System boundary selection in life-cycle inventories using hybrid approaches

Life-cycle assessment (LCA) is a method for evaluating the environmental impacts of products holistically, including direct and supply chain impacts. The current LCA methodologies and the standards by the International Organization for Standardization (ISO) impose practical difficulties for drawing system boundaries; decisions on inclusion or exclusion of processes in an analysis (the cutoff criteria) are typically not made on a scientific basis. In particular, the requirement of deciding which processes could be excluded from the inventory can be rather difficult to meet because many excluded processes have often never been assessed by the practitioner, and therefore, their negligibility cannot be guaranteed. LCA studies utilizing economic input−output analysis have shown that, in practice, excluded processes can contribute as much to the product system under study as included processes; thus, the subjective determination of the system boundary may lead to invalid results. System boundaries in LCA are discussed herein with particular attention to outlining hybrid approaches as methods for resolving the boundary selection problem in LCA. An input−output model can be used to describe at least a part of a product system, and an ISO-compatible system boundary selection procedure can be designed by applying hybrid input−output-assisted approaches. There are several hybrid input−output analysis-based LCA methods that can be implemented in practice for broadening system boundary and also for ISO compliance.

Enzyme-assisted self-assembly under thermodynamic control

The production of functional molecular architectures through self-assembly is commonplace in biology, but despite advances^{1, 2, 3}, it is still a major challenge to achieve similar complexity in the laboratory. Self-assembled structures that are reproducible and virtually defect free are of interest for applications in three-dimensional cell culture^{4, 5}, templating⁶, biosensing⁷ and supramolecular electronics⁸. Here, we report the use of reversible enzyme-catalysed reactions to drive self-assembly. In this approach, the self-assembly of aromatic short peptide derivatives^{9, 10} provides a driving force that enables a protease enzyme to produce building blocks in a reversible and spatially confined manner. We demonstrate that this system combines three features: (i) self-correction—fully reversible self-assembly under thermodynamic control; (ii) component-selection—the ability to amplify the most stable molecular self-assembly structures in dynamic combinatorial libraries^{11, 12, 13}; and (iii) spatiotemporal confinement of nucleation and structure growth. Enzyme-assisted self-assembly therefore provides control in bottom-up fabrication of nanomaterials that could ultimately lead to functional nanostructures with enhanced complexities and fewer defects.