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At least 811 records · Page 45

Insights into the Structure–Activity Relationships in Metal–Organic Framework-Supported Nickel Catalysts for Ethylene Hydrogenation

Solid supports play an indispensable role in heterogeneous catalysis, as they can directly affect the catalytic activity and selectivity of supported catalysts. However, the specific roles of such supports remain to be demystified owing to the difficulties in obtaining precise structural information on supported catalysts. To understand the effects of MOF topology, pore environment, and metal identity of node supports on the catalytic activity, a Ni catalyst was supported on eight Zr- or Hf-MOFs based on 8-connected nodes: namely M-NU-1200, M-NU-1000, M-NU-1008, and M-NU-1010 (M = Zr, Hf). Single-crystal X-ray diffraction (SCXRD), diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS), and X-ray photoelectron spectroscopy (XPS) were employed to characterize the supported catalyst structures. To investigate the support effects on their activities, the supported Ni catalysts were evaluated by using ethylene hydrogenation as a model reaction. The results revealed that all Hf-based-MOF-supported Ni catalysts exhibited higher catalytic reactivity with TOF (turnover frequency) values at least double of those isostructural Zr counterparts. Additionally, MOFs with less congested metal anchoring sites, as a result of the topology and surrounding pore environment, yielded higher TOFs, suggesting the importance of supports in dictating both the catalyst accessibility and activity. Computational analysis complemented the experimental observations and provided insights into reaction barrier differences and their performance variation. Furthermore, this study demonstrates the essential role of the supports and provides a thought for selecting/designing suitable supports in heterogeneous catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Highly multicolored light-emitting arrays for compressive spectroscopy

Miniaturized, multicolored light-emitting device arrays are promising for applications in sensing, imaging, computing, and more, but the range of emission colors achievable by a conventional light-emitting diode is limited by material or device constraints. In this work, we demonstrate a highly multicolored light-emitting array with 49 different, individually addressable colors on a single chip. The array consists of pulsed-driven metal-oxide-semiconductor capacitors, which generate electroluminescence from microdispensed materials spanning a diverse range of colors and spectral shapes, enabling facile generation of arbitrary light spectra across a broad wavelength range (400 to 1400 nm). When combined with compressive reconstruction algorithms, these arrays can be used to perform spectroscopic measurements in a compact manner without diffractive optics. As an example, we demonstrate microscale spectral imaging of samples using a multiplexed electroluminescent array in conjunction with a monochrome camera.

42 ENGINEERING↗

Laser-Induced Thermal Decomposition of Uranium Coordination Compounds with Non-oxidic Ligands to Produce Nitride and Carbide Materials

The production of ceramics from uranium coordination compounds can be achieved through thermal processing if an excess amount of the desired atoms (i.e., C or N), or reactive gaseous products (e.g., methane or nitrogen oxide) is made available to the reactive uranium metal core via decomposition/fragmentation of the surrounding ligand groups. Here, computational thermodynamic approaches were utilized to identify the temperatures necessary to produce uranium metal from some starting compounds—UI 4 (TMEDA) 2 , UCl 4 (TMEDA) 2 , UCl 3 (pyridine) x , and UI 3 (pyridine) 4 . Experimentally, precursors were irradiated by a laser under various gaseous environments (argon, nitrogen, and methane) creating extreme reaction conditions (i.e., fast heating, high temperature profile >2000 °C, and rapid cooling). Despite the fast dynamics associated with laser irradiation, the central uranium atom reacted with the thermal decomposition products of the ligands yielding uranium ceramics. Residual gas analysis identified vaporized products from the laser irradiation, and the final ceramic products were characterized by powder X-ray diffraction. The composition of the uranium precursor as well as the gaseous environment had a direct impact on the production of the final phases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Prediction of structure and cation ordering in an ordered normal-inverse double spinel

Abstract Spinels represent an important class of technologically relevant materials, used in diverse applications ranging from dielectrics, sensors and energy materials. While solid solutions combining two “single spinels” have been explored in a number of past studies, no ordered “double” spinels have been reported. Based on our first principles computations, here we predict the existence of such a double spinel compound MgAlGaO 4 , formed by an equimolar mixing of MgAl 2 O 4 normal and MgGa 2 O 4 inverse spinels. After studying the details of its atomic and electronic structure, we use a cluster expansion based effective Hamiltonian approach with Monte Carlo simulations to study the thermodynamic behavior and cation distribution as a function of temperature. Our simulations provide strong evidence for short-ranged cation order in the double spinel structure, even at significantly elevated temperatures. Finally, an attempt was made to synthesize the predicted double spinel compound. Energy Dispersive X-ray Spectrometry and X-ray diffraction Rietveld refinements were performed to characterize the single-phase chemical composition and local configurational environments, which showed a favorable agreement with the theoretical predictions. These findings suggest that a much larger number of compounds can potentially be realized within this chemical space, opening new avenues for the design of spinel-structured materials with tailored functionality.

36 MATERIALS SCIENCE↗

Reactive phosphine combinatorial co-sputtering of cation disordered ZnGeP2 films

The discovery of new materials by coupling high-throughput synthesis with computational screening is being increasingly adopted. However, thus far, phosphides have been largely overlooked for both computational screening and high-throughput synthesis. In this paper, we report on the use of a high-throughput synthesis technique, reactive combinatorial co-sputtering with PH 3 , to deposit ZnGeP 2 thin films. We grew amorphous films over a wide range of compositions and found an upper limit in growth temperature determined by Zn and P volatility. We found that depositing in a Ge-limited regime could be utilized to slow the growth rate to compensate for the desorption of the Zn and P. Crystalline films were achieved by depositing films at higher temperatures in this Ge-limited regime with a reduced deposition rate. X-ray diffraction revealed that the films had crystallized in the zinc blende, cation-disordered structure. The crystalline films exhibited optical absorption energy threshold values ranging from 0.8 to 1.3 eV. Increased Ge content was found in films that exhibited a decreased absorption onset energy. Native defect calculations were used to gain an understanding of the off-stoichiometry seen in these films. This work provides the first high-throughput investigation of ZnGeP 2 , demonstrating the ability to grow amorphous and cation disordered ZnGeP 2 over a wide range of compositions with varying optical properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Integrated analysis of X-ray diffraction patterns and pair distribution functions for machine-learned phase identification

Abstract To bolster the accuracy of existing methods for automated phase identification from X-ray diffraction (XRD) patterns, we introduce a machine learning approach that uses a dual representation whereby XRD patterns are augmented with simulated pair distribution functions (PDFs). A convolutional neural network is trained directly on XRD patterns calculated using physics-informed data augmentation, which accounts for experimental artifacts such as lattice strain and crystallographic texture. A second network is trained on PDFs generated via Fourier transform of the augmented XRD patterns. At inference, these networks classify unknown samples by aggregating their predictions in a confidence-weighted sum. We show that such an integrated approach to phase identification provides enhanced accuracy by leveraging the benefits of each model’s input representation. Whereas networks trained on XRD patterns provide a reciprocal space representation and can effectively distinguish large diffraction peaks in multi-phase samples, networks trained on PDFs provide a real space representation and perform better when peaks with low intensity become important. These findings underscore the importance of using diverse input representations for machine learning models in materials science and point to new avenues for automating multi-modal characterization.

36 MATERIALS SCIENCE↗

Sub‐Nanosecond Reconfiguration of Ferroelectric Domains in Bismuth Ferrite

Abstract Domain switching is crucial for achieving desired functions in ferroic materials that are used in various applications. Fast control of domains at sub‐nanosecond timescales remains a challenge despite its potential for high‐speed operation in random‐access memories, photonic, and nanoelectronic devices. Here, ultrafast laser excitation is shown to transiently melt and reconfigure ferroelectric stripe domains in multiferroic bismuth ferrite on a timescale faster than 100 picoseconds. This dynamic behavior is visualized by picosecond‐ and nanometer‐resolved X‐ray diffraction and time‐resolved X‐ray diffuse scattering. The disordering of stripe domains is attributed to the screening of depolarization fields by photogenerated carriers resulting in the formation of charged domain walls, as supported by phase‐field simulations. Furthermore, the recovery of disordered domains exhibits subdiffusive growth on nanosecond timescales, with a non‐equilibrium domain velocity reaching up to 10 m s −1 . These findings present a new approach to image and manipulate ferroelectric domains on sub‐nanosecond timescales, which can be further extended into other complex photoferroic systems to modulate their electronic, optical, and magnetic properties beyond gigahertz frequencies. This approach could pave the way for high‐speed ferroelectric data storage and computing, and, more broadly, defines new approaches for visualizing the non‐equilibrium dynamics of heterogeneous and disordered materials.

36 MATERIALS SCIENCE↗

Identifying Decoherence Mechanisms in Superconducting Qubits through Advanced Materials Characterization

Although superconducting qubits have emerged as a leading technology platform for quantum computing through large improvements in device coherence times and gate fidelity in recent years, the presence of defects and impurities at the interfaces and surfaces in the constituent materials continue to limit performance and serve as a critical barrier in achieving scalable quantum systems. Understanding and eliminating these sources of quantum decoherence in superconducting qubit devices requires dedicated studies aimed at establishing robust structure-property relationships that will enable researchers to target and eliminate defects strategically. As part of the Superconducting Materials and Systems (SQMS) center, we have extensively employed state-of-the-art materials characterization techniques, including scanning/transmission electron microscopy, secondary ion mass spectrometry, atom probe tomography, x-ray diffraction, and x-ray photoelectron spectroscopy in conjunction with device measurements to elucidate such relationships. In this talk, I will discuss some of our recent findings, including linking atomic defects to microwave loss in surface oxides, linking impurities in the Josephson Junction to qubit parameters, and linking low temperature precipitates to device performance. By applying these insights, we have been able to strategically develop and implement mitigation strategies for reliable fabrication of high coherence superconducting qubits.

Murthy, A. [Fermilab] (ORCID:0000000176776866)↗

Identifying Decoherence Mechanisms in Superconducting Qubits through Advanced Materials Characterization

Although superconducting qubits have emerged as a leading technology platform for quantum computing through large improvements in device coherence times and gate fidelity in recent years, the presence of defects and impurities at the interfaces and surfaces in the constituent materials continue to limit performance and serve as a critical barrier in achieving scalable quantum systems. Understanding and eliminating these sources of quantum decoherence in superconducting qubit devices requires dedicated studies aimed at establishing robust structure-property relationships that will enable researchers to target and eliminate defects strategically. As part of the Superconducting Materials and Systems (SQMS) center, we have extensively employed state-of-the-art materials characterization techniques, including scanning/transmission electron microscopy, secondary ion mass spectrometry, atom probe tomography, x-ray diffraction, and x-ray photoelectron spectroscopy in conjunction with device measurements to elucidate such relationships. In this talk, I will discuss some of our recent findings, including linking atomic defects to microwave loss in surface oxides, linking impurities in the Josephson Junction to qubit parameters, and linking low temperature precipitates to device performance. By applying these insights, we have been able to strategically develop and implement mitigation strategies for reliable fabrication of high coherence superconducting qubits.

Murthy, A. [Fermilab] (ORCID:0000000176776866)↗

Identify the Limits of Geometric Optics Ray Tracing by Numerically Solving the Vector Kirchhoff Integral

The properties of a pencil of light as defined approximately in the geometric optics ray tracing method are investigated. The vector Kirchhoff integral is utilized to accurately compute the electromagnetic near field in and around the pencil of light with various beam base sizes, shapes, propagation directions and medium refractive indices. If a pencil of light has geometric mean cross section size of the order p times the wavelength, it can propagate independently to a distance p2 times the wavelength, where most of the beam energy diffuses out of the beam region. This is consistent with a statement that van de Hulst made in a classical text on light scattering. The electromagnetic near fields in the pencil of light are not uniform, have complicated patterns within short distances from the beam base, and the fields tend to converge to Fraunhofer diffraction fields far away from the base.

Far field diffraction↗

Radiation Characteristics of Cavity Backed Aperture Antennas in Finite Ground Plane Using the Hybrid FEM/MoM Technique and Geometrical Theory of Diffraction

A technique using hybrid Finite Element Method (FEM)/Method of Moments (MoM), and Geometrical Theory of Diffraction (GTD) is presented to analyze the radiation characteristics of cavity fed aperture antennas in a finite ground plane. The cavity which excites the aperture is assumed to be fed by a cylindrical transmission line. The electromagnetic (EM) fields inside the cavity are obtained using FEM. The EM fields and their normal derivatives required for FEM solution are obtained using (1) the modal expansion in the feed region and (2) the MoM for the radiating aperture region(assuming an infinite ground plane). The finiteness of the ground plane is taken into account using GTD. The input admittance of open ended circular, rectangular, and coaxial line radiating into free space through an infinite ground plane are computed and compared with earlier published results. Radiation characteristics of a coaxial cavity fed circular aperture in a finite rectangular ground plane are verified with experimental results.

Reddy, C. J.↗

NASA Tech Briefs, April 2010

Topics covered include: Active and Passive Hybrid Sensor; Quick-Response Thermal Actuator for Use as a Heat Switch; System for Hydrogen Sensing; Method for Detecting Perlite Compaction in Large Cryogenic Tanks; Using Thin-Film Thermometers as Heaters in Thermal Control Applications; Directional Spherical Cherenkov Detector; AlGaN Ultraviolet Detectors for Dual-Band UV Detection; K-Band Traveling-Wave Tube Amplifier; Simplified Load-Following Control for a Fuel Cell System; Modified Phase-meter for a Heterodyne Laser Interferometer; Loosely Coupled GPS-Aided Inertial Navigation System for Range Safety; Sideband-Separating, Millimeter-Wave Heterodyne Receiver; Coaxial Propellant Injectors With Faceplate Annulus Control; Adaptable Diffraction Gratings With Wavefront Transformation; Optimizing a Laser Process for Making Carbon Nanotubes; Thermogravimetric Analysis of Single-Wall Carbon Nanotubes; Robotic Arm Comprising Two Bending Segments; Magnetostrictive Brake; Low-Friction, Low-Profile, High-Moment Two-Axis Joint; Foil Gas Thrust Bearings for High-Speed Turbomachinery; Miniature Multi-Axis Mechanism for Hand Controllers; Digitally Enhanced Heterodyne Interferometry; Focusing Light Beams To Improve Atomic-Vapor Optical Buffers; Landmark Detection in Orbital Images Using Salience Histograms; Efficient Bit-to-Symbol Likelihood Mappings; Capacity Maximizing Constellations; Natural-Language Parser for PBEM; Policy Process Editor for P(sup 3)BM Software; A Quality System Database; Trajectory Optimization: OTIS 4; and Computer Software Configuration Item-Specific Flight Software Image Transfer Script Generator.

Source record↗

On the efficacy of post-build thermomechanical treatments to improve properties of Zirconium fabricated using ultrasonic additive manufacturing

Here, hot-isostatic pressing has been applied to Zirconium plate fabricated using the ultrasonic additive manufacturing (UAM) technique to enhance interfacial bond quality. Specimens heated to 800 C for 1 h at 100 MPa pressure showed grain growth across many prior foil-to-foil interfaces, thereby increasing foil adhesion. In addition to the material softening induced by a loss of Hall-Petch strengthening, premature failure of specimens loaded parallel to the build direction was observed. Premature specimen failure was attributed to the local delamination at prior foil-to-foil boundaries where grain growth was pinned by Ti impurities introduced during the UAM process via the interaction between a Ti-alloy buffer foil and the welded Zr-foils underneath. In addition, the presence of Ti along select foil interfaces resulted in the nucleation and growth of secondary (Zr,Ti)(Fe,Cr) laves phases during higher-temperature thermomechanical processing. Using a combination of micro-scale X-ray computed tomography, fractography, and in-situ digital image correlation, the effect of defects along prior foil-to-foil boundaries was revealed as delamination-assisted plasticity accelerated specimen failure in preferred tensile orientations. These findings underscore the importance of impurity control when optimizing weld quality of higher-strength material systems using ultrasonic welding.

36 MATERIALS SCIENCE↗

Large Hyperfine Coupling Arising from Pseudo- 2 S Ground States in a Series of Lutetium(II) Metallocene Complexes

The synthesis of molecules with strong coupling between electronic and nuclear spins represents an important challenge in molecular quantum information science. Here, we report the synthesis and characterization of the divalent lutetium metallocene complexes Lu(Cp Me 5 )(Cp iPr 5 ) (Cp Me 5 = pentamethylcyclopentadienyl; Cp iPr 5 = pentaisopropylcyclopentadienyl), Lu(Cp iPr 4 Et ) 2 (Cp iPr 4 Et = ethyltetraisopropylcyclopentadienyl), and Lu(Cp iPr 4 ) 2 (Cp iPr 4 = tetraisopropylcyclopentadienyl). The molecular structures of these complexes, as determined through singlecrystal X-ray diffraction, feature a common bent sandwich geometry, with average Cp–Lu–Cp angles ranging from 159.9° to 152.6°. Analysis of continuous-wave electron paramagnetic resonance (EPR) spectra for the complexes reveals nearly isotropic g tensors with only a slight deviation from that of a free electron. Moreover, an extremely large splitting of the eight-line spectra indicates the presence of strong hyperfine coupling, and simulations provide isotropic hyperfine coupling constants of A iso = 4.38, 4.30, and 4.17 GHz across the series, where the value of A iso is found to decrease as the Cp–Lu–Cp angle becomes more acute. Notably, these values are the largest yet observed for any lanthanide complex. Moreover, EPR and computational analysis show that the large values of A iso stem from large s-orbital character up to 41.2% in the corresponding singly occupied molecular orbitals. To our knowledge, this degree of s-character in a molecular orbital is the largest yet reported for an open-shell isolable complex. These results outline a general strategy toward the isolation of paramagnetic molecules with strong hyperfine coupling and highly isotropic doublet electronic ground states.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Chapter 4: Physically informed deep learning networks for simulating microstructure evolution of 3D polycrystals

As discussed in the previous chapter, high energy diffraction microscopy (HEDM) is used to study the micromechanical evolution of a material during in situ loading. HEDM experiments have been used to verify crystal plasticity (CP) simulations [119, 91, 90, 120], for experimental planning, material design, and to further analyze experimental results. However, Fast Fourier transform-based CP (CP-FFT) or finite element-based CP (CP-FE) methods are often too slow to be used in real-time during an experiment. CP-FFT is faster than CP-FE simulations due to the absence of meshing, but can still take hours to simulate the response of a single volume depending on the size and number of strain steps [127]. Reducing computation time would create a larger exploration space in planning and design, and enable faster analysis of experimental results and real-time feedback during an experiment. This research expands upon previous works to develop a workflow for predicting the full-field evolution of a 3D polycrystal. The workflow is simplified from previous works to predict only orientation and elastic strain tensors (from which stress tensors are calculated). The network is physically informed through loss functions and network architecture for a more robust model. The orientation predictions are informed about the cubic crystal symmetry of the material by incorporating disorientation and misorientation information into the network architecture and loss. The Von Mises stress is used to enforce the correct stress-strain trends in the strain tensor predictions. Additional total strain steps from the elastic and elastoplastic region are included to better capture the stress-strain evolution at smaller total strain steps. Material and hardening parameters are additional inputs into the networks to further inform the network and to study the network’s ability to predict different materials other than those used for training.

36 MATERIALS SCIENCE↗

Probing the structure of cometary ice

Computer simulations of bulk and vapor deposited amorphous ices are presented. The structure of the bulk low density amorphous ice is in good agreement with experiments on pressure disordered amorphous ice. Both the low density bulk ice and the vapor deposited ices exhibit strong ordering. Vapor deposition of hot (300 K) water molecules onto a cold (77 K) substrate yields less porous ices than deposition of cold (77 K) water molecules onto a cold substrate. Both vapor deposited ices are more porous than the bulk amorphous ice. The structure of bulk high density amorphous ice is only in fair agreement with experimental results. Attempts to simulate high density amorphous ice via vapor deposition were not successful. Electron diffraction results on vapor deposited amorphous ice indicate that the temperature of the nucleation of the cubic phase depends upon the amount of time between the deposition and the onset of crystallization, suggesting that freshly deposited ice layers reconstruct on time of the order of hours. The temperature dependence of the microporosity of the vapor deposited amorphous ices might affect laboratory experiments that are aimed at simulating astrophysical ices in the context of the origin of prebiotic organic material and its transport to the Earth.

Wilson, Michael A.↗

2022 AI Testbed Expeditions Report

By exploiting the coherent properties of a light source, coherent diffraction imaging (CDI) is able to obtain the sample image at a nanoscale resolution using the measured diffraction pattern. Bragg Coherent Diffraction Imaging (BCDI) has become valuable for recovering the displacement and strain field of crystals, providing a valuable tool in material science and solid-state physics. X-ray ptychography is another emerging CDI technique that can produce a high-resolution image of the extended sample and has become popular in many research areas (e.g., materials science, biology, electronics, and optics characterization). CDI including BCDI and ptychography has become an established technique in Synchrotron Facilities including the Advanced Photon Source (APS) and will greatly benefit from the 100x coherent flux increase of the upcoming APS Upgrade (APSU). The current image formation process in CDI employs iterative phase retrieval algorithms, which is a time-consuming and computationally expensive process. Especially after APSU, the traditional iterative methods will not be able to match the experimental data acquisition speed. We employ deep learning (DL) approach to replace the iterative approaches, therefore allowing hundreds of times faster recovery of the object. We developed AutoPhaseNN, a DL-based approach which learns to solve the inverse problem without labeled data. Taking 3D BCDI as a representative technique, AutoPhaseNN has been demonstrated to be one hundred times faster than traditional iterative phase retrieval methods while providing comparable image quality. The current network is trained with 64 x 64 x 64 data size, to achieve higher resolution imaging, we will need to scale the network to input and train/infer 3D arrays of size 256 x 256 x 256 (today) and of size 2560x2560x2560 (APSU). However, the scalability of the network is restricted due to the memory-intensive training process. To perform the training for a 256 x 256 x 256 data size, the required memory exceeds the capacity of the current machine. In this project, we explore using Sambanova system to train the network for the direct data inversion for CDI.

36 MATERIALS SCIENCE↗

Mapping crystal defects with a digital scanning ultramicroscope

A computer controlled scanning ultramicroscope has been built to assist in the characterization of transparent crystals. The device measures the scattering of a focused He-Ne laser beam by crystalline defects. As an XYZ translation table moves the crystal under the ultramicroscope, the scattered light is measured by a photodetector whose output is digitized and recorded. From this data, contour maps or three dimensional perspective plots of the scattering regions of the crystal can be generated to assist in finding patterns of defects which might be correlated with perturbations in the growth process. The verified resolution of the present instrument is about 1 micrometer, which is limited by the minimum step of the stepper-motor driven translation stages, optical diffraction effects and the sensitivity of the detector at the laser light frequency. The instrument was used to build a database of defects patterns in commercial laboratory grown triglycine sulphate (TGS) crystals, and to map defects in a TGS crystal grown from aqueous solution during the flight of Spacelab 3. This crystal shows indications of a reduction both in the generation of defects at the seed-new growth interface and in their propagation into the new crystal.

Springer, J. M.↗