All abstracts by Nikolaos Prasianakis in conference series: Goldschmidt

(2024) Insights into the Metastability of Amorphous Calcium Carbonate (ACC): Microfluidic Experiments Combined with an AI-Assisted Toolbox for Quantifying Mineral Transformations
Obaied A, Poonoosamy J, Peng H, Kaspor A, Bosbach D, Prasianakis N & Deissmann G

(2024) Accelerating Reactive Transport Simulations by Combining Machine Learning, Smart Algorithms and High Performance Computing
Prasianakis N, Baur M, Peng H, Mokos A & Churakov SV

(2024) Towards Digital Twins of Capillary Mass Diffusion Experiments: A Physics-Based Machine-Learning Framework for Inverse Modeling of Mass Transport Processes
Peng H, Rajyaguru A, Curti E, Grolimund D, Churakov SV & Prasianakis N

(2023) Towards Digital Twin of Carbonate Precipitation Experiments: An Integrated Physics-Based Machine-Learning Framework for Modeling of Reactive Transport Processes
Peng H, Rajyaguru A, Mokos A, Curti E, Grolimund D, Churakov SV & Prasianakis N

(2023) Pore-Level Modelling of Cement Paste Degradation due to Cement-Clay Interaction
Mokos A, Peng H, Miron GD, Kulik DA, Griffa M, Ma B, Prasianakis N & Churakov SV

(2023) Comparison of Physical Informed Neural Network and Other Machine Learning Methods for Simulating Heat Transport in a Nuclear Waste Disposal System
Hu G, Prasianakis N & Pfingsten W

(2020) Towards Digital Twins: Machine Learning Based Process Coupling and Multiscale Modelling of Reactive Transport Phenomena
Prasianakis N

(2019) Approaches for Porosity & Permeability Initialization in Continuum-Scale Reactive Transport Simulations
Mahrous M, Sultan A, Liao Q, Prasianakis N, Curti E & Churakov S

(2019) A Microfluidic Experiment and Pore Scale Modelling for Assessing Mineral Precipitation and Dissolution in Confined Spaces
Poonoosamy J, Deissmann G, Mahrous M, Curti E, Churakov S, Klinkenberg M, Bosbach D & Prasianakis N