Background Information: 

Donovan Chaffart is an assistant professor at the Eastern Institute of Technology (EIT)’s College of Engineering in Ningbo, China. Originating from Canada, he obtained his BASc in Nanotechnology Engineering, as well as his MASc and PhD in Chemical Engineering, from the University of Waterloo, before joining EIT as a PI. His research predominantly consists of computational simulations, numerical modelling, and AI investigations and implementations within Chemical Engineering. In particular, Dr. Chaffart is interested in improving the reliability and trustworthiness of AI in Chemical Engineering applications. Furthermore, he is interested in the development and implementation of novel modelling approaches to various Chemical Engineering systems, such as the Moving Front kinetic Monte Carlo algorithm he developed to capture moving interface systems.

Research Field:

Reliable AI Applications in Chemical Engineering: Transparency Exploration and Analysis

Physics-informed Hybrid Multiscale Modelling in Chemical Engineering Applications

Physics-informed AI for Molecular-Scale Modelling Applications

Model Development for Molecular-Scale and Multiscale Modeling Applications

Multiscale & Hybrid Modelling for Sessile Droplet Spreading and Superhydrophobic Surface Development

Moving Front kinetic Monte Carlo Simulations of Moving Interface Systems

AI Implementation for Uncertainty Propagation and Robust Optimization of Multiscale Systems

Educational Background:

2018-2023: PhD (Majoring in Chemical Engineering), Department of Chemical Engineering, University of Waterloo 

2017: Masters of Applied Science (Majoring in Chemical Engineering), Department of Chemical Engineering, University of Waterloo

2011-2016: Bachelors of Applied Science (Majoring in Nanotechnology Engineering), Departments of Chemical Engineering, Electrical and Computer Engineering, and Chemistry, University of Waterloo

Work Experience:

2023-Present: Assistant Professor, College of Engineering, Eastern Institute of Technology, Ningbo

2015: Simulation Designer & Research Assistant, Department of Chemical Engineering, University of Waterloo 

2013-2014: Laboratory Engineering Research Assistant, Kingston Process Engineering Inc.

Academic Part-time Jobs (Partial):

Peer reviewer for Materials Letters

Representative Works:

General Information

13+ SCI Papers

Google Scholar:

https://scholar.google.ca/citations?user=MzJ8q0kAAAAJ&hl=en&oi=ao

Web of Science:

https://www.webofscience.com/wos/author/record/JDM-4158-2023

10 Representative Works (* refers to the corresponding author)

• D. Chaffart, L. A. Ricardez-Sandoval*, “A Moving Front Kinetic Monte Carlo Approach to Model Sessile Droplet Spreading on Superhydrophobic Surfaces.” Chemical Engineering Science, 280: 119006 (2023)

• D. Chaffart, S. Shi, C. Ma, C. Lv, L. A. Ricardez-Sandoval*, “A Semi-Empirical Force Balance-based Model to Capture Sessile Droplet Spread on Smooth Surfaces: A Moving Front Kinetic Monte Carlo Study.” Physics of Fluids, 35 no. 3: 032109 (2023)

• D. Chaffart, S. Shi, C. Ma, C. Lv, L. A. Ricardez-Sandoval*, “A Moving Front kinetic Monte Carlo algorithm for moving interface systems.” Journal of Physical Chemistry B 126, no. 9: 2040-2059 (2022)

• D. Chaffart, L. A. Ricardez-Sandoval*, “A three dimensional kinetic Monte Carlo defect-free crystal dissolution model for biological systems, with application to uncertainty analysis and robust optimization.” Computers & Chemical Engineering 157: 107586 (2022) 

• Y. Guan, D. Chaffart, G. Liu, Z. Tan, D. Zhang, Y. Wang, J. Li*, L. A. Ricardez-Sandoval*, “Machine learning in solid heterogeneous catalysis: Recent developments, challenges and perspectives.” Chemical Engineering Science 248: 117224 (2022)

• G. Kimaev, D. Chaffart, L. A. Ricardez-Sandoval*, “Multilevel Monte Carlo applied for uncertainty quantification in stochastic multiscale systems.” AIChE Journal 66, no. 8: e16262 (2020)

• H. Wang, D. Chaffart, L. A. Ricardez-Sandoval*, “Modelling and optimization of a pilot-scale entrained-flow gasifier using artificial neural networks.” Energy 188: 116076 (2019)

• D. Chaffart, L. A. Ricardez-Sandoval*, “Optimization and control of a thin film growth process: A hybrid first principles/artificial neural network based multiscale modelling approach.” Computers & Chemical Engineering 119: 465–479 (2018)  

• D. Chaffart, L. A. Ricardez-Sandoval*, “Robust optimization of a multiscale heterogeneous catalytic reactor system with spatially-varying uncertainty descriptions using polynomial chaos expansions.” Canadian Journal of Chemical Engineering 96, no. 1: 113–131 (2018)

• D. Chaffart, L. A. Ricardez-Sandoval*, “Robust dynamic optimization in heterogeneous multiscale catalytic flow reactors using polynomial chaos expansion.” Journal of Process Control 60: 128–140 (2017)