AIMC Topic: Solvents

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Viscosity of Ionic Liquids: Application of the Eyring's Theory and a Committee Machine Intelligent System.

Molecules (Basel, Switzerland) Dec 31, 2020
Accurate determination of the physicochemical characteristics of ionic liquids (ILs), especially viscosity, at widespread operating conditions is of a vital role for various fields. In this study, the viscosity of pure ILs is modeled using three appr...
Algorithms Temperature Support Vector Machine Artificial Intelligence Solvents Viscosity Thermodynamics Bayes Theorem Ionic Liquids
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Presence of emerging organic contaminants and solvents in schools using passive sampling.

The Science of the total environment Oct 13, 2020
In this study, we report on the applicability of passive sampling with Carbopack X adsorbent tubes followed by thermal desorption gas-chromatography-mass spectrometry (TD-GC-MS) to monitor the concentrations of emerging organic contaminants (EOCs) an...
Gas Chromatography-Mass Spectrometry Schools Solvents Environmental Monitoring Diffusion Air Pollutants
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Combining Molecular Dynamics and Machine Learning to Predict Self-Solvation Free Energies and Limiting Activity Coefficients.

Journal of chemical information and modeling Sep 1, 2020
Computational prediction of limiting activity coefficients is of great relevance for process design. For highly nonideal mixtures including molecules with directed interactions, methods that maintain the molecular character of the solvent are most pr...
Thermodynamics Molecular Dynamics Simulation Solvents Machine Learning
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SUSSOL-Using Artificial Intelligence for Greener Solvent Selection and Substitution.

Molecules (Basel, Switzerland) Jul 3, 2020
Solvents come in many shapes and types. Looking for solvents for a specific application can be hard, and looking for green alternatives for currently used nonbenign solvents can be even harder. We describe a new methodology for solvent selection and ...
Humans Solvents Green Chemistry Technology Software Algorithms Neural Networks, Computer Databases, Factual Artificial Intelligence
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A high-throughput system combining microfluidic hydrogel droplets with deep learning for screening the antisolvent-crystallization conditions of active pharmaceutical ingredients.

Lab on a chip May 18, 2020
Crystallization of active pharmaceutical ingredients (APIs) is a crucial process in the pharmaceutical industry due to its great impact in drug efficacy. However, conventional approaches for screening the optimal crystallization conditions of APIs ar...
Deep Learning Solvents Crystallization Microfluidics Hydrogels
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Feedforward Artificial Neural Network-Based Model for Predicting the Removal of Phenolic Compounds from Water by Using Deep Eutectic Solvent-Functionalized CNTs.

Molecules (Basel, Switzerland) Mar 26, 2020
In the recent decade, deep eutectic solvents (DESs) have occupied a strategic place in green chemistry research. This paper discusses the application of DESs as functionalization agents for multi-walled carbon nanotubes (CNTs) to produce novel adsorb...
Nanotubes, Carbon Solvents Models, Theoretical Water Pollutants, Chemical Phenols Kinetics Adsorption Neural Networks, Computer Algorithms Water Purification
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Ionic Liquid-Based Ultrasonic-Assisted Extraction Coupled with HPLC and Artificial Neural Network Analysis for .

Molecules (Basel, Switzerland) Mar 13, 2020
is widely used in traditional Chinese medicine (TCM). Ganoderic acid A and D are the main bioactive components with anticancer effects in . To obtain the maximum content of two compounds from , a novel extraction method, an ionic liquid-based ultras...
Solutions Anions Reference Standards Reishi Rotation Chromatography, High Pressure Liquid Solvents Ultrasonics Ionic Liquids Neural Networks, Computer Reproducibility of Results Time Factors
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Prediction of P-glycoprotein inhibitors with machine learning classification models and 3D-RISM-KH theory based solvation energy descriptors.

Journal of computer-aided molecular design Nov 19, 2019
Development of novel in silico methods for questing novel PgP inhibitors is crucial for the reversal of multi-drug resistance in cancer therapy. Here, we report machine learning based binary classification schemes to identify the PgP inhibitors from ...
Thermodynamics Small Molecule Libraries ATP Binding Cassette Transporter, Subfamily B, Member 1 Solvents Machine Learning Humans Drug Discovery
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Response surface methodology and artificial neural network approach for the optimization of ultrasound-assisted extraction of polyphenols from garlic.

Food and chemical toxicology : an international journal published for the British Industrial Biological Research Association Nov 16, 2019
This paper aimed to establish the optimal conditions for ultrasound-assisted extraction of polyphenols from domestic garlic (Allium sativum L.) using response surface methodology (RSM) and artificial neural network (ANN) approach. A 4-factor-3-level ...
Free Radical Scavengers Garlic Neural Networks, Computer Solid Phase Extraction Polyphenols Solvents Models, Chemical Ultrasonic Waves
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Exploring the limitations of biophysical propensity scales coupled with machine learning for protein sequence analysis.

Scientific reports Nov 15, 2019
Machine learning (ML) is ubiquitous in bioinformatics, due to its versatility. One of the most crucial aspects to consider while training a ML model is to carefully select the optimal feature encoding for the problem at hand. Biophysical propensity s...
Oxidation-Reduction Amino Acids Propensity Score Cysteine Solvents Machine Learning Computational Biology Proteins Biophysical Phenomena Sequence Analysis, Protein
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