AIM3: Additive and intelligent manufacturing of multi-functional membranes

可持续的膜基技术可以降低能源密集型工艺的能源、运营和资本成本，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。这些纯化和分离过程占世界能源消耗的10-15%，膜技术每年可节省40亿美元的能源成本。目前，英国有670多个沼气厂在运营，每年产生近12 TWh的沼气。这意味着需要净化大量的沼气，因为沼气含有约15-50%的CO2。这些工厂每年已经减少了510万吨二氧化碳的排放。此外，预计到2040年，全球沼气潜力将达到8000万吨油当量，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，一直在寻找未来的纯化技术，以利用氢气，这是混合二氧化碳和甲烷，需要纯化。膜是阻隔膜，选择性地分离分子的性质，如大小或形状。该技术的广泛实施取决于膜材料的性能和它们的制造成本。虽然聚合物膜在全球膜市场上占据主导地位，但其性能受到影响。因此，需要新的材料。目前的努力针对来自极多孔材料的膜，例如沸石咪唑骨架（ZIF）和金属有机骨架（MOF）膜。一克这些材料的表面积相当于2.5个足球场。然而，它们的生产是昂贵的。因此，需要创新的技术以在商业规模上更便宜地制造这些膜。在我们之前的项目中，我们通过电化学将ZIF膜涂覆在折叠的基底上来增加ZIF膜的表面积。然而，柔性基板的有限可用性是挑战之一。此外，现有的柔性表面仅在小区域（例如，1平方厘米），并需要手动折叠，这是不实际的。我们还使用人工智能方法（机器学习模型）来减少项目期间的实验数量。然而，基本的模型并不适用于定义膜合成。因此，本提案将提供一种用于制造3D折叠柔性基板的增材制造方法。我们还将通过复杂的机器学习模型而不是经典方法来定义复杂的ZIF/MOF膜合成系统。这将确保我们最初的目标--超致密膜的大规模生产，并使膜分离技术在可持续发展的未来得到广泛应用。

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.