AIMC Topic: Porosity

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Deep learning to overcome Zernike phase-contrast nanoCT artifacts for automated micro-nano porosity segmentation in bone.

Journal of synchrotron radiation
Bone material contains a hierarchical network of micro- and nano-cavities and channels, known as the lacuna-canalicular network (LCN), that is thought to play an important role in mechanobiology and turnover. The LCN comprises micrometer-sized lacuna...

Fully Integrated Patch Based on Lamellar Porous Film Assisted GaN Optopairs for Wireless Intelligent Respiratory Monitoring.

Nano letters
Respiratory pattern is one of the most crucial indicators for accessing human health, but there has been limited success in implementing fast-responsive, affordable, and miniaturized platforms with the capability for smart recognition. Herein, a full...

Prediction of fluid flow in porous media by sparse observations and physics-informed PointNet.

Neural networks : the official journal of the International Neural Network Society
We predict steady-state Stokes flow of fluids within porous media at pore scales using sparse point observations and a novel class of physics-informed neural networks, called "physics-informed PointNet" (PIPN). Taking the advantages of PIPN into acco...

An End-to-End Dynamic Posture Perception Method for Soft Actuators Based on Distributed Thin Flexible Porous Piezoresistive Sensors.

Sensors (Basel, Switzerland)
This paper proposes a method for accurate 3D posture sensing of the soft actuators, which could be applied to the closed-loop control of soft robots. To achieve this, the method employs an array of miniaturized sponge resistive materials along the so...

High-Fidelity Permeability and Porosity Prediction Using Deep Learning With the Self-Attention Mechanism.

IEEE transactions on neural networks and learning systems
Accurate estimation of reservoir parameters (e.g., permeability and porosity) helps to understand the movement of underground fluids. However, reservoir parameters are usually expensive and time-consuming to obtain through petrophysical experiments o...

Evaluation of reproducible cryogel preparation based on automated image analysis using deep learning.

Journal of biomedical materials research. Part A
Cryogels represent a class of porous sponge-like materials possessing unique properties including high-fidelity reproduction of tissue structure and maximized permeability. Their architecture is mainly based on an interconnected network of macropores...

Stacked ensemble machine learning for porosity and absolute permeability prediction of carbonate rock plugs.

Scientific reports
This study employs a stacked ensemble machine learning approach to predict carbonate rocks' porosity and absolute permeability with various pore-throat distributions and heterogeneity. Our dataset consists of 2D slices from 3D micro-CT images of four...

Deep learning for diffusion in porous media.

Scientific reports
We adopt convolutional neural networks (CNN) to predict the basic properties of the porous media. Two different media types are considered: one mimics the sand packings, and the other mimics the systems derived from the extracellular space of biologi...

Constructing porous ZnFC-PA/PSF composite spheres for highly efficient Cs removal.

Journal of environmental sciences (China)
Radioisotope leaking from nuclear waste has become an intractable problem due to its gamma radiation and strong water solubility. In this work, a novel porous ZnFC-PA/PSF composite sphere was fabricated by immobilization of ferrocyanides modified zin...

Automated, calibration-free quantification of cortical bone porosity and geometry in postmenopausal osteoporosis from ultrashort echo time MRI and deep learning.

Bone
BACKGROUND: Assessment of cortical bone porosity and geometry by imaging in vivo can provide useful information about bone quality that is independent of bone mineral density (BMD). Ultrashort echo time (UTE) MRI techniques of measuring cortical bone...