Tools

The Amber plugin for AiiDA aims to enable the capture and sharing of the full provenance of data when parameterising and running molecular dynamics simulations.

A tool to visualize predicted NMR parameters in an intuitive, graphically accessible way and convert these parameters into input files for the most common NMR simulation programs. SSNMR parameters like magnetic shielding and electric field gradient can be visually represented as scaled ellipsoids super-imposed on the crystal structure for visualisation.

This demo application will create an SQLite database that can be used to include aiida archive files produced from several aiida plugins (aiida -gromacs and -amber presently). This database can be used to store and explore archive files and gives a taster for how biomolecular MD simulation data provenance can be stored for multiple research projects.

Transferring data is crucial for researchers to share information with colleagues and back up their work. However, setting up specialized software for this can be challenging. The Data Transfer and Synchronisation (DSync) tool simplifies this process by bundling the necessary software for transferring data to and from S3 storage - commonly used in cloud computing - into a single container image which can be run using Docker. This makes it easier for researchers to manage data transfers without having to install and configure the software themselves.

Transferring data is crucial for researchers to share information with colleagues and back up their work. However, setting up specialized software for this can be challenging. The Data Transfer and Synchronisation (DSync) tool simplifies this process by bundling the necessary software for transferring data to and from S3 storage - commonly used in cloud computing - into a single container image which can be run using Apptainer and Singularity. This makes it easier for researchers to manage data transfers without having to install and configure the software themselves.

The GROMACS plugin for AiiDA aims to enable the capture and sharing of the full provenance of data when parameterising and running molecular dynamics simulations.

PSDI Data Conversion is your one stop shop for file format conversion. This enables users to seamlessly convert between different file formats and view information about the quality of the proposed conversion. The PSDI Command Line interface for Data Conversion application can be installed and run on your own computing infrastructure. It contains all of the same file conversion functionality of our online service but without the need to upload your data to PSDI and without any restrictions on file sizes.

PSDI Data Conversion is your one stop shop for file format conversion. This enables users to seamlessly convert between different file formats and view information about the quality of the proposed conversion. The PSDI Python Library for Data Conversion is available via PyPi and can be installed and run on your own computing infrastructure, enabling you to include a data conversion in your own pipelines. It contains all of the same file conversion functionality of our online service but without the need to upload your data to PSDI and without any restrictions on file sizes.

PSDI Data Conversion is your one stop shop for file format conversion. This enables users to seamlessly convert between different file formats and view information about the quality of the proposed conversion. The PSDI Python/Flask application for Data Conversion can be installed and run on your own computing infrastructure using the Flask framework. It contains all of the same file conversion functionality of our online service, complete with a graphical user interface, but without the need to upload your data to PSDI and without any restrictions on file sizes.

Soprano is a Python library to help scientists working with crystallography and simulations to generate, manipulate, run calculations on and analyse large data sets of crystal structures. It provides a number of functionalities to help automate many common tasks in computational crystallography, including NMR parameter manipulation. Documentation and tutorials are provided to help users get started with the library.

The code for the thematic portal is open source, enabling communities to customize it to meet their specific needs. Its flexibility allows for rapid deployment and personalization, including logos, custom headings, and tailored functionality. The open-source licensing ensures communities can download, modify, and adapt the code further. We offer support for deployment on institutional servers or commercial platforms.

Janus_core provides versatile tools for exploring a range of machine learning interatomic potentials. It can be accessed through the command line, Python scripts, Jupyter Notebooks, or a web interface. The platform supports various tasks, from basic calculations like single-point energies and geometry optimization to more advanced analyses, such as phonon calculations, molecular dynamics simulations, and nudged elastic band methods.

AiiDA-MLIP is a plugin for AiiDA, a versatile workflow management system designed for simulations in materials and molecular sciences. Beyond managing workflows, AiiDA distinguishes itself from traditional tools by providing detailed data provenance, ensuring transparency and reproducibility in simulations. AiiDA-MLIP integrates the Janus core into the AiiDA ecosystem, enabling seamless utilization of machine-learned interatomic potentials (MLIPs) within this robust framework.

abcd, Data Management for Machine Learning Interatomic Potentials (MLIP), offers a suite of tools that allow users to programmatically import data from a repository and utilize it on their local infrastructure. This enables exploration of data in ways that would be too resource-intensive for a general service. Designed specifically for machine-learned interatomic potentials, abcd supports both OpenSearch and MongoDB as backend options, giving users flexibility in their setup. The tool is developed in collaboration with the University of Cambridge.

The DL_MONTE Container Image enables users to run the Monte Carlo molecular simulation program DL_MONTE on their own computing infrastructure using Docker. The tool supports many Monte Carlo methods, including grand-canonical Monte Carlo and advanced free energy techniques such as Wang-Landau. The tool supports many types of interatomic interactions facilitating the modelling of a wide range of materials and fluids. The container enables users to run DL_MONTE simulations directly with input files, removing the need to manually compile a DL_MONTE binary from the source code.

The DL_MONTE Container Image enables users to run the Monte Carlo molecular simulation program DL_MONTE on their own computing infrastructure using Singularity and Apptainer. The tool supports many Monte Carlo methods, including grand-canonical Monte Carlo and advanced free energy techniques such as Wang-Landau. The tool supports many types of interatomic interactions facilitating the modelling of a wide range of materials and fluids. The container enables users to run DL_MONTE simulations directly with input files, removing the need to manually compile a DL_MONTE binary from the source code.

This container image enables users to run the computational chemistry program Metadise on their own computing infrastructure using Docker. Metadise stands for 'Minimum Energy Technique Applied to Dislocation, Interface and Surface Energies'. The program has multiple uses. For instance it can be used to model dislocations, surfaces and grain boundaries at the atomic scale using force fields; and it can be used to create input files for other computational chemistry programs. This container image enables users to use Metadise directly with Metadise input files, removing the need to manually compile Metadise from its source code.

This container image enables users to run the computational chemistry program Metadise on their own computing infrastructure using Singularity or Apptainer. Metadise stands for 'Minimum Energy Technique Applied to Dislocation, Interface and Surface Energies'. The program has multiple uses. For instance it can be used to model dislocations, surfaces and grain boundaries at the atomic scale using force fields; and it can be used to create input files for other computational chemistry programs. This container image enables users to use Metadise directly with Metadise input files, removing the need to manually compile Metadise from its source code.