Review of machine learning for hydrodynamics, transport, and reactions in multiphase flows and reactors
Artificial intelligence (AI), machine learning (ML), and data science are leading to a
promising transformative paradigm. ML, especially deep learning and physics-informed ML …
promising transformative paradigm. ML, especially deep learning and physics-informed ML …
[HTML][HTML] Science-based, data-driven developments in plasma processing for material synthesis and device-integration technologies
M Kambara, S Kawaguchi, HJ Lee… - Japanese Journal of …, 2022 - iopscience.iop.org
Low-temperature plasma-processing technologies are essential for material synthesis and
device fabrication. Not only the utilization but also the development of plasma-related …
device fabrication. Not only the utilization but also the development of plasma-related …
Optimization of a vertical axis wind turbine with a deflector under unsteady wind conditions via Taguchi and neural network applications
Vertical axis wind turbines (VAWTs), so named because of their vertical axis of rotation, are
a sustainable, opportune, and versatile means of producing energy. Their operation is not …
a sustainable, opportune, and versatile means of producing energy. Their operation is not …
Combining computational fluid dynamics, photon fate simulation and machine learning to optimize continuous-flow photocatalytic systems
Photoredox catalysis is a well-established area with great potential for industrial
applications. The need for an optimum process with less waste generation and economic …
applications. The need for an optimum process with less waste generation and economic …
Rapid monitoring of indoor air quality for efficient HVAC systems using fully convolutional network deep learning model
S Shin, K Baek, H So - Building and Environment, 2023 - Elsevier
Indoor air quality (IAQ) monitoring technology is crucial for achieving optimized heating,
ventilation, and air conditioning (HVAC) strategies for efficient energy management. In this …
ventilation, and air conditioning (HVAC) strategies for efficient energy management. In this …
Materials processing model-driven discovery framework for porous materials using machine learning and genetic algorithm: A focus on optimization of permeability …
T Yasuda, S Ookawara, S Yoshikawa… - Chemical Engineering …, 2023 - Elsevier
This study proposes a material discovery framework for porous materials to identify design
variable recipes and the corresponding material structures that can be utilized to improve …
variable recipes and the corresponding material structures that can be utilized to improve …
Physics-informed deep learning for multi-species membrane separations
D Rehman, JH Lienhard - Chemical Engineering Journal, 2024 - Elsevier
Conventional continuum models for ion transport across polyamide membranes require
solving partial differential equations (PDEs). These models typically introduce a host of …
solving partial differential equations (PDEs). These models typically introduce a host of …
Intensification of catalytic reactors: a synergic effort of multiscale modeling, machine learning and additive manufacturing
M Bracconi - Chemical Engineering and Processing-Process …, 2022 - Elsevier
The intensification of catalytic reactors is expected to play a crucial role to address the
challenges that the chemical industry is facing in the transition to more sustainable …
challenges that the chemical industry is facing in the transition to more sustainable …
From computational fluid dynamics to structure interpretation via neural networks: an application to flow and transport in porous media
The modeling of flow and transport in porous media is of the utmost importance in many
chemical engineering applications, including catalytic reactors, batteries, and CO2 storage …
chemical engineering applications, including catalytic reactors, batteries, and CO2 storage …
[HTML][HTML] Prediction of local concentration fields in porous media with chemical reaction using a multi scale convolutional neural network
The study of solute transport in porous media is of interest in many chemical engineering
systems. Some example applications include packed bed catalytic reactors, filtration …
systems. Some example applications include packed bed catalytic reactors, filtration …