| Life cycle assessment for the design of chemical processes, products, and supply chains J Kleinekorte, L Fleitmann, M Bachmann, A Kätelhön, A Barbosa-Póvoa, ... Annual review of chemical and biomolecular engineering 11, 203-233, 2020 | 72 | 2020 |
| COSMO-CAMD: A framework for optimization-based computer-aided molecular design using COSMO-RS J Scheffczyk, L Fleitmann, A Schwarz, M Lampe, A Bardow, K Leonhard Chemical Engineering Science 159, 84-92, 2017 | 70 | 2017 |
| COSMO-CAMPD: a framework for integrated design of molecules and processes based on COSMO-RS J Scheffczyk, P Schäfer, L Fleitmann, J Thien, C Redepenning, ... Molecular Systems Design & Engineering 3 (4), 645-657, 2018 | 45 | 2018 |
| Rx-COSMO-CAMD: computer-aided molecular design of reaction solvents based on predictive kinetics from quantum chemistry C Gertig, L Kröger, L Fleitmann, J Scheffczyk, A Bardow, K Leonhard Industrial & Engineering Chemistry Research 58 (51), 22835-22846, 2019 | 29 | 2019 |
| COSMO-susCAMPD: Sustainable solvents from combining computer-aided molecular and process design with predictive life cycle assessment L Fleitmann, J Kleinekorte, K Leonhard, A Bardow Chemical Engineering Science 245, 116863, 2021 | 14 | 2021 |
| Rx‐COSMO‐CAMPD: Enhancing reactions by integrated computer‐aided design of solvents and processes based on quantum chemistry C Gertig, L Fleitmann, J Schilling, K Leonhard, A Bardow Chemie Ingenieur Technik 92 (10), 1489-1500, 2020 | 14 | 2020 |
| In-tegrated design of solvents in hybrid reaction-separation processes using COSMO-RS L Fleitmann, J Scheffczyk, P Schäfer, C Jens, K Leonhard, A Bardow Chem. Eng 69, 2018 | 10 | 2018 |
| CAT-COSMO-CAMPD: Integrated in silico design of catalysts and processes based on quantum chemistry C Gertig, L Fleitmann, C Hemprich, J Hense, A Bardow, K Leonhard Computers & Chemical Engineering 153, 107438, 2021 | 9 | 2021 |
| Ultimate reaction selectivity limits for intensified reactor–separators JA Frumkin, L Fleitmann, MF Doherty Industrial & Engineering Chemistry Research 58 (15), 6042-6048, 2018 | 7 | 2018 |
| Optimal experimental design of physical property measurements for optimal chemical process simulations L Fleitmann, J Pyschik, L Wolff, J Schilling, A Bardow Fluid phase equilibria 557, 113420, 2022 | 5 | 2022 |
| APPROPRIATE Life Cycle Assessment: A PROcess-Specific, PRedictive Impact AssessmenT Method for Emerging Chemical Processes J Kleinekorte, J Kleppich, L Fleitmann, V Beckert, L Blodau, A Bardow ACS Sustainable Chemistry & Engineering 11 (25), 9303-9319, 2023 | 4 | 2023 |
| Molecular Design of Fuels for Maximum Spark-Ignition Engine Efficiency by Combining Predictive Thermodynamics and Machine Learning L Fleitmann, P Ackermann, J Schilling, J Kleinekorte, JG Rittig, ... Energy & Fuels 37 (3), 2213-2229, 2023 | 4 | 2023 |
| Integrated In Silico design of catalysts and processes based on quantum chemistry C Gertig, L Fleitmann, C Hemprich, J Hense, A Bardow, K Leonhard Computer Aided Chemical Engineering 48, 889-894, 2020 | 4 | 2020 |
| From molecules to heat‐integrated processes: computer‐aided design of solvents and processes using quantum chemistry L Fleitmann, C Gertig, J Scheffczyk, J Schilling, K Leonhard, A Bardow Chemie Ingenieur Technik 95 (3), 368-380, 2023 | 3 | 2023 |
| Making more from bio-based platforms: life cycle assessment and techno-economic analysis of N-vinyl-2-pyrrolidone from succinic acid MO Haus, B Winter, L Fleitmann, R Palkovits, A Bardow Green Chemistry 24 (17), 6671-6684, 2022 | 3 | 2022 |
| Computer-aided molecular design by combining genetic algorithms and COSMO-RS J Scheffczyk, L Fleitmann, A Schwarz, A Bardow, K Leonhard Computer Aided Chemical Engineering 38, 115-120, 2016 | 3 | 2016 |
| Optimal physical property data for process simulations by optimal experimental design L Fleitmann, J Pyschik, L Wolff, A Bardow Computer Aided Chemical Engineering 50, 851-857, 2021 | 2 | 2021 |
| Predictive Life Cycle Assessment with Limited Training Data: Artificial Neural Networks Vs. Gaussian Process Regression J Kleinekorte, V Beckert, L Fleitmann, L Kröger, K Leonhard, A Bardow 2020 Virtual AIChE Annual Meeting, 2020 | 1 | 2020 |
| Combining process short cuts and artificial neural networks for predictive life cycle assessment of chemicals J Kleinekorte, M Welz, LHJ Fleitmann, LC Kröger, K Leonhard, A Bardow Foundations of Process Analytics and Machine learning (FOPAM 2019), 2019 | 1 | 2019 |
| Energieeffizienz vs. Umweltauswirkungen: Integration von Molekül‐und Prozessdesign mit prädiktiver Ökobilanzierung J Kleinekorte, L Fleitmann, J Scheffczyk, A Bardow Chemie Ingenieur Technik 90 (9), 1163-1163, 2018 | 1 | 2018 |
