Materials Discovery in Combinatorial and High-throughput Synthesis and Processing: A New Frontier for SPM

TL;DR

This paper discusses how scanning probe microscopy (SPM) can revolutionize materials discovery by enabling high-throughput, quantitative characterization in combinatorial and accelerated synthesis processes, bridging the gap from material design to analysis.

Contribution

It highlights the potential of SPM techniques to meet the demands of modern materials synthesis and provides an overview of applicable methods and future challenges.

Findings

SPM offers high-throughput, quantitative data for material characterization.

Emerging SPM methods are suited for combinatorial and accelerated synthesis applications.

SPM will be integral in closing the loop from material prediction to synthesis and analysis.

Abstract

For over three decades, scanning probe microscopy (SPM) has been a key method for exploring material structures and functionalities at nanometer and often atomic scales in ambient, liquid, and vacuum environments. Historically, SPM applications have predominantly been downstream, with images and spectra serving as a qualitative source of data on the microstructure and properties of materials, and in rare cases of fundamental physical knowledge. However, the fast-growing developments in accelerated material synthesis via self-driving labs and established applications such as combinatorial spread libraries are poised to change this paradigm. Rapid synthesis demands matching capabilities to probe structure and functionalities of materials on small scales and with high throughput. SPM inherently meets these criteria, offering a rich and diverse array of data from a single measurement. Here, we overview SPM methods applicable to these emerging applications and emphasize their quantitativeness, focusing on piezoresponse force microscopy, electrochemical strain microscopy, conductive, and surface photovoltage measurements. We discuss the challenges and opportunities ahead, asserting that SPM will play a crucial role in closing the loop from material prediction and synthesis to characterization.