This submission contains an Aspen Plus V12.1 file (.bkp) and a ProMax V6 file (.pmx) as part of the publication "Design of biocarbon by-product utilization processes for ironmaking and steelmaking". The Aspen Plus file contains a simulation of an autothermal reforming reactor for a bio-oil model using an RGibbs block, as well as heat exchangers and condensers used for determining equipment and utility costs. The ProMax file contains a simulation of a carbon dioxide removal process using an absorber and stripper loop with recycled MDEA solvent.

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.

In Quebec, the chemical sector is rapidly changing, with old facilities closing and new ones opening. Similar situation is happening in other geographies as well. Utilities need to understand the energy needs of these industries, particularly as they transition towards decarbonization. By studying existing data, they can estimate energy requirements and identify alternative technologies such as heat pumps, electric boilers, biomass boilers, and green hydrogen. Two key indicators to measure decarbonization performance: the Decarbonization Efficiency Coefficient and the GHG Performance Indicator. Decarbonizing could significantly reduce energy use, depending on the selected technologies, leading to variations of 6.1 TWh for electricity and 3.5 TWh for biomass.

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]

Predicting the critical micelle concentration (CMC) of surfactants is essential for optimizing their applications in various industries, including pharmaceuticals, detergents, and emulsions. In this study, we investigate the per-formance of graph-based machine learning models, specifically Graph Convolutional Networks (GCN), Graph At-tention Networks (GAT), and a graph-transformer model, PharmHGT, for predicting CMC values. We aim to de-termine the most effective model for capturing the structural and physicochemical properties of surfactants. Our results provide insights into the relative strengths of each approach, highlighting the potential advantages of transformer-based architectures like PharmHGT in handling molecular graph representations compared to traditional graph neural networks. This comparative study serves as a step towards enhancing the accuracy of CMC predictions, contributing to the efficient design of surfactants for targeted applications.

This document contains digital supplementary material (characterization of the case-studies, developed simulation models (and final configurations), optimisation models and post-processing assessments) related to the article entitled “The Paradigm of Water and Energy Integration Systems (WEIS): Methodology and Performance Indicators”, which is part of the peer reviewed conference proceeding of the 35th European Symposium on Computer Aided Process Engineering (ESCAPE 35). 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".

Soybean is a highly valuable global commodity due to its versatility and numerous derivative products. During harvest, all non-seed materials become “straw”. Currently, this waste is pri-marily used for low-value purposes such as animal feed, landfilling, and incineration. To address this, the present work proposes a conceptual biorefinery aimed at converting soybean straw into higher-value products. The study began with data collection to identify potential conversion routes. Based on this information, a superstructure was developed, comprising seven conversion routes: four thermochemical routes (pyrolysis, combustion, hydrothermal gasification, and lique-faction), two biological routes (fermentation and anaerobic fermentation), and one chemical route (alkaline extraction). Each process was evaluated based on product yields, conversion times, and associated capital and operating costs. Using this data, an MILP (Mixed-Integer Linear Program-ming) optimization model was built in Pyomo u... [more]

The document is the digital supplementary material for the article titled "Closed-Loop Data-Driven Model Predictive Control For A Wet Granulation Process Of Continuous Pharmaceutical Tablet Production", submitted to the ESCAPE 35 conference. It contains the state-space equations, mathematical formulation, and additional figures.

The proposed model focuses on yields and several properties, such as octane number (ON) pre-dictions, in the gasoline production. External streams such as ethanol and methyl terc-butyl ether (MTBE) are imported to the petroleum refinery complementing the gasoline production when boosting ON quality; these imports are considered exogenous independent variables (IVs). On the other hand, numerous trade-offs exist inside the refinery walls (the endogenous IVs) when producing the so-called pure petroleum-refined gasoline (PPRG). These diverse manufacturing IVs (endogenous factors) interplaying with out-of-refinery walls or exogenous options such as ethanol blending and banning MTBE for sustainable liquid fuels are simulated and optimized in NLP problems, whereby linear approaches are proposed in the tailored modeling and optimiza-tion in the search for optimal solutions.

The escalating urgency to address climate change has driven carbon capture (CC) technologies into the spotlight, particularly for large-scale emitters, which benefit from economies of scale. However, small-scale emitters account for a significant share of CO2 emissions, yet such applica-tions remain largely overlooked in the literature. While CC cost is often used as a key perfor-mance indicator (KPI) for CC technologies, the lack of standardized cost estimation methods leads to inconsistencies, complicating comparisons, and hindering the deployment of CC sys-tems. This study addresses these challenges by developing flexible short-cut correlations for selected CC technologies, providing estimates of the total equipment cost (TEC) and energy consumption specific to small-scale applications across various CO2 inlet concentrations (mol%) and capture scales (10 – 100 kt/y). The flexibility of the correlations enables the integration of various cost estimation methods available in the liter... [more]

This document contains digital supplementary material (LCA model including parametrized LCI with sources, unit processes and LCA results) related to the article "Integrated LCA and Eco-design Process for Hydrogen Technologies: Case Study of the Solid Oxide Electrolyser" which is submitted to the peer reviewed conference proceeding of the 35th European Symposium on Computer Aided Process Engineering (ESCAPE 35).

The growing size and complexity of energy system optimization models, driven by high-resolution spatial data, pose significant computational challenges. This study introduces methods to reduce model’s size and improve computational efficiency while preserving solution accuracy. First, a composite-curve-based approach is proposed to aggregate granular data into larger resolutions without averaging out specific properties. Second, a general clustering method groups geographically proximate fields, replacing multiple transportation arcs with a single arc to reduce transportation-related variables. Lastly, a two-step algorithm that decomposes the sup-ply chain design problems into two smaller, more manageable subproblems is introduced. These methods are applied to a case study of switchgrass-to-biofuels network design in eight U.S. Midwest states, demonstrating their effectiveness with realistic and detailed spatial data.

This document contains supplementary materials for full-paper submission to ESCAPE 35 - European Symposium on Computer Aided Process Engineering.

This is an Aspen Plus V14 model of a furnace process. Natural gas is combusted in excess air to produce heat. A heat exchanger model simulates the boiling of boiler feed water near 29 bar pressure to produce steam at about 235 deg C. Design specs are used to ensure certain process conditions and scales are met. This is supplementary material for the paper Adams TA. Exergy in Chemical Engineering Education, submitted to the ESCAPE 35 conference.

Supplementary Material for the contribution "Synthesis of Distillation Flowsheets with Reinforcement Learning using Transformer Blocks" by Niklas Slager and Meik Franke (UTwente) for ESCAPE 35

The complete stochastic-based optimization model for the CSP-TCES-OFC and CSP-TCES-ASU processes are given here.

The transition to renewable energy sources, such as biogas, requires purification processes to separate methane from carbon dioxide, with adsorption-based methods being widely employed. Accurate simulations of these systems, governed by coupled PDEs, ODEs, and algebraic equations, critically depend on precise parameter determination. While traditional approaches often result in significant errors or complex procedures, optimization algorithms provide a more efficient and reliable means of parameter estimation, simplifying the process, improving simulation accuracy, and enhancing the understanding of these systems.
This work introduces an Artificial Intelligence-based methodology for estimating the isotherm parameters of a mathematical phenomenological model for fixed-bed experiments. The separation of CO₂ and CH₄ is used as case study. This work develops an algorithm for parameter estimation for the system's mathematical model. The results show that the validated model has a close fi... [more]

L-lactic acid (L-LA), a key monomer in biodegradable plastics, is a sustainable alternative that can be derived from LCB. The L-LA production process typically involves several various technologies such as fermentation, filtration, and distillation. In the L-LA production process, large amounts of buffers are used to maintain proper pH during fermentation, so conventional buffers (e.g., CaCO3) are often selected because of their low cost. However, these buffers cannot be recycled efficient-ly, and the potential for alternative buffers remains uncertain. In this work, we aim to develop and evaluate novel processes for sustainable L-LA production using the alternative buffer (i.e., KOH). The processes involve a series of different unit operations such as pretreatment, fermentation, ex-traction, and electrolysis. An efficient buffer regeneration process using membrane electrolysis is implemented to recycle the buffer with minimal energy input. Then, we evaluated the viability of the propo... [more]

Deploying engineered carbon dioxide removal strategies like direct air capture (DAC) will be
imperative to meet net-zero targets, given the biophysical constraints associated with land-based
methods. Thoroughly devised deployment pathways for DAC could ease the financial burdens of
adopting the technology at climate-relevant scales. Key drivers for the optimal regional rollouts of
DAC include the available energy supply and geological capacities for CO2 storage. These factors
also impose temporal constraints considering the evolving nature of energy systems and the
development of CO2 transport and storage infrastructure over time. As DAC technologies exhibit
differences in their system demands, integrating various methods into deployment strategies may
address potential trade-offs arising from regional resource endowments. Commercial-ready options
use solid sorbents or liquid solvents, while emerging methods extend to electrochemical devices
like bipolar membranes. These tech... [more]

The document is the digital supplementary material for the article titled "Application of Artificial Intelligence in process simulation tool", submitted to the ESCAPE 35 conference. It contains additional information and figures.

This model uses the CHEMCAD unit operation Batch Column together with tools for data reconciliation and optimization. Some experimental data is included.
It is used as a template in the course Green Processes at Berlin University of Applied Science (BHT), where students use it to regress measured data from lab experiments and to design an optimal process.

This model uses standard CHEMCAD unit operations and thermodynamic models to simulate the separation of ethanol and water from a fermenter broth.
It is used as a template in the course Green Processes at Berlin University of Applied Science (BHT), where students use it to regress measured data from lab experiments and to design an optimal process.

This model uses the kinetic model from Foglers textbook "Elements of Chemical Reaction Engineering" to describe the fermentation of glucose to ethanol.
It is used as a template in the course Green Processes at Berlin University of Applied Science (BHT), where students use it to regress measured data from lab experiments and to design an optimal process.

This document contains digital supplementary material (detailed model results and complete database) related to the article "A two-level model to assess the economic feasibility of renewable urea production from agricultural wastes" which is submitted to the peer reviewed conference proceedings of the 35th European Symposium on Computer Aided Process Engineering (ESCAPE 35).