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$\mathrm{SIM}$-$\mathrm{STEM}$ $\mathrm{Lab}$: Incorporating Compressed Sensing Theory for Fast STEM Simulation

We report recently it has been shown that precise dose control and an increase in the overall acquisition speed of atomic resolution scanning transmission electron microscope (STEM) images can be achieved by acquiring only a small fraction of the pixels in the image experimentally and then reconstructing the full image using an inpainting algorithm. In this paper, we apply the same inpainting approach (a form of compressed sensing) to simulated, sub-sampled atomic resolution STEM images. We find that it is possible to significantly sub-sample the area that is simulated, the number of g-vectors contributing the image, and the number of frozen phonon configurations contributing to the final image while still producing an acceptable fit to a fully sampled simulation. Here we discuss the parameters that we use and how the resulting simulations can be quantifiably compared to the full simulations. As with any Compressed Sensing methodology, care must be taken to ensure that isolated events are not excluded from the process, but the observed increase in simulation speed provides significant opportunities for real time simulations, image classification and analytics to be performed as a supplement to experiments on a microscope to be developed in the future

47 OTHER INSTRUMENTATION↗

Temperature separation under compression of moderately coupled plasma

In moderately coupled plasmas, a significant fraction of the internal energy resides in electric fields. As these plasmas are heated or compressed, the shifting partition of energy between particles and fields leads to surprising effects, particularly when ions and electrons have different temperatures. In this work, quasi-equations of state (quasi-EOS) are derived for two-temperature moderately coupled plasma in a thermodynamic framework and expressed in a simple form. These quasi-EOS readily yield expressions for correlation heating, in which heating of the electrons causes a rapid increase in ion temperature even in the absence of collisional energy exchange between species. It is also shown that, remarkably, compression of moderately coupled plasma drives a temperature difference between electrons and ions, even when the species start at equal temperatures. These additional channels for ion heating may be relevant in designing ignition schemes for inertial confinement fusion.

Fetsch, H. (ORCID:0000000256133975)↗

Compression Algorithm Analysis of In-Situ (S)TEM Video: Towards Automatic Event Detection and Characterization

Precise analysis of both (S)TEM images and video are time and labor intensive processes. As an example, determining when crystal growth and shrinkage occurs during the dynamic process of Li dendrite deposition and stripping involves manually scanning through each frame in the video to extract a specific set of frames/images. For large numbers of images, this process can be very time consuming, so a fast and accurate automated method is desirable. Given this need, we developed software that uses analysis of video compression statistics for detecting and characterizing events in large data sets. This software works by converting the data into a series of images which it compresses into an MPEG-2 video using the open source “avconv” utility [1]. The software does not use the video itself, but rather analyzes the video statistics from the first pass of the video encoding that avconv records in the log file. This file contains statistics for each frame of the video including the frame quality, intra-texture and predicted texture bits, forward and backward motion vector resolution, among others. In all, avconv records 15 statistics for each frame. By combining different statistics, we have been able to detect events in various types of data. We have developed an interactive tool for exploring the data and the statistics that aids the analyst in selecting useful statistics for each analysis. Going forward, an algorithm for detecting and possibly describing events automatically can be written based on statistic(s) for each data type.

algorithm analysis↗

Phase Imaging: A Compressive Sensing Approach

Since Wolfgang Pauli posed the question in 1933, whether the probability densities |Ψ(r)|² (real-space image) and |Ψ(q)|² (reciprocal space image) uniquely determine the wave function Ψ(r) [1], the so called Pauli Problem sparked numerous methods in all fields of microscopy [2, 3]. Reconstructing the complete wave function Ψ(r) = a(r)e-iφ(r) with the amplitude a(r) and the phase φ(r) from the recorded intensity enables the possibility to directly study the electric and magnetic properties of the sample through the phase. In transmission electron microscopy (TEM), electron holography is by far the most established method for phase reconstruction [4]. Requiring a high stability of the microscope, next to the installation of a biprism in the TEM, holography cannot be applied to any microscope straightforwardly. Recently, a phase retrieval approach was proposed using conventional TEM electron diffractive imaging (EDI). Using the SAD aperture as reciprocal-space constraint, a localized sample structure can be reconstructed from its diffraction pattern and a real-space image using the hybrid input-output algorithm [5]. We present an alternative approach using compressive phase-retrieval [6]. Our approach does not require a real-space image. Instead, random complimentary pairs of checkerboard masks are cut into a 200 nm Pt foil covering a conventional TEM aperture (cf. Figure 1). Used as SAD aperture, subsequently diffraction patterns are recorded from the same sample area. Hereby every mask blocks different parts of gold particles on a carbon support (cf. Figure 2). The compressive sensing problem has the following formulation. First, we note that the complex-valued reciprocal-space wave-function is the Fourier transform of the (also complex-valued) real-space wave-function, Ψ(q) = F[Ψ(r)], and subsequently the diffraction pattern image is given by |Ψ(q)|2 = |F[Ψ(r)]|2. We want to find Ψ(r) given a few differently coded diffraction pattern measurements yn = |F[HnΨ(r)]|2, where the matrices Hn encode the mask structure of the aperture. This is a nonlinear inverse problem, but has been shown to be solvable even in the underdetermined case [6]. Since each diffraction pattern yn contains diffraction information from selected regions of the same sample, the differences in each pattern contain local phase information, which can be combined to form a full estimate of the real-space wave-function[7]. References: [1] W. Pauli in “Die allgemeinen Prinzipien der Wellenmechanik“, ed. H Geiger and W Scheel, (Julius Springer, Berlin). [2] A. Tonomura, Rev. Mod. Phys. 59 (1987), p. 639. [3] J. Miao et al, Nature 400 (1999), p. 342. [4] H. Lichte et al, Annu. Rev. Mater. Res. 37 (2007), p. 539. [5] J. Yamasaki et al, Appl. Phys. Lett. 101 (2012), 234105. [6] P Schniter and S Rangan. Signal Proc., IEEE Trans. on. 64(4), (2015), pp. 1043. [7] Supported by the Chemical Imaging, Signature Discovery, and Analytics in Motion initiatives at PNNL. PNNL is operated by Battelle Memorial Inst. for the US DOE; contract DE-AC05-76RL01830.

Schneider, Sebastian↗

Acquisition of STEM Images by Adaptive Compressive Sensing

Compressive Sensing (CS) allows a signal to be sparsely measured first and accurately recovered later in software [1]. In scanning transmission electron microscopy (STEM), it is possible to compress an image spatially by reducing the number of measured pixels, which decreases electron dose and increases sensing speed [2,3,4]. The two requirements for CS to work are: (1) sparsity of basis coefficients and (2) incoherence of the sensing system and the representation system. However, when pixels are missing from the image, it is difficult to have an incoherent sensing matrix. Nevertheless, dictionary learning techniques such as Beta-Process Factor Analysis (BPFA) [5] are able to simultaneously discover a basis and the sparse coefficients in the case of missing pixels. On top of CS, we would like to apply active learning [6,7] to further reduce the proportion of pixels being measured, while maintaining image reconstruction quality. Suppose we initially sample 10% of random pixels. We wish to select the next 1% of pixels that are most useful in recovering the image. Now, we have 11% of pixels, and we want to decide the next 1% of “most informative” pixels. Active learning methods are online and sequential in nature. Our goal is to adaptively discover the best sensing mask during acquisition using feedback about the structures in the image. In the end, we hope to recover a high quality reconstruction with a dose reduction relative to the non-adaptive (random) sensing scheme. In doing this, we try three metrics applied to the partial reconstructions for selecting the new set of pixels: (1) variance, (2) Kullback-Leibler (KL) divergence using a Radial Basis Function (RBF) kernel, and (3) entropy. Figs. 1 and 2 display the comparison of Peak Signal-to-Noise (PSNR) using these three different active learning methods at different percentages of sampled pixels. At 20% level, all the three active learning methods underperform the original CS without active learning. However, they all beat the original CS as more of the “most informative” pixels are sampled. One can also argue that CS equipped with active learning requires less sampled pixels to achieve the same value of PSNR than CS with pixels randomly sampled, since all the three PSNR curves with active learning grow at a faster pace than that without active learning. For this particular STEM image, by observing the reconstructed images and the sensing masks, we find that while the method based on RBF kernel acquires samples more uniformly, the one on entropy samples more areas of significant change, thus less uniformly. The KL-divergence method performs the best in terms of reconstruction error (PSNR) for this example [8].

Xie, Weiyi↗

Stability and Compressibility of Cation-Doped High-Entropy Oxide MgCoNiCuZnO 5

High-entropy oxides (HEOx) are multicomponent (≥5) complex oxides that possess material properties and functions unexpected from their constituent simple oxides. Previous studies demonstrated that a cation-doped HEOx, MgCoNiCuZnO 5 , shows good catalytic activity, excellent ionic conductivity, and high energy storage. The structural and mechanical stabilities of materials are pivotal to their applications. However, how temperature and pressure influence the structural stability of cation-doped HEOx and how doping affects the mechanical properties are yet to be understood. In this work, we investigated the structural stabilities of undoped and Li/Mn-doped MgCoNiCuZnO 5 in heating or under compression using in situ synchrotron X-ray diffraction (XRD), and determined their elastic moduli using high-pressure XRD. Our results show that the HEOx compounds are structurally stable at temperatures up to ~450 °C or at pressures up to ~50 GPa, and that Li/Mn doping makes the HEOx more compressible. Our molecular static (MS) calculations predicted that the formation reaction of a HEOx is endothermic, consistent with the fact that a single-phase HEOx can only be produced at high temperatures. The MS calculations also revealed that the observed doping-induced elastic softening stems from the introduction of the Li-O/Mn-O ionic bonds in the HEOx compound, which are weaker than other cation-oxygen ionic bonds in the undoped HEOx. These findings will be indispensable to engineer HEOx materials for use in ion batteries, catalysis, and other fields.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Correlated High-Pressure Phase Sequence of VO 2 under Strong Compression

Understanding how the structures of a crystal behave under compression is a fundamental issue both for condensed matter physics and for geoscience. Traditional description of a crystal as the stacking of a unit cell with special symmetry has gained much success on the analysis of physical properties. Unfortunately, it is hard to reveal the relationship between the compressed phases. Taking the family of metal dioxides (MO 2 ) as an example, the structural evolution, subject to fixed chemical formula and highly confined space, often appears as a set of random and uncorrelated events. In this work, we provide an alternative way to treat the crystal as the stacking of the coordination polyhedron and then discover a unified structure transition pattern, in our case VO 2 . X-ray diffraction (XRD) experiments and first-principles calculations show that the coordination increase happens only at one apex of the V-centered octahedron in an orderly fashion, leaving the base plane and the other apex topologically intact. The polyhedron evolves toward increasing their sharing, indicating a general rule for the chemical bonds of MO 2 to give away the ionicity in exchange for covalency under pressure.

36 MATERIALS SCIENCE↗

Polystyrene Glasses under Compression: Ductile and Brittle Responses

Polystyrene of different molecular weights and their binary mixtures are studied in terms of their various mechanical responses to uniaxial compression at different temperatures. PS of Mw = 25 kg/mol is completely brittle until it is above its glass transition temperature Tg. In contrast, upon incorporation of a high molecular weight component, PS mixtures turn from barely ductile a few degrees below its Tg to ductile over 40 below Tg. In the upper limit, a PS of Mw = 319 kg/mol yields and undergoes plastic flow, even at T = 70 C. The observed dependence of mechanical responses on molecular weight and molecular weight distribution can be adequately rationalized by the idea that yielding and plastic compression are caused by chain networking.

36 MATERIALS SCIENCE↗

Advanced Polymer Characterization: Modular Operations for Spectral Alignment by Iterative Compression (MOSAIC)

Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry encodes structural information across diverse homo- and copolymer ensembles, yet decrypting these spectra requires a systematic analytical approach. We introduce Modular Operations for Spectral Alignment by Iterative Compression (MOSAIC)─a general cipher algorithm that applies modular arithmetic to filter monomer-derived mass contributions and cluster MALDI peaks by nonconstitutional repeating units (non-CRUs). MOSAIC performs sequential modular operations using monomer mass differences as base units to compress complex spectral data, revealing end-group distributions and comonomer incorporation. As a demonstration, we applied MOSAIC to five copolymers formed by two different polymerization mechanisms. Furthermore, the resulting remainder–mass plots clearly resolve polymer homologs with distinct non-CRUs into visually apparent clusters, enabling intuitive assignment of mass spectral features.

Wang, Hanlin M. [University of Illinois at Urbana−↗

Electrochemical CO 2 Reduction over Compressively Strained CuAg Surface Alloys with Enhanced Multi-Carbon Oxygenate Selectivity

The electrochemical reduction of carbon dioxide using renewably generated electricity offers a potential means for producing fuels and chemicals in a sustainable manner. To date, copper has been found to be the most effective catalyst for electrochemically reducing carbon dioxide to products such as methane, ethene, and ethanol. Unfortunately, the current efficiency of the process is limited by competition with the relatively facile hydrogen evolution reaction. Since multi-carbon products are more valuable precursors to chemicals and fuels than methane, there is considerable interest in modifying copper to enhance the multi-carbon product selectivity. In this paper, we report our investigations of electrochemical carbon dioxide reduction over CuAg bimetallic electrodes and surface alloys, which we find to be more selective for the formation of multi-carbon products than pure copper. This selectivity enhancement is a result of the selective suppression of hydrogen evolution, which occurs due to compressive strain induced by the formation of a CuAg surface alloy. Furthermore, we report that these bimetallic electrocatalysts exhibit an unusually high selectivity for the formation of multi-carbon carbonyl-containing products, which we hypothesize to be the consequence of a reduced coverage of adsorbed hydrogen and the reduced oxophilicity of the compressively strained copper. Thus and finally, we show that promoting copper surface with small amounts of Ag is a promising means for improving the multi-carbon oxygenated product selectivity of copper during electrochemical CO 2 reduction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Aperture‐Synthesis Radar Imaging With Compressive Sensing for Ionospheric Research

Abstract Inverse methods involving compressive sensing are tested in the application of two‐dimensional aperture‐synthesis imaging of radar backscatter from field‐aligned plasma density irregularities in the ionosphere. We consider basis pursuit denoising, implemented with the fast iterative shrinkage thresholding algorithm, and orthogonal matching pursuit (OMP) with a wavelet basis in the evaluation. These methods are compared with two more conventional optimization methods rooted in entropy maximization (MaxENT) and adaptive beamforming (linearly constrained minimum variance or often “Capon's Method.”) Synthetic data corresponding to an extended ionospheric radar target are considered. We find that MaxENT outperforms the other methods in terms of its ability to recover imagery of an extended target with broad dynamic range. Fast iterative shrinkage thresholding algorithm performs reasonably well but does not reproduce the full dynamic range of the target. It is also the most computationally expensive of the methods tested. OMP is very fast computationally but prone to a high degree of clutter in this application. We also point out that the formulation of MaxENT used here is very similar to OMP in some respects, the difference being that the former reconstructs the logarithm of the image rather than the image itself from basis vectors extracted from the observation matrix. MaxENT could in that regard be considered a form of compressive sensing.

Hysell, D. L.↗

Equation of State Measurements on Iron Near the Melting Curve at Planetary Core Conditions by Shock and Ramp Compressions

The outer core of the Earth is composed primarily of liquid iron, and the inner core boundary is governed by the intersection of the melt line and the geotherm. While there are many studies on the thermodynamic equation of state for solid iron, the equation of state of liquid iron is relatively unexplored. In this work, we use dynamic compression to diagnose the high-pressure liquid equation of state of iron by utilizing the shock-ramp capability at Sandia National Laboratories’ Z-Machine. This technique enables measurements of material states off the Hugoniot by initially shocking samples and subsequently driving a further, shockless compression. Planetary studies benefit greatly from isentropic, off-Hugoniot experiments since they can cover pressure-temperature (P-T) conditions that are close to adiabatic profiles found in planetary interiors. We used this method to drive iron to P-T conditions similar to those of the Earth’s outer-inner core boundary, along an elevated-temperature isentrope in the liquid from 275 GPa to 400 GPa. We derive the equation of state using a hybrid backward integration – forward Lagrangian technique on particle velocity traces to determine the pressure-density history of the sample. Our results are in excellent agreement with SESAME 92141, a previously published equation of state table. With our data and previous experimental data on liquid iron we provide new information on the iron melting line and derive new parameters for a Vinet-based equation of state. The table and our parameterized equation of state are applied to provide an updated means of modeling the pressure, mass, and density of liquid iron cores in exoplanetary interiors.

58 GEOSCIENCES↗

High-Fidelity Analysis of ULF Wave Mode Structure Following Interplanetary Shock Compression of the Dayside Magnetopause Using MMS Multi-Point Observations

During the 9 March 2018 event with two consecutive interplanetary shocks compressing the dayside magnetosphere, the azimuthal mode structure and frequency spectrum of ultra low frequency magnetic pulsations are resolved using a cross-spectral analysis based on high-fidelity multi-probe Magnetospheric Multiscale Mission (MMS) magnetometer data. The results based on the MMS 4 and MMS 3 pair of measurements show that shock arrival leads to low mode (|m| ≤ 3) magnetic fluctuations in the Pc4-5 regimes, and smaller spatial scale fluctuations implied by the dominant high mode numbers are observed after both shock signatures hit and passed the magnetosphere. Detailed evolution of the mode structure is also shown for the first shock to reveal the development of high mode structure from a bump-on-tail distribution at m≈20 to a dominant peak at m≈50 in about 10 min. In addition, an interesting change of sign in m from negative to positive is observed as MMS crosses ~11 MLT pre-noon, which is consistent with the picture of wave generation by dayside magnetopause compression and then anti-sunward propagation. Finally, for both shocks, the contribution of higher frequency waves (Pc-4 range compared with Pc-5) to the total wave power is found to be negligible before and after the shock impact, but it becomes more significant during the shock impact.

79 ASTRONOMY AND ASTROPHYSICS↗

The Viscoplastic Behavior of Natural Hydrate‐Bearing Sandy‐Silts Under Uniaxial Strain Compression ( K 0 Loading)

Abstract The in‐situ stress state and geomechanical properties of hydrate‐bearing sediments impact hydrate formation and gas production strategies. We explore the uniaxial strain compression and stress evolution of natural hydrate‐bearing sandy‐silts from Green Canyon Block 955 in the deep‐water Gulf of Mexico. We performed constant rate of strain uniaxial strain experiments, interrupted by periods where we held the axial stress constant, to explore the vertical deformation and the evolution of the ratio of lateral to axial effective stress ( K 0 ) with time. The hydrate‐bearing sandy‐silt is stiffer and has a larger K 0 than the equivalent hydrate‐free sediment upon loading. During stress holds, the void ratio decreases sigmoidally with the log of time, and K 0 converges to isotropic conditions. We interpret that during loading, the hydrate bears the load and deforms. With time, the hydrate redistributes the load and K 0 increases. We used a viscoelastic model to describe the behavior. The model accurately captures deformation and K 0 trends but does not reproduce all the complex interactions of the hydrate with the porous skeleton. We anticipate that viscous effects within hydrate sediments will impact reservoir compression and stresses during production (hours to days), result in isotropic stress state over geological timescales, and explain the creeping movement in submarine landslides.

58 GEOSCIENCES↗

High temperature deformability of ductile flash-sintered ceramics via in-situ compression

Flash sintering has attracted significant attention as its remarkably rapid densification process at low sintering furnace temperature leads to the retention of fine grains and enhanced dielectric properties. However, high-temperature mechanical behaviors of flash-sintered ceramics remain poorly understood. Here, we present high-temperature (up to 600 °C) in situ compression studies on flash-sintered yttria-stabilized zirconia (YSZ). Below 400 °C, the YSZ exhibits high ultimate compressive strength exceeding 3.5 GPa and high inelastic strain (~8%) due primarily to phase transformation toughening. At higher temperatures, crack nucleation and propagation are significantly retarded, and prominent plasticity arises mainly from dislocation activity. The high dislocation density induced in flash-sintered ceramics may have general implications for improving the plasticity of sintered ceramic materials.

36 MATERIALS SCIENCE↗

Fast wide-field upconversion luminescence lifetime thermometry enabled by single-shot compressed ultrahigh-speed imaging

Photoluminescence lifetime imaging of upconverting nanoparticles is increasingly featured in recent progress in optical thermometry. Despite remarkable advances in photoluminescent temperature indicators, existing optical instruments lack the ability of wide-field photoluminescence lifetime imaging in real time, thus falling short in dynamic temperature mapping. Here, we report video-rate upconversion temperature sensing in wide field using single-shot photoluminescence lifetime imaging thermometry (SPLIT). Developed from a compressed-sensing ultrahigh-speed imaging paradigm, SPLIT first records wide-field luminescence intensity decay compressively in two views in a single exposure. Then, an algorithm, built upon the plug-and-play alternating direction method of multipliers, is used to reconstruct the video, from which the extracted lifetime distribution is converted to a temperature map. Using the core/shell NaGdF 4 :Er 3+ ,Yb 3+ /NaGdF 4 upconverting nanoparticles as the lifetime-based temperature indicators, we apply SPLIT in longitudinal wide-field temperature monitoring beneath a thin scattering medium. SPLIT also enables video-rate temperature mapping of a moving biological sample at single-cell resolution.

47 OTHER INSTRUMENTATION↗

Structural complexity in ramp-compressed sodium to 480 GPa

Abstract The properties of all materials at one atmosphere of pressure are controlled by the configurations of their valence electrons. At extreme pressures, neighboring atoms approach so close that core-electron orbitals overlap, and theory predicts the emergence of unusual quantum behavior. We ramp-compress monovalent elemental sodium, a prototypical metal at ambient conditions, to nearly 500 GPa (5 million atmospheres). The 7-fold increase of density brings the interatomic distance to 1.74 Å well within the initial 2.03 Å of the Na + ionic diameter, and squeezes the valence electrons into the interstitial voids suggesting the formation of an electride phase. The laser-driven compression results in pressure-driven melting and recrystallization in a billionth of a second. In situ x-ray diffraction reveals a series of unexpected phase transitions upon recrystallization, and optical reflectivity measurements show a precipitous decrease throughout the liquid and solid phases, where the liquid is predicted to have electronic localization. These data reveal the presence of a rich, temperature-driven polymorphism where core electron overlap is thought to stabilize the formation of peculiar electride states.

36 MATERIALS SCIENCE↗

Formation of diamonds in laser-compressed hydrocarbons at planetary interior conditions

The effects of hydrocarbon reactions and diamond precipitation on the internal structure and evolution of icy giant planets such as Neptune and Uranus have been discussed for more than three decades. Inside these celestial bodies, simple hydrocarbons such as methane, which are highly abundant in the atmospheres, are believed to undergo structural transitions that release hydrogen from deeper layers and may lead to compact stratified cores. Indeed, from the surface towards the core, the isentropes of Uranus and Neptune intersect a temperature–pressure regime in which methane first transforms into a mixture of hydrocarbon polymers, whereas, in deeper layers, a phase separation into diamond and hydrogen may be possible. Here in this paper, we show experimental evidence for this phase separation process obtained by in situ X-ray diffraction from polystyrene (C 8 H 8 ) n samples dynamically compressed to conditions around 150 GPa and 5,000 K; these conditions resemble the environment around 10,000 km below the surfaces of Neptune and Uranus. Our findings demonstrate the necessity of high pressures for initiating carbon–hydrogen separation and imply that diamond precipitation may require pressures about ten times as high as previously indicated by static compression experiments. In conclusion, our results will inform mass–radius relationships of carbon-bearing exoplanets, provide constraints for their internal layer structure and improve evolutionary models of Uranus and Neptune, in which carbon–hydrogen separation could influence the convective heat transport.

79 ASTRONOMY AND ASTROPHYSICS↗