funsies: A minimalist, distributed and dynamic workflow engine

Lavigne, Cyrille; Aspuru‐Guzik, Alán

doi:10.21105/joss.03274

Cited by 2 publications

(1 citation statement)

References 12 publications

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“…The integration of automated workflows has flourished within the field of computational chemistry, where the automation of repetitive and error-prone tasks is straightforward due to the programmatic nature of the field. This is evident in the emergence of tools such as AiiDA, 95 Fireworks 96 and Snakemake 97 among others, [98][99][100][101][102][103][104][105][106][107] which excel in constructing and managing software workflows for ab initio simulations. On the experimental side, autonomous chemical laboratories constitute an emerging field where the adoption of such orchestration techniques has been hampered by the physical challenges inherent to wet laboratories, the lack of an orchestration standard, and the scarcity of resources for automated instrumentation.…”

Section: Orchestrationmentioning

confidence: 99%

Self-Driving Laboratories for Chemistry and Materials Science

Tom,

Schmid,

Baird

et al. 2024

Preprint

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Self-driving laboratories (SDLs) promise an accelerated application of the scientific method. Through the automation of experimental workflows, along with the autonomization of experiment planning, SDLs hold the potential to greatly accelerate research in chemistry and materials discovery. This review article provides an in-depth analysis of the state-of-the-art in SDL technology, its applications across various scientific disciplines, and the potential implications for research, and industry. This review additionally provides an overview of the enabling technologies for SDLs, including their hardware, software, and integration with laboratory infrastructure. Most importantly, this review explores the diverse range of scientific domains where SDLs have made significant contributions, from drug discovery and materials science to genomics and chemistry. We provide a comprehensive review of existing real-world examples of SDLs, their different levels of automation, and the challenges and limitations associated with each domain.

show abstract

Section: Orchestrationmentioning

confidence: 99%

Self-Driving Laboratories for Chemistry and Materials Science

Tom,

Schmid,

Baird

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

Self-Driving Laboratories for Chemistry and Materials Science

Tom,

Schmid,

Baird

et al. 2024

Chem. Rev.

View full text Add to dashboard Cite

Self-driving laboratories (SDLs) promise an accelerated application of the scientific method. Through the automation of experimental workflows, along with autonomous experimental planning, SDLs hold the potential to greatly accelerate research in chemistry and materials discovery. This review provides an in-depth analysis of the state-of-the-art in SDL technology, its applications across various scientific disciplines, and the potential implications for research and industry. This review additionally provides an overview of the enabling technologies for SDLs, including their hardware, software, and integration with laboratory infrastructure. Most importantly, this review explores the diverse range of scientific domains where SDLs have made significant contributions, from drug discovery and materials science to genomics and chemistry. We provide a comprehensive review of existing real-world examples of SDLs, their different levels of automation, and the challenges and limitations associated with each domain.

show abstract

funsies: A minimalist, distributed and dynamic workflow engine

Abstract: Large-scale, high-throughput computational investigations are increasingly common in chemistry and physics. Until recently, computational chemistry was primarily performed using all-in-one monolithic software packages (

Cited by 2 publications

References 12 publications

Self-Driving Laboratories for Chemistry and Materials Science

Self-Driving Laboratories for Chemistry and Materials Science

Self-Driving Laboratories for Chemistry and Materials Science

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