Concepts of artificial intelligence for computer-assisted drug discovery
X Yang, Y Wang, R Byrne, G Schneider… - Chemical …, 2019 - ACS Publications
Artificial intelligence (AI), and, in particular, deep learning as a subcategory of AI, provides
opportunities for the discovery and development of innovative drugs. Various machine …
opportunities for the discovery and development of innovative drugs. Various machine …
[HTML][HTML] Big data creates new opportunities for materials research: a review on methods and applications of machine learning for materials design
Materials development has historically been driven by human needs and desires, and this is
likely to continue in the foreseeable future. The global population is expected to reach ten …
likely to continue in the foreseeable future. The global population is expected to reach ten …
Holistic Prediction of the pKa in Diverse Solvents Based on a Machine‐Learning Approach
Q Yang, Y Li, JD Yang, Y Liu, L Zhang… - Angewandte …, 2020 - Wiley Online Library
While many approaches to predict aqueous pKa values exist, the fast and accurate
prediction of non‐aqueous pKa values is still challenging. Based on the iBonD experimental …
prediction of non‐aqueous pKa values is still challenging. Based on the iBonD experimental …
Prediction of CO2 solubility in ionic liquids using machine learning methods
A comprehensive database containing 10,116 CO 2 solubility data measured in various
ionic liquids (ILs) at different temperatures and pressures is established. Based on this …
ionic liquids (ILs) at different temperatures and pressures is established. Based on this …
pKa values in organic chemistry–Making maximum use of the available data
A Kütt, S Selberg, I Kaljurand, S Tshepelevitsh… - Tetrahedron letters, 2018 - Elsevier
Acids and bases are ubiquitous. Sometimes, it is essential to know the accurate strength (pK
a values) of the acids/bases to work with, but sometimes just acidity/basicity order is enough …
a values) of the acids/bases to work with, but sometimes just acidity/basicity order is enough …
Next generation pure component property estimation models: With and without machine learning techniques
Physiochemical properties of pure components serve as the basis for the design and
simulation of chemical products and processes. Models based on the molecular structural …
simulation of chemical products and processes. Models based on the molecular structural …
Group contribution-based property estimation methods: advances and perspectives
R Gani - Current Opinion in Chemical Engineering, 2019 - Elsevier
Highlights•A brief overview on the state of the art in group-contribution based property
estimation methods, which are simple methods, easy to use, have some predictive …
estimation methods, which are simple methods, easy to use, have some predictive …
[HTML][HTML] Chemical product design–recent advances and perspectives
Chemical industry is continuously looking for opportunities to manufacture the necessary
commodity chemicals as well as to convert them into higher value-added chemicals-based …
commodity chemicals as well as to convert them into higher value-added chemicals-based …
[HTML][HTML] Computer-aided solvent selection and design for efficient chemical processes
The chemical industry makes extensive use of solvents, especially for chemical reactions
and separations. When considering the large number of existing solvents and the necessity …
and separations. When considering the large number of existing solvents and the necessity …
Enhancement and estimation of thermo-physical properties of organic-phase change materials (O-PCMs) and their applications in solar thermal technologies: A …
A Kumar, R Kumar - Journal of Energy Storage, 2024 - Elsevier
As the demand for green and sustainable energy grows, solar thermal technologies face
performance challenges due to intermittent solar energy. Integrating heat storage units …
performance challenges due to intermittent solar energy. Integrating heat storage units …