Data Science and Artificial Intelligence for smart sustainable plastic

高密度聚乙烯(HDPE)是一种半结晶聚合物，正是这种结晶和无定形区域的组合为聚合物提供了诱人的性能，导致了聚合物在日常生活中的广泛使用。聚合物中的晶体有助于提高刚性、阻隔性能和韧性，而无定形区域则提供弹性、延展性和韧性。HDPE可以被收集并机械回收，以生产消费后树脂(PCR)，促进循环经济，与新的原始塑料相比，这种塑料具有更低的环境足迹。分拣后的包装通过研磨、洗涤、挤出等过程机械回收，生产出聚合酶链球。用聚合酶链式反应代替包装中的原始塑料的一个主要问题是，它是一种可变材料。它可能含有不同等级的塑料，分子量或弯曲强度不同，它可能会被其他材料污染，回收过程本身可能会导致塑料降解。这些变化中的许多都会影响聚合物的结晶度。为了能够更有效地重复使用PCRHDPE，我们需要了解晶体尺寸、结晶度、结合分子浓度是如何控制聚合物的性能的。HDPE被广泛使用的一个应用领域是包装，特别是用于容纳家庭/个人护理产品和食品的包装，每年约使用270,000吨。HDPE密度低、化学惰性好、韧性好，是一种优良的包装材料。它是一种热塑性塑料，可以加热，然后通过挤出吹塑加工成瓶子。该项目的一个实际成果是了解回收HDPE中的结晶度是如何变化的，以及这随后如何影响聚合物的用户性能。这一理解可用于指导选择用于包装的PCR，最终增加塑料在包装中的可持续性。该博士生将与我们由英国工业战略挑战基金资助的智能可持续塑料包装项目一起运行，并由联合利华共同资助。我们将使用关于原始塑料的现有文献数据，结合对回收塑料进行的各种内部化学技术(FTIR/拉曼/DSC/X射线衍射)的新实验数据，尝试并预测性地将塑料的化学结构与其性能联系起来。这些特性最终决定了回收塑料样品是否适合用于生产。因此，如果能够建立一个准确的预测模型，我们将能够节省时间和金钱，而不必将回收的PCR经过制造过程才能确定其性质。我们将在拓扑数据分析领域使用尖端数据科学技术来做到这一点。这应该使我们能够了解某些化学技术和某些化学性质之间的关系，并且由于光谱中的峰对应于某些物理现象，我们可能能够建立新的结构-性质关系。我们还旨在了解挤出过程中与其他塑料的污染、物理老化和氧化如何影响塑料的物理性能。这将有助于我们了解当前塑料回收流的可行性，如果要应对在制造业中转向100%回收塑料的挑战。

High-density polyethylene (HDPE) is a semi-crystalline polymer, it is this combination of crystalline and amorphous regions that provide the polymer with its attractive properties that result in the polymer's widespread use in day-to-day life. The crystals within the polymer contribute towards the stiffness, barrier properties and toughness while the amorphous regions provide flexibility, ductility and contribute towards toughness. HDPE can be collected and mechanically recycled to produce a post-consumer resin (PCR), promoting a circular economy with a plastic that has a lower environmental footprint compared to new, virgin plastic. The sorted packaging is mechanically recycled through grinding, washing and then extruding to produce PCR pellets.One of the major issues with using PCR to replace virgin plastic in packaging is that it is a variable material. It may contain different grades of plastic differing in molecular weight or flexural strength, it can be contaminated with other materials and the recycling process itself can lead to degradation of the plastic. Many of these changes influence the crystallinity in the polymer. In order to be able to more effectively reuse PCR HDPE we need to understand how crystal size, degree of crystallinity, tie molecule concentration control the performance of the polymer. One application area where HDPE is widely used is packaging, particularly for containing home/personal care products and food, with approximately 270,000 tonnes used annually. HDPE is an excellent packaging material due to its low density, chemical inertness, and toughness. It is a thermoplastic that can be heated and then processed into bottles by extrusion blow-moulding. A practical outcome of the project is to understand how the crystallinity changes in recycled HDPE and how this subsequently impacts the in-user properties of the polymer. This understanding could be used in inform the selection of PCR for use in packaging, ultimately increasing the sustainability of plastics in packaging.This PhD studentship will run alongside our project funded by the UK Industrial Strategy Challenge Fund in Smart Sustainable Plastic Packaging, and is co-funded by Unilever. We will use existing literature data on virgin plastics, combined with new experimental data from various in-house chemical techniques (FTIR/Raman/DSC/XRD) performed on recycled plastics, to try and predictively link the chemical structure of the plastic to its properties. These properties ultimately determine whether a sample of recycled plastic will be desirable for use in manufacturing. Therefore, if an accurate predictive model could be established, we would be able to save time and money and not have to put a recycled PCR through the manufacturing process before we could determine its properties. We will do this using cutting edge data science techniques in the space of Topological Data Analysis. This should allow us to understand relationships between certain chemical techniques and certain chemical properties, and since peaks in the spectra correspond to certain physical phenomena, we may be able to establish new structure-property relationships. We also aim to understand how contamination with other plastics, physical weathering and oxidation in the extrusion process impact the physical properties of the plastic. This will help us to understand the viability of the current plastic recycling stream if challenges to shift to 100% recycled plastic in manufacturing are to be met.