AIMC Topic: Emulsions

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Influence of descriptor database selection on modeling retention factors in capillary micellar and microemulsion electrokinetic chromatography using the solvation parameter model.

Journal of chromatography. A Apr 25, 2025
Abraham's solvation parameter model has been widely used to model retention in capillary micellar and microemulsion electrokinetic chromatography systems. To fit or predict retention factors in separation systems experimentally determined compound de...
Machine Learning Databases, Factual Emulsions Chromatography, Micellar Electrokinetic Capillary Databases, Chemical Models, Chemical Micelles
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Microscopic water dispersion and hydrogen-bonding structures in margarine spreads with Raman hyperspectral imaging and machine learning.

Food chemistry Nov 13, 2024
Margarine, a water-in-oil (W/O) emulsion, offers advantages such as lower costs in comparison to similar products, but large amounts of saturated fats pose health risks. Reduction of saturated fat content is difficult and often leads to "oil-off," i....
Hydrogen Bonding Margarine Machine Learning Water Spectrum Analysis, Raman Emulsions
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Artificial intelligence and classic methods to segment and characterize spherical objects in micrographs of industrial emulsions.

International journal of pharmaceutics Nov 22, 2023
The stability of emulsions is a critical concern across multiple industries, including food products, agricultural formulations, petroleum, and pharmaceuticals. Achieving prolonged emulsion stability is challenging and depends on various factors, wit...
Emulsions Drug Compounding Artificial Intelligence Prospective Studies
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Shortwave infrared diffuse optical wearable probe for quantification of water and lipid content in emulsion phantoms using deep learning.

Journal of biomedical optics Jun 12, 2023
SIGNIFICANCE: The shortwave infrared (SWIR, to 2000 nm) holds promise for label-free measurements of water and lipid content in thick tissue, owed to the chromophore-specific absorption features and low scattering in this range. water and lipid est...
Humans Water Lipids Emulsions Deep Learning Wearable Electronic Devices
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Deep learning in food science: An insight in evaluating Pickering emulsion properties by droplets classification and quantification via object detection algorithm.

Advances in colloid and interface science Apr 6, 2022
Understanding the complicated emulsion microstructures by microscopic images will help to further elaborate their mechanisms and relevance. The formidable goal of the classification and quantification of emulsion microstructure appears difficult to a...
Food Technology Particle Size Emulsions Deep Learning
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Semisolid Pharmaceutical Product Characterization Using Non-invasive X-ray Microscopy and AI-Based Image Analytics.

The AAPS journal Mar 21, 2022
This work reports the use of X-ray microscopy (XRM) imaging to characterize the microstructure of semisolid formulations containing multiple immiscible phases. For emulsion-based semisolid formulations, the disperse phase globule size and its distrib...
Microscopy Emulsions X-Rays Artificial Intelligence
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Application of NIRs coupled with PLS and ANN modelling to predict average droplet size in oil-in-water emulsions prepared with different microfluidic devices.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Jan 6, 2022
In this study, the potential of microfluidic systems with different microchannel geometries (microchannel with teardrop micromixers and microchannel with swirl micromixers) for the preparation of oil-in-water (O/W) emulsions using two different emuls...
Lab-On-A-Chip Devices Least-Squares Analysis Emulsions Neural Networks, Computer Water
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Formulation and physicochemical stability of oil-in-water nanoemulsion loaded with α-terpineol as flavor oil using Quillaja saponins as natural emulsifier.

Food research international (Ottawa, Ont.) Dec 15, 2021
Alpha-terpineol (α-TOH) is a promising monoterpenoid detaining several biological activities. However, as a volatile molecule, the incorporation of α-TOH within formulated products poses several challenges related to its stability. In this sense, nan...
Quillaja Saponins Emulsions Water Oils Cyclohexane Monoterpenes
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Application of Design of Experiments® Approach-Driven Artificial Intelligence and Machine Learning for Systematic Optimization of Reverse Phase High Performance Liquid Chromatography Method to Analyze Simultaneously Two Drugs (Cyclosporin A and Etodolac) in Solution, Human Plasma, Nanocapsules, and Emulsions.

AAPS PharmSciTech May 13, 2021
The objectives of current investigation are (1) to find out wavelength of maximum absorbance (λ) for combined cyclosporin A and etodolac solution followed by selection of mobile phase suitable for the RP-HPLC method, (2) to define analytical target p...
Artificial Intelligence Machine Learning Algorithms Research Design Nanocapsules Chromatography, High Pressure Liquid Humans Chromatography, Reverse-Phase Emulsions Cyclosporine Neural Networks, Computer Etodolac Antifungal Agents
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Nanoemulsions and acidified milk gels as a strategy for improving stability and antioxidant activity of yarrow phenolic compounds after gastrointestinal digestion.

Food research international (Ottawa, Ont.) Dec 18, 2019
The aim of this study was to improve the stability and antioxidant activity of yarrow phenolic compounds upon an in vitro simulated gastrointestinal digestion. Therefore, two types of caseins-based delivery systems, sodium caseinate stabilized nanoem...
Digestion Hydrogen-Ion Concentration Food Handling Nanotechnology Animals Gels Emulsions Phenols In Vitro Techniques Achillea Milk Beverages Antioxidants
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