AIMC Topic: Porosity

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Bridging nano- and microscale X-ray tomography for battery research by leveraging artificial intelligence.

Nature nanotechnology
X-ray computed tomography (CT) is a non-destructive imaging technique in which contrast originates from the materials' absorption coefficient. The recent development of laboratory nanoscale CT (nano-CT) systems has pushed the spatial resolution for b...

Machine learning to predict effective reaction rates in 3D porous media from pore structural features.

Scientific reports
Large discrepancies between well-mixed reaction rates and effective reactions rates estimated under fluid flow conditions have been a major issue for predicting reactive transport in porous media systems. In this study, we introduce a framework that ...

Prediction of the performance of pre-packed purification columns through machine learning.

Journal of separation science
Pre-packed columns have been increasingly used in process development and biomanufacturing thanks to their ease of use and consistency. Traditionally, packing quality is predicted through rate models, which require extensive calibration efforts throu...

Soft Capacitive Pressure Sensors: Trends, Challenges, and Perspectives.

ACS nano
Soft pressure sensors are critical components of e-skins, which are playing an increasingly significant role in two burgeoning fields: soft robotics and bioelectronics. Capacitive pressure sensors (CPS) are popular given their mechanical flexibility,...

Generative machine learning algorithm for lattice structures with superior mechanical properties.

Materials horizons
Lattice structures are typically made up of a crisscross pattern of beam elements, allowing engineers to distribute material in a more structurally effective way. However, a main challenge in the design of lattice structures is a trade-off between th...

Modeling of the dynamics of vascular embolization by using porous media for the design of injection robots of embolic agents.

Medical engineering & physics
Embolization is the prevailing therapy for tumor-targeting, anti-organ hyperfunction, and hemostasis. However, the injection of embolic agents largely depends on the experiences of doctors as assisted by X-ray, which will negate the health of the doc...

Large-Area Pixelized Optoelectronic Neuromorphic Devices with Multispectral Light-Modulated Bidirectional Synaptic Circuits.

Advanced materials (Deerfield Beach, Fla.)
The complete hardware implementation of an optoelectronic neuromorphic computing system is considered as one of the most promising solutions to realize energy-efficient artificial intelligence. Here, a fully light-driven and scalable optoelectronic n...

Materials Precursor Score: Modeling Chemists' Intuition for the Synthetic Accessibility of Porous Organic Cage Precursors.

Journal of chemical information and modeling
Computation is increasingly being used to try to accelerate the discovery of new materials. One specific example of this is porous molecular materials, specifically porous organic cages, where the porosity of the materials predominantly comes from th...

Artificial intelligence applications in implant dentistry: A systematic review.

The Journal of prosthetic dentistry
STATEMENT OF PROBLEM: Artificial intelligence (AI) applications are growing in dental implant procedures. The current expansion and performance of AI models in implant dentistry applications have not yet been systematically documented and analyzed.

Intelligent Prediction for Rock Porosity While Drilling Complex Lithology in Real Time.

Computational intelligence and neuroscience
Rock porosity is an important parameter for the formation evaluation, reservoir modeling, and petroleum reserve estimation. The conventional methods for determining the rock porosity are considered costly and time-consuming operations during the well...