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At least 163 records · Page 9

Enhanced Electrocatalytic and Selective CO 2 -to-CO Reduction by a Rhenium(I) Complex Bearing 6,6′-Substituted 2,2′-Bipyridines

The electrochemical reduction of CO 2 (CO 2 RR) into value-added chemicals offers a promising route toward a circular carbon economy and reduced reliance on fossil fuels. A detailed understanding of the structural and electronic factors governing the performance of molecular CO 2 RR electrocatalysts is essential for the design of efficient, tunable systems. Here, in this study, we report a series of rhenium(I) complexes, fac-[Re I (6,6′-(R) 2 -bpy)(CO) 3 Cl] (bpy = 2,2′-bipyridine; R = mesityl (mes), 2,4,6-triisopropylphenyl (trip), or isophthalic acid (phth)) and evaluate their electrocatalytic activity. Among these, fac-[Re I (6,6′-(mes) 2 -bpy)(CO) 3 Cl] exhibited the highest performance, enabling selective CO 2 -to-CO conversion for 1 hour with Faradaic efficiency (FE) > 97%, representing an unprecedented activity level for a Re-bpy catalysts. Single-crystal X-ray diffraction and density functional theory (DFT) calculations indicated that favorable CO 2 binding could be promoted by the tilting of the 6,6′-(mes)2-bpy ligand (from the Re-CO coordination plane), providing mechanistic insight into the observed enhancement. The study consequently demonstrates a rational correlation between the CO 2 electrocatalytic performance of Re-bpy catalysts and their structural variations, as derived from X-ray data and corroborated by computational modeling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Optical neural engine for solving scientific partial differential equations

Abstract Solving partial differential equations (PDEs) is the cornerstone of scientific research and development. Data-driven machine learning (ML) approaches are emerging to accelerate time-consuming and computation-intensive numerical simulations of PDEs. Although optical systems offer high-throughput and energy-efficient ML hardware, their demonstration for solving PDEs is limited. Here, we present an optical neural engine (ONE) architecture combining diffractive optical neural networks for Fourier space processing and optical crossbar structures for real space processing to solve time-dependent and time-independent PDEs in diverse disciplines, including Darcy flow equation, the magnetostatic Poisson’s equation in demagnetization, the Navier-Stokes equation in incompressible fluid, Maxwell’s equations in nanophotonic metasurfaces, and coupled PDEs in a multiphysics system. We numerically and experimentally demonstrate the capability of the ONE architecture, which not only leverages the advantages of high-performance dual-space processing for outperforming traditional PDE solvers and being comparable with state-of-the-art ML models but also can be implemented using optical computing hardware with unique features of low-energy and highly parallel constant-time processing irrespective of model scales and real-time reconfigurability for tackling multiple tasks with the same architecture. The demonstrated architecture offers a versatile and powerful platform for large-scale scientific and engineering computations.

Tang, Yingheng (ORCID:0009000153622546)↗

Two-dimensional perovskite templates for durable, efficient formamidinium perovskite solar cells

We present a design strategy for fabricating ultrastable phase-pure films of formamidinium lead iodide (FAPbI 3 ) by lattice templating using specific two-dimensional (2D) perovskites with FA as the cage cation. When a pure FAPbI 3 precursor solution is brought in contact with the 2D perovskite, the black phase forms preferentially at 100°C, much lower than the standard FAPbI 3 annealing temperature of 150°C. X-ray diffraction and optical spectroscopy suggest that the resulting FAPbI 3 film compresses slightly to acquire the (011) interplanar distances of the 2D perovskite seed. The 2D-templated bulk FAPbI 3 films exhibited an efficiency of 24.1% in a p-i-n architecture with 0.5–square centimeter active area and an exceptional durability, retaining 97% of their initial efficiency after 1000 hours under 85°C and maximum power point tracking.

14 SOLAR ENERGY↗

Robust atom optics for Bragg atom interferometry

Multi-photon Bragg diffraction is a powerful method for fast, coherent momentum transfer of atom waves. However, laser noise, Doppler detunings, and cloud expansion limit its efficiency in large momentum transfer (LMT) pulse sequences. We present simulation studies of robust Bragg pulses developed through numerical quantum optimal control. Optimized pulse performance under noise and cloud inhomogeneities is analyzed and compared to analogous Gaussian and adiabatic rapid passage pulses in simulated LMT Mach–Zehnder interferometry sequences. The optimized pulses maintain robust population transfer and phase response over a broader range of noise, resulting in superior contrast in LMT sequences with thermal atom clouds and intensity inhomogeneities. Large optimized LMT sequences use lower pulse area than Gaussian pulses, making them less susceptible to spontaneous emission loss. The optimized sequences maintain over five times better contrast with tens of momentum separation and offer more improvement with greater LMT. Such pulses could allow operation of Bragg atom interferometers with unprecedented sensitivity, improved contrast, and hotter atom sources.

74 ATOMIC AND MOLECULAR PHYSICS↗

Phonon‐Dominated Energy Transport in Purely Metallic Heterostructures

Abstract Ultrafast X‐ray diffraction is used to quantify the transport of energy in laser‐excited nanoscale gold–nickel (Au–Ni) bilayers. Electron transport and efficient electron–phonon coupling in Ni convert the laser‐deposited energy in the conduction electrons within a few picoseconds into a strong non‐equilibrium between hot Ni and cold Au phonons at the bilayer interface. Modeling of the subsequent equilibration dynamics within various two‐temperature models confirms that for ultrathin Au films, the thermal transport is dominated by phonons instead of conduction electrons because of the weak electron–phonon coupling in Au.

36 MATERIALS SCIENCE↗

Interaction of radio frequency waves with cylindrical density filaments: scattering and radiation pressure

The propagation of radio-frequency (RF) waves in tokamaks can be affected by filamentary structures, or blobs, that are present in the edge plasma and the scrape-off layer. The difference in the permittivity between the surrounding plasma and interior of a filament leads to reflection, refraction and diffraction of the waves. This, in turn, can affect the power flow into the core of the plasma and reduce the efficiency of heating and/or current generation. The scattering of RF waves, lower hybrid, helicon and ion cyclotron waves, by a single cylindrical filament, embedded in a background plasma, is studied using a full-wave analytical theory developed previously (Ram & Hizanidis, Phys. Plasmas , vol. 23, 2016, 022504). The theory assumes that the plasma in and around a filament is homogeneous and cold. A detailed scattering analysis reveals a variety of common features that exist among the three distinctly different RF waves. These common attributes can be inferred intuitively based on an examination of the cold plasma dispersion relation. The physical intuition is a useful step to understanding experimental observations on scattering, as well as results from simulations that include general forms of edge plasma turbulence. While a filament can affect the propagation of RF waves, the radiation force exerted by the waves can influence the filament. The force on a filament is determined using the Maxwell stress tensor. In 1905, Poynting was the first to evaluate and measure the radiation force on an interface separating two different dielectric media (Poynting, London Edinburgh Dublin Philos. Mag. J. Sci. , vol. 9, 1905, pp. 393–406). For ordinary light propagating in vacuum and incident on a glass surface, Poynting noted that the surface is ‘pulled’ towards the vacuum. In a magnetized cold plasma, there are two independent wave modes. Even if only one of these modes is excited by an RF antenna, a filament will couple power to the other mode: a consequence of electromagnetic boundary conditions. This facet of scattering has consequences on the radiation force that go beyond Poynting's seminal contribution. The direction of the force depends on the polarization of the incident wave and on the mode structure of the waves inside and in the vicinity of a filament. It can either pull the filament toward the RF source or push it away. For slow lower hybrid waves, filaments with densities greater than the ambient density are pulled in, while filaments with lower densities are pushed out, thereby enhancing the density in front of the antenna. In the case of fast helicon and ion cyclotron waves, the direction of the force depends on the plasma and wave parameters; in particular, on the ambient density. The radiation force, in all three frequency ranges, is large enough to affect the motion of a filament and could be measured experimentally. This also suggests the possibility of modifying the edge turbulence using RF waves.

Physics↗

Interaction of radio frequency waves with cylindrical density filaments -- scattering and radiation pressure

The propagation of radio-frequency (RF) waves in tokamaks can be affected by filamentary structures, or blobs, that are present in the edge plasma and the scrape-off layer. The difference in the permittivity between the surrounding plasma and interior of a filament leads to reflection, refraction and diffraction of the waves. This, in turn, can affect the power flow into the core of the plasma and reduce the efficiency of heating and/or current generation. The scattering of RF waves, lower hybrid, helicon and ion cyclotron waves, by a single cylindrical filament, embedded in a background plasma, is studied using a full-wave analytical theory developed previously (Ram & Hizanidis, Phys. Plasmas, vol. 23, 2016, 022504). The theory assumes that the plasma in and around a filament is homogeneous and cold. A detailed scattering analysis reveals a variety of common features that exist among the three distinctly different RF waves. These common attributes can be inferred intuitively based on an examination of the cold plasma dispersion relation. The physical intuition is a useful step to understanding experimental observations on scattering, as well as results from simulations that include general forms of edge plasma turbulence. While a filament can affect the propagation of RF waves, the radiation force exerted by the waves can influence the filament. The force on a filament is determined using the Maxwell stress tensor. In 1905, Poynting was the first to evaluate and measure the radiation force on an interface separating two different dielectric media (Poynting, London Edinburgh Dublin Philos. Mag. J. Sci., vol. 9, 1905, pp. 393–406). For ordinary light propagating in vacuum and incident on a glass surface, Poynting noted that the surface is ‘pulled’ towards the vacuum. In a magnetized cold plasma, there are two independent wave modes. Even if only one of these modes is excited by an RF antenna, a filament will couple power to the other mode: a consequence of electromagnetic boundary conditions. This facet of scattering has consequences on the radiation force that go beyond Poynting's seminal contribution. The direction of the force depends on the polarization of the incident wave and on the mode structure of the waves inside and in the vicinity of a filament. It can either pull the filament toward the RF source or push it away. For slow lower hybrid waves, filaments with densities greater than the ambient density are pulled in, while filaments with lower densities are pushed out, thereby enhancing the density in front of the antenna. In the case of fast helicon and ion cyclotron waves, the direction of the force depends on the plasma and wave parameters; in particular, on the ambient density. The radiation force, in all three frequency ranges, is large enough to affect the motion of a filament and could be measured experimentally. This also suggests the possibility of modifying the edge turbulence using RF waves.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Cu-, Co-, and Zn-Based Metal–Organic Framework-Derived Nanoporous Ion Emitters for Picogram Level Analysis of Actinides

Thermal ionization mass spectrometry (TIMS) is often regarded as the preferred technique for trace-level isotopic analysis of actinides owing to its high sensitivity and absence of carry-over effects. However, actinide sample utilization efficiency (SUE) is typically low (<0.05%) without the use of activators or specialized loading approaches which can yield SUEs of >5%. To this effect, we investigate a series of metal–organic framework (MOF)-based nanoporous ion emitters (nano-PIEs) that show enhanced ionization of actinides when used in TIMS loading. We study the impact of physical and chemical properties of MOFs on TIMS SUEs using two families of MOFs that can be synthesized under similar reaction conditions. The structural and chemical properties of these MOFs can be systematically modified one at a time while keeping other features the same. This allows us to strategically investigate their impact on SUEs. The first family of MOFs considered in this study is Zeolitic Imidazole Frameworks (ZIFs) which are made using 2 methyl-imidazole as an organic linker with zinc (ZIF-8) and cobalt (ZIF-67) as metal centers. Additionally, the effect of morphology was also studied using Zn-based ZIF-L with a 2-dimensional structure. The second family of MOFs was synthesized using benzene-1,3,5-tricarboxylate (BTC) with copper (Cu-BTC) and zinc (Zn-BTC) as the metal center. Among the MOFs tested, Cu-BTC showed the highest SUE with an average SUE of 0.27 ± 0.15%, followed closely by Zn-BTC (0.24 ± 0.10%), ZIF-8 (0.17 ± 0.10%), and trailed by the other MOFs. When the MOFs were pyrolyzed in N 2 before loading, an apparent increase in the SUE was observed with ZIF-8 and Cu-BTC showing average SUEs of 0.25 ± 0.08% and 0.34 ± 0.13%, respectively, with the highest measured SUE of 0.53% for pyrolyzed Cu-BTC. In conclusion, this observed increase in SUE by up to an order of magnitude compared to bare filaments demonstrates the efficacy and potential of MOF-derived nano-PIEs for TIMS application.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Concurrent multi-peak Bragg coherent x-ray diffraction imaging of 3D nanocrystal lattice displacement via global optimization

Abstract In this paper we demonstrated a method to reconstruct vector-valued lattice distortion fields within nanoscale crystals by optimization of a forward model of multi-reflection Bragg coherent diffraction imaging (MR-BCDI) data. The method flexibly accounts for geometric factors that arise when making BCDI measurements, is amenable to efficient inversion with modern optimization toolkits, and allows for globally constraining a single image reconstruction to multiple Bragg peak measurements. This is enabled by a forward model that emulates the multiple Bragg peaks of a MR-BCDI experiment from a single estimate of the 3D crystal sample. We present this forward model, we implement it within the stochastic gradient descent optimization framework, and we demonstrate it with simulated and experimental data of nanocrystals with inhomogeneous internal lattice displacement. We find that utilizing a global optimization approach to MR-BCDI affords a reliable path to convergence of data which is otherwise challenging to reconstruct.

36 MATERIALS SCIENCE↗

An adaptive approach to machine learning for compact particle accelerators

Abstract Machine learning (ML) tools are able to learn relationships between the inputs and outputs of large complex systems directly from data. However, for time-varying systems, the predictive capabilities of ML tools degrade if the systems are no longer accurately represented by the data with which the ML models were trained. For complex systems, re-training is only possible if the changes are slow relative to the rate at which large numbers of new input-output training data can be non-invasively recorded. In this work, we present an approach to deep learning for time-varying systems that does not require re-training, but uses instead an adaptive feedback in the architecture of deep convolutional neural networks (CNN). The feedback is based only on available system output measurements and is applied in the encoded low-dimensional dense layers of the encoder-decoder CNNs. First, we develop an inverse model of a complex accelerator system to map output beam measurements to input beam distributions, while both the accelerator components and the unknown input beam distribution vary rapidly with time. We then demonstrate our method on experimental measurements of the input and output beam distributions of the HiRES ultra-fast electron diffraction (UED) beam line at Lawrence Berkeley National Laboratory, and showcase its ability for automatic tracking of the time varying photocathode quantum efficiency map. Our method can be successfully used to aid both physics and ML-based surrogate online models to provide non-invasive beam diagnostics.

97 MATHEMATICS AND COMPUTING↗

Femtosecond photoemission electron microscopy of surface plasmon polariton beam steering via nanohole arrays

Directional control over surface plasmon polariton (SPP) waves is a prerequisite for the development of miniaturized optical circuitry. Here, the efficacy of single and dual component SPP steering elements is explored through photoemission electron microscopy. Our imaging scheme relies on two-color photoemission and counter-propagating SPP generation, which collectively allow SPPs to be visualized in real space. Wave-vector difference mixing between two-dimensional arrays of nanoholes and photon momenta enables SPP steering with directionality governed by the array lattice constant. The magnitude of grating momentum required to achieve counter-propagation guarantees efficient steering over the full range of the negative half-space. In our dual component configuration, separate SPP generation and Bragg diffraction based steering optics are employed. We find that array Bragg planes principally influence the SPP angles through the array band structure, which allows us to visualize both positive and negative refractory waves.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Thermally driven phase transition of halide perovskites revealed by big data-powered in situ electron microscopy

Halide perovskites are promising light-absorbing materials for high-efficiency solar cells, while the crystalline phase of halide perovskites may influence the device’s efficiency and stability. In this work, we investigated the thermally driven phase transition of perovskite (CsPbIxBr3—x), which was confirmed by electron diffraction and high-resolution transmission electron microscopy results. CsPbIxBr3—x transitioned from δ phase to α phase when heated, and the γ phase was obtained when the sample was cooled down. The γ phase was stable as long as it was isolated from humidity and air. A template matching-based data analysis method enabled visualization of the thermally driven phase evolution of perovskite during heating. Here, we also proposed a possible atomic movement in the process of phase transition based on our in situ heating experimental data. The results presented here may improve our understanding of the thermally driven phase transition of perovskite as well as provide a protocol for big-data analysis of in situ experiments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

SGD-Net: Efficient Model-Based Deep Learning with Theoretical Guarantees

Deep unfolding networks have recently gained popularity for solving imaging inverse problems. However, the computational and memory complexity of data-consistency layers within traditional deep unfolding networks scales with the number of measurements, limiting their applicability to large-scale imaging inverse problems. We propose SGD-Net as a new methodology for improving the efficiency of deep unfolding through stochastic approximations of the data-consistency layers. Our theoretical analysis shows that SGD-Net can be trained to approximate batch deep unfolding networks to an arbitrary precision. Our simulations on intensity diffraction tomography and sparse-view computed tomography show that SGD-Net can match the performance of the traditional batch network at a fraction of training and testing complexity.Deep unfolding networks have recently gained popularity for solving imaging inverse problems. However, the computational and memory complexity of data-consistency layers within traditional deep unfolding networks scales with the number of measurements, limiting their applicability to large-scale imaging inverse problems. We propose SGD-Net as a new methodology for improving the efficiency of deep unfolding through stochastic approximations of the data-consistency layers. Our theoretical analysis shows that SGD-Net can be trained to approximate batch deep unfolding networks to an arbitrary precision. Our simulations on intensity diffraction tomography and sparse-view computed tomography show that SGD-Net can match the performance of the traditional batch network at a fraction of training and testing complexity.

97 MATHEMATICS AND COMPUTING↗

Toward monochromated sub-nanometer UEM and femtosecond UED

A preliminary design of a mega-electron-volt (MeV) monochromator with 10 –5 energy spread for ultrafast electron diffraction (UED) and ultrafast electron microscopy (UEM) is presented. Such a narrow energy spread is advantageous in both the single shot mode, where the momentum resolution in diffraction is improved, and the accumulation mode, where shot-to-shot energy jitter is reduced. In the single-shot mode, we numerically optimized the monochromator efficiency up to 13% achieving 1.3 million electrons per pulse. In the accumulation mode, to mitigate the efficiency degradation caused by the shot-to-shot energy jitter, an optimized gun phase yields only a mild reduction of the single-shot efficiency, therefore the number of accumulated electrons nearly proportional to the repetition rate. Inspired by the recent work of Qi et al. (Phys Rev Lett 124:134803, 2020), a novel concept of applying reverse bending magnets to adjust the energy-dependent path length difference has been successfully realized in designing a MeV monochromator to achieve the minimum energy-dependent path length difference between cathode and sample. Thanks to the achromat design, the pulse length of the electron bunches and the energy-dependent timing jitter can be greatly reduced to the 10 fs level. The introduction of such a monochromator provides a major step forward, towards constructing a UEM with sub-nm resolution and a UED with ten-femtosecond temporal resolution. The one-to-one mapping between the electron beam parameter and the diffraction peak broadening enables a real-time nondestructive diagnosis of the beam energy spread and divergence. The tunable electric–magnetic monochromator allows the scanning of the electron beam energy with a 10 –5 precision, enabling online energy matching for the UEM, on-momentum flux maximizing for the UED and real-time energy measuring for energy-loss spectroscopy. A combination of the monochromator and a downstream chicane enables “two-color” double pulses with femtosecond duration and the tunable delay in the range of 10 to 160 fs, which can potentially provide an unprecedented femtosecond time resolution for time resolved UED.

36 MATERIALS SCIENCE↗

XFEL Microcrystallography of Self-Assembling Silver n -Alkanethiolates

New synthetic hybrid materials and their increasing complexity have placed growing demands on crystal growth for single-crystal X-ray diffraction analysis. Unfortunately, not all chemical systems are conducive to the isolation of single crystals for traditional characterization. Here, small-molecule serial femtosecond crystallography (smSFX) at atomic resolution (0.833 Å) is employed to characterize microcrystalline silver n-alkanethiolates with various alkyl chain lengths at X-ray free electron laser facilities, resolving long-standing controversies regarding the atomic connectivity and odd–even effects of layer stacking. smSFX provides high-quality crystal structures directly from the powder of the true unknowns, a capability that is particularly useful for systems having notoriously small or defective crystals. We present crystal structures of silver n-butanethiolate (C4), silver n-hexanethiolate (C6), and silver n-nonanethiolate (C9). We show that an odd–even effect originates from the orientation of the terminal methyl group and its role in packing efficiency. We also propose a secondary odd–even effect involving multiple mosaic blocks in the crystals containing even-numbered chains, identified by selected-area electron diffraction measurements. Finally, we conclude with a discussion of the merits of the synthetic preparation for the preparation of microdiffraction specimens and compare the long-range order in these crystals to that of self-assembled monolayers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Actinide Separation Inspired by Self-Assembled Metal–Polyphenolic Nanocages

The separation of actinides has a vital place in nuclear fuel reprocessing, recovery of radionuclides, and remediation of environmental contamination. Here we propose a new paradigm of nanocluster-based actinide separation, namely, nanoextraction, that can achieve efficient sequestration of uranium in an unprecedented form of giant coordination nanocages using a cone-shaped macrocyclic pyrogallol[4]arene as the extractant. The U 24 -based hexameric pyrogallol[4]arene nanocages with distinctive [U 2 (PG) 2 ] binuclear units (PG = pyrogallol) that rapidly assembled in situ in monophasic solvent were identified by single-crystal X-ray diffraction, MALDI-TOF mass spectrometry, NMR spectroscopy, and small-angle X-ray and neutron scattering. Furthermore, comprehensive biphasic extraction studies showed that this novel separation strategy has enticing advantages such as fast kinetics, high efficiency, and good selectivity over lanthanides, thereby demonstrating its potential for efficient separation of actinide ions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Time-Resolved Structural Measurement of Thermal Resistance across a Buried Semiconductor Heterostructure Interface

The precise control and understanding of heat flow in heterostructures is pivotal for advancements in thermoelectric energy conversion, thermal barrier coatings, and efficient heat management in electronic and optoelectronic devices. In this study, we employ high-angular-resolution time-resolved X-ray diffraction to structurally measure thermal resistance in a laser-excited AlGaAs/GaAs semiconductor heterostructure. Our methodology offers femtometer-scale spatial sensitivity and nanosecond time resolution, enabling us to directly observe heat transport across a buried interface. We corroborate established Thermal Boundary Resistance (TBR) values for AlGaAs/GaAs heterostructures and demonstrate that TBR arises from material property discrepancies on either side of a nearly flawless atomic interface. This work not only sheds light on the fundamental mechanisms governing heat flow across buried interfaces but also presents a robust experimental framework that can be extended to other heterostructure systems, paving the way for optimized thermal management in next-generation devices.

36 MATERIALS SCIENCE↗

Microwave-assisted ammonia decomposition over metal nitride catalysts at low temperatures

The negative environmental impact of fossil fuel-based energy systems has unveiled the need to develop a CO x -free sustainable hydrogen (H 2 ) economy. Employing a microwave-assisted route, a ternary metal nitride catalyst (i.e., Co 2 Mo 3 N), and a low-temperature-pressure NH 3 decomposition process, this study investigated the possibility of developing a distributed H 2 production process. Here, this study not only explored lower cost-based catalyst systems but also the use of a microwave reactor to increase the energy efficiency of the process. Results from catalytic NH 3 decomposition experiments, performed in microwave reactors on Co 2 Mo 3 N catalyst, demonstrated the peak energy efficiency (of ~0.006 kgH 2 /kWh) at 400 °C in ambient pressure (with an NH 3 conversion >90%) which was around ninety times (~90 x) more efficient than a conventional system. Activation energy calculation also displayed a 20% less energy requirement for the microwave-based process (~31 kJ mol -1 ) than the conventional system (~37 kJ mol -1 ), indicating the advantage of the microwave-based process. Further microwave-assisted catalytic measurements and characterization of the Co 2 Mo 3 N catalyst, using x-ray diffraction (XRD) technique and scanning electron microscopic (SEM) images, revealed the excellent stability of this material at its peak performance (at 400 °C) and illustrated the potential of using this catalyst for a sustainable, economic, and energy-efficient approach for producing CO x -free H 2 .

08 HYDROGEN↗