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A First Approach towards Adsorption-Oriented Physics-Informed Neural Networks: Monoclonal Antibody Adsorption Performance on an Ion-Exchange Column as a Case Study.
- Published in:
- ChemEngineering, 2022, v. 6, n. 2, p. 21, doi. 10.3390/chemengineering6020021
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- Article
Improved modeling of crystallization processes by Universal Differential Equations.
- Published in:
- Chemical Engineering Research & Design: Transactions of the Institution of Chemical Engineers Part A, 2023, v. 200, p. 538, doi. 10.1016/j.cherd.2023.11.032
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- Article
A novel nested loop optimization problem based on deep neural networks and feasible operation regions definition for simultaneous material screening and process optimization.
- Published in:
- Chemical Engineering Research & Design: Transactions of the Institution of Chemical Engineers Part A, 2022, v. 180, p. 243, doi. 10.1016/j.cherd.2022.02.013
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- Article
Using scientific machine learning to develop universal differential equation for multicomponent adsorption separation systems.
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- Canadian Journal of Chemical Engineering, 2022, v. 100, n. 9, p. 2279, doi. 10.1002/cjce.24495
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- Article
Mapping Uncertainties of Soft-Sensors Based on Deep Feedforward Neural Networks through a Novel Monte Carlo Uncertainties Training Process.
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- Processes, 2022, v. 10, n. 2, p. 409, doi. 10.3390/pr10020409
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- Article
Machine Learning-Based Dynamic Modeling for Process Engineering Applications: A Guideline for Simulation and Prediction from Perceptron to Deep Learning.
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- Processes, 2022, v. 10, n. 2, p. 250, doi. 10.3390/pr10020250
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- Article
A Hybrid Modeling Framework for Membrane Separation Processes: Application to Lithium-Ion Recovery from Batteries.
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- Processes, 2021, v. 9, n. 11, p. 1939, doi. 10.3390/pr9111939
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- Article
A Reinforcement Learning Framework to Discover Natural Flavor Molecules.
- Published in:
- Foods, 2023, v. 12, n. 6, p. 1147, doi. 10.3390/foods12061147
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- Article