AIMC Topic: Porosity

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Development of hybrid robust model based on computational modeling and machine learning for analysis of drug sorption onto porous adsorbents.

Scientific reports
This study investigates the utilization of three regression models, i.e., Kernel Ridge Regression (KRR), nu-Support Vector Regression ([Formula: see text]-SVR), and Polynomial Regression (PR) for the purpose of forecasting the concentration (C) of a ...

Integrated learning framework for enhanced specific surface area, pore size, and pore volume prediction of biochar.

Bioresource technology
Specific surface area, pore size, and pore volume are essential biochar properties. Optimization typically reduces yield by focusing on per gram of biochar. This work introduces new indicators and an integrated model to balance quality and quantity, ...

Design and optimization of tamarind seed polysaccharide-based scaffold for tissue engineering applications using statistical modeling and machine learning, and it's in-vitro validation.

International journal of biological macromolecules
This study explores the development and optimization of a novel biomaterial scaffold for tissue engineering, composed of Tamarind seed polysaccharide (TSP), Hydroxypropyl methylcellulose (HPMC), Chitosan (CS), and Sodium alginate (ALG). Scaffold prop...

Interpretable machine learning reveals transport of aged microplastics in porous media: Multiple factors co-effect.

Water research
Microplastics (MPs) easily migrate into deeper soil layers, posing potential risks to subterranean habitats and groundwater. However, the mechanisms governing the vertical migration of MPs in soil, particularly aged MPs, remain unclear. In this study...

Computational analysis of controlled drug release from porous polymeric carrier with the aid of Mass transfer and Artificial Intelligence modeling.

Scientific reports
Controlled release of a desired drug from porous polymeric biomaterials was analyzed via computational method. The method is based on simulation of mass transfer and utilization of artificial intelligence (AI). This study explores the efficacy of thr...

A Deep Learning-Based Approach to Characterize Skull Physical Properties: A Phantom Study.

Journal of biophotonics
Transcranial ultrasound imaging is a popular method to study cerebral functionality and diagnose brain injuries. However, the detected ultrasound signal is greatly distorted due to the aberration caused by the skull bone. The aberration mechanism mai...

Nanomaterial Texture-Based Machine Learning of Ciprofloxacin Adsorption on Nanoporous Carbon.

International journal of molecular sciences
Drug substances in water bodies and groundwater have become a significant threat to the surrounding environment. This study focuses on the ability of the nanoporous carbon materials to remove ciprofloxacin from aqueous solutions under specific experi...

Roller compaction: Measuring ribbon porosity by terahertz spectroscopy and machine learning.

International journal of pharmaceutics
Roller compaction is a crucial unit operation in pharmaceutical manufacturing, with its ribbon porosity widely recognised as a critical quality attribute. Terahertz spectroscopy has emerged as a fast and non-destructive technique to measure porosity ...

Preparation of Multistage Pore TS-1 with Enhanced Photocatalytic Activity, Including Process Studies and Artificial Neural Network Modeling for Synergy Assessment.

Langmuir : the ACS journal of surfaces and colloids
Antibiotic residues have been found in several aquatic ecosystems as a result of the widespread use of antibiotics in recent years, which poses a major risk to both human health and the environment. At present, photocatalytic degradation is the most ...

Deep-learning-based pyramid-transformer for localized porosity analysis of hot-press sintered ceramic paste.

PloS one
Scanning Electron Microscope (SEM) is a crucial tool for studying microstructures of ceramic materials. However, the current practice heavily relies on manual efforts to extract porosity from SEM images. To address this issue, we propose PSTNet (Pyra...