Energy Landscape of Nanocrystal-Based Devices Revealed by Operando Photoemission Microscopy
Mariarosa Cavallo a, Dario Mastrippolito a b, Erwan Bossavit a b, Pavel Dudin b, Yoann Prado a, Jose Avila b, Emmanuel Lhuillier a, Debora Pierucci a
a Sorbonne Université, CNRS, Institut des NanoSciences de Paris, 75005 Paris
b Synchrotron SOLEIL, L'Orme des Merisiers, Départementale 128, 91190 Saint-Aubin, France
Materials for Sustainable Development Conference (MATSUS)
Proceedings of MATSUS Spring 2025 Conference (MATSUSSpring25)
Advances in Nanocrystals: Fundamental approaches and technological perspectives - #NCAdv
Sevilla, Spain, 2025 March 3rd - 7th
Organizers: Carmelita Rodà and Matteo Zaffalon
Invited Speaker, Debora Pierucci, presentation 084
DOI: https://doi.org/10.29363/nanoge.matsusspring.2025.084
Publication date: 16th December 2024

Colloidal nanocrystals (NCs), with their tunable optical properties, have emerged as essential components in modern optoelectronic devices [1]. While traditional optimization approaches focus on pristine material properties, they often neglect the influence of the complex operational environment, where NCs interact with transport layers, electrodes, and applied electric fields. This gap highlights the need for advanced techniques capable of probing the electronic structure of devices in situ and operando.

In this talk, I will show how scanning photoemission microscopy [2] addresses this need, providing unique insights into the energy landscape of NC-based devices during operation with sub-micron spatial resolution [3]. By unveiling the whole device energy landscape, this technique reveals key parameters such as diode built-in potential and transistor lever arm. Beyond scalar information, the high spatial resolution of this technique enables access to the vectorial distribution of the electric field, uncovering the current pathways within the NC film [4].

This approach significantly advances our ability to study nanocrystal-based devices under realistic conditions, fostering a deeper understanding that can drive rational design and performance optimization.

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