{"id":35658184,"url":"https://github.com/ireaml/defects_workflow","last_synced_at":"2026-01-05T16:01:38.654Z","repository":{"id":218055162,"uuid":"743612289","full_name":"ireaml/defects_workflow","owner":"ireaml","description":"Code used to build the defects dataset for the publication \"Machine-learning structural reconstructions for accelerated point defect calculations\"","archived":false,"fork":false,"pushed_at":"2024-01-22T09:43:34.000Z","size":83,"stargazers_count":2,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2024-01-22T12:51:38.943Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/ireaml.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null}},"created_at":"2024-01-15T15:54:40.000Z","updated_at":"2024-01-19T14:25:42.000Z","dependencies_parsed_at":"2024-01-22T11:46:15.822Z","dependency_job_id":"94de1efb-e0bd-4adb-b601-3ed7916793cf","html_url":"https://github.com/ireaml/defects_workflow","commit_stats":null,"previous_names":["ireaml/defects_workflow"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/ireaml/defects_workflow","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ireaml%2Fdefects_workflow","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ireaml%2Fdefects_workflow/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ireaml%2Fdefects_workflow/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ireaml%2Fdefects_workflow/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ireaml","download_url":"https://codeload.github.com/ireaml/defects_workflow/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ireaml%2Fdefects_workflow/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":28217519,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2026-01-05T02:00:06.358Z","response_time":57,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2026-01-05T16:00:38.275Z","updated_at":"2026-01-05T16:01:38.649Z","avatar_url":"https://github.com/ireaml.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# `defects_workflow`\nWorkflow to run defect calculations with aiida.\n\nCurrently, it automates the following steps:\n1. Relaxation of host structure (from mp-id or user defined structure)\n2. Defect generation\n   * Defect charge states are determined based on the most common oxidation states for the element (following\n     the strategy implemented in [defectivator](https://github.com/alexsquires/defectivator)\n     by Dr Alex Squires)\n3. Screening of symmetry inequivalent interstitials.\n   This is done by relaxing the neutral state of all the symmetry inequivalent\n   configurations for a given interstitial. The following cases are filtered out:\n    * Configurations that lead to the same final structures (only one is used for later calculations)\n    * Configurations very high in energy compared to the most stable one (e.g. if \u003e 1 eV)\n4. Structure searching using shakenbreak and submission of calculations\n\n\n# Installation\n\n1. Crate conda environment (python 3.10)\n\n2. Install `aiida-core` using the [system-wide installation](https://aiida.readthedocs.io/projects/aiida-core/en/latest/intro/install_system.html#intro-get-started-system-wide-install) and using `pip` rather than `conda`.\n\n3. Install other dependencies, including `aiida-archer2-scheduler` (to use the HPC `archer2`),\n    `parsevasp`, `aiida-vasp`, `aiida-user-addons` and `defectivator`:\n```\ngit clone git@github.com:SMTG-UCL/aiida-archer2-scheduler.git\ncd aiida-archer2-scheduler\npip install -e ./\nreentry scan -r aiida\n```\n```\ngit clone https://github.com/aiida-vasp/parsevasp.git\ncd parsevasp\ngit checkout develop\ncd ../\npip install -e ./parsevasp\n```\n```\ngit clone https://github.com/aiida-vasp/aiida-vasp.git\ncd aiida-vasp\ngit checkout develop\ncd ../\npip install -e ./aiida-vasp\n```\n```\ngit clone https://github.com/SMTG-UCL/aiida-user-addons.git\ncd aiida-user-addons\ngit checkout dev\ncd ../\npip install -e ./aiida-user-addons\n```\n```\ngit clone https://github.com/alexsquires/defectivator.git\ncd defectivator\ngit checkout dev\ncd ../\npip install ./defectivator\n```\n\nRun `pip install reentry` and `reentry scan -r aiida`\n\n4. Configure `aiida-vasp` (potcars)\n\n5. Install `shakenbreak`\n```\ngit clone https://github.com/SMTG-UCL/shakenbreak.git\npip install .\n```\n\n6. Install `defects_workflow`\n```\ngit clone https://github.com/ireaml/defects_workflow.git\npip install .\n```\n\n7. Add ab-initio codes to aiida profile\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fireaml%2Fdefects_workflow","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fireaml%2Fdefects_workflow","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fireaml%2Fdefects_workflow/lists"}