This document contains supplementary material related to the article "Valorization of refinery fuel gas and biogenic gases from thermochemical conversion into low-carbon methanol", submitted to the 35th European Symposium on Computer Aided Process Engineering (ESCAPE 35).

The reduction and recovery of organic fraction of municipal solid waste is a major challenge for contemporary society. It requires the establishment of regional strategies with minimized environ-mental impact. This study employs life cycle assessment to evaluate the respective environmental performances of the current French system based on incineration, and those of alternative systems including (i) anaerobic digestion with composting and (ii) composting for biowaste treatment under different energy scenarios. The environmental impacts of Parisian waste are calculated by consid-ering the French energy mix in 2022, the average European energy mix in 2022 and the projected French energy mix for 2030. The results show that the proportion of fossil-based sources in the energy mixes significantly influences the environmental performance of waste management sys-tems. Systems with high fossil-based sources dependency tend to favour incineration-based pro-cessing systems. This is driven by th... [more]

The PDF document includes five figures that complement the article "Surface Tension Data Analysis for Advancing Chemical Engineering Applications." The figures illustrate the data distribution for parameters A and B, as well as the quality of the regressions for both parameters.

This document contains digital supplementary material (detailed model description, parameters for different case studies and figure of exemplary waste heat supply and heat demand) related to the article "A Data-Driven Conceptual Approach to Heat Pump Sizing in Chemical Processes with Fluctuating Heat Supply and Demand" which is submitted to the peer reviewed conference proceeding of the 35th European Symposium on Computer Aided Process Engineering (ESCAPE 35).

Contains optimized design data, aspen simulation files for the three chemical heat pumps namely:
Isopropanol–acetone–hydrogen
2-Butanol–methyl ethyl ketone–hydrogen
2-Pentanol–methyl propyl ketone–hydrogen.
Optimization code (written in python) is also provided.

The document is the digital supplementary material for the article titled "Synthesis of Liquid Mixture Separation Networks Using Multi-Material Membranes", submitted to the ESCAPE 35 conference. It contains the mathematical formulation, data tables, and additional figures.

This document contains digital supplementary material (model validation, flowsheets and detailed simulation/optimisation results) related to the article entitled “Modelling of a Heat Recovery System (HRS) Integrated with Steam Turbine Combined Heat and Power (CHP) Unit in a Petrochemical Plant”, which is part of the peer reviewed conference proceeding of the 35th European Symposium on Computer Aided Process Engineering (ESCAPE 35).

This document is supplementary information for the article titled Materials-Related Challenges of Energy Transition, submitted to the ESCAPE 35 conference. It contains the data used in the calculations and referenced in the main article.

The submission contains problems names with the initial guesses that were used to solve them for the reference of the reader.

This code is of a Non-Convex Mixed Integer Quadratic Programme of a hydrogen export facility. This programme is a multistage stochastic model, using inheritance based indexing in order to account for the influence of uncertainty in weather forecasting on the optimal scheduling of the export facility.

In this file can be found:
- Energy demands and scope 1 CO2 emissions for different lime production routes
- Assumptions underlying the price scenarios
- Commodities prices used for cost estimation

To match the growing demand for biomethane production, anaerobic digestors need an optimal and time-varying adaptation of the input diet. Dynamic co-digestion constitutes a hard challenge for the limited instrumentation and control equipment typically installed aboard full-scale plants. The development of prediction models is foreseen to support process (optimal) design and control. In this work, a rigorous framework is applied to take full-scale applicability into account while dealing with the design and training of both high-fidelity and control-oriented first-principle/grey-box models, intended to be exploited for real-time optimization and actual process control respectively.