Minireview on Porous Media and Microstructure Reconstruction Using Machine Learning Techniques: Recent Advances and Outlook

No abstract is available for this paper.

• Publication year

  2023

• Venue

  Energy & Fuels

• Publication date

  2023-09-27

• Fields of study

  Not labeled

• Identifiers
  DOI 10.1021/acs.energyfuels.3c02126
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• A state-of-the-art review of experimental and computational studies of granular materials: Properties, advances, challenges, and future directions

  2023cited by this paper
• Recent Advances in Multiscale Digital Rock Reconstruction, Flow Simulation, and Experiments during Shale Gas Production

  2023cited by this paper
• Review of Shale Gas Transport Prediction: Basic Theory, Numerical Simulation, Application of AI Methods, and Perspectives

  2023cited by this paper
• U-Net model for multi-component digital rock modeling of shales based on CT and QEMSCAN images

  2022cited by this paper
• Data-driven modeling of process, structure and property in additive manufacturing: A review and future directions

  2022cited by this paper
• A review of the recent progress in battery informatics

  2022cited by this paper
• Stochastic reconstruction of 3D microstructures from 2D cross-sectional images using machine learning-based characterization

  2022cited by this paper
• MicroLib: A library of 3D microstructures generated from 2D micrographs using SliceGAN

  2022cited by this paper
• Framework for discovering porous materials: Structural hybridization and Bayesian optimization of conditional generative adversarial network

  2022cited by this paper
• Machine learning-facilitated multiscale imaging for energy materials

  2022cited by this paper
• Multi-scale reconstruction of porous media from low-resolution core images using conditional generative adversarial networks

  2022cited by this paper
• Progress in nanomaterials fabrication and their prospects in artificial intelligence towards solid oxide fuel cells: A review

  2022cited by this paper
• An improved 3D microstructure reconstruction approach for porous media

  2022cited by this paper
• Reconstruction, optimization, and design of heterogeneous materials and media: Basic principles, computational algorithms, and applications

  2021cited by this paper
• Guiding the Design of Heterogeneous Electrode Microstructures for Li‐Ion Batteries: Microscopic Imaging, Predictive Modeling, and Machine Learning

  2021cited by this paper
• Deep learning in pore scale imaging and modeling

  2021cited by this paper
• Deep learning-based segmentation of lithium-ion battery microstructures enhanced by artificially generated electrodes

  2021cited by this paper
• 3D-PMRNN: Reconstructing three-dimensional porous media from the two-dimensional image with recurrent neural network

  2021cited by this paper
• Unsupervised Generative Adversarial Network for 3-D Microstructure Synthesis from 2-D Image

  2021cited by this paper
• 3D reconstruction of digital cores based on a model using generative adversarial networks and variational auto-encoders

  2021cited by this paper
• Artificial Intelligence Applied to Battery Research: Hype or Reality?

  2021cited by this paper
• Characterization of pore and grain size distributions in porous geological samples - An image processing workflow

  2021cited by this paper
• Reconstructing porous media using generative flow networks

  2021cited by this paper
• Data-Driven Learning of 3-Point Correlation Functions as Microstructure Representations

  2021cited by this paper
• RockGPT: reconstructing three-dimensional digital rocks from single two-dimensional slice with deep learning

  2021cited by this paper
• Bridging nano- and microscale X-ray tomography for battery research by leveraging artificial intelligence

  2021cited by this paper
• Segmentation of Solid Oxide Cell Electrodes by Patch Convolutional Neural Network

  2021cited by this paper
• Generating three-dimensional structures from a two-dimensional slice with generative adversarial network-based dimensionality expansion

  2021cited by this paper
• Deep neural networks for improving physical accuracy of 2D and 3D multi-mineral segmentation of rock micro-CT images

  2021cited by this paper
• Shale Digital Core Image Generation Based on Generative Adversarial Networks

  2021cited by this paper
• Slice-to-voxel stochastic reconstructions on porous media with hybrid deep generative model

  2021cited by this paper
• Mapping the architecture of single lithium ion electrode particles in 3D, using electron backscatter diffraction and machine learning segmentation

  2021cited by this paper
• Statistical characterization and reconstruction of heterogeneous microstructures using deep neural network

  2021cited by this paper
• Fusion of Complementary 2D and 3D Mesostructural Datasets Using Generative Adversarial Networks

  2021cited by this paper
• Reconstructing the 3D digital core with a fully convolutional neural network

  2020cited by this paper
• Linking Morphology of Porous Media to Their Macroscopic Permeability by Deep Learning

  2020cited by this paper
• Multi-scale X-ray tomography and machine learning algorithms to study MoNi4 electrocatalysts anchored on MoO2 cuboids aligned on Ni foam

  2020cited by this paper
• Coupled generative adversarial and auto-encoder neural networks to reconstruct three-dimensional multi-scale porous media

  2020cited by this paper
• Comparison of the pore size distributions of concretes with different air-entraining admixture dosages using 2D and 3D imaging approaches

  2020cited by this paper
• Stochastic reconstruction of 3D porous media from 2D images using generative adversarial networks

  2020cited by this paper
• Reconstruction of shale image based on Wasserstein Generative Adversarial Networks with gradient penalty

  2020cited by this paper
• Palabos: Parallel Lattice Boltzmann Solver

  2020cited by this paper
• Machine learning in geo- and environmental sciences: From small to large scale

  2020cited by this paper
• Microstructure Generation via Generative Adversarial Network for Heterogeneous, Topologically Complex 3D Materials

  2020cited by this paper
• Pores for thought: generative adversarial networks for stochastic reconstruction of 3D multi-phase electrode microstructures with periodic boundaries

  2020cited by this paper
• Reconstruction of 3D Microstructures from 2D Images via Transfer Learning

  2020cited by this paper
• Multimodal imaging and machine learning to enhance microscope images of shale

  2020cited by this paper
• An end-to-end three-dimensional reconstruction framework of porous media from a single two-dimensional image based on deep learning

  2020cited by this paper
• Digital Rock Techniques to Study Shale Permeability: A Mini-Review

  2020cited by this paper
• RockFlow: Fast Generation of Synthetic Source Rock Images Using Generative Flow Models

  2020cited by this paper
• A case study on homogeneous and heterogeneous reservoir porous media reconstruction by using generative adversarial networks

  2019cited by this paper
• Segmentation of digital rock images using deep convolutional autoencoder networks

  2019cited by this paper
• Enhancing images of shale formations by a hybrid stochastic and deep learning algorithm

  2019cited by this paper
• Reconstruction of three-dimensional anisotropic media based on analysis of morphological completeness

  2019cited by this paper
• A New Approach To Clastic Rocks Pore-Scale Topology Reconstruction Based On Automatic Thin-Section Images and Ct Scans Analysis

  2019cited by this paper
• Coal Cleat/Fracture Segmentation Using Convolutional Neural Networks

  2019cited by this paper
• Computational microstructure characterization and reconstruction: Review of the state-of-the-art techniques

  2018cited by this paper
• Accelerating multi-point statistics reconstruction method for porous media via deep learning

  2018cited by this paper
• CT-image Super Resolution Using 3D Convolutional Neural Network

  2018cited by this paper
• Porous Structure Reconstruction Using Convolutional Neural Networks

  2018cited by this paper
• A stochastic multiscale algorithm for modeling complex granular materials

  2018cited by this paper
• Parametric generation of conditional geological realizations using generative neural networks

  2018cited by this paper
• A Transfer Learning Approach for Microstructure Reconstruction and Structure-property Predictions

  2018cited by this paper
• Generation of 3D representative volume elements for heterogeneous materials: A review

  2018cited by this paper
• Stochastic Reconstruction of an Oolitic Limestone by Generative Adversarial Networks

  2017cited by this paper
• Improving direct physical properties prediction of heterogeneous materials from imaging data via convolutional neural network and a morphology-aware generative model

  2017cited by this paper
• Industrial applications of digital rock technology

  2017cited by this paper
• Inversion using a new low-dimensional representation of complex binary geological media based on a deep neural network

  2017cited by this paper
• MorphoLibJ: integrated library and plugins for mathematical morphology with ImageJ

  2016cited by this paper
• Multiscale study for stochastic characterization of shale samples

  2016cited by this paper
• Microstructure Representation and Reconstruction of Heterogeneous Materials via Deep Belief Network for Computational Material Design

  2016cited by this paper
• Metrics for evaluating 3D medical image segmentation: analysis, selection, and tool

  2015cited by this paper
• Modeling and characterizing anisotropic inclusion orientation in heterogeneous material via directional cluster functions and stochastic microstructure reconstruction

  2014cited by this paper
• DREAM.3D: A Digital Representation Environment for the Analysis of Microstructure in 3D

  2014cited by this paper
• Quantification of soil structure based on Minkowski functions

  2010cited by this paper
• A superior descriptor of random textures and its predictive capacity

  2009cited by this paper
• 3D Stochastic Modelling of Heterogeneous Porous Media – Applications to Reservoir Rocks

  2006cited by this paper
• Random Heterogeneous Materials

  2002cited by this paper
• Two‐point cluster function for continuum percolation

  1988cited by this paper

• A diffusion-based generative framework for virtual porous granular media generation

  2026cites this paper
• Three-dimensional digital core reconstruction from 2D SEM images of heterogeneous shale samples

  2026cites this paper
• Synthetic geological porous media generation using deep learning: a comprehensive review

  2026cites this paper
• RAFT: A program for area fraction measurement of digital micrographs.

  2026cites this paper
• Interpolating beyond dimensions: 3D porous materials generation from sparse 2D slices

  2026cites this paper
• Intelligent Reconstruction of Digital Shale and Its Application in the Analysis of Conductivity Mechanism

  2026cites this paper
• Inverse design of hypoeutectoid pearlite steel microstructures using a deep learning and genetic algorithm optimization framework

  2026cites this paper
• Ensemble-guided machine learning for feature-constrained porous media

  2026cites this paper
• Determining the macro mechanical properties of basalt from pore characteristics and meso-mechanical parameters of grain interfaces

  2025cites this paper
• Machine learning applications in SEM-based pore analysis: a review

  2025cites this paper
• Recent Advances in Flow Through Porous Media for Energy Exploitation

  2025cites this paper
• A parameterized model reconstruction method for multi-mineral porous rocks

  2025cites this paper
• Computational Intelligence in Stochastic Reconstruction of Porous Microstructures for Image-Based Poro/Micro-Mechanical Modeling

  2025cites this paper
• Latent diffusion modeling of porous media informed by spatial statistics.

  2025cites this paper
• Machine learning applications in tight porous media: Challenges, advances, and future directions

  2025cites this paper
• Learning to Fill: Reconstructing Scientific Microstructure Images Using Probabilistic Networks

  2025cites this paper
• From Traditional Approaches to Single-Image Generative Models for Stationary and Nonstationary Porous Media

  2025cites this paper
• Generative Modeling of Three-Dimensional Multiphase Flow in Porous Media

  2025cites this paper
• Pore-Network Topology Impact on CO 2 Sequestration via Capillary-Connectivity Mechanism

  2025cites this paper
• Elastic constants from charge density distribution in FCC high-entropy alloys using CNN and DFT

  2024cites this paper
• New 2D to 3D Reconstruction of Heterogeneous Porous Media via Deep Generative Adversarial Networks (GANs)

  2024cites this paper
• Recent Advances in Machine Learning‐Assisted Multiscale Design of Energy Materials

  2024cites this paper
• An Autoencoder-Based Deep Learning Model for Enhancing Noise Characterization and Microseismic Event Detection in Underground Longwall Coal Mines Using Distributed Acoustic Sensing Monitoring

  2024cites this paper
• Inverse Design of Microstructures Using Conditional Continuous Normalizing Flows

  2024cites this paper
• Three-dimensional reconstruction of porous media by fusing multi-grid image features based on extended feature pyramid network

  2024cites this paper
• True 2D-to-3D Reconstruction of Heterogeneous Porous Media via Deep Generative Adversarial Networks (GANs)

  year unknowncites this paper