Applications of Artificial Intelligence to Computational Chemistry
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Thermodynamic properties of liquid water as well as hexagonal (Ih) and cubic (Ic) ice are predicted based on density functional theory at the hybrid-functional level, rigorously taking into account quantum nuclear motion, anharmonic fluctuations, and proto ...
The predictive simulation of molecular liquids requires potential energy surface (PES) models that are not only accurate but also computationally efficient enough to handle the large systems and long time scales required for reliable prediction of macrosco ...
Molecular-level understanding and characterization of solvation environments are often needed across chemistry, biology, and engineering. Toward practical modeling of local solvation effects of any solute in any solvent, we report a static and all-quantum ...
Transition-metal compounds pose serious challenges to first-principles calculations based on density functional theory (DFT), due to the inability of most approximate exchange-correlation functionals to capture the localization of valence electrons on thei ...
Predictive modelling and quantitative understanding of nucleation is essential for predicting phase transformation processes in nature and precisely controlling material synthesis and processing. Atomistic modeling is a powerful tool for capturing the dyna ...
Establishing a unified framework for describing the structures of molecular and periodic systems is a long-standing challenge in physics, chemistry, and material science. With the rise of machine learning methods in these fields, there is a growing need fo ...
For properties of interacting electron systems, Kohn-Sham (KS) theory is often favored over many-body perturbation theory (MBPT), owing to its low computational cost. However, the exact KS potential can be challenging to approximate, for example in the pre ...
Quantitative evaluation of the thermodynamic properties of materials—most notably their stability, as measured by the free energy—must take into account the role of thermal and zero-point energy fluctuations. While these effects can easily be estimated wit ...
Optimized protocols for the synthesis of diazolyl alpha,alpha-difluoroacetates via deoxofluorination of the corresponding glyoxylates with Morph-DAST are described. The method allowed the preparation of the title fluoridated building blocks in 73-96 % yiel ...
The aim of this thesis is to explore the power and the limits of classical and quantum molecular modelling, for the investigation of the adsorption properties of microporous crystalline materials. The materials analyzed are metal organic frameworks (MOFs) ...
