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]

Model simulation flowsheet of biomass gasification combined cycle system for simultaneous power and hydrogen production coupled with direct air capture in Aspen Plus.

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).

This document contains digital supplementary material for the article “An Extended Superstructure Formulation for Non-Isobaric Flowsheet Synthesis”, 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).

Aspen Plus is used to simulate the process and compute the mass and energy flows for the complete process of polystyrene waste conversion into value-added chemicals. This demonstrates a pathway for the recycling of PS waste, which could contribute to a more sustainable industry environment

We designed a novel methylcyclohexane–toluene–hydrogen (MTH) based chemical heat pump (CHP) and determined its key performance indicators using Aspen Plus process simulations.

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.

The climate crisis and dependence on fossil fuels make the transition to renewable energy sources imperative, with biomass standing out for promoting decarbonization and circular economy. In this context, fluidized bed gasification emerges as an efficient route for converting waste into syngas, applicable to power and hydrogen generation. Given the variability of real operating conditions, dynamic models are essential to represent coupled fluid dynamic, thermal, and kinetic phenomena over time. In this work, a dynamic phenomenological model was developed using a lumped 0D ap-proach, in which the reactor is divided into two interacting zones represented as continuous stirred-tank reactors (CSTRs): a dense bed, where drying, devolatilization, and heterogeneous re-actions occur, and a freeboard, dominated by homogeneous gas-phase reactions. The model was validated against experimental data from a bubbling fluidized bed gasifier, showing good agree-ment for major syngas species (CO and H₂,... [more]

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 deterministic model formulation describes one root-to-leaf path in a scenario tree that describes the evolution of uncertainty for power grid capacity expansion planning problems. The main manuscript then extends this deterministic formulation to multi-stage and two-stage stochastic programs.

Digital supplementary material for the ESCAPE 36 submission "Modeling and Simulation of Nitrogen Generation by Pressure Swing Adsorption for Power-to-Ammonia". Contains relevant model parameters from the literature.

This document contains the supplementary material for the paper titled “Assessing the Impact of Solvent Recycling in Cooling Crystallization using Computer-Aided Molecular and Process Design”, submitted to the ESCAPE36 conference for consideration.

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 document contains the supplementary material for the paper titled “A Comparative Analysis of Sequential Active Learning Approaches: Statistical Design of Experiments versus Bayesian Optimisation”, submitted to the ESCAPE36 conference for consideration.

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.