[HTML][HTML] Impact of inhibition mechanisms, automation, and computational models on the discovery of organic corrosion inhibitors
The targeted removal of efficient but toxic corrosion inhibitors based on hexavalent
chromium has provided an impetus for discovery of new, more benign organic compounds …
chromium has provided an impetus for discovery of new, more benign organic compounds …
Melt viscosity of light alloys: Progress and challenges
The viscosity of molten metals is a critical parameter influencing melt fluidity, alloy forming
quality, and casting performance. It is therefore essential to maintain melt viscosity within an …
quality, and casting performance. It is therefore essential to maintain melt viscosity within an …
Temperature-dependent density and viscosity prediction for hydrocarbons: machine learning and molecular dynamics simulations
Machine learning-based predictive models allow rapid and reliable prediction of material
properties and facilitate innovative materials design. Base oils used in the formulation of …
properties and facilitate innovative materials design. Base oils used in the formulation of …
Machine learning models for prediction of electrochemical properties in supercapacitor electrodes using MXene and graphene nanoplatelets
Herein, machine learning (ML) models using multiple linear regression (MLR), support
vector regression (SVR), random forest (RF) and artificial neural network (ANN) are …
vector regression (SVR), random forest (RF) and artificial neural network (ANN) are …
Vapor-liquid phase equilibria behavior prediction of binary mixtures using machine learning
Basic thermodynamic data plays an important role in chemical applications. However, the
traditional acquisition of thermodynamic data through experiments is laborious …
traditional acquisition of thermodynamic data through experiments is laborious …
Application and development of optical-based viscosity measurement technology
Y Ge, X Huang, X Tang, Y Wang, F Chen, D **ao… - Optics and Lasers in …, 2024 - Elsevier
Viscosity, as a crucial property of liquids, plays a vital role in various fields, including food,
chemical, pharmaceutical, personal care, and biomedicine. Therefore, it is of great …
chemical, pharmaceutical, personal care, and biomedicine. Therefore, it is of great …
Comment on 'physics-based representations for machine learning properties of chemical reactions'
In a recent article in this journal, van Gerwen et al (2022 Mach. Learn.: Sci. Technol. 3
045005) presented a kernel ridge regression model to predict reaction barrier heights. Here …
045005) presented a kernel ridge regression model to predict reaction barrier heights. Here …
Gibbs–Duhem-informed neural networks for binary activity coefficient prediction
We propose Gibbs–Duhem-informed neural networks for the prediction of binary activity
coefficients at varying compositions. That is, we include the Gibbs–Duhem equation …
coefficients at varying compositions. That is, we include the Gibbs–Duhem equation …
Differentiable modeling and optimization of non-aqueous Li-based battery electrolyte solutions using geometric deep learning
Electrolytes play a critical role in designing next-generation battery systems, by allowing
efficient ion transfer, preventing charge transfer, and stabilizing electrode-electrolyte …
efficient ion transfer, preventing charge transfer, and stabilizing electrode-electrolyte …
Viscosity of deep eutectic solvents: Predictive modeling with experimental validation
DM Makarov, AM Kolker - Fluid Phase Equilibria, 2025 - Elsevier
Viscosity, the measure of a fluid's resistance to deformation, is a critical parameter in many
industries. Being able to accurately predict viscosity is essential for the successful design …
industries. Being able to accurately predict viscosity is essential for the successful design …