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ZENODO
Model . 2026
License: CC BY
Data sources: ZENODO
ZENODO
Model . 2026
License: CC BY
Data sources: Datacite
ZENODO
Model . 2026
License: CC BY
Data sources: Datacite
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Rigid Bioplastics with Preserved Natural Structures Offer Greater Resource Efficiency and Cost-Competitiveness

Authors: Jones, Marie J.; Lukic, Jana; Astour, Antoine; Florez-Orrego, Daniel; Maréchal, François; Luterbacher, Jeremy;

Rigid Bioplastics with Preserved Natural Structures Offer Greater Resource Efficiency and Cost-Competitiveness

Abstract

Process models used to generate the results for Figure 2, 4 and 5 of "Rigid Bioplastics with Preserved Natural Structures Offer Greater Resource Efficiency and Cost-Competitiveness". Aspen_Plus_V11_models: process flowsheet simulations saved as back-up files (.bkp) developped on Aspen Plus V11. A licence is required to open and run the simulation files. Capital_costs: Excel spreadsheet with equipment sizing and costing, and cost linearisation. Datasets_costs_ecoinvent.xlsx: Excel spreadsheet with tabulated cost factors and life cycle inventories (Tables S19-25). OSMOSE_Fig2: Lua scripts to run single-objective optimisation. A valid AMPL licence is required to run the script. The OSMOSE infrastructure must be installed locally or accessed via a server before running the files. OSMOSE is an in-house platform developped at IPESE, EPFL Valais-Wallis, Swizterland. Reach out to the group to request an access to the tool. ET: Lua scripts with mass and energy balances for the models considered to generate the results from Figure 2. The files can be read with VS Code without any licence. project: Lua scripts connecting ET files and lauching the optimiser. OSMOSE_Fig4: Same comments as for OSMOSE_Fig2 but with the models and objective functions required to generated the results from Figure 4. OSMOSE_Fig5: Lua scripts to run multi-objective optimisation. data: Empty Excel file where the results are automatically written. Sensitivity_analysis_Fig2: Jupyter notebook and associated Excel file to perform a univariate sensitivity analysis on the cost and impact factor estimates used to generate Figure 2. The code to make the Tornado plots is also included. Uncertainty_analysis_Fig4: Jupyter notebook and associated Excel file to perform a stochastic uncertainty analysis on the cost and impact factor estimates used to generate Figures 4 and 6. The notebook first creates triangular probability density functions and samples 10000 times.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average