Collaborative Computational Project in NMR Crystallography
Lead Research Organisation:
Durham University
Department Name: Chemistry
Abstract
Solid-state nuclear magnetic resonance (NMR) is capable of providing extremely detailed insights into the structure and dynamics of a wide range of materials - from organic systems, such as pharmaceutical compounds and supramolecular arrays, to inorganic materials for next-generation batteries and safe storage of nuclear waste. Such information is crucial for harnessing the properties of increasingly complex new materials, and to address major challenges across the physical sciences. However, the true potential of this experimental technique is only realized through combination with advanced computational methods. In particular, first-principles electronic structure predictions of key NMR interactions, such as chemical shifts, allow experimental measurements to be directly linked to structure. In tackling challenging problems, the developing field of NMR crystallography benefits from close interaction with other experimental techniques, typically powder X-ray diffraction, and computational approaches, particularly crystal structure prediction. The Collaborative Computational Project for NMR Crystallography supports this multidisciplinary community of NMR spectroscopists, crystallographers, materials modellers and application scientists, who work both within academia and industry. We develop overarching software tools enabling a largely experimentally focused community to exploit advanced computational techniques.
Planned Impact
As detailed in the Pathways to Impact, we will use both our networking and industrial placement programme to develop and showcase effective use of CCP-NC tools and NMR crystallography techniques more widely, in both academia and industry. Most of the major companies for whom the solid state is critical, such as the pharmaceutical industry, or developers of catalysts (such as Johnson Matthey) have existing experience of solid-state NMR and will be able to benefit directly from a CCP-NC-supported researcher being seconded to the company. In other cases we will use our networking activities, in particular joint meetings with cognate disciplines, to widen exposure to the potential benefits of NMR crystallography. This will be backed up by showcasing different applications of NMR crystallography and CCP-NC tools through our website and social media.
A direct economic impact of this research is the potential for commercialisation of the outputs, particularly related to the developments in the CASTEP software. Dassault Systèmes / Biovia (www.3dsbiovia.com) provide a commercially supported version of CASTEP to industrial users, which is licensed from the UK-based CASTEP Developers Group (in addition to a global no-cost licence for academic users). Sales of the NMR-CASTEP program have now exceeded $3.5M, including to many international companies in the pharmaceutical and catalysis sectors.
An important aspect of the project is the training of post-graduate students and PDRAs, some of whom will go on to use these skills in industry (previous students and PDRAs with the Investigators are carrying out NMR work at companies such as GSK, Johnson Matthey and JEOL). The interdisciplinary nature of NMR crystallography, bringing together experimental techniques such as solid-state NMR and X-ray diffraction, and computational methods, means that these researchers will be well-placed to meet the challenges of developing new materials for a wide range of applications, e.g. energy storage, fuel cells and batteries, nuclear waste disposal, catalysts, and novel bioactive materials.
A direct economic impact of this research is the potential for commercialisation of the outputs, particularly related to the developments in the CASTEP software. Dassault Systèmes / Biovia (www.3dsbiovia.com) provide a commercially supported version of CASTEP to industrial users, which is licensed from the UK-based CASTEP Developers Group (in addition to a global no-cost licence for academic users). Sales of the NMR-CASTEP program have now exceeded $3.5M, including to many international companies in the pharmaceutical and catalysis sectors.
An important aspect of the project is the training of post-graduate students and PDRAs, some of whom will go on to use these skills in industry (previous students and PDRAs with the Investigators are carrying out NMR work at companies such as GSK, Johnson Matthey and JEOL). The interdisciplinary nature of NMR crystallography, bringing together experimental techniques such as solid-state NMR and X-ray diffraction, and computational methods, means that these researchers will be well-placed to meet the challenges of developing new materials for a wide range of applications, e.g. energy storage, fuel cells and batteries, nuclear waste disposal, catalysts, and novel bioactive materials.
Publications
Andersen C
(2021)
OPTIMADE, an API for exchanging materials data
in Scientific Data
Banerjee H
(2023)
Importance of electronic correlations in exploring the exotic phase diagram of layered Li x MnO 2
in Physical Review B
Davis ZH
(2023)
Computational NMR investigation of mixed-metal (Al,Sc)-MIL-53 and its phase transitions.
in Physical chemistry chemical physics : PCCP
Dawson D
(2024)
Site-directed cation ordering in chabazite-type Al x Ga 1- x PO 4 -34 frameworks revealed by NMR crystallography
in Chemical Science
Dawson D
(2021)
Thermal Dehydrofluorination of GaPO-34 Revealed by NMR Crystallography
in The Journal of Physical Chemistry C
Dawson DM
(2024)
An NMR crystallographic characterisation of solid (+)-usnic acid.
in Physical chemistry chemical physics : PCCP
Ells A
(2022)
Phase Transformations and Phase Segregation during Potassiation of Sn x P y Anodes
in Chemistry of Materials
Evans CL
(2022)
Resolving alternative structure determinations of indapamide using 13C solid-state NMR.
in Chemical communications (Cambridge, England)
Evans M
(2020)
matador: a Python library for analysing, curating and performing high-throughput density-functional theory calculations
in Journal of Open Source Software
Genreith-Schriever A
(2023)
Oxygen hole formation controls stability in LiNiO2 cathodes
in Joule
Title | CCP-NC database of calculated NMR data |
Description | A repository for the results of first-principles calculations of NMR parameters for solid materials. |
Type Of Material | Database/Collection of data |
Year Produced | 2021 |
Provided To Others? | Yes |
Impact | (just published) |
URL | https://www.ccpnc.ac.uk/database/ |
Description | Industrial Engagement of CCP-NC at Johnson Matthey |
Organisation | Johnson Matthey |
Country | United Kingdom |
Sector | Private |
PI Contribution | The team utilized computational analyses to assign and validate experimental results (solid-state Nuclear Magnetic Resonance (ssNMR) spectroscopy) obtained at Johnson Matthey. Collaborating with Prof. Sharon Ashbrook from the University of St. Andrews, I provided scientific support to the team. Additionally, we developed a Python code to expedite the generation and modification of the structural framework of catalytic materials. This tool is now integrated into Johnson Matthey's computational modeling team's workflow, facilitating in-depth exploration of the structure-property relationship of catalytic materials. Research work carried out in this collaboration was presented at the Industrial Meeting for solid-state NMR experts held at Johnson Matthey and at a conference jointly organized by CCP-NC, CCP5, and CCP9. |
Collaborator Contribution | The synthesis and advanced characterization team at Johnson Matthey synthesized and performed solid-state characterized the catalytic materials, respectively. Johnson Matthey provided access to additional high-performance computing facilities along with the tools and software necessary for the computational analyses. Moreover, to foster collaboration and knowledge exchange, a member from our research team was hosted by Johnson Matthey's advanced characterisation team. We also received valuable inputs from the modeling team of the collaborators. |
Impact | No articles or patents published yet. |
Start Year | 2023 |
Description | Industrial Engagement of CCP-NC at Pfizer |
Organisation | Pfizer Ltd |
Country | United Kingdom |
Sector | Private |
PI Contribution | The team proposed different approaches to generate accurate structural models for validating the structural transformation due to the hydration/dehydration of active pharmaceutical ingredients. These methods involved using Density Functional Theory (DFT) and molecular dynamics calculations to obtain a precise structural model. Although these methods showed good potential, they need more adjustments to be completely accurate. The team benefitted from the valuable inputs from Prof. Steven Brown (University of Warwick). |
Collaborator Contribution | Pfizer provided access to additional high-performance computing facilities along with the software necessary for computational analyses. A member of our research team was hosted by Pfizer to have hands-on experience in an industrial set-up. We also received insightful remarks from the other team members at Pfizer. |
Impact | No publications or patents published yet. |
Start Year | 2023 |
Title | A toolbox for improving the workflow of NMR crystallography |
Description | NMR crystallography is a powerful tool with applications in structural characterization and crystal structure verification, to name two. However, applying this tool presents several challenges, especially for industrial users, in terms of consistency, workflow, time consumption, and the requirement for a high level of understanding of experimental solid-state NMR and GIPAW-DFT calculations. Here, we have developed a series of fully parameterized scripts for use in Materials Studio and TopSpin, based on the .magres file format, with a focus on organic molecules (e.g. pharmaceuticals), improving efficiency, robustness, and workflow. We separate these tools into three major categories: performing the DFT calculations, extracting & visualizing the results, and crystallographic modelling. These scripts will rapidly submit fully parameterized CASTEP jobs, extract data from the calculations, assist in visualizing the results, and expedite the process of structural modelling. Accompanied with these tools is a description on their functionality, documentation on how to get started and use the scripts, and links to video tutorials for guiding new users. Through the use of these tools, we hope to facilitate NMR crystallography and to harmonize the process across users. |
Type Of Technology | Software |
Year Produced | 2021 |
Open Source License? | Yes |
Impact | The scripts developed in this project were done so in partnership with AstraZeneca and have been tailored therefore to expedite NMR crystallography within industry settings. Since publication, the scripts have been downloaded 63 times. |
URL | https://doi.org/10.1016/j.ssnmr.2021.101761 |
Title | MagresView 2.0 |
Description | NMR crystallography visualisation app |
Type Of Technology | Webtool/Application |
Year Produced | 2022 |
Open Source License? | Yes |
Impact | It is too early to say how widely the new app will be used. The previous version of MagresView was very widely used within NMR crystallography and its successor MagresView2 is likely to be as popular if not more so. |
URL | https://stur86.github.io/magresview-2/ |
Title | Support for advanced transition state search techniques in CASTEP |
Description | Density functional theory (DFT) is a quantum mechanical simulation method that has become one of the most widely used research tools, with approximately 30,000 papers using it published each year. The CASTEP DFT code is a UK flagship code, specialised for solid materials, and is heavily used on ARCHER (300-400 active users). While support for obtaining the ground-state electronic and atomic configurations is now very good, computing transition states, reaction rates, and exploring free energy barriers with enhanced sampling were all still poorly supported in the CASTEP code before this eCSE was completed, despite their importance for a wide range of chemistry and materials science applications. In this eCSE project we have implemented two key new features in the CASTEP code to address these issues: (i) support for the extremely widely used (>12k citations) nudged elastic band (NEB) transition state search tool, augmented by a state-of-the-art robust optimizer; (ii) an interface to the i-PI universal force engine which allows CASTEP to be connected efficiently to a wide range of external codes with enhanced sampling capabilities. The new NEB implementation has also been parallelised so that it can be used efficiently on massively parallel computing centres, such as ARCHER2. We used a farm-based MPI parallelization approach where each image along the chain of states representing the reaction path runs on its own set of cores. The farms are loosely coupled, since they only need to exchange information at the end of each electronic minimisation. This leads to perfect weak scaling, validated on a 16-image system with up to 16 farms respectively. Our new code has been merged into the CASTEP development repository and will be included in the forthcoming 2022 release of the code, after which it will be widely available to ARCHER users. Key beneficients of the project include the CCP-NC, CCP9 and UKCP communities, where the new tools will aid in reconciling experimental observations with atomic-scale behaviour, helping to guide and interpret future experiments. |
Type Of Technology | Software |
Year Produced | 2022 |
Impact | The new functionality was included in the 2022 release of CASTEP, a very widely used density functional theory code. |
URL | https://www.archer2.ac.uk/ecse/reports/eCSE02-04/ |
Title | pynics |
Description | Python scripts for computing Nuclear Independent Chemical Shifts and buildup functions from Castep data. The chemical shift at which a nuclear environment appears in solid-state NMR is dependent not only on the local intramolecular interactions affecting that environment, but also on interactions with longer range features such as ring currents and hydrogen bonding. Utilising DFT GIPAW calculations, it is possible to partition the contributions of these different features to chemical shift. Further, it is possible to observe the spatial effects of these contributions, and the distance at which these contributions arise. These scripts facilitate computing such interactions. |
Type Of Technology | Software |
Year Produced | 2022 |
Open Source License? | Yes |
Impact | Not aware of any, though this specialised code continues to be downloaded from both GitHub and PyPI (> 60 downloads). |
URL | https://www.ccpnc.ac.uk/docs/nics |
Description | CCP-NC Website Refresh |
Form Of Engagement Activity | Engagement focused website, blog or social media channel |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Postgraduate students |
Results and Impact | The CCP-NC website underwent a major refresh in the second half of 2021, updating outdated content and modifying the structure of the website to better showcase the breadth of work done by the CCP-NC. This refresh included, for example, updating user guides for various software and facility support the CCP-NC provides, as well as making the software and documentation easier to access. The updated website was presented to, and approved by, the Steering Group in November 2021. |
Year(s) Of Engagement Activity | 2021 |
URL | https://www.ccpnc.ac.uk/ |
Description | Case Studies for CCP-NC Website |
Form Of Engagement Activity | Engagement focused website, blog or social media channel |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Postgraduate students |
Results and Impact | The first two (of an ongoing series of) computational NMR crystallography case studies were published on the CCP-NC website. The aim of these case studies is to showcase the breadth of research activities covered by the CCP-NC and to share some exciting examples of the potential of this growing field of research. |
Year(s) Of Engagement Activity | 2021,2022 |
URL | https://www.ccpnc.ac.uk/research/case-studies |