Related papers: Comparative analysis of machine learning models fo…
Ionic liquids (ILs) are an exciting class of electrolytes finding applications in many areas from energy storage to solvents, where they have been touted as ``designer solvents'' as they can be mixed to precisely tailor the physiochemical…
We present an AI-driven approach to discover compounds with optimal properties for CO2 capture from flue gas-refinery emissions' primary source. Focusing on ionic liquids (ILs) as alternatives to traditional amine-based solvents, we…
Ionic liquids (ILs) are an emerging group of chemical compounds which possess promising properties such as having negligible vapor pressure. These so called designer solvents have the potential to replace volatile organic compounds in…
Ionic liquids are a special category of molten salts with melting points near ambient temperatures or by convention below 100 C. Owing to their numerous valuable physicochemical properties as bulk liquids, solvents, at surfaces and in…
Ionic Liquids (ILs) provide a promising solution for CO$_2$ capture and storage to mitigate global warming. However, identifying and designing the high-capacity IL from the giant chemical space requires expensive, and exhaustive simulations…
The discovery of novel Ionic Liquids (ILs) is hindered by critical challenges in property prediction, including limited data, poor model accuracy, and fragmented workflows. Leveraging the power of Large Language Models (LLMs), we introduce…
Recently, machine-learning approaches have accelerated computational materials design and the search for advanced solid electrolytes. However, the predictors are currently limited to static structural parameters, which may not fully account…
Ionic liquids (ILs) have emerged as versatile replacements for traditional solvents because their physicochemical properties can be precisely tailored to various applications. However, accurately predicting key thermophysical properties…
Predicting the dissolution rates of silicate glasses in aqueous conditions is a complex task as the underlying mechanism(s) remain poorly understood and the dissolution kinetics can depend on a large number of intrinsic and extrinsic…
Climate emergency has led to the investigation of CO$_{2}$ valorization routes. A competitive process included in this framework is the catalytic CO$_{2}$ cycloaddition to epoxides, to produce cyclic carbonates. Halide-based Ionic liquids…
This study introduces a machine learning framework to predict the suitability of ionic liquids with unknown physical properties as propellants for electrospray thrusters based on their molecular structure. We construct a training dataset by…
Liquid metals are central to energy-storage and nuclear technologies, yet quantitative knowledge of their thermophysical properties remains limited. While atomistic simulations offer a route to computing liquid properties directly from…
Lennard-Jones (LJ) fluids serve as an important theoretical framework for understanding molecular interactions. Binary LJ fluids, where two distinct species of particles interact based on the LJ potential, exhibit rich phase behavior and…
The integration of machine learning (ML) into chemistry offers transformative potential in the design of molecules with targeted properties. However, the focus has often been on creating highly efficient predictive models, sometimes at the…
The melting temperature is important for materials design because of its relationship with thermal stability, synthesis, and processing conditions. Current empirical and computational melting point estimation techniques are limited in…
At the Institute for Thermodynamics and Thermal Process Engineering (ITT) about 100 molecular models for pure substances have been developed so far. These models reproduce vapor pressure, saturated liquid density, and enthalpy of…
The diffusivity of water in aqueous cesium iodide solutions is larger than that in neat liquid water, and vice versa for sodium chloride solutions. Such peculiar ion-specific behavior, called anomalous diffusion, is not reproduced in…
The interactions of ionic liquids (ILs) with organic solutes are of interest to many applications involving the use of ILs as task-specific solvents, such as in sensing devices or catalysis. However, currently little is known about these…
An optimized molecular model for ammonia, which is based on a previous work of Kristoef et al., Mol. Phys. 97 (1999) 1129--1137, is presented. Improvements are achieved by including data on geometry and electrostatics from quantum…
Determining the aqueous solubility of molecules is a vital step in many pharmaceutical, environmental, and energy storage applications. Despite efforts made over decades, there are still challenges associated with developing a solubility…