This document provides supplementary material supporting the Conference Paper “A Multi-Objective Optimisation and Superstructure-Based Decision-Support Tool for Regional Low-Carbon Hydrogen Roadmaps: Methodology and Application to a region of Spain”.

It includes additional methodological details, input data, model assumptions, and extended results that complement the analyses presented in the main manuscript.

Aluminium cold rolling is an energy-intensive process that has a substantial impact on CO₂ emis-sions and production cost, yet plant-level optimization remains challenging due to strong process nonlinearities and various operational constraints. This study develops a physics-consistent hy-brid model that combines a Stone–Hitchcock–Ludwik analytical rolling-energy formulation with a residual deep neural network to predict the daily electricity consumption of three single-stand cold rolling mills. Using plant raw data, the hybrid model achieves lower prediction errors than conventional data driven model and yields line-specific physical parameters that agree well with the observed behaviour of each mill. On this basis, an NSGA-II-based tri-objective optimization is carried out to minimise daily energy use, CO₂ emissions, and specific production cost (SPC) by adjusting pass-wise reduction and tension schedules and line-wise production allocation. Case studies on a representative operating... [more]

The attached table shows the raw experimental data used for Figure 2 in the conference paper.

Digital supplementary information for the ESCAPE36 conference paper titled: High Performance HPs Using Tailored Refrigerants

Anomaly detection is essential for keeping chemical plants safe and running efficiently. Although many deep-learning methods have been proposed, most are still tested mainly on synthetic benchmarks such as the Tennessee Eastman Process (TEP). While these simulators enable fair comparisons, they do not reflect the noise, complexity, and irregular fault behavior of real industrial plants. As a result, it remains unclear how well these models generalize in practice. In this work, we extend our earlier ESCAPE study and move beyond water systems to industrially relevant chemical processes. We analyze data from two continuously operated pilot plant scenarios at the Technical University of Munich: n-butanol/water heteroazeotropic distillation and poly(oxymethylene) ether purification. We published these datasets for the first time at NeurIPS 2025. In this work, 30 anomaly detection methods, including 26 deep-learning and 4 classical approaches, are benchmarked using the open-source TimeSeAD l... [more]

Supplementary Material for Estimation of Thermodynamic Properties for Cellulosic Biomass-Derived Compounds: Application to Heat and Work Balances in Process Simulation that will be submitted to Escape36.

SUPPORTING INFORMATION for the work "Particle Swarm Optimization for simultaneous design and optimization of heat pumps considering Mixed Integer problems", submited to ESCAPE 36.

This document provides the Supplementary Material for the study titled: Virtual Plant–Model Pair as a Step Towards Real-Time Optimization of a Simulated Moving Bed System. The work has been submitted to the peer-reviewed proceedings of the 36th European Symposium on Computer-Aided Process Engineering (ESCAPE 2026).

Supplementary material for: Generative AI for the optimal design of seawater desalination processes (ESCAPE 36, Sheffield, June 2026)

This document contains digital supplementary material for the article “Integrated molecular and process design with technoeconomic and lifecycle assessment for solvent-based recycling of end-of-life vehicle plastics,” submitted to the peer-reviewed proceedings of the 36th European Symposium on Computer-Aided Process Engineering (ESCAPE 2026).

This document provides digital supplementary material related to the article “Development of a methodology for heat pump-based heat integration in batch processes” which has been submitted to the peer-reviewed proceedings of the 36th European Symposium on Computer-Aided Process Engineering (ESCAPE 2026).

Supplementary material for "Techno-Economic Assessment of Decarbonization Pathways for Methanol and Formaldehyde Production: A Superstructure Optimization Approach" (ESCAPE36, Sheffield, June 2026)

Supplementary material for the conference paper "Evaluating the potential of e-fuels for decarbonizing European truck transport: A techno-economic and life cycle approach" (ESCAPE36, Sheffield, June 2026).

This document compiles the digital supplementary material associated with the article entitled “Optimizing Steam Flux for Energy Efficiency in Ammonia Recovery during Sodium Carbonate Production”, published in the peer-reviewed proceedings of the 36th European Symposium on Computer Aided Process Engineering (ESCAPE 36). It presents the effects of variations in steam pressure and temperature on the system’s temperature and mass flow rate.

This document contains digital supplementary material (assessment of sustainability promotion potential) related to the article entitled “Methodology to assess the integrity of Water and Energy Integration Systems (WEIS) models using the ThermWatt computational tool”, which is part of the peer reviewed conference proceeding of the 36th European Symposium on Computer Aided Process Engineering (ESCAPE 36). The present content has been adapted from the PhD thesis entitled "Simulation and Optimisation of Water and Energy Integration Systems (WEIS): An Innovative Approach for Process Industries".

Supplementary material for the article "Utilizing Machine Learning for Phenomena-based Synthesis of Intensified Process Flowsheets", submitted to The 36th European Symposium on Computer Aided Process Engineering (ESCAPE 36). The document includes information about the heurstic and samplic logic rules used in generating the initial dataset, and the grid search results for hyperparamter optimization.

Supplemental information for the article "Multi-Scale Design for Clean Energy Systems: Industrial Electrification and Flexible Operation of Ammonia Synthesis", which has been submitted to 36th European Symposium on Computer Aided Process Engineering. The document includes parametric data and model information.

This document contains digital supplementary material (detailed model description, parameters for different case studies and additional figures) related to the article "Optimization of Site-wide Heat-Integrated Utility Systems with Heat Pumps using MILP" which is submitted to the peer reviewed conference proceeding of the 36th European Symposium on Computer Aided Process Engineering (ESCAPE 36).

This study presents a mixed-integer bilinear optimization model for the cost-optimal design of a Northern European hydrogen supply chain with integrated CCS, focusing on exports from Norway to Germany and CO2 sequestration in Norway. The model is formulated as a superstructure problem and implemented in Pyomo, considering multiple locations for infrastructure nodes and transport options for hydrogen, wood chips, and CO2.

Isotherm data for CO2 and N2 adsorption for Fe3O4@HKUST1 (MOF) and Mass and Energy balance equations for Magnetic Inductive Swing Adsorption system.

The introduction, peer review policy, and International Scientific Committee for Systems and Control Transactions volume 4 (ESCAPE 35 Proceedings)

This is the cover page and front matter for Systems and Control Transactions volume 4 (ESCAPE 35 Proceedings)

This study evaluates the introduction of Carbon Capture and Utilization (CCU) process in two Colombian refineries, focusing on their potential to reduce CO2 emissions and their associated impacts under a scenario aligned with the Net Zero Emissions by 2050 Scenario defined in the 2023 IEA report. The work uses a MILP programming tool (Linny-R) to model the operational processes of refinery sites, incorporating a net total cost calculation to optimize process performance over five-year intervals. This optimization was constrained by the maximum allowable CO2 emissions. The methodology includes the calculation of surplus refinery off-gas availability, the selection of products and CCU technologies, and the systematic collection of data from refinery operations, as well as scientific and industrial publications. The results indicate that integrating surplus refinery fuel gas (originally used for combustion processes) and HTL bio-crude off-gas (as a source of biogenic CO2) can significantl... [more]

This document is supplementary material for the full paper titled "Flow Simulation of Plastic Life Cycle Considering Carbon Renewability and Environmental Impact," submitted for the ESCAPE 35 conference. It includes a detailed explanation of the system boundary construction method used in the flow analysis, as well as the data sources for information such as the GHG emission intensities, which could not be explained in the main text.

This study proposes a model-based approach utilizing a hybrid population balance model (PBM) to optimize temperature profiles for minimizing agglomeration and enhancing crystal growth. The PBM incorporates key mechanisms—nucleation, growth, dissolution, agglomeration, and deagglomeration—and is ap-plied to the crystallization of an industrial active pharmaceutical ingredient (API), Compound K. Parameters were estimated through prior design of experiments (DoE) and refined via additional thermocycle experiments. In-silico DoE simulations demonstrate that the hybrid PBM outperforms traditional methods in assessing process performance under agglomeration-prone conditions. Results confirm that thermocycles effectively reduce agglomeration and promote bulk crystal formation, though their efficiency plateaus be-yond a certain cycle number. This model-based approach provides a more robust strategy for agglomeration control compared to conventional methods, offering valuable insights for indus... [more]