A Framework for the Optimal Selection of High-Throughput Data Collection Workflows by Autonomous Experimentation Systems

Casukhela, Rohan; Vijayan, Sriram; Jinschek, Joerg R.; Niezgoda, Stephen R.

doi:10.1007/s40192-022-00280-5

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“…The central concept in AE is the workflow, 29 , 30 defined as the sequence of steps and operations performed by automated laboratories or measurement tools. Generally, a workflow can combine steps performed by human and non-human agents.…”

Section: Introductionmentioning

confidence: 99%

Explainability and human intervention in autonomous scanning probe microscopy

Liu,

Ziatdinov,

Vasudevan

et al. 2023

Patterns

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Section: Introductionmentioning

confidence: 99%

Explainability and human intervention in autonomous scanning probe microscopy

Liu,

Ziatdinov,

Vasudevan

et al. 2023

Patterns

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Designing workflows for materials characterization

Kalinin,

Ziatdinov,

Ahmadi

et al. 2024

Applied Physics Reviews

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Experimental science is enabled by the combination of synthesis, imaging, and functional characterization organized into evolving discovery loop. Synthesis of new material is typically followed by a set of characterization steps aiming to provide feedback for optimization or discover fundamental mechanisms. However, the sequence of synthesis and characterization methods and their interpretation, or research workflow, has traditionally been driven by human intuition and is highly domain specific. Here, we explore concepts of scientific workflows that emerge at the interface between theory, characterization, and imaging. We discuss the criteria by which these workflows can be constructed for special cases of multiresolution structural imaging and functional characterization, as a part of more general material synthesis workflows. Some considerations for theory–experiment workflows are provided. We further pose that the emergence of user facilities and cloud labs disrupts the classical progression from ideation, orchestration, and execution stages of workflow development. To accelerate this transition, we propose the framework for workflow design, including universal hyperlanguages describing laboratory operation, ontological domain matching, reward functions and their integration between domains, and policy development for workflow optimization. These tools will enable knowledge-based workflow optimization; enable lateral instrumental networks, sequential and parallel orchestration of characterization between dissimilar facilities; and empower distributed research.

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Integrating Computational and Physical Lab Modules in Materials Science and Engineering

Brown,

Beach

2024 ASEE Annual Conference &Amp; Exposition Proceedings

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A Framework for the Optimal Selection of High-Throughput Data Collection Workflows by Autonomous Experimentation Systems

Cited by 3 publications

References 38 publications

Explainability and human intervention in autonomous scanning probe microscopy

Explainability and human intervention in autonomous scanning probe microscopy

Designing workflows for materials characterization

Integrating Computational and Physical Lab Modules in Materials Science and Engineering

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