X-ray fluorescence techniques in special operation modes can provide valuable quantitative insights for semiconductor related applications and can be made compatible to typical sizes of homogeneously structured metrology pads. As their dimensions are usually in the order of several 10 μm per direction, it must be ensured that no adjacent regions are irradiated or that no x-ray fluorescence radiation from adjacent areas reaches the detector. As this can be realized by using small excitation beams, a multitude of information can be retrieved from such XRF data. In addition to elemental composition, including sensitivity to sub-surface features, one can derive quantitative amounts of material and even dimensional properties of the nanostructures under study. Here, we show three different approaches for studies related to semiconductor applications that are capable to be performed on real world dies with commonly sized metrology pads.
EUV scatterometry can retrieve geometrical information from nanoscale grating structures through elastic scattering of EUV radiation and the evaluation of the diffraction intensities. Its geometry and energy range place it in between grazing incidence x-ray scattering (GISAXS) and optical critical dimension (OCD). PTB recently commissioned a new scatterometry setup for the EUV and soft x-ray region that can address sample areas below 100 × 100 μm size by using a comparably steep, grazing angle of incidence of up to 30°. At the same time, the full cone of exit angles of 30° can be detected such that also the higher orders can be recorded in scatterometry measurements. It has been commissioned at PTB’s monochromatic soft x-ray beamline at the synchrotron radiation facility BESSY II and can also be used for simultaneous x-ray fluorescence detection. Its great tunability and energy resolution allows to scan across absorption edges of the relevant semiconductor materials to increase the contrast between different materials. The nanoscale geometry of modern transistor designs features different materials and structure sizes in the single digit nanometer range. Using the information wealth of spectrally resolved scatterometry measurements from the new setup, we present data and first geometrical reconstructions of selected, complex, industry-relevant design studies. The geometrical reconstruction of these structures relies on precise measurements, modelling of the scattering process, and statistical data evaluation methods.
The increasing complexity and decreasing sizes of nanostructures in microelectronic devices challenge the existing metrology methods. Moreover, as the dimensions of nanostructures continue to decrease, the overall effect of imperfections increases. For lithographic lamellar gratings, the most characteristic type of roughness is lineedge roughness, which affects the uniformity of the line edge of the line. Grazing incidence X-Ray fluorescence (GIXRF) is a non-destructive, ensemble and element sensitive method with high sensitivity to the line shapes of lamellar nanostructures. However, the effect of line-edge roughness on the angular distribution of the GIXRF is unknown. Here, the effect of line-edge roughness of lamellar gratings on the GIXRF intensity is investigated using a series of test samples with different artificial line-edge roughness profiles. We observed that the angular distribution of the GIXRF intensity is affected by the roughness.
The characterization of nanostructures and nanostructured surfaces with high sensitivity in the sub-nm range has gained enormously in importance for the development of the next generation of integrated electronic circuits. A reliable and non-destructive characterization of the material composition and dimensional parameters of nanostructures, including their uncertainties, is strongly required. Here, an optical technique based on grazing incidence X-ray fluorescence measurements is proposed. The reconstruction of a lamellar nanoscale grating made of Si3N4 is presented as an example. This technique uses the X-ray standing wave field, which arises due to interference between the incident and the reflected radiation, as nanoscale gauge. This enables the spatial distribution of the specific elements to be reconstructed using a finite-element method for the calculation of the standing wave field inside the material. For this, the optical constants for the constituent materials of the structure are needed. We derived them from soft X-ray reflectivity measurements on an unstructured part of the wafer sample. To counteract the expensive computation of the finite-element-Maxwell-solver, a Bayesian optimizer is exploited to obtain a most efficient sampling of the searched parameter space. The method is also used to determine the uncertainties of the reconstructed parameters. The homogeneity of the sample was also analyzed by evaluating several measurement spots across the grating area. For the validation of the reconstruction results, the grating line shape was measured by means of Atomic Force Microscopy.
A parallelism is reported between reticle lifetime experiments undertaken on TNO’s EBL2 platform and wafer printing on the ASML NXE EUV scanner installed at imec. EBL2 mimics reticle impact due to exposure of ten thousand wafers in NXE representative conditions in less than a day. In-situ X-ray Photoelectron Spectroscopy (XPS) has shown that a local high-dose EUV exposure removes surface carbon and reduces ruthenium oxide to ruthenium. These effects not only happen at the directly exposed location, but equally centimeters away. Repeating XPS after a period of reticle storage outside of the vacuum, revealed regrowth of such contamination layer and re-oxidation of ruthenium. This learning based on EBL2 explains a small but significant trend noticed in critical dimension measurement results on wafer through a batch of wafers exposed on NXE, depending on the prior storage conditions of the reticle. During first exposures following reticle entry into vacuum reticle storage effects become gradually undone. Both storage-induced mask contamination effects are shown to build-up beyond one month. Local effects of the high-dose EUV exposure remain measurable by EUV reflectometry after several weeks of storage in air.
In next-generation EUV imaging for foundry N5 dimensions and beyond, inherent pitch- and orientation-dependent effects on wafer level will consume a significant part of the lithography budget using the current Ta-based mask. Mask absorber optimization can mitigate these so-called mask 3D effects [1-3]. Last year at the SPIE Photomask and EUVL conference [4,5], EUV mask absorber change is recognized by the community as key enabler of next-generation EUV lithography. Through rigorous lithographic simulations we have identified regions, based on the material optical properties and their gain in imaging performance compared to the reference Ta-based absorber [6]. In addition, we have established a mask absorber requirement test flow to validate the candidate material to the full mask supply chain. In this paper we discuss in more detail Te- and Ru- based alloys which cover these different improvement regions. Candidate materials are evaluated on film morphology, stability during combined hydrogen and EUV loading, and thermal and chemical durability. The EUV optical constants are measured by EUV reflectometry, and preliminary results of plasma etching are shown to enable patterning.
For the reliable fabrication of the current and next generation of nanostructures it is essential to be able to determine their material composition and dimensional parameters. Using the grazing incidence X-ray fluoresence technique, which is taking advantage of the X-ray standing wave field effect, nanostructures can be investigated with a high sensitivity with respect to the structural and elemental composition. This is demonstrated using lamellar gratings made of Si3N4. Rigorous field simulations obtained from a Maxwell solver based on the finite element method allow to determine the spatial distribution of elemental species and the geometrical shape with sub-nm resolution. The increasing complexity of nanostructures and demanded sensitivity for small changes quickly turn the curse of dimensionality for numerical simulation into a problem which can no longer be solved rationally even with massive parallelisation. New optimization schemes, e.g. machine learning, are required to satisfy the metrological requirements. We present reconstruction results obtained with a Bayesian optimization approach to reduce the computational effort.
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