Accelerating Discovery and Implementation of Effective Porous Liquids for CO2 Removal

在这个项目中，我们的目标是展示自动化高通量平台的潜力，结合过程建模的见解，筛选和确定有效的气体分离设计吸附剂。我们将特别关注使用多孔液体作为设计吸附剂从CO2/N2和CO2/CH4气体混合物中去除CO2。近几十年来的研究工作导致了新型吸附剂材料或所谓的“设计吸附剂”的爆炸式增长。这些吸附剂的可调性意味着在理论上，人们可以为任何给定的分子分离生产高性能的吸附剂。然而，这些吸附剂的可调性也代表了一个挑战：为给定的分离确定最佳吸附剂意味着筛选数十万种可能的吸附剂。分子模型和过程模型可以帮助缩小有希望的候选者的数量。然而，从实验的角度来看，这个数字可能仍然很大，特别是考虑到每种吸附剂都需要合成优化和升级。这就是自动化高通量（HT）合成和表征平台可以提供帮助的地方。

In this project, we aim to demonstrate the potential of automated high-throughput platforms, combined with insights from process modelling, in screening and identifying effective designer sorbents for gas separations. We will specifically focus on the removal of CO2 from CO2/N2 and CO2/CH4 gas mixtures using porous liquids as designer sorbents.Research efforts in recent decades have led to an explosion of new sorbent materials or so-called "designer sorbents". The tunability of these sorbents mean that in theory, one could produce a performant sorbent for any given molecular separation. Yet, the tunability of these sorbents also represents a challenge: identifying the best sorbent for a given separation means screening hundreds-of-thousands of possible sorbents. Molecular modelling and process modelling can help narrow down the number of promising candidates. However, this number may still be large from an experimental standpoint, especially considering that each sorbent will require synthesis optimisation and upscaling. This is where automated high-throughput (HT) synthesis and characterisation platforms can help.