Publication date: 11th March 2026
Non-fullerene acceptor (NFA) based systems have enabled significant advancements in the field of organic photovoltaics. Understanding how nanoscale morphology and local electronic properties influence device performance requires characterization techniques capable of probing multiple physical properties with high spatial resolution. Scanning Probe Microscopy (SPM) provides such a capability by enabling local measurements of mechanical, chemical, and electronic properties at the nanoscale. However, characterization of NFA active layers remains challenging due to the small domain size and high degree of intermixing.
In this work, we demonstrate how correlative analysis using multiple SPM modes can investigate complex relationships between morphology, chemical composition, mechanical, electrical, and photovoltaic local properties in model systems. Peak Force Tapping is used to identify different phases based on their nanomechanical properties. AFM-IR provides information on the spatial distribution of the donor and acceptor components through detection of local thermal expansion induced by infrared absorption at selected wavenumber. Photoconductive AFM measurements are used to probe the nanoscale response under illumination, providing information about the local photocurrent generation. Kelvin Probe Force Microscopy (KPFM) is used to distinguish the two materials based on differences in their work function, and measurements performed in the dark and under illumination enable extraction of the local photovoltage.
By the correlative analysis of these properties, a deeper understanding of the organization of the donor and acceptor within the active layer is possible. This original approach enables multichannel properties extraction that can help optimize and design higher efficient devices for the future.
This research was partially funded by the F.R.S. – FNRS Grands Equipements and F.R.S. – FNRS Missions Out (PL) and In (EM)
We acknowledges the Swedish Research Council for financial support of the project (grant nr. 2021−04798). For financial support of the research infrastructure the authors thank the Knut and Alice Wallenberg Foundation (grant nr. 2016.0059).
