Machine learning meets continuous flow chemistry: Automated optimization towards the Pareto front of multiple objectives AM Schweidtmann, AD Clayton, N Holmes, E Bradford, RA Bourne, ... Chemical Engineering Journal 352, 277-282, 2018 | 311 | 2018 |
Efficient multiobjective optimization employing Gaussian processes, spectral sampling and a genetic algorithm E Bradford, AM Schweidtmann, A Lapkin Journal of Global Optimization 71 (2), 407-438, 2018 | 256 | 2018 |
Correction to: Efficient multiobjective optimization employing Gaussian processes, spectral sampling and a genetic algorithm E Bradford, AM Schweidtmann, A Lapkin Journal of Global Optimization 71 (2), 439-440, 2018 | 256* | 2018 |
Deterministic global optimization with artificial neural networks embedded AM Schweidtmann, A Mitsos Journal of Optimization Theory and Applications 180 (3), 925-948, 2019 | 201 | 2019 |
Automated self-optimisation of multi-step reaction and separation processes using machine learning AD Clayton, AM Schweidtmann, G Clemens, JA Manson, CJ Taylor, ... Chemical Engineering Journal 384, 123340, 2020 | 129 | 2020 |
Machine learning in chemical engineering: A perspective AM Schweidtmann, E Esche, A Fischer, M Kloft, JU Repke, S Sager, ... Chemie Ingenieur Technik 93 (12), 2029-2039, 2021 | 128 | 2021 |
Machine learning and molecular descriptors enable rational solvent selection in asymmetric catalysis Y Amar, AM Schweidtmann, P Deutsch, L Cao, A Lapkin Chemical science 10 (27), 6697-6706, 2019 | 116 | 2019 |
Graph neural networks for prediction of fuel ignition quality AM Schweidtmann, JG Rittig, A Konig, M Grohe, A Mitsos, M Dahmen Energy & fuels 34 (9), 11395-11407, 2020 | 113 | 2020 |
Model-based bidding strategies on the primary balancing market for energy-intense processes P Schäfer, HG Westerholt, AM Schweidtmann, S Ilieva, A Mitsos Computers & Chemical Engineering 120, 4-14, 2019 | 69 | 2019 |
Deterministic global process optimization: Accurate (single-species) properties via artificial neural networks AM Schweidtmann, WR Huster, JT Lüthje, A Mitsos Computers & Chemical Engineering 121, 67-74, 2019 | 65 | 2019 |
Dynamic modeling and optimization of sustainable algal production with uncertainty using multivariate Gaussian processes E Bradford, AM Schweidtmann, D Zhang, K Jing, EA del Rio-Chanona Computers & Chemical Engineering 118, 143-158, 2018 | 65 | 2018 |
Rational design of ion separation membranes D Rall, D Menne, AM Schweidtmann, J Kamp, L von Kolzenberg, A Mitsos, ... Journal of Membrane Science 569, 209-219, 2019 | 63 | 2019 |
Multi-scale membrane process optimization with high-fidelity ion transport models through machine learning D Rall, AM Schweidtmann, M Kruse, E Evdochenko, A Mitsos, M Wessling Journal of Membrane Science 608, 118208, 2020 | 51 | 2020 |
Obey validity limits of data-driven models through topological data analysis and one-class classification AM Schweidtmann, JM Weber, C Wende, L Netze, A Mitsos Optimization and engineering 23 (2), 855-876, 2022 | 44 | 2022 |
Deterministic global optimization with Gaussian processes embedded AM Schweidtmann, D Bongartz, D Grothe, T Kerkenhoff, X Lin, J Najman, ... Mathematical Programming Computation 13 (3), 553-581, 2021 | 43 | 2021 |
Working fluid selection for organic rankine cycles via deterministic global optimization of design and operation WR Huster, AM Schweidtmann, A Mitsos Optimization and Engineering 21 (2), 517-536, 2020 | 43 | 2020 |
A Multiobjective Optimization Including Results of Life Cycle Assessment in Developing Biorenewables‐Based Processes D Helmdach, P Yaseneva, PK Heer, AM Schweidtmann, AA Lapkin ChemSusChem 10 (18), 3632-3643, 2017 | 42 | 2017 |
Simultaneous rational design of ion separation membranes and processes D Rall, AM Schweidtmann, BM Aumeier, J Kamp, J Karwe, K Ostendorf, ... Journal of Membrane Science 600, 117860, 2020 | 41 | 2020 |
Techno-economic Optimization of a Green-Field Post-Combustion CO2 Capture Process Using Superstructure and Rate-Based Models U Lee, J Burre, A Caspari, J Kleinekorte, AM Schweidtmann, A Mitsos Industrial & Engineering Chemistry Research 55 (46), 12014-12026, 2016 | 38 | 2016 |
Chemical data intelligence for sustainable chemistry JM Weber, Z Guo, C Zhang, AM Schweidtmann, AA Lapkin Chemical Society Reviews 50 (21), 12013-12036, 2021 | 33 | 2021 |