# Graphene-Based Membranes for CO2/CH4 Separation: Key Challenges and Perspectives
## 5 Conclusions  
In this short paper, we have provided a succinct summary of the current status of nanoporous single-layer graphene, few- to multi-layer graphene-based stacked laminates, and mixed-matrix membranes with an emphasis towards CO\({}_{2}\)/CH\({}_{4}\) separation. Notably, the major challenges faced  
Figure 4: (**a**) CO\({}_{2}\)/CH\({}_{4}\) Robeson plot showing the prior upper bound (1991) and the present upper bound (2008) with a slope of \(-2.636\). Adapted from Reference [75]. (**b**) The performance plot of 470 filler materials surveyed to date, showing their selectivity enhancement as a function of their permeability enhancement. (**c**) Top 20 fillers selected based on their permeability and selectivity enhancements. (**d**) Top 20 fillers selected based on their \(F_{\text{index}}\) values with outstanding performance enhancements accurately singled out from Figure 4**b**. Adapted from Reference [5]. (**e**) Schematic illustration of the graphene-based thin-film nanocomposite membranes with both flat-sheet and hollow fiber configurations. Creative Commons license CC BY 4.0.  
by each membrane design, as well as key insights and proposed solutions, are put into perspective. In essence, nanoporous single-layer graphene membranes boast the highest separation performances, owing to the monoatomic thickness, and thus they have the lowest conceptual transport resistance of a single-layer graphene. However, the low scalability and high cost of production will continue to plague this type of membrane design. Few- to multi-layer graphene-based stacked laminates as membranes for CO\({}_{2}\)/CH\({}_{4}\) separation appear to be more technically scalable and exhibit reasonably good performances. Yet, the cost of production is likely to remain higher than mixed-matrix and current polymeric membranes. Also, literature reports are scarce in terms of the hollow fiber stacked laminates aimed at CO\({}_{2}\)/CH\({}_{4}\) separation, rendering the relevance and feasibility of this membrane design for industrial application indefinite. At present, graphene-based mixed-matrix membranes, including the hollow fiber membrane configuration, have the highest commercial value given the relative ease of fabrication and scalability potential. The challenge lies in deepening our understanding of the real impact brought by the graphene-based materials and how to realize optimized mixed-matrix membranes by matching the right polymer matrix to the graphene-based material to achieve maximized separation performances. For this purpose, we recommend a data-driven approach using a newly developed \(F_{\text{index}}\) to help enhance decision-making competencies of researchers, as well as to use it as a benchmark to complement the current Robeson upper bound. Overall, from a big picture standpoint, we map out the current technology landscape of graphene-based membranes from three aspects: (1) separation performance enhancement, (2) commercial viability that includes scalability and mechanical robustness, as well as industrial relevance, and (3) production cost (Figure 5). Apparently, nanoporous single-layer graphene stands at the top of the plot, while conventional polymeric membranes take the opposite end. Graphene-based stacked laminates are likely to be in the center of the plot given the higher technical difficulties in large-scale fabrications and the lack of rigorous techno-economic analysis. Obviously, mixed-matrix and thin-film nanocomposite membranes are positioned in between the stacked laminates and conventional polymeric membranes (Figure 5). Pushing beyond these efforts, we believe that optimizing graphene-based mixed-matrix and thin-film nanocomposite membranes (in particular hollow fiber membranes) by leveraging data analytics will not only open up more compelling opportunities to elevate membrane-based CO\({}_{2}\)/CH\({}_{4}\) separation but also reduce risk to a level that is appealing to the industry and for ensuring commercial success.