Interdisciplinary collaborations to address the uncertainty problem in life cycle assessment of nano-enabled products: case of the quantum dot-enabled display

Abstract

Life cycle assessment (LCA) is a powerful tool for assessing the environmental impacts of established processes and products. However, its use in decision-making for sustainable development of emerging technologies is challenging. High levels of uncertainty and lack of data over the complete value chain associated with nascent nano-enabled products (NEPs) makes it difficult to perform LCA studies early in the design process. This study addresses the uncertainty problem faced by LCA, and a demonstration is performed with a case study of quantum dot (QD)-enabled display. The study at hand proposes a dynamic life cycle assessment (dLCA) framework, which emphasizes iterative evaluation and collaborative efforts to tackle the data scarcity problem faced by retrospective (traditional) LCA. Experimental study of two commercially available QD-enabled displays (hand-held tablet with CdSe QD-enabled display and TV set with InP QD-enabled display) is performed for data collection of QD amount and release. After complete digestion, the experimental result shows that the concentration of CdSe (3.92 ± 0.32 μg cm⁻²) in the QD enhancement film (QDEF) of the tablet is comparable with the concentration of InP (3.56 ± 0.24 μg cm⁻²) in the QDEF of the TV. After accounting for the experimental results, the second traversal of dLCA is performed, and it shows that cumulative energy demand (CED) per unit area for InP QD-enabled displays is 5.28 × 10⁻³ MJ cm⁻² (first traversal was 2.59 × 10¹ MJ cm⁻²) and CdSe QD-enabled displays is 3.92 × 10⁻⁴ MJ cm⁻² (first traversal was 4.32 × 10⁻² MJ cm⁻²). This study highlights the role of collaborative research between life cycle modelers and experimentalists to improve the credibility of LCA results for emerging NEPs. Even though this study is based on the case of QD-enabled displays, the proposed dLCA framework and interdisciplinary collaboration method can also be applied to other emerging technologies.