The Interoperability Challenge in DFT Workflows Across Implementations
Interoperability and cross‐validation remain significant challenges in the computational materials discovery community. In this context, we introduce a common input/output standard designed for internal translation by various workflow managers (AiiDA, PerQueue, Pipeline Pilot, and SimStack) to produce results in a unified schema. This standard aims to enable engine‐agnostic workflow execution across multiple density functional theory (DFT) codes, including CASTEP, GPAW, Quantum ESPRESSO, and VASP. As a demonstration, we have implemented a workflow to calculate the open‐circuit voltage across several battery cathode materials using the proposed universal input/output schema. We analyze and resolve the challenges of reconciling energetics computed by different DFT engines and document the code‐specific idiosyncrasies that make straightforward comparisons difficult. Motivated by these challenges, we outline general design principles for robust automated DFT workflows. This work represents a practical step toward more reproducible and interoperable workflows for high‐throughput materials screening, while highlighting challenges of aligning electronic properties, especially for nonpristine structures.
Authors
- Johan M. Carlsson (ORCID: https://orcid.org/0000-0002-1596-0923)
- Manuel Dillenz (ORCID: https://orcid.org/0000-0002-4901-154X)
- Felix Hanke (ORCID: https://orcid.org/0000-0002-4155-5980)
- Ivano E. Castelli (ORCID: https://orcid.org/0000-0001-5880-5045)
- Eibar Flores (ORCID: https://orcid.org/0000-0003-2954-1233)
- Hamidreza Hajiyani (ORCID: https://orcid.org/0000-0002-1150-0567)
- Wolfgang Wenzel (ORCID: https://orcid.org/0000-0001-9487-4689)
- Simon Krarup Steensen (ORCID: https://orcid.org/0009-0008-8649-3542)
- Celso R. C. Rêgo
- Juan Maria Garcia Lastra
- Tushar Singh Thakur
- Nicola Marzari
- Tejs Vegge
- Giovanni Pizzi
Institutions
- Karlsruhe Institute of Technology (DE)
- SINTEF (NO)
- Paul Scherrer Institute (CH)
- Dassault Systèmes (Germany) (DE)
- Kerntechnische Entsorgung Karlsruhe (Germany) (DE)
- Institute of Nanotechnology (GB)
- Dassault Systèmes (United Kingdom) (GB)
- École Polytechnique Fédérale de Lausanne (CH)
- Technical University of Denmark (DK)
Publication Details
- Journal
- Advanced Intelligent Discovery
- Published
- 2026-03-27
- DOI
- https://doi.org/10.1002/aidi.202500232
- Primary Topic
- Machine Learning in Materials Science
- Type
- article
- Field-Weighted Citation Impact
- 0.00