Computer-aided molecular design of ionic liquids as advanced process media: a review from fundamentals to applications
The unique physicochemical properties, flexible structural tunability, and giant chemical
space of ionic liquids (ILs) provide them a great opportunity to match different target …
space of ionic liquids (ILs) provide them a great opportunity to match different target …
Combining machine learning with physical knowledge in thermodynamic modeling of fluid mixtures
Thermophysical properties of fluid mixtures are important in many fields of science and
engineering. However, experimental data are scarce in this field, so prediction methods are …
engineering. However, experimental data are scarce in this field, so prediction methods are …
Molecular-based artificial neural network for predicting the electrical conductivity of deep eutectic solvents
Due to their unique features, deep eutectic solvents (DESs) are well-known as promising
and environmentally friendly solvents. Their use in various processes has recently become …
and environmentally friendly solvents. Their use in various processes has recently become …
[HTML][HTML] Prediction of CO2 solubility in deep eutectic solvents using random forest model based on COSMO-RS-derived descriptors
This work presents the development of molecular-based mathematical model for the
prediction of CO 2 solubility in deep eutectic solvents (DESs). First, a comprehensive …
prediction of CO 2 solubility in deep eutectic solvents (DESs). First, a comprehensive …
Data-driven model for ternary-blend concrete compressive strength prediction using machine learning approach
Ternary-blend concrete is a complex composite material, and the nonlinearity in its
compressive strength behavior is unquestionable. Entirely many models have been …
compressive strength behavior is unquestionable. Entirely many models have been …
Insights into modeling refractive index of ionic liquids using chemical structure-based machine learning methods
Ionic liquids (ILs) have drawn much attention due to their extensive applications and
environment-friendly nature. Refractive index prediction is valuable for ILs quality control …
environment-friendly nature. Refractive index prediction is valuable for ILs quality control …
Utilizing artificial intelligence techniques for modeling minimum miscibility pressure in carbon capture and utilization processes: a comprehensive review and …
MN Amar, H Djema, K Ourabah, FM Alqahtani… - Energy & …, 2024 - ACS Publications
The carbon dioxide (CO2) based enhanced oil recovery methods (EORs) are considered
among the promising techniques for increasing the recovery factor from mature oil reservoirs …
among the promising techniques for increasing the recovery factor from mature oil reservoirs …
Pressing matter: why are ionic liquids so viscous?
Room temperature ionic liquids are considered to have huge potential for practical
applications such as batteries. However, their high viscosity presents a significant challenge …
applications such as batteries. However, their high viscosity presents a significant challenge …
Modeling resilient modulus of subgrade soils using LSSVM optimized with swarm intelligence algorithms
Resilient modulus (Mr) of subgrade soils is one of the crucial inputs in pavement structural
design methods. However, the spatial variability of soil properties and the nature of test …
design methods. However, the spatial variability of soil properties and the nature of test …
Carbon capture using ionic liquids: An explicit data driven model for carbon (IV) Oxide solubility estimation
In this study, carbon dioxide (CO 2) solubility in 20 different ionic liquids (ILs) belonging to
various chemical families was estimated across a broad range of pressures (0.0098–72.24 …
various chemical families was estimated across a broad range of pressures (0.0098–72.24 …