Modeling polymorphic molecular crystals with electronic structure theory

GJO Beran - Chemical reviews, 2016 - ACS Publications
Interest in molecular crystals has grown thanks to their relevance to pharmaceuticals,
organic semiconductor materials, foods, and many other applications. Electronic structure …

NMR crystallography of molecular organics

P Hodgkinson - Progress in Nuclear Magnetic Resonance …, 2020 - Elsevier
Developments of NMR methodology to characterise the structures of molecular organic
structures are reviewed, concentrating on the previous decade of research in which density …

Atomic-level structure determination of amorphous molecular solids by NMR

M Cordova, P Moutzouri, SO Nilsson Lill… - Nature …, 2023 - nature.com
Abstract Structure determination of amorphous materials remains challenging, owing to the
disorder inherent to these materials. Nuclear magnetic resonance (NMR) powder …

[HTML][HTML] Fantasy versus reality in fragment-based quantum chemistry

JM Herbert - The Journal of chemical physics, 2019 - pubs.aip.org
Since the introduction of the fragment molecular orbital method 20 years ago, fragment-
based approaches have occupied a small but growing niche in quantum chemistry. These …

First‐principles modeling of molecular crystals: structures and stabilities, temperature and pressure

J Hoja, AM Reilly, A Tkatchenko - Wiley Interdisciplinary …, 2017 - Wiley Online Library
The understanding of the structure, stability, and response properties of molecular crystals at
finite temperature and pressure is crucial for the field of crystal engineering and their …

Can computed crystal energy landscapes help understand pharmaceutical solids?

SL Price, DE Braun, SM Reutzel-Edens - Chemical Communications, 2016 - pubs.rsc.org
Computational crystal structure prediction (CSP) methods can now be applied to the smaller
pharmaceutical molecules currently in drug development. We review the recent uses of …

Structure determination of an amorphous drug through large-scale NMR predictions

M Cordova, M Balodis, A Hofstetter, F Paruzzo… - Nature …, 2021 - nature.com
Abstract Knowledge of the structure of amorphous solids can direct, for example, the
optimization of pharmaceutical formulations, but atomic-level structure determination in …

Predicting density functional theory-quality nuclear magnetic resonance chemical shifts via δ-machine learning

PA Unzueta, CS Greenwell… - Journal of Chemical …, 2021 - ACS Publications
First-principles prediction of nuclear magnetic resonance chemical shifts plays an
increasingly important role in the interpretation of experimental spectra, but the required …

Machine learning accelerates quantum mechanics predictions of molecular crystals

Y Han, I Ali, Z Wang, J Cai, S Wu, J Tang, L Zhang… - Physics Reports, 2021 - Elsevier
Quantum mechanics (QM) approaches (DFT, MP2, CCSD (T), etc.) play an important role in
calculating molecules and crystals with a high accuracy and acceptable efficiency. In recent …

Benchmark fragment-based 1 H, 13 C, 15 N and 17 O chemical shift predictions in molecular crystals

JD Hartman, RA Kudla, GM Day, LJ Mueller… - Physical Chemistry …, 2016 - pubs.rsc.org
The performance of fragment-based ab initio1H, 13C, 15N and 17O chemical shift
predictions is assessed against experimental NMR chemical shift data in four benchmark …