The semiconductor industry plans to keep fabricating integrated circuits, progressively decreasing there features size, by employing extreme ultraviolet lithography (EUVL). With this method, new designs and concepts for photoresist materials need to be conceived. In this work, we explore an alternative concept to the classic photoresist material by using an organic self-assembled monolayer (SAM) on a gold substrate. The monolayer, composed of a richly fluorinated thiol sensitive to low-energy electrons, is adsorbed on the Au substrate which acts as main EUV-absorber and as the source of photoelectrons and secondary electrons. We investigate the stability of the SAM adsorbed on gold towards EUV radiation by means of in-situ photoelectron spectroscopy. The photoelectron spectra indicate that the monolayer attenuates a significant amount of primary electrons generated in the gold layer. The spectral evolution upon EUV irradiation indicates that the SAM loses a significant amount of its initial fluorine content (ca. 40% at 200 mJ/cm2). We attribute these chemical changes mostly to the interaction with the electrons generated in the thiol/Au system.@en

Monte Carlo simulations are frequently used to describe electron–matter interaction in the 0–50 keV energy range. It often takes hours to simulate electron microscope images using first-principle physical models. In an attempt to maintain a reasonable speed, empirical models are sometimes used. We present an open-source software package with first-principle physical models, which can run on GPUs for fast results. Typical electron microscope images can be obtained in minutes instead of hours on consumer-grade hardware, without any loss of accuracy.@en

Large-scale electron microscopy (EM) allows analysis of both tissues and macromolecules in a semi-automated manner, but acquisition rate forms a bottleneck. We reasoned that a negative bias potential may be used to enhance signal collection, allowing shorter dwell times and thus increasing imaging speed. Negative bias potential has previously been used to tune penetration depth in block-face imaging. However, optimization of negative bias potential for application in thin section imaging will be needed prior to routine use and application in large-scale EM. Here, we present negative bias potential optimized through a combination of simulations and empirical measurements. We find that the use of a negative bias potential generally results in improvement of image quality and signal-to-noise ratio (SNR). The extent of these improvements depends on the presence and strength of a magnetic immersion field. Maintaining other imaging conditions and aiming for the same image quality and SNR, the use of a negative stage bias can allow for a 20-fold decrease in dwell time, thus reducing the time for a week long acquisition to less than 8 h. We further show that negative bias potential can be applied in an integrated correlative light electron microscopy (CLEM) application, allowing fast acquisition of a high precision overlaid LM-EM dataset. Application of negative stage bias potential will thus help to solve the current bottleneck of image acquisition of large fields of view at high resolution in large-scale microscopy.@en

Background: Monte Carlo simulations of scanning electron microscopy (SEM) images ignore most surface effects, such as surface plasmons. Previous experiments have shown that surface plasmons play an important role in the emission of secondary electrons (SEs).Aim: We investigate the influence of incorporating surface plasmons into simulations of low-voltage critical dimension SEM (CD-SEM).Approach: We use a modified inelastic scattering model, derived for infinite flat surfaces, and apply it to nonflat, but smooth, geometries. This simplification captures most qualitative effects, including both surface plasmons and a reduced interaction with bulk plasmons near interfaces.Results: We find that the SE signal hardly changes when surface interactions are turned on for a perpendicularly incident beam. When the incident beam is perfectly parallel to a surface, the SE signal does significantly increase. However, the beam must be extremely close to the surface for this effect to be appreciable. An SEM is unable to produce a beam that is both narrow and parallel enough to be noticeably affected.Conclusions: The position of edges may appear shifted under specific circumstances. In realistic situations, it is unlikely to be a large effect.@en

Background: Line-edge roughness (LER) is often measured from top-down critical dimension scanning electron microscope (CD-SEM) images. The true three-dimensional roughness profile of the sidewall is typically ignored in such analyses. Aim: We study the response of a CD-SEM to sidewall roughness (SWR) by simulation. Approach: We generate random rough lines and spaces, where the SWR is modeled by a known power spectral density. We then obtain corresponding CD-SEM images using a Monte Carlo electron scattering simulator. We find the measured LER from these images and compare it to the known input roughness. Results: For isolated lines, the SEM measures the outermost extrusion of the rough sidewall. The result is that the measured LER is up to a factor of 2 less than the true on-wafer roughness. The effect can be modeled by making a top-down projection of the rough edge. Our model for isolated lines works fairly well for a dense grating of lines and spaces as long as the trench width exceeds the line height. Conclusions: In order to obtain and compare accurate LER values, the projection effect of SWR needs to be taken into account. @en

Line-edge roughness (LER) is often measured from top-down critical dimension scanning electron microscope (CD-SEM) images. The true three-dimensional roughness profile of the sidewall is typically ignored in such analyses. We study the response of a CD-SEM to sidewall roughness (SWR) by simulation. We generate random rough lines and spaces, where the SWR is modelled by a known power spectral density. We then obtain corresponding CD-SEM images using a Monte Carlo electron scattering simulator. We find the measured LER from these images, and compare it to the known input roughness. We find that, for isolated lines, the SEM measures the outermost extrusion of the rough sidewall. The result is that the measured LER is up to a factor 2 less than the true on-wafer roughness. The effect can be accurately modelled by making a top-down projection of the rough edge. Our model for isolated lines works fairly well for a dense grating of lines and spaces, as long as the trench width exceeds the line height.@en

We have investigated the contributions of surface effects to Monte Carlo simulations of top-down scanning electron microscopy (SEM) images. The elastic and inelastic scattering mechanisms in typical simulations assume that the electron is deep in the bulk of the material. In this work, we correct the inelastic model for surface effects. We use a model for infinite flat surfaces, and apply it to non-flat, but smooth, geometries. Though this is a simplification, it captures most qualitative differences to the bulk model, including coupling to surface plasmons. We find that this correction leads to an increased SE signal near a feature's sidewall in low-voltage critical dimension SEM (CD-SEM). The effect is strongest for low beam energies. Due to some of the assumptions in our model, we are unable to quantitatively predict the extent by which the signal from the sidewall is enhanced. The enhancement of signal from the sidewall may be large enough to cause the measured edge position to shift significantly.@en

Electrons with an energy ranging from 0 to 50 keV are among the most versatile tools in nanotechnology. A common example is the scanning electron microscope (SEM), which focuses an electron beam with an energy ranging from several hundred eV to tens of keV on a sample. When landing on the sample, the electrons in the beam penetrate the material. They can excite secondary electrons in the material, for example by ionization. Some of the electrons escape the sample again and reach a detector, where a high-resolution image of the sample is formed. Thanks to the small wavelength of electrons, a SEM is able to achieve single nanometre resolution while conventional optical microscopes are limited to hundreds of nanometres....@en