Nanoworks: A multi-scale python-based orchestrator for materials science simulations

LİŞESİVDİN B., LİŞESİVDİN S. B.

Computational Condensed Matter, cilt.48, 2026 (ESCI, Scopus) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 48
  • Basım Tarihi: 2026
  • Doi Numarası: 10.1016/j.cocom.2026.e01362
  • Dergi Adı: Computational Condensed Matter
  • Derginin Tarandığı İndeksler: Emerging Sources Citation Index (ESCI), Scopus
  • Anahtar Kelimeler: ASE, Automation, Density functional theory (DFT), GPAW, High-throughput screening, Machine learning potentials, Molecular dynamics, Nanoworks, Python
  • Gazi Üniversitesi Adresli: Evet

Özet

Atomic simulations play an important role in modern materials science for the discovery of new structures and the determination of their properties. This study introduces Nanoworks , a Python package resulting from a comprehensive re-architecture and expansion of the capabilities of the previously developed gpaw-tools Python package. Unlike its predecessor, gpaw-tools, Nanoworks aims to be not just a DFT interface, but an integrated simulation orchestrator that combines quantum-mechanical (DFT), classical molecular dynamics (MD), and machine-learned interatomic potential (MLIP)-based calculations under one roof. The software architecture of the Nanoworks package, transformed into a secure, modular structure, performs calculations of electronic structure, optical properties, elastic properties, phonon dispersion, dynamics of large-scale multi-atomic systems, and MLIP through the dftsolve , mdsolve , and mlsolve main modules, using standardized, simplified input files. Nanoworks aims to accelerate high-performance material screening studies by enabling educators and researchers to focus on scientific problems rather than coding details.