Designing Workflows for Materials Characterization

TL;DR

This paper discusses the development of universal, knowledge-based workflows for materials characterization that integrate theory, imaging, and experimental data, facilitated by emerging cloud labs and user facilities.

Contribution

It introduces concepts and criteria for constructing scientific workflows at the interface of theory and experiment, emphasizing universal frameworks and hyper-languages for workflow design.

Findings

Proposes criteria for multi-resolution imaging workflows

Highlights the role of cloud labs in workflow disruption

Suggests development of universal hyper-languages for lab operations

Abstract

Experimental science is enabled by the combination of synthesis, imaging, and functional characterization. Synthesis of a new material is typically followed by a set of characterization methods 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 multi-resolution structural imaging and structural and functional characterization. Some considerations for theory-experiment workflows are provided. We further pose that the emergence of user facilities and cloud labs disrupt the classical progression from ideation, orchestration, and execution stages of workflow development and necessitate development of universal frameworks for workflow design, including universal hyper-languages describing laboratory operation, 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.