| Nielsen |
2020 |
Hybrid machine learning assisted modelling framework for particle processes |
Data driven – deep neural network (soft sensor) |
| Mechanistic – PBM |
| Lima |
2022 |
Development of a recurrent neural networks-based NMPC for controlling the concentration of a crystallization process |
Data driven – RNN |
| Mechanistic – PBM embedded in NMPC |
| Zheng |
2022 |
Machine learning modeling and predictive control of the batch crystallization process |
Data driven – RNN and autoencoder–RNN (AERNN) |
| Mechanistic – PBM |
| Wu |
2023 |
Physics-informed machine learning for MPC: application to a batch crystallization process |
Data driven – RNN |
| Mechanistic – PBM (as a system of ordinary differential equations) |
| Lima |
2023 |
Improved modeling of crystallization processes by universal differential equations |
Data driven – RNN/UDE |
| Mechanistic – PBM |
| Tadepalli |
2023 |
A crystallization case study toward optimization of expensive to evaluate mathematical models using Bayesian approach |
Data driven – MOBO (Gaussian process) |
| Mechanistic – PBM |
| Kovacs |
2023 |
A synthetic machine learning framework for complex crystallization processes: the case study of the second-order asymmetric transformation of enantiomers |
Data driven – decision tree random forest classifiers |
| Mechanistic – PBM |
| Ma |
2024 |
Digital design of cooling crystallization processes using a machine learning-based strategy |
Data driven – NN predictive model |
| Mechanistic – mechanistic equations and underlying theory |
| Lima |
2024 |
Neural-network inverse model controllers for paracetamol unseeded batch cooling crystallization |
Data driven – NN inverse model |
| Mechanistic – PBM based NLMPC |
| Dong, Y. |
2025 |
Neural network-based kinetic model for antisolvent crystallization of benzophenone |
Data driven – NN |
| Mechanistic – PBM |
| Ali |
2025 |
Data-driven machine learning approach based on physics-informed neural network for PBM |
Data driven – PINN |
| Mechanistic – PBM |
| Pahari |
2025 |
Predicting both thermodynamic and kinetic properties of crystallizing molecules via transformer-based language model |
Data driven – encoder based transformer models and NN |
| Mechanistic – PBM |
