publicações selecionadas
- Optimal fragrances formulation using a deep learning neural network architecture: a novel systematic approach.
- Machine Learning-Based Dynamic Modeling for Process Engineering Applications: A Guideline for Simulation and Prediction from Perceptron to Deep Learning
- Transient Analysis of True/Simulated Moving Bed Reactors: A Case Study on the Synthesis of n-Propyl Propionate
- Abnormal Operation Tracking through Big-Data-Based Gram-Schmidt Orthogonalization: Production of -Propyl Propionate in a Simulated Moving-Bed Reactor: A Case Study
- Using scientific machine learning to develop universal differential equation for multicomponent adsorption separation systems
- A novel nested loop optimization problem based on deep neural networks and feasible operation regions definition for simultaneous material screening and process optimization
- Dynamics of a True Moving Bed Reactor: Synthesis of n-Propyl Propionate and an alternative optimization method
- Mapping Uncertainties of Soft-Sensors Based on Deep Feedforward Neural Networks through a Novel Monte Carlo Uncertainties Training Process
- A First Approach towards Adsorption-Oriented Physics-Informed Neural Networks: Monoclonal Antibody Adsorption Performance on an Ion-Exchange Column as a Case Study