Concept

Crystal structure prediction

Publications associées (33)

Chemical Shift-Dependent Interaction Maps in Molecular Solids

Structure determinationof molecular solids through NMR crystallographyrelies on the generation of a comprehensive set of candidate crystalstructures and on the comparison of chemical shifts computed for thosecandidates with experimental values. Exploring t ...

AMER CHEMICAL SOC2023

Controlling the crystal structure of succinic acid via microfluidic spray-drying

Esther Amstad, Aysu Ceren Okur

Many properties of materials, including their dissolution kinetics, hardness, and optical appearance, depend on their structure. Unfortunately, it is often difficult to control the structure of low molecular weight organic compounds that have a high propen ...

ROYAL SOC CHEMISTRY2023

NMR Crystallography in the Big Data Era: New Methods and Applications Powered by Machine Learning

Manuel Cordova

Structure determination of materials is key to understanding their physical properties. While single-crystal X-ray diffraction is the gold standard for structures displaying long-range order, many materials of interest are polycrystalline and/or disordered ...

EPFL2023

Machine-learned interatomic potentials: Recent developments and prospective applications

William Curtin

High-throughput generation of large and consistent ab initio data combined with advanced machine-learning techniques are enabling the creation of interatomic potentials of near ab initio quality. This capability has the potential of dramatically impacting ...

Heidelberg2023

Bootstrapping traceless symmetric O(N) scalars

Alessandro Vichi, Maria Refinetti, Marten Jan Reehorst

We use numerical bootstrap techniques to study correlation functions of traceless sym-metric tensors of O(N) with two indices ti j. We obtain upper bounds on operator dimen-sions for all the relevant representations and several values of N. We discover sev ...

SCIPOST FOUNDATION2023

De Novo Crystal Structure Determination from Machine Learned Chemical Shifts

David Lyndon Emsley, Albert Hofstetter, Manuel Cordova, Martins Balodis

Determination of the three-dimensional atomic-level structure of powdered solids is one of the key goals in current chemistry. Solid-state NMR chemical shifts can be used to solve this problem, but they are limited by the high computational cost associated ...

AMER CHEMICAL SOC2022

New methods for structure determination and speciation by NMR crystallography

Martins Balodis

NMR crystallography has been around for half a century, but with the advent of NMR crystal structure determination protocols in the last decade it has shown perspectives that were not seen before. Amalgamation of NMR and crystal structure determination has ...

EPFL2022

Cubic, hexagonal and tetragonal FeGex phases (x = 1, 1.5, 2): Raman spectroscopy and magnetic properties

Anna Fontcuberta i Morral, Dirk Grundler, Santhanu Panikar Ramanandan, Nicolas Tappy, Anna Kúkol'ová

There is currently an emerging drive towards computational materials design and fabrication of predicted novel materials. One of the keys to developing appropriate fabrication methods is determination of the composition and phase. Here we explore the FeGe ...

2021

Physics-enhanced machine learning with symmetry-adapted and long-range representations

Andrea Grisafi

Theoretical and computational approaches to the study of materials and molecules have, over the last few decades, progressed at an exponential rate. Yet, the possibility of producing numerical predictions that are on par with experimental measurements is t ...

EPFL2021

Electrochemical reconstruction of ZnO for selective reduction of CO2 to CO

Andreas Züttel, Emanuele Moioli, Wen Luo, Jie Zhang, Kun Zhao, Qin Zhang

Electrocatalytic conversion of CO2 to valuable chemicals is a highly promising route to close the carbon cycle. Herein, Zn catalysts derived from electrochemical reconstruction of ZnO materials are presented as efficient CO2-to-CO catalysts. We found that ...

2020

Graph Chatbot

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

Connectez-vous pour utiliser Chat avec Graph Search