# Multiple Parameter Dynamic Photoresponse Microscopy for data-intensive optoelectronic measurements of van der Waals heterostructures

## TL;DR

This paper introduces MPDPM, a high-throughput microscopy technique combining ultrafast lasers and automation to efficiently characterize the complex photoresponse of van der Waals heterostructures, enabling comprehensive data collection for advanced material analysis.

## Contribution

The paper presents a novel multi-parameter microscopy method that integrates ultrafast laser technology and automation for detailed optoelectronic measurements of 2D heterostructures.

## Key findings

- Successful implementation of MPDPM on vdW heterostructures
- Generation of large, complex data sets requiring advanced analysis
- Demonstration on graphene-boron nitride-graphite heterostructure photocell

## Abstract

Quantum devices made from van der Waals (vdW) heterostructures of two dimensional (2D) materials may herald a new frontier in designer materials that exhibit novel electronic properties and unusual electronic phases. However, due to the complexity of layered atomic structures and the physics that emerges, experimental realization of devices with tailored physical properties will require comprehensive measurements across a large domain of material and device parameters. Such multi-parameter measurements require new strategies that combine data-intensive techniques - often applied in astronomy and high energy physics - with the experimental tools of solid state physics and materials science. We discuss the challenges of comprehensive experimental science and present a technique, called Multi-Parameter Dynamic Photoresponse Microscopy (MPDPM), that utilizes ultrafast lasers, diffraction limited scanning beam optics, and hardware automation to characterize the photoresponse of 2D heterostructures in a time efficient manner. Using comprehensive methods on vdW heterostructures results in large and complicated data sets; in the case of MPDPM, we measure a large set of images requiring advanced image analysis to extract the underlying physics. We discuss how to approach such data sets in general, and in the specific case of a graphene - boron nitride - graphite heterostructure photocell.