Abstract

Lensless imaging with short-wavelength light is a promising method for achieving high-resolution, chemically sensitive images of a wide variety of samples. The use of 13 nm illumination is of particular interest for materials science and the imaging of next-generation nanofabricated devices. Prior to this work, there was an unmet need for a microscope that can image general samples with extreme ultraviolet light, which requires a reflection geometry. Here, we fulfill this need by performing lensless imaging using a 13 nm high-harmonic beam at grazing incidence, where most materials are reflective. Furthermore, we demonstrate to our knowledge the first 13 nm reflection-mode lensless microscope on a tabletop by using a compact high-harmonic generation source. Additionally, we present an analytic formalism that predicts when general lensless imaging geometries will yield Nyquist sampled data. Our grazing-incidence ptychographic approach, which we call GLIDER, provides the first route for achieving wide field-of-view, high-resolution, lensless images of general samples with extreme ultraviolet and soft x-ray light.

© 2017 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

1. INTRODUCTION

In recent years, extreme ultraviolet (EUV) and x-ray coherent diffraction imaging (CDI) [1,2], particularly using ptychography [3,4], has emerged as a robust method for imaging extended samples with high-contrast, diffraction-limited spatial resolution and chemical sensitivity [59]. However, most imaging with these wavelengths has been performed in a transmission geometry [1013], which requires relatively thin samples (<1  μm). Imaging in reflection with this wavelength range has been less explored due to the low EUV/soft x-ray reflectivity of most samples near normal incidence, and the reconstruction challenges that arise from reflection geometries. A few notable reflection-mode experiments have been performed, allowing imaging at or near the surface of arbitrarily thick samples. These experiments have been performed both at synchrotrons [1417] and using tabletop high-harmonic generation sources [5,1820].

Near-normal-incidence, 13 nm reflection-mode CDI microscopes [1517] have been implemented at synchrotron sources for imaging lithography masks. This geometry is effective for this application because masks are printed on multilayer mirrors designed for high reflectivity of 13 nm light. However, near normal incidence, general samples (i.e., those not fabricated on a multilayer mirror) typically cannot be imaged because of their low reflectivity (typically 0.001%–0.1% [21]). A grazing incidence was used in Ref. [14], utilizing a hard x-ray synchrotron source. However, this experimental geometry was sample-specific and not suitable for imaging general specimens since single-diffraction-pattern CDI was used, necessitating an isolated object.

Here we demonstrate the first general CDI microscope, to our knowledge, at the technologically important 13 nm wavelength by imaging at grazing incidence where most materials are reflective. This work also represents to our knowledge the first reflection-mode 13 nm lensless imaging performed at the tabletop scale. Furthermore, we develop the first straightforward, analytic approach to predict when off-axis or high-NA lensless imaging experiments will be properly sampled, which will be of use to the general lensless imaging community. We show, somewhat unexpectedly, that this grazing imaging mode allows us to combine a very wide field of view with high spatial resolution in ptychographic imaging.

The grazing-incidence geometry allows nearly any material to be imaged within reasonable exposure times using the photon flux generated using a tabletop-scale 13 nm high-harmonic generation (HHG) light source. Materials generally have significant reflectivity (>1%) to 13 nm light at grazing incidence, and exhibit excellent chemical-specific contrast [21]. We call our technique GLancing Incidence Diffractive Imaging with EUV in Reflection, or GLIDER.

Most microscopes suffer from a fundamental tradeoff between field of view (FOV) and either resolution or data-acquisition time. In GLIDER, this tradeoff may be partially circumvented by exploiting the wide projected beam and conical diffraction that occurs on a sample at grazing incidence [14,22]. Without changing the sample-to-camera distance, the resolution in the direction of tilted incidence is decreased, but the resolution in the perpendicular direction is essentially unaffected. This yields significantly wider FOV images as compared to normal-incidence ptychography CDI for the same scan time. Contrastingly, in most conventional imaging modalities, obtaining a wider FOV in a set time period requires sacrificing resolution in all directions. Furthermore, simply tilting the sample in most imaging systems defocuses much of the FOV, negating the benefit of a wider projected beam. This typically forces a relaxed NA to increase the depth of focus, resulting in decreased resolution in all directions.

In GLIDER, the entire FOV remains in focus when the sample tilts, giving the full benefit of FOV extension. We believe this technique has wide applicability, especially for imaging semiconductor samples—in particular, grating-type structures including FINFET, memory, or overlay reference patterns that require large FOVs with directional high resolution.

2. SPATIALLY DEPENDENT OVERSAMPLING

In CDI, the oversampling constraint requires that the diffraction pattern (proportional to field intensity) must at least be Nyquist sampled by the detector in order to be reconstructed in a straightforward manner [1,23]. In ptychography, this limits the maximum allowable beam size on the sample for a given sample-to-camera distance and camera pixel size. At low numerical aperture (NA) and normal incidence, this requirement is given by

σ=λzpD2,
where λ is the wavelength, z is the sample-to-camera distance, p is the detector pixel size, D is the diameter of the beam, and σ is the oversampling, which must be greater than 2 to ensure Nyquist sampled data. At high NA or non-normal incidence, Eq. (1) ceases to hold because conical diffraction from the sample changes the spacing between diffracted orders from that predicted using a Fourier transform relationship between the sample and detector planes [see Fig. 1(b)]. This results in spatially dependent oversampling on the detector.

 

Fig. 1. (a) 13 nm reflection-mode lensless microscope design (GLIDER). (b) Comparison of diffraction patterns due to a small square beam at normal incidence (left), the resulting wide projected beam due to tilting the sample (middle), and the post-TPC diffraction (right) identical to diffraction due to a wide beam at normal incidence. (c) 13 nm ptychographic unwrapped phase reconstruction.

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When a round beam of diameter D [Fig. 1(b), left] is incident on a sample at grazing incidence, the projection of the beam in the sample plane becomes wide [Fig. 1(b), center], stretching the beam to a diameter of D/sin(α), where α is the incidence angle between the sample surface and the beam. Using parameters relevant to the present experiment and Eq. (1), at normal incidence we would predict an oversampling of 6.8 in the horizontal direction. For the same beam at grazing incidence with a projected width of 70.1 μm, Eq. (1) would predict an oversampling of 1.1, suggesting that the data would not be Nyquist sampled on the detector and thus would not reconstruct [1] without advanced techniques such as [24,25] that require smaller scan steps and thus increased data-acquisition time. However, if we take into account the spatially dependent oversampling due to conical diffraction in this grazing-incidence geometry, we predict a minimum oversampling of 3.6 and max oversampling of 12.4 on the detector [see Fig. 2(f)], suggesting that the data actually can be reconstructed even in the presence of a wide projected beam that would apparently violate Eq. (1).

 

Fig. 2. Results of new analytic spatially dependent oversampling formalism. Representative diffraction patterns (logarithmic colorscale) from (a) a round beam at normal incidence versus (d) grazing incidence. In (b) and (e), the theoretical spatially dependent oversampling on a 2048×2048 pixel camera with 13.5 μm square pixels is shown for a high-NA geometry with a round beam, where σ=2 according to Eq. (1). Spatially dependent oversampling is compared for (b) normal incidence versus (e) grazing incidence. In (c) and (f), the theoretical oversampling is shown on the same detector for the experimental geometry used in this work (z=84.4  mm, beam with height 6.5 μm and width 11.6 μm at normal incidence). Images (b) and (c) are at normal incidence; (e) and (f) are at grazing incidence (α=9.5°). The oversampling predicted by Eq. (1) for the geometries in (b), (c), (e), and (f) is shown on the colorbar. See Visualization 1.

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We derive the spatially dependent oversampling at high NA and tilted incidence, and present numeric simulations to confirm it in Supplement 1. Our derivation is based upon analytically propagating pairs of Dirac delta functions that trace out the shape of the beam in the sample plane to the detector plane using the Rayleigh–Sommerfeld formalism [26]. In the detector plane, the resulting highest frequencies observed are compared to the pixel spacing in the direction these frequencies occur, on a pixel-by-pixel basis. Figure 2 shows representative diffraction patterns at normal (a) versus grazing (d) incidence for a round beam. In Fig. 2(b), the theoretical spatially dependent oversampling at normal incidence for a round beam oversampled by 2 according to Eq. (1) at the DC (center pixel) is shown for a detector with 2048×2048 pixels that are 13.5 μm square. The oversampling for the same detector and beam geometry is shown in Fig. 2(e) at a grazing incidence of 9.5° from the sample surface. The same normal/grazing incidence comparison is shown in Figs. 2(c) and 2(f) for the experimental geometry used here (84.4 mm between sample and camera, 6.5×11.6  μm beam at normal incidence).

3. EXPERIMENT

Our GLIDER microscope [see Fig. 1(a)] uses an ultrafast Ti:Sapphire oscillator-amplifier system at 795 nm (KMLabs Wyvern-HP). The 3 mJ, 38 fs pulses at 3 kHz drive a 13 nm HHG source (KMLabs XUUS 4.0). High-harmonic generation of coherent 13 nm light occurs in a 150 μm inner diameter, hollow glass waveguide filled with 700 Torr He gas, into which the pointing-stabilized IR laser light is focused. After the waveguide, residual fundamental laser light co-propagating with the emitted EUV beam is removed using two rejecter mirrors oriented near Brewster’s angle for the 795 nm light, as well as two 200 nm thick ZrO2 filters. Next, the 12.6 nm harmonic is selected using two 45° angle of incidence multilayer Mo:Si mirrors. The EUV beam is then focused onto the sample using an ellipsoidal focusing optic to a spot size of 6.5×11.6  μm (1/e2 diameter, as viewed at normal incidence). The sample is placed at a grazing incidence to the beam, with an angle of 9.5° between the sample surface and the incident beam. At this incidence angle, the projected beam’s 1/e2 diameter becomes 6.5×70.1  μm wide. The sample consisted of 29-nm-tall nickel structures deposited on a Si wafer. The sample was scanned using a Fermat spiral pattern [27] with nominally 1.56 μm between each of 121 adjacent scan positions. Diffraction patterns were detected on a 2048×2048 Andor iKon-L CCD detector with 13.5 μm pixels, 84.4 mm from the sample.

4. RESULTS

A reconstructed image using 13 nm GLIDER is shown in Fig. 3. The full FOV object intensity [Fig. 3(a)] is compared to a scanning electron microscopy (SEM) image of the same region [Fig. 3(b)]. The substrate discoloration in the center of both images is due to contamination buildup from extensive prior imaging performed on this sample using a 30 nm EUV microscope. The square discoloration in Fig. 3(b) is due to hydrocarbon buildup from a few prior SEM images of the sample. We see good agreement between the ptychographic intensity, phase images, and the SEM in both the narrow [Figs. 3(c) and 3(d)] and full fields of view.

 

Fig. 3. (a) EUV ptychography intensity image, full field of view. (b) SEM with rectangular darkening due to hydrocarbon burn-on from prior SEM imaging completed after the EUV ptychography data was obtained. (c) EUV ptychography unwrapped phase image, zoomed in to reveal detail. (d) SEM image, zoomed in to reveal detail. Images (a) and (b) share a scale bar, as do images (c) and (d); all share the colorbar. Note that the roughly round discoloration visible in all of these images on the left side of the labyrinth-like structure and on the substrate beneath it is due to hydrocarbon deposition. This deposition resulted from extensive previous imaging experiments on this sample using a different EUV microscope that illuminated the sample in these regions with focused illumination.

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Prior to performing ptychographic reconstructions, the data was remapped onto a linear frequency grid using tilted-plane correction (TPC) [14,22], allowing the fast Fourier transform to be used during reconstructions even though the raw data shows extreme conical diffraction [see Fig. 1(b)]. To ensure that originally oversampled data remained so after the remapping, the diffraction patterns were interpolated during TPC onto a grid with eight times finer spacing in the horizontal direction and two times finer spacing in the vertical direction compared to the detector grid. This upsampling step is crucial to GLIDER because, if not performed, all of the data will be remapped during TPC to the oversampling predicted by Eq. (1) (σ=1.1), which is lower than the detector’s oversampling at any pixel (σmin=3.6).

Ptychographic reconstructions were performed using a combination of the extended and regularized ptychographic iterative engines (ePIE [4] and rPIE [28]). We found that running ePIE (equivalent to rPIE with α=1) to solve for the probe and rPIE (with α=0.5) as a refinement gave better results than starting with rPIE, which was prone to yielding multiple copies of the probe on the large probe grid resulting from upsampling in TPC. We note that this work is the first to apply rPIE to experimental data. We also used the Shrinkwrap algorithm [29] to constrain the probe; its first application in this capacity in ptychography to our knowledge. By running Shrinkwrap on the probe for just a few iterations relatively early in the reconstruction, we were able to suppress the development of artifacts in the reconstructed beam without having to carefully tune the Shrinkwrap parameters. More details about the reconstruction process are given in Supplement 1.

During all iterations, we added a saturation constraint to our ptychographic algorithm. We set pixels whose reconstructed reflectivity was brighter than a reasonable maximum (which is typically 1 in qua