Publications of Edgar Ivan Sanchez Medina
All genres
Journal Article (6)
1.
Journal Article
495, 153524 (2024)
Machine learning-supported solvent design for lignin-first biorefineries and lignin upgrading. Chemical Engineering Journal 2.
Journal Article
Towards Digital Twins for Power-to-X Processes: Comparing Surrogate Models for a Catalytic CO2 Methanation Reactor. IEEE Transactions on Automation Science and Engineering (2024)
3.
Journal Article
127, pp. 9863 - 9873 (2023)
Gibbs–Helmholtz Graph Neural Network for the Prediction of Activity Coefficients of Polymer Solutions at Infinite Dilution. The Journal of Physical Chemistry A 4.
Journal Article
2 (3), pp. 781 - 798 (2023)
Gibbs–Helmholtz graph neural network: capturing the temperature dependency of activity coefficients at infinite dilution. Digital Discovery 5.
Journal Article
1 (3), pp. 216 - 225 (2022)
Graph neural networks for the prediction of infinite dilution activity coefficients. Digital Discovery 6.
Journal Article
92 (7), pp. 842-855 - 855 (2020)
Hybrid Semi‐parametric Modeling in Separation Processes: A Review. Chemie Ingenieur Technik Conference Paper (4)
7.
Conference Paper
A symbolic regression based methodology for the construction of interpretable and predictive thermodynamic models. In: 34th European Symposium on Computer Aided Process Engineering / 15th International Symposium on Process Systems Engineering, pp. 2701 - 2706 (Eds. Manenti, F.; Reklaitis, G. V.). 34th European Symposium on Computer Aided Process Engineering / 15th International Symposium on Process Systems Engineering, Florence, Italy, June 02, 2024 - June 06, 2024. Elsevier, Amsterdam/Netherlands (2024)
8.
Conference Paper
52, pp. 2037 - 2042 (Eds. Kokossis, A.; Georgiadis, M.C.; Pistikopoulos, E.). 33rd European Symposium on Computer Aided Process Engineering, Athen, Greece, June 18, 2023 - June 21, 2023. Elsevier, Amsterdam/Netherlands (2023)
Solvent pre-selection for extractive distillation using Gibbs-Helmholtz Graph Neural Networks. In: 33rd European Symposium on Computer Aided Process Engineering, Vol. 9.
Conference Paper
Prediction of Bioconcentration Factors (BCF) using Graph Neural Networks. In: 31st European Symposium on Computer Aided Process Engineering, pp. 991 - 997 (Eds. Türkay, M.; Gani, R.). 31st European Symposium on Computer Aided Process Engineering, Istanbul, Turkey/virtual, June 06, 2021 - June 09, 2021. Elsevier, Amsterdam, Netherlands (2021)
10.
Conference Paper
Acyclic modular flowsheet optimization using multiple trust regions and Gaussian process regression. In: 31st European Symposium on Computer Aided Process Engineering, pp. 1117 - 1123 (Eds. Türkay, M.; Gani, R.). 31st European Symposium on Computer Aided Process Engineering, Istanbul, Turkey/virtual, June 06, 2021 - June 09, 2021. Elsevier, Amsterdam, Netherlands (2021)
Talk (9)
11.
Talk
Comparing Surrogate Models for Real-Time Dynamic Reactor Simulations. Digital Twins in Engineering 2025, Paris, France (accepted)
12.
Talk
A symbolic regression based methodology for the construction of interpretable and predictive thermodynamic models. ESCAPE-34, Florence, Italy (2024)
13.
Talk
PSEvolve: A graph-based solvent design framework. ESCAPE34 , Florence, Italy (2024)
14.
Talk
A Comparison of the UNIFAC Model vs. Graph Neural Network-based Models for the Prediction of Binary Vapor-Liquid Equilibria. 33rd European Symposium on Applied Thermodynamics 2024, Edinburgh, UK (2024)
15.
Talk
Tailored solvent design for lignin dissolution using graph neural networks. ECCE 14 & ECAB 7: 14th European Congress of Chemical Engineering and 7th European Congress of Applied Biotechnology, Berlin, Germany (2023)
16.
Talk
An introductory course of machine learning for chemical engineering students: a prototype. WCCE11 - 11th WORLD CONGRESS OF CHEMICAL ENGINEERING, Buenos Aires, Argentina (2023)
17.
Talk
Predicting activity coefficients at infinite dilution of polymer solutions using Graph Neural Networks. WCCE11 - 11th WORLD CONGRESS OF CHEMICAL ENGINEERING, Buenos Aires, Argentina (2023)
18.
Talk
Solvent pre-selection for extractive distillation using Gibbs-Helmholtz Graph Neural Networks. ESCAPE-33, Athens, Greece (2023)
19.
Talk
Multi-Objective Bayesian optimization of process flowsheets using trust regions and quality set metrics. 2021 AIChE Annual Meeting, Virtual (2021)
Poster (7)
20.
Poster
BOHO CAT - Bayesian Optimization for Low Throughput Ligand Selection in Homogeneous Catalysis. Cambridge ELLIS Unit Summer School 2024, Cambridge, UK (2024)