Want to create interactive content? It’s easy in Genially!
Copy - NTNU AI day
Idelfonso Bessa
Created on March 14, 2024
Start designing with a free template
Discover more than 1500 professional designs like these:
Transcript
Machine Learning as a Bridge: Enhanced High-Throughput Materials Screening Considering Application Scale
All-FACET Meeting
Associate Professor in Process Systems EngineeringDepartment of Chemical Engineeringidelfonso.b.d.r.nogueira@ntnu.no +47 73592399 Kjemi 4, 232, Gløshaugen
A short tal by Idelfonso Nogueira
15
L4
L3
L2
L1
Concise Integration: Developing a new standpoint of Chemical Engineering
Bridging two scales L1+L2
X High computational cost
High predictive capacity for several systems
X Limited to the system in analysis
X Time demanding
Reliable
Modeling
Estimation
Ab initio molecular simulations
Experimental approach
Bridging two scales L1+L2
14
Encoding molecular and materials structures.
Creating a data base.
Challenges
Reverse Engineering is easier, i.e., generative models.
Advantages
Molecular strucutures can be encoded as inputs
If ML is used, only computational resources are used to build the data base
Approach Ongoing Research
Bridging two scales L1+L2
Bridging two scales L1+L2
General database
Bridging two scales L1+L2
Bridging two scales L1+L2
Bridging two scales L1+L2
Bridging two scales L1+L2
Generative Neural Networks + Reinforcement learning + Process Scale
Bridging three scales
Generative Neural Networks + Reinforcement learning + Process Scale
Bridging three scales
Generative Neural Networks + Reinforcement learning + Process Scale
Bridging three scales
L2
Process Design & Modeling
L1
FundamentalScale
15
Idelfonso Nogueira Associate Professor Department of Chemical Engineering Process Systems Engineering Research Group idelfonso.b.d.r.nogueira@ntnu.no +47 73592399 Kjemi 4, 232, Gløshaugen
Let's discuss these topics Please feel free to ask or to get in touch!