Person
Edgar Albert Engel
This person is no longer with EPFL
Related publications (10)
A data-driven interpretation of the stability of organic molecular crystals
Michele Ceriotti, Edgar Albert Engel, Maria Pakhnova
Due to the subtle balance of intermolecular interactions that govern structure-property relations, predicting the stability of crystal structures formed from molecular building blocks is a highly non-trivial scientific problem. A particularly active and fr ...
ROYAL SOC CHEMISTRY2023Local Kernel Regression and Neural Network Approaches to the Conformational Landscapes of Oligopeptides
Michele Ceriotti, Alberto Fabrizio, Benjamin André René Meyer, Edgar Albert Engel, Raimon Fabregat I De Aguilar-Amat, Veronika Juraskova
The application of machine learning to theoretical chemistry has made it possible to combine the accuracy of quantum chemical energetics with the thorough sampling of finite-temperature fluctuations. To reach this goal, a diverse set of methods has been pr ...
2022A complete description of thermodynamic stabilities of molecular crystals
Venkat Kapil, Edgar Albert Engel
Predictions of relative stabilities of (competing) molecular crystals are of great technological relevance, most notably for the pharmaceutical industry. However, they present a long-standing challenge for modeling, as often minuscule free energy differenc ...
NATL ACAD SCIENCES2022Uncertainty estimation for molecular dynamics and sampling
Michele Ceriotti, Federico Grasselli, Yongbin Zhuang, Venkat Kapil, Kevin Rossi, Edgar Albert Engel, Giulio Imbalzano
Machine-learning models have emerged as a very effective strategy to sidestep time-consuming electronic-structure calculations, enabling accurate simulations of greater size, time scale, and complexity. Given the interpolative nature of these models, the r ...
2021Improving sample and feature selection with principal covariates regression
Michele Ceriotti, Edgar Albert Engel, Benjamin Aaron Helfrecht, Sergei Kliavinek
Selecting the most relevant features and samples out of a large set of candidates is a task that occurs very often in the context of automated data analysis, where it improves the computational performance and often the transferability of a model. Here we ...
IOP PUBLISHING LTD2021Importance of Nuclear Quantum Effects for NMR Crystallography
Michele Ceriotti, Venkat Kapil, Edgar Albert Engel
The resolving power of solid-state nuclear magnetic resonance (NMR) crystallography depends heavily on the accuracy of computational predictions of NMR chemical shieldings of candidate structures, which are usually taken to be local minima in the potential ...
AMER CHEMICAL SOC2021A Bayesian approach to NMR crystal structure determination
David Lyndon Emsley, Michele Ceriotti, Albert Hofstetter, Edgar Albert Engel, Federico Maria Paruzzo, Andrea Anelli
Nuclear Magnetic Resonance (NMR) spectroscopy is particularly well suited to determine the structure of molecules and materials in powdered form. Structure determination usually proceeds by finding the best match between experimentally observed NMR chemica ...
2019Ab initio thermodynamics of liquid and solid water
Michele Ceriotti, Bingqing Cheng, Edgar Albert Engel
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 ...
NATL ACAD SCIENCES2019Assessment of Approximate Methods for Anharmonic Free Energies
Michele Ceriotti, Venkat Kapil, Edgar Albert Engel, Mariana Rossi Carvalho
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 ...
2019Generalized convex hull construction for materials discovery
Michele Ceriotti, Edgar Albert Engel, Andrea Anelli
Searching for novel materials involves identifying potential candidates and selecting those that have desirable properties and facile synthesis. It is relatively easy to generate large numbers of potential candidates, for instance, by computational searche ...
2018