Manuel Dahmen
Manuel Dahmen
IEK-10 Energy Systems Engineering at Forschungszentrum Jülich
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Cited by
Cited by
Tailor-made fuels for future engine concepts
F Hoppe, B Heuser, M Thewes, F Kremer, S Pischinger, M Dahmen, ...
International Journal of Engine Research 17 (1), 16-27, 2016
A novel group contribution method for the prediction of the derived cetane number of oxygenated hydrocarbons
M Dahmen, W Marquardt
Energy & Fuels 29 (9), 5781-5801, 2015
Graph neural networks for prediction of fuel ignition quality
AM Schweidtmann, JG Rittig, A König, M Grohe, A Mitsos, M Dahmen
Energy & Fuels 34 (9), 11395-11407, 2020
Model-based design of tailor-made biofuels
M Dahmen, W Marquardt
Energy & Fuels 30 (2), 1109-1134, 2016
Model-Based Formulation of Biofuel Blends by Simultaneous Product and Pathway Design
M Dahmen, W Marquardt
Energy & Fuels 31 (4), 4096-4121, 2017
COMANDO: A Next-Generation Open-Source Framework for Energy Systems Optimization
M Langiu, DY Shu, FJ Baader, D Hering, U Bau, A Xhonneux, D Müller, ...
Computers & Chemical Engineering 152, 107366, 2021
Decarbonizing copper production by power-to-hydrogen: A techno-economic analysis
FTC Röben, N Schöne, U Bau, MA Reuter, M Dahmen, A Bardow
Journal of Cleaner Production 306, 127191, 2021
Electrochemical cross-coupling of biogenic di-acids for sustainable fuel production
FJ Holzhäuser, G Creusen, G Moos, M Dahmen, A König, J Artz, ...
Green Chemistry 21 (9), 2334-2344, 2019
Graph neural networks for temperature-dependent activity coefficient prediction of solutes in ionic liquids
JG Rittig, KB Hicham, AM Schweidtmann, M Dahmen, A Mitsos
Computers & Chemical Engineering 171, 108153, 2023
Integrated design of processes and products: Optimal renewable fuels
A König, L Neidhardt, J Viell, A Mitsos, M Dahmen
Computers & Chemical Engineering 134, 106712, 2020
Towards Model-Based Identification of Biofuels for Compression Ignition Engines
M Dahmen, M Hechinger, JV Villeda, W Marquardt
SAE International Journal of Fuels and Lubricants 5 (3), 990-1003, 2012
Multivariate probabilistic forecasting of intraday electricity prices using normalizing flows
E Cramer, D Witthaut, A Mitsos, M Dahmen
Applied Energy 346, 121370, 2023
Integrated design of renewable fuels and their production processes: recent advances and challenges
A König, W Marquardt, A Mitsos, J Viell, M Dahmen
Current Opinion in Chemical Engineering 27, 45-50, 2020
Toward co-optimization of renewable fuel blend production and combustion in ultra-high efficiency SI engines
P Burkardt, T Ottenwälder, A König, J Viell, A Mitsos, C Wouters, ...
International Journal of Engine Research 24 (1), 29-41, 2023
Designing production-optimal alternative fuels for conventional, flexible-fuel, and ultra-high efficiency engines
A König, M Siska, AM Schweidtmann, JG Rittig, J Viell, A Mitsos, ...
Chemical Engineering Science 237, 116562, 2021
Physical pooling functions in graph neural networks for molecular property prediction
AM Schweidtmann, JG Rittig, JM Weber, M Grohe, M Dahmen, ...
Computers & Chemical Engineering 172, 108202, 2023
The demand response potential in copper production
FTC Röben, D Liu, MA Reuter, M Dahmen, A Bardow
Journal of Cleaner Production 362, 132221, 2022
Towards model-based design of biofuel value chains
JJV Villeda, M Dahmen, M Hechinger, A Voll, W Marquardt
Current Opinion in Chemical Engineering 1 (4), 465-471, 2012
Graph Neural Networks for the Prediction of Molecular Structure–Property Relationships
JG Rittig, Q Gao, M Dahmen, A Mitsos, AM Schweidtmann
Graph machine learning for design of high‐octane fuels
JG Rittig, M Ritzert, AM Schweidtmann, S Winkler, JM Weber, P Morsch, ...
AIChE Journal 69 (4), e17971, 2023
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