Tailor-made electrode work functions are indispensable to control energy-level offsets at the interfaces of (opto-)electronic devices. We show by means of photoelectron spectroscopy that several nanometer thick layers of the organic semiconductor 1,4,5,8,9,3,6,7,10, on virtually all substrates provide holeinjecting electrodes with work functions of around 5.60 eV. This substrate-independent energy-level alignment is due to a relatively large density of gap states in HAT-CN thin films, which is clearly visible in the photoemission data. Furthermore, this additional density of occupied states makes the wide-gap semiconductor thin films sufficiently conductive for electrode applications. Moreover, our study highlights a quite intriguing energy-level alignment scenario as the Fermi-level in HAT-CN thin films is located far from the midgap position, this is rather uncommon for undoped organic semiconductor thin films.

Low-voltage transmission electron microscopy (≤80 kV) has many applications in imaging beam-sensitive samples, such as metallic nanoparticles, which may become damaged at higher voltages. To improve resolution, spherical aberration can be corrected for in a scanning transmission electron microscope (STEM); however, chromatic aberration may then dominate, limiting the ultimate resolution of the microscope. Using image simulations, we examine how a chromatic aberration corrector, different objective lenses, and different beam energy spreads each affect the image quality of a gold nanoparticle imaged at low voltages in a spherical aberration-corrected STEM. A quantitative analysis of the simulated examples can inform the choice of instrumentation for low-voltage imaging. We here demonstrate a methodology whereby the optimum energy spread to operate a specific STEM can be deduced. This methodology can then be adapted to the specific sample and instrument of the reader, enabling them to make an informed economical choice as to what would be most beneficial for their STEM in the cost-conscious landscape of scientific infrastructure.

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