer G. van der
• 通讯作者: Zee，Kristoffer G. van der

Neural control of discrete weak formulations: Galerkin, least squares & minimal-residual methods with quasi-optimal weights

离散弱公式的神经控制：伽辽金、最小二乘法

• DOI: 10.1016/j.cma.2022.115716
• 发表时间: 2022
• 期刊: Computer Methods in Applied Mechanics and Engineering
• 影响因子: 7.2
• 作者: Brevis I

A unified framework for Navier-Stokes Cahn-Hilliard models with non-matching densities

具有不匹配密度的 Navier-Stokes Cahn-Hilliard 模型的统一框架

• DOI: 10.1142/s0218202523500069
• 发表时间: 2023
• 期刊: Mathematical Models and Methods in Applied Sciences
• 影响因子: 3.5
• 作者: Ten Eikelder M

Thermodynamically consistent diffuse-interface mixture models of incompressible multicomponent fluids

不可压缩多组分流体的热力学一致扩散界面混合模型

• DOI: 10.48550/arxiv.2302.09287
• 发表时间: 2023
• 作者: Eikelder M

Linearization of the Travel Time Functional in Porous Media Flows

• DOI: 10.1137/21m1451105
• 发表时间: 2022-05
• 期刊: SIAM J. Sci. Comput.
• 作者: Paul Houston;Connor J. Rourke;Kristoffer G. van der Zee