Cost and Capability Compromises in STEM Instrumentation for Low-Voltage Imaging

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.

The abTEM code: transmission electron microscopy from first principles

Simulation of transmission electron microscopy (TEM) images or diffraction patterns is often required to interpret experimental data. Since nuclear cores dominate electron scattering, the scattering potential is typically described using the independent atom model, which completely neglects valence bonding and its effect on the transmitting electrons. As instrumentation has advanced, new measurements have revealed subtle details of the scattering potential that were previously not accessible to experiment. We have created an open-source simulation code designed to meet these demands by integrating the ability to calculate the potential via density functional theory (DFT) with a flexible modular software design. abTEM can simulate most standard imaging modes and incorporates the latest algorithmic developments. The development of new techniques requires a program that is accessible to domain experts without extensive programming experience. abTEM is written purely in Python and designed for easy modification and extension. The effective use of modern open-source libraries makes the performance of abTEM highly competitive with existing optimized codes on both CPUs and GPUs and allows us to leverage an extensive ecosystem of libraries, such as the Atomic Simulation Environment and the DFT code GPAW. abTEM is designed to work in an interactive Python notebook, creating a seamless and reproducible workflow from defining an atomic structure, calculating molecular dynamics (MD) and electrostatic potentials, to the analysis of results, all in a single, easy-to-read document.  This article provides ongoing documentation of abTEM development. In this first version, we show use cases for hexagonal boron nitride, where valence bonding can be detected, a 4D-STEM simulation of molybdenum disulfide including ptychographic phase reconstruction, a comparison of MD and frozen phonon modeling for convergent-beam electron diffraction of a 2.6-million-atom silicon system, and a performance comparison of our fast implementation of the PRISM algorithm for a decahedral 20000-atom gold nanoparticle.

The abTEM code: transmission electron microscopy from first principles

Simulation of transmission electron microscopy (TEM) images or diffraction patterns is often required to interpret experimental data. Since nuclear cores dominate electron scattering, the scattering potential is typically described using the independent atom model, which completely neglects valence bonding and its effect on the transmitting electrons. As instrumentation has advanced, new measurements have revealed subtle details of the scattering potential that were previously not accessible to experiment. We have created an open-source simulation code designed to meet these demands by integrating the ability to calculate the potential via density functional theory (DFT) with a flexible modular software design. abTEM can simulate most standard imaging modes and incorporates the latest algorithmic developments. The development of new techniques requires a program that is accessible to domain experts without extensive programming experience. abTEM is written purely in Python and designed for easy modification and extension. The effective use of modern open-source libraries makes the performance of abTEM highly competitive with existing optimized codes on both CPUs and GPUs and allows us to leverage an extensive ecosystem of libraries, such as the Atomic Simulation Environment and the DFT code GPAW. abTEM is designed to work in an interactive Python notebook, creating a seamless and reproducible workflow from defining an atomic structure, calculating molecular dynamics (MD) and electrostatic potentials, to the analysis of results, all in a single, easy-to-read document.  This article provides ongoing documentation of abTEM development. In this first version, we show use cases for hexagonal boron nitride, where valence bonding can be detected, a 4D-STEM simulation of molybdenum disulfide including ptychographic phase reconstruction, a comparison of MD and frozen phonon modeling for convergent-beam electron diffraction of a 2.6-million-atom silicon system, and a performance comparison of our fast implementation of the PRISM algorithm for a decahedral 20000-atom gold nanoparticle.

Validation of a mammographic image quality modification algorithm using 3D-printed breast phantoms

Purpose: To validate a previously proposed algorithm that modifies a mammogram to appear as if it was acquired with different technique factors using realistic phantom-based mammograms. Approach: Two digital mammography systems (an indirect- and a direct-detector-based system) were used to acquire realistic mammographic images of five 3D-printed breast phantoms with the technique factors selected by the automatic exposure control and at various other conditions (denoted by the original images). Additional images under other simulated conditions were also acquired: higher or lower tube voltages, different anode/filter combinations, or lower tube current-time products (target images). The signal and noise in the original images were modified to simulate the target images (simulated images). The accuracy of the image modification algorithm was validated by comparing the target and simulated images using the local mean, local standard deviation (SD), local variance, and power spectra (PS) of the image signals. The absolute relative percent error between the target and simulated images for each parameter was calculated at each sub-region of interest (local parameters) and frequency (PS), and then averaged. Results: The local mean signal, local SD, local variance, and PS of the target and simulated images were very similar, with a relative percent error of 5.5%, 3.8%, 7.8%, and 4.4% (indirect system), respectively, and of 3.7%, 3.8%, 7.7%, and 7.5% (direct system), respectively. Conclusions: The algorithm is appropriate for simulating different technique factors. Therefore, it can be used in various studies, for instance to evaluate the impact of technique factors in cancer detection using clinical images.

Manufacture of Contact Lens of Nanoparticle-Doped Polymer Complemented with ZEMAX

Many people suffer from myopia or hyperopia due to the refractive errors of the cornea all over the world. The use of high refractive index (RI), Abbe number (ν_d), and visible light transmittance (T%) polymeric contact lenses (CLs) holds great promise in vision error treatment as an alternative solution to the irreversible laser-assisted in situ keratomileusis (LASIK) surgery. Titanium dioxide nanoparticles (TiO₂ NPs) have been suggested as a good candidate to rise the RI and maintain high transparency of a poly(methyl methacrylate) (PMMA)-TiO₂ nanocomposite. This work includes a preparation of TiO₂ NPs using the sol gel method as well as a synthesis of pure PMMA by free radical polarization and PMMA-TiO₂ CLs using a cast molding method of 0.005 and 0.01 w/v concentrations and a study of their effect on the aberrated human eye. ZEMAX optical design software was used for eye modeling based on the Liou and Brennan eye model and then the pure and doped CLs were applied. Ocular performance was evaluated by modulation transfer function (MTF), spot diagram, and image simulation. The used criteria show that the best vision correction was obtained by the CL of higher doping content (p < 0.0001) and that the generated spherical and chromatic aberrations in the eye had been reduced.

"How much realism is needed?" - the wrong question in silico imagers have been asking

PURPOSE

To discuss the use of realism as a first approximation for assessing computational imaging methods.

METHODS

Although in silico methods are increasingly becoming promising surrogates to physical experimentation for various stages of device development, their acceptance remains challenging. Realism is often considered as a first approximation for assessing computational imaging methods. However, realism is subjective and does not always ensure that key features of the methodologies reflect relevant aspects of devices of interest to imaging scientists, regulators, and medical practitioners. Moreover, in some cases (e.g., in computerized image analysis applications where human interpretation is not needed) how realistic in silico images are is irrelevant and perhaps misleading.

RESULTS

I emphasize a divergence from this methodology by providing a rationale for evaluating in silico imaging methods and tools in an objective and measurable manner.

CONCLUSIONS

Improved approaches for in silico imaging will lead to the rapid advancement and acceptance of computational techniques in medical imaging primarily but not limited to the regulatory evaluation of new imaging products.

Important factors determining the nanoscale tracking precision of dynamic microtubule ends

Tracking dynamic microtubule ends in fluorescence microscopy movies provides insight into the statistical properties of microtubule dynamics and is vital for further analysis that requires knowledge of the trajectories of the microtubule ends. Here we analyse the performance of a previously developed automated microtubule end tracking routine; this has been optimized for comparatively low signal-to-noise image sequences that are characteristic of microscopy movies of dynamic microtubules growing in vitro. Sequences of simulated microtubule images were generated assuming a variety of different experimental conditions. The simulated movies were then tracked and the tracking errors were characterized. We found that the growth characteristics of the microtubules within realistic ranges had a negligible effect on the tracking precision. The fluorophore labelling density, the pixel size of the images, and the exposure times were found to be important parameters limiting the tracking precision which could be explained using concepts of single molecule localization microscopy. The signal-to-noise ratio was found to be a good single predictor of the tracking precision: typical experimental signal-to-noise ratios lead to tracking precisions in the range of tens of nanometres, making the tracking program described here a useful tool for dynamic microtubule end tracking with close to molecular precision.

Quantitative annular dark-field imaging of single-layer graphene-II: atomic-resolution image contrast

We have investigated how accurately atomic-resolution annular dark-field (ADF) images match between experiments and simulations to conduct more reliable crystal structure analyses. Quantitative ADF imaging, in which the ADF intensity at each pixel represents the fraction of the incident probe current, allows us to perform direct comparisons with simulations without the use of fitting parameters. Although the conventional comparison suffers from experimental uncertainties such as an amorphous surface layer and specimen thickness, in this study we eliminated such uncertainties by using a single-layer graphene as a specimen. Furthermore, to reduce image distortion and shot noises in experimental images, multiple acquisitions with drift correction were performed, and the atomic ADF contrast was quantitatively acquired. To reproduce the experimental ADF contrast, we used three distribution functions as the effective source distribution in simulations. The optimum distribution function and its full-width at half-maximum were evaluated by measuring the residuals between the experimental and simulated images. It was found that the experimental images could be explained well by a linear combination of a Gaussian function and a Lorentzian function with a longer tail than the Gaussian function.

Quantitative annular dark-field imaging of single-layer graphene

A quantification procedure for annular dark-field (ADF) imaging, in which a quantitative contrast is given as a scattering intensity normalized by an incident probe current, is presented. The obtained ADF images are converted to quantitative ADF images using an empirical equation, which is a function of an ADF imaging system setting. The quantification procedure fully implements the nonlinear response of the ADF imaging system, which is critical in high-sensitivity observation. We applied the procedure for observation of a graphene specimen with 1-4 layers. The inner and outer angles of an ADF detector, which are important parameters in quantitative analyses, were precisely measured. The quantitative contrast of ADF images was in agreement with that of simulated images, and the quantitative ADF imaging allowed us to directly count the number of graphene layers.

Algorithms for Scanned Probe Microscope Image Simulation, Surface Reconstruction, and Tip Estimation

To the extent that tips are not perfectly sharp, images produced by scanned probe microscopies (SPM) such as atomic force microscopy and scanning tunneling microscopy are only approximations of the specimen surface. Tip-induced distortions are significant whenever the specimen contains features with aspect ratios comparable to the tip's. Treatment of the tip-surface interaction as a simple geometrical exclusion allows calculation of many quantities important for SPM dimensional metrology. Algorithms for many of these are provided here, including the following: (1) calculating an image given a specimen and a tip (dilation), (2) reconstructing the specimen surface given its image and the tip (erosion), (3) reconstructing the tip shape from the image of a known "tip characterizer" (erosion again), and (4) estimating the tip shape from an image of an unknown tip characterizer (blind reconstruction). Blind reconstruction, previously demonstrated only for simulated noiseless images, is here extended to images with noise or other experimental artifacts. The main body of the paper serves as a programmer's and user's guide. It includes theoretical background for all of the algorithms, detailed discussion of some algorithmic problems of interest to programmers, and practical recommendations for users.