AIMC Topic: Porosity
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Nanomaterial Texture-Based Machine Learning of Ciprofloxacin Adsorption on Nanoporous Carbon.
International journal of molecular sciences
Oct 30, 2024
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
Oct 28, 2024
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
Sep 6, 2024
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
Sep 4, 2024
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...
Osteoinductive biomaterials: Machine learning for prediction and interpretation.
Acta biomaterialia
Aug 22, 2024
Biomaterials with osteoinductivity are widely used for bone defect repair due to their unique structures and functions. Machine learning (ML) is pivotal in analyzing osteoinductivity and accelerating new material design. However, challenges include c...
Predicting ultrasound wave stimulated bone growth in bioinspired scaffolds using machine learning.
Journal of the mechanical behavior of biomedical materials
Aug 14, 2024
For conditions like osteoporosis, changes in bone pore geometry even when porosity is constant have been shown to correlate to increased fracture risk using techniques such as dual-energy x-ray absorptiometry (DXA) and computed tomography (CT). Addit...
Predicting and refining acid modifications of biochar based on machine learning and bibliometric analysis: Specific surface area, average pore size, and total pore volume.
The Science of the total environment
Jul 6, 2024
Acid-modified biochar is a modified biochar material with convenient preparation, high specific surface area, and rich pore structure. It has great potential for application in the heavy metal remediation, soil amendments, and carrying catalysts. Spe...
Au-decorated TiCT/porous carbon immunoplatform for ECM1 breast cancer biomarker detection with machine learning computation for predictive accuracy.
Talanta
Jul 4, 2024
Electrochemical immunosensors, surpassing conventional diagnostics, exhibit significant potential for cancer biomarker detection. However, achieving a delicate balance between signal sensitivity and operational stability, especially at the heterostru...
Causal prior-embedded physics-informed neural networks and a case study on metformin transport in porous media.
Water research
Jun 22, 2024
This study introduces a novel approach to transport modelling by integrating experimentally derived causal priors into neural networks. We illustrate this paradigm using a case study of metformin, a ubiquitous pharmaceutical emerging pollutant, and i...
Deep learning prediction and experimental investigation of specific capacitance of nitrogen-doped porous biochar.
Bioresource technology
May 25, 2024
N-doped porous biochar is a promising carbon material for supercapacitor electrodes due to its developed pore structure and high chemical activity which greatly affect the capacitive performance. Predicting the capacitance and exploring the most infl...
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