| A brief introduction to chemical reaction optimization CJ Taylor, A Pomberger, KC Felton, R Grainger, M Barecka, ... Chemical Reviews 123 (6), 3089-3126, 2023 | 158 | 2023 |
| Automated microfluidic platform for systematic studies of colloidal perovskite nanocrystals: towards continuous nano-manufacturing RW Epps, KC Felton, CW Coley, M Abolhasani Lab on a Chip 17 (23), 4040-4047, 2017 | 146 | 2017 |
| Summit: benchmarking machine learning methods for reaction optimisation KC Felton, JG Rittig, AA Lapkin Chemistry‐Methods 1 (2), 116-122, 2021 | 89 | 2021 |
| Optimization of formulations using robotic experiments driven by machine learning DoE L Cao, D Russo, K Felton, D Salley, A Sharma, G Keenan, W Mauer, ... Cell Reports Physical Science 2 (1), 2021 | 58 | 2021 |
| Accelerated chemical reaction optimization using multi-task learning CJ Taylor, KC Felton, D Wigh, MI Jeraal, R Grainger, G Chessari, ... ACS Central Science 9 (5), 957-968, 2023 | 46 | 2023 |
| DeepGamma: A deep learning model for activity coefficient prediction KC Felton, H Ben-Safar, AA Alexei 1st Annual AAAI Workshop on AI to Accelerate Science and Engineering (AI2ASE), 2022 | 14 | 2022 |
| Gibbs–Duhem-informed neural networks for binary activity coefficient prediction JG Rittig, KC Felton, AA Lapkin, A Mitsos Digital Discovery 2 (6), 1752-1767, 2023 | 12 | 2023 |
| Multi-task Bayesian optimization of chemical reactions K Felton, D Wigh, A Lapkin | 8 | 2020 |
| A modular microfluidic technology for systematic studies of colloidal semiconductor nanocrystals RW Epps, KC Felton, CW Coley, M Abolhasani JoVE (Journal of Visualized Experiments), e57666, 2018 | 8 | 2018 |
| Multi-objective Bayesian optimisation using q-noisy expected hypervolume improvement (q NEHVI) for the Schotten–Baumann reaction J Zhang, N Sugisawa, KC Felton, S Fuse, AA Lapkin Reaction Chemistry & Engineering 9 (3), 706-712, 2024 | 7 | 2024 |
| ORDerly: Data Sets and Benchmarks for Chemical Reaction Data DS Wigh, J Arrowsmith, A Pomberger, KC Felton, AA Lapkin Journal of Chemical Information and Modeling 64 (9), 3790-3798, 2024 | 5 | 2024 |
| ML-SAFT: a machine learning framework for PCP-SAFT parameter prediction KC Felton, L Raßpe-Lange, JG Rittig, K Leonhard, A Mitsos, ... Chemical Engineering Journal 492, 151999, 2024 | 4 | 2024 |
| Transfer Learning for Accelerated Process Development K Felton University of Cambridge, 2023 | 2 | 2023 |
| Thermodynamics-Informed Graph Neural Networks for Predicting Molecular and Mixture Properties JG Rittig, K Felton, AA Lapkin, A Mitsos 2024 AIChE Annual Meeting, 2024 | | 2024 |
| Devices and methods of use thereof M Abolhasani, KC FELTON US Patent 11,499,948, 2022 | | 2022 |
| Kolloidal yarı iletken Nanocrystals sistematik çalışmalar için modüler bir mikrosıvısal teknolojisi RW Epps, KC Felton, CW Coley, M Abolhasani Journal of Visualized Experiments (JoVE), e57666, 2018 | | 2018 |
| High Throughput Screening Platform for Cesium-Lead Perovskite Nanocrystal Synthesis K Felton, R Epps, C Coley, M Abolhasani 2017 AIChE Annual Meeting, 2017 | | 2017 |
Alexei LapkinUniversity of CambridgePreverjeni e-poštni naslov na cam.ac.uk
