Tools


Computational tools offered as a service: no download, no installation, but click-and-run.

Authors:  Kristjan Eimre, Jusong Yu, Gabriel M. Nascimento, Elsa Passaro, Sebastiaan P. Huber, Giovanni Pizzi, Nicola Marzari
Description: A tool to generate the input file of the Quantum ESPRESSO PWscf code and to visualize the corresponding structure.
Authors:  Yoyo Hinuma, Giovanni Pizzi, Yu Kumagai, Fumiyasu Oba, Isao Tanaka
Description: A k-path finder that provides band paths compatible with space group symmetry, and an interactive 3D visualizer.
Authors:  Casper Welzel Andersen
Description: A friendly client to search through materials databases and other implementations exposing an OPTIMADE RESTful API.
Authors:  Snehal Kumbhar, Giovanni Pizzi, Thibault Sohier, Henrique Miranda
Description: A tool for the interactive visualization and inspection of lattice vibrations.

Contributed Tools

The tools below have been contributed and are maintained by authors affiliated with the Materials Cloud partners.

Authors:  K. R. Briling, O. Hernandez-Cuellar, J. W. Abbott, M. Ceriotti, C. Corminboeuf
Description: This tool predicts the electronic density of molecules using a symmetry-adapted Gaussian process regression model.
Authors:  O. Hernandez-Cuellar, Y. Cho, R. Laplaza, L. O. Marsh, S. Vela, C. Corminboeuf
Description: A tool to interpret crystallographic data and retrieve the connectivity, total charge, and spin of molecular complexes and their components including the oxidation state (OS) of metal atoms and the charge of ligands.
Authors:  Mohammad Tohidi Vahdat, Kumar Agrawal Varoon, Giovanni Pizzi
Description: This tool allows users to upload the bulk crystal structure in several standard formats (or to choose from a few examples), and then layered structures are identified based on geometrical criteria. Finally, after generating feature vectors representing the crystal structure, the tool uses a machine learning model to see if the crystal structure can be exfoliated or have high binding energy.
Authors:  Leo P. Goutte, Oleg V. Yazyev, QuanSheng Wu
Description: A tunable model for the energy spectrum of twisted mixed multilayer graphene.
Authors:  K. M. Jablonka, D. Ongari, S. M. Moosavi, B. Smit
Description: This tool takes a crystal structure and predicts the oxidation state for each metal site.
Authors:  G. Pizzi, S. Milana, A. C. Ferrari, N. Marzari, M. Gibertini
Description: A tool to upload the bulk crystal structure of a layered material and determine the symmetry of the inter-layer force-constant matrices and the corresponding optical-activity fan diagram.
Authors:  Kristiāns Čerņevičs, Valeria Granata, Oleg V. Yazyev
Description: A tool for building and analyzing electronic transport properties of graphene nanoribbon junctions.
Authors:  Seyed Mohamad Moosavi, Leopold Talirz, Berend Smit
Description: A tool for optimizing the experimental synthesis conditions for metal-organic frameworks using machine learning and genetic algorithms.
Authors:  David M. Wilkins, Andrea Grisafi, Yang Yang, Ka Un Lao, Robert A. DiStasio Jr., Michele Ceriotti
Description: A machine learning framework for the prediction of molecular polarizabilities based on comparisons of local environments.
Authors:  Andrea Anelli, Félix Musil, Federico M. Paruzzo, Albert Hofstetter, Sandip De, Edgar Engel, Lyndon Emsley, Michele Ceriotti
Description: A machine learning model to predict the isotropic chemical shielding of molecular crystals containing H, C, N, O and S, including the uncertainty of the prediction, and an interactive 3D visualiser.