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At least 1,099 records · Page 61

Space-Time Structured Plasma Waves

Electrostatic waves play a critical role in nearly every branch of plasma physics from fusion to advanced accelerators, to astro, solar, and ionospheric physics. The properties of planar electrostatic waves are fully determined by the plasma conditions, such as density, temperature, ionization state, or details of the distribution functions. Furthermore we demonstrate that electrostatic wave packets structured with space-time correlations can have properties that are independent of the plasma conditions. For instance, an appropriately structured electrostatic wave packet can travel at any group velocity, even backward with respect to its phase fronts, while maintaining a localized energy density. These linear, propagation-invariant wave packets can be constructed with or without orbital angular momentum by superposing natural modes of the plasma and can be ponderomotively excited by space-time structured laser pulses like the flying focus.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Comparing GGA, GGA+ U , and meta-GGA functionals for redox-dependent binding at open metal sites in metal–organic frameworks

Metal–organic frameworks (MOFs) with open metal sites have been widely investigated for the selective adsorption of small molecules via redox mechanisms where charge transfer can take place between the binding site and the adsorbate of interest. Quantum-chemical screening methods based on density functional theory have emerged as a promising route to accelerate the discovery of MOFs with enhanced binding affinities toward various adsorbates. However, the success of this approach is linked to the accuracy of the underlying density functional approximations (DFAs). In this work, we compare commonly used generalized gradient approximation (GGA), GGA+U, and meta-GGA exchange-correlation functionals in modeling redox-dependent binding at open metal sites in MOFs using O 2 and N 2 as representative small molecules. We find that the self-interaction error inherent to the widely used Perdew, Burke, and Ernzerhof (PBE) GGA predicts metal sites that are artificially redox-active, as evidenced by their strong binding affinities, short metal–adsorbate bond distances, and large degree of charge transfer. The incorporation of metal-specific, empirical Hubbard U corrections based on the transition metal oxide literature systematically reduces the redox activity of the open metal sites, often improving agreement with experiment. Additionally, the binding behavior shifts from strong chemisorption to weaker physisorption as a function of U. The M06-L meta-GGA typically predicts binding energies between those of PBE-D3(BJ) and PBE-D3(BJ)+U when using empirically derived U values from the transition metal oxide literature. Despite the strong sensitivity of the binding affinities toward a given DFA, the GGA, GGA+U, and meta-GGA approaches often yield the same qualitative trends and structure–property relationships.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Photon noise correlations in millimeter-wave telescopes

Many modern millimeter and submillimeter (“mm-wave”) telescopes for astronomy are deploying more detectors by increasing the detector pixel density and, with the rise of lithographed detector architectures and high-throughput readout techniques, it is becoming increasingly practical to overfill the focal plane. However, when the pixel pitch p pix is small compared to the product of the wavelength λ and the focal ratio F , or p pix ≲1.2 F λ , the Bose term of the photon noise correlates between neighboring detector pixels due to the Hanbury Brown and Twiss (HBT) effect. When this HBT effect is non-negligible, the array-averaged sensitivity scales with the detector count N det less favorably than the uncorrelated limit of N det −1/2 . In this paper, we present a general prescription to calculate this HBT correlation based on a quantum optics formalism and extend it to polarization-sensitive detectors. We then estimate the impact of HBT correlations on the sensitivity of a model mm-wave telescope and discuss the implications for a focal plane design.

Hill, Charles A. (ORCID:0000000226416878)↗

Structural Flexibility of Metal Chelate Complexes and Its Relation to Supramolecular Chemistry

In this study, crystal structures of metal chelate and related complexes in the Cambridge Structural Database have been analyzed, with respect to their use as components in supramolecular metal-organic compounds. In β-diketonate complexes, the distribution of angles between ligands is relatively broad; other ligands, such as 2,2'-bipyridine, yield significantly narrower distributions. According to the principle of structure correlation, these distributions reflect the ease of distorting the various families of complexes. A comparison through density functional theory calculations also indicates that angular distortions require significantly less energy for M(β-diketonate) 3 than for M(2,2'-bipyridine) 3 . The differences are likely to affect the construction of supramolecular systems from different combinations of metals and ligands, including the likelihood that the desired structures will be obtained.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Identification of Kelvin-Helmholtz generated vortices in magnetised fluids

The Kelvin-Helmholtz Instability (KHI), arising from velocity shear across the magnetopause, plays a significant role in the viscous-like transfer of mass, momentum, and energy from the shocked solar wind into the magnetosphere. While the KHI leads to growth of surface waves and vortices, suitable detection methods for these applicable to magnetohydrodynamics (MHD) are currently lacking. A novel method is derived based on the well-established λ-family of hydrodynamic vortex identification techniques, which define a vortex as a local minimum in an adapted pressure field. The J × B Lorentz force is incorporated into this method by using an effective total pressure in MHD, including both magnetic pressure and a pressure-like part of the magnetic tension derived from a Helmholtz decomposition. The λ MHD method is shown to comprise of four physical effects: vortical momentum, density gradients, fluid compressibility, and the rotational part of the magnetic tension. A local three-dimensional MHD simulation representative of near-flank magnetopause conditions (plasma β’s 0.5 – 5 and convective Mach numbers M f ∼ 0.4) under northward interplanetary magnetic field (IMF) is used to validate λ MHD . Analysis shows it correlates well with hydrodynamic vortex definitions, though the level of correlation decreases with vortex evolution. Overall, vortical momentum dominates λ MHD at all times. During the linear growth phase, density gradients act to oppose vortex formation. By the highly nonlinear stage, the formation of small-scale structures leads to a rising importance of the magnetic tension. Compressibility was found to be insignificant throughout. Finally, a demonstration of this method adapted to tetrahedral spacecraft observations is performed.

79 ASTRONOMY AND ASTROPHYSICS↗

Tetragonal Kondo Insulator EuCd 2 Sb 2 Discovered via High Pressure High Temperature Synthesis

Abstract Magnetic and electronic properties of quantum materials heavily rely on the crystal structure even in the same chemical compositions. In this study, it is demonstrated that a layered tetragonal EuCd 2 Sb 2 structure can be obtained by treating bulk trigonal EuCd 2 Sb 2 under high pressure (6 GPa) and high temperature (600 °C). Magnetization measurements of the newly formed layered tetragonal EuCd 2 Sb 2 confirm an antiferromagnetic ordering with Neel temperature ( T N ) around 16 K, which is significantly higher than that ( T N ≈ 7 K) of trigonal EuCd 2 Sb 2 , consistent with heat capacity measurements. Moreover, bad metal behavior is observed in the temperature dependence of the electrical resistivity and the resistivity shows a dramatic increase around the Neel temperature. Electronic structure calculations with local density approximation dynamic mean–field theory (LDA+DMFT) show that this material is strongly correlated with well‐formed large magnetic moments, due to Hund's coupling, which is known to dramatically suppress the Kondo scale.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Combining ToF‐SIMS and Multivariate Analysis to Resolve Active Sites on Ni‐Based HER Catalysts

Unambiguous identification of active sites in heterogeneous catalysis remains a major challenge, particularly for materials with ultrathin, chemically mixed surface layers. Here, we demonstrate a generalizable approach that combines time-of-flight secondary ion mass spectrometry (ToF-SIMS) with multivariate statistical analysis (principal component analysis [PCA] and multivariate curve resolution [MCR]) to resolve catalytically relevant motifs at the nanoscale. Using Ni electrodes as a model system, PCA distinguished hydroxide-enriched domains from oxide- and metal-rich regions, while MCR decomposed depth profiles and 3D images into hydroxide, oxide, and metallic layers with nanometer resolution. A unique secondary-ion fragment, NiO 3 H 3 − (m/z 108.94), emerged as a marker of hydroxide-rich environments and correlated with hydrogen evolution reaction (HER) activity across a series of Ni electrodes. Complementary density functional theory (DFT) calculations revealed that Ni(OH) 2 clusters adjacent to metallic Ni offer the most favorable water dissociation energetics, establishing the structural origin of the marker. While illustrated here for Ni-based HER, this workflow provides a broadly applicable framework to isolate and rank near-surface patterns that govern catalytic activity, thereby extending ToF-SIMS from a qualitative probe to a predictive tool for active site identification.

HER active sites↗

Phosphate‐functionalized Zirconium Metal–Organic Frameworks for Enhancing Lithium–Sulfur Battery Cycling

Abstract Lithium–sulfur batteries are promising candidates for next‐generation energy storage devices due to their outstanding theoretical energy density. However, they suffer from low sulfur utilization and poor cyclability, greatly limiting their practical implementation. Herein, we adopted a phosphate‐functionalized zirconium metal–organic framework (Zr‐MOF) as a sulfur host. With their porous structure, remarkable electrochemical stability, and synthetic versatility, Zr‐MOFs present great potential in preventing soluble polysulfides from leaching. Phosphate groups were introduced to the framework post‐synthetically since they have shown a strong affinity towards lithium polysulfides and an ability to facilitate Li ion transport. The successful incorporation of phosphate in MOF‐808 was demonstrated by a series of techniques including infrared spectroscopy, solid‐state nuclear magnetic resonance spectroscopy, and X‐ray pair distribution function analysis. When employed in batteries, phosphate‐functionalized Zr‐MOF (MOF‐808‐PO4) exhibits significantly enhanced sulfur utilization and ion diffusion compared to the parent framework, leading to higher capacity and rate capability. The improved capacity retention and inhibited self‐discharge rate also demonstrate effective polysulfide encapsulation utilizing MOF‐808‐PO4. Furthermore, we explored their potential towards high‐density batteries by examining the cycling performance at various sulfur loadings. Our approach to correlate structure with function using hybrid inorganic–organic materials offers new chemical design strategies for advancing battery materials.

Liu, Bingqian↗

Machine learning for accuracy in density functional approximations

Machine learning techniques have found their way into computational chemistry as indispensable tools to accelerate atomistic simulations and materials design. In addition, machine learning approaches hold the potential to boost the predictive power of computationally efficient electronic structure methods, such as density functional theory, to chemical accuracy and to correct for fundamental errors in density functional approaches. In this paper, recent progress in applying machine learning to improve the accuracy of density functional and related approximations is reviewed. Promises and challenges in devising machine learning models transferable between different chemistries and materials classes are discussed with the help of examples applying promising models to systems far outside their training sets.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DeePKS-kit: A package for developing machine learning-based chemically accurate energy and density functional models

We introduce DeePKS-kit, an open-source software package for developing machine learning based energy and density functional models. DeePKS-kit is interfaced with PyTorch, an open-source machine learning library, and PySCF, an ab initio computational chemistry program that provides simple and customized tools for developing quantum chemistry codes. It supports the DeePHF and DeePKS methods. In addition to explaining the details in the methodology and the software, we also provide an example of developing a chemically accurate model for water clusters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Comparison of fiber-optic distributed temperature sensing and high-sensitivity sensor spatial surveying of stream temperature

Measuring surface water temperature spatial variability is needed to estimate the interaction between surface water and groundwater, evaluate fish habitat and thermal inertia, and to estimate streamflow frequency and duration. Fiber optic distributed temperature sensing (FO-DTS) has been used in rivers and lakes, providing high-resolution and sensitive temperature monitoring over large temporal and spatial scales. However, in streams with cobbly or bedrock-lined streambeds and variable bathymetry, use of FO-DTS to measure temperature close to the surface water and groundwater interface can be challenging if even feasible. FO-DTS can also be costly, involve difficult installations, and require an advanced understanding of the technology, calibration, and data processing. In this study, we compared FO-DTS stream temperature survey results to an alternative temperature survey method employing a towed transect of high-resolution temperature loggers spaced at 1-m and transported in the stream along the study reach, to measure the spatial distribution of stream-water temperature in East Fork Poplar Creek near Oak Ridge, Tennessee, USA. We assessed the applicability and limitations of the two methods, and quantitatively compared in-situ temperature survey results measured simultaneously with each method. Regression results showed strong temporal and spatial correlation between the two methods. Differences were only elevated near the stream banks in areas that were coincident with correlation slope deviations from unity, which was attributed to shallower water and lower data density. Kriging standard errors were also low at channel center with minor increases near the stream banks. Furthermore, the results suggested that the array of the individual temperature sensors can provide a practical alternative to FO-DTS for thermal characterization of surface water, providing slightly lower spatial and temporal resolution, but with higher accuracy of temperature measurement, with greater simplicity, and with a broader range of conditions where it may be applied.

54 ENVIRONMENTAL SCIENCES↗

Molecular dynamics simulation of the effect of cooling rate on the structure and properties of lithium disilicate glass

The effects of cooling rate on the structure and properties of lithium disilicate (LS2) glass are investigated using molecular dynamics (MD) computer simulations. The evolution of structural features such as pair distribution function, bond angle distribution, and Li coordination distribution are determined, and correlated with dynamic and static properties to elucidate the effects of cooling rate. The density, elastic moduli, and diffusion coefficient are found to be highly sensitive to cooling rate, whereas the Si pair distribution function and bond angle distribution are weakly affected by the cooling rate. Additionally, the changes of Si-O-Si bond angle and Li coordination number suggest the formation of Li cluster at lower cooling rates. Furthermore, by comparing results from other simulations and reported experiments, we confirm that the increase of cooling rate leads to an increase of conductivity and a decrease of density. Finally, at very high cooling rates, we find that all the atoms in LS2-glass do not relax simultaneously, but do so in two distinct configurations.

36 MATERIALS SCIENCE↗

Machine Learning-Driven Solvent Screening for Biobased 2,3-Butanediol Extraction

Biobased 2,3-butanediol (2,3-BDO) is a valuable biomass-derived chemical due to its versatility in being transformed into a wide variety of products. However, the separation and purification of 2,3-BDO from fermentation broth remain a significant challenge owing to its high boiling point and hydrophilic nature. Herein, we developed a machine learning (ML)-based screening workflow that uses molecular calculations as training data and requires only a small number of experimental measurements for validation to identify alternative solvent candidates for the liquid–liquid extraction (LLE) of 2,3-BDO from aqueous solution. In particular, 130 density functional theory (DFT) calculations with the implicit solvation method not only built a correlation between the computational partition coefficient and the experimental distribution coefficient of 2,3-BDO but also parameterized an Extra-Trees ML model to screen the distribution coefficient for a wider range of 6717 organic solvents. The experimental measurements of only 24 solvents were needed to validate the computational results. A list of 50 prioritized solvents was proposed for 2,3-BDO LLE, and seven additional experimental measurements were conducted to further verify our selected solvents. The impact of the extraction temperature and solvent-to-feed ratio was also investigated for selected solvents in experiments. Furthermore, this work suggested alternative solvents for 2,3-BDO LLE and proposed a versatile workflow that requires fewer experiments and can be applied to a broader range of LLE studies.

Extraction↗

Design and Characterization of Metal Nanoparticle Infiltrated Mesoporous Metal–Organic Frameworks

The infiltration of palladium and platinum nanoparticles (NPs) into the mesoporous metal–organic framework (MOF) CYCU-3 through chemical vapor infiltration (CVI) and incipient wetness infiltration (IWI) processes was systematically explored as a means to design novel NP@MOF composite materials for potential hydrogen storage applications. We employed a traditional CVI process and a new "green" IWI process using methanol for precursor infiltration and reduction under mild conditions. Transmission electron microscopy-based direct imaging techniques combined with synchrotron-based powder diffraction (SPD), energy-dispersive X-ray spectroscopy, and physisorption analysis reveal that the resulting NP@MOF composites combine key NP and MOF properties. Room temperature hydrogen adsorption capacities of 0.95 and 0.20 mmol/g at 1 bar and 2.9 and 1.8 mmol/g at 100 bar are found for CVI and IWI samples, respectively. Additionally, hydrogen spillover and/or physisorption are proposed as the dominating adsorption mechanisms depending on the NP infiltration method. Mechanistic insights were obtained through the crystallographic means using SPD-based difference envelope density analysis, providing previously underexplored details on NP@MOF preparations. Consequently, important host–guest correlations influencing the global hydrogen adsorption properties are discussed, and they demonstrate that employing MOFs as platforms for NPs is an alternative approach to the development of versatile materials for improving current hydrogen storage technologies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Unusual Role of Point Defects in Perovskite Nickelate Electrocatalysts

Low-cost transition-metal oxide is regarded as a promising electrocatalyst family for an oxygen evolution reaction (OER). The classic design principle for an oxide electrocatalyst believes that point defect engineering, such as oxygen vacancies (VO .. ) or heteroatom doping, offers the opportunities to manipulate the electronic structure of material toward optimal OER activity. Oppositely, in this work, we discover a counterintuitive phenomenon that both VO .. and an aliovalent dopant (i.e., proton (H + )) in perovskite nickelate (i.e., NdNiO 3 (NNO)) have a considerably detrimental effect on intrinsic OER performance. Detailed characterizations unveil that the introduction of these point defects leads to a decrease in the oxidative state of Ni and weakens Ni-O orbital hybridization, which triggers the local electron-electron correlation and a more insulating state. Evidenced by first-principles calculation using the density functional theory (DFT) method, the OER on nickelate electrocatalysts follows the lattice oxygen mechanism (LOM). The incorporation of point defect increases the energy barrier of transformation from OO*(V O ) to OH*(V O ) intermediates, which is regarded as the rate-determining step (RDS). Furthermore, this work offers a new and significant perspective of the role that lattice defects play in the OER process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Sub-system self-consistency in coupled cluster theory

Here, in this article, we provide numerical evidence indicating that the single-reference coupled-cluster (CC) energies can be calculated alternatively to their copybook definition. We demonstrate that the CC energy can be reconstructed by diagonalizing the effective Hamiltonians describing correlated sub-systems of the many-body system. In the extreme case, we provide numerical evidence that the CC energy can be reproduced through the diagonalization of the effective Hamiltonian describing sub-system composed of a single electron. These properties of the CC formalism can be exploited to design protocols to define effective interactions in sub-systems used as probes to calculate the energy of the entire system and introduce a new type of self-consistency for approximate CC approaches.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Disordered hyperuniform solid state materials

Disordered hyperuniform (DHU) states are recently discovered exotic states of condensed matter. DHU systems are similar to liquids or glasses in that they are statistically isotropic and lack conventional long-range translational and orientational order. On the other hand, they completely suppress normalized infinite-wavelength density fluctuations like crystals and, in this sense, possess a hidden long-range correlation. Very recently, there have been several exciting discoveries of disordered hyperuniformity in solid-state materials, including amorphous carbon nanotubes, amorphous 2D silica, amorphous graphene, defected transition metal dichalcogenides, defected pentagonal 2D materials, and medium/high-entropy alloys. It has been found that the DHU states of these materials often possess a significantly lower energy than other disorder models and can lead to unique electronic and thermal transport properties, which results from mechanisms distinct from those identified for their crystalline counterparts. For example, DHU states can enhance electronic transport in 2D amorphous silica; DHU medium/high-entropy alloys realize the Vegard's law and possess enhanced electronic bandgaps and thermal transport at low temperatures. These unique properties open up many promising potential device applications in optoelectronics and thermoelectrics. Here, we provide a focused review on these important new developments of hyperuniformity in solid-state materials, taking an applied and “materials” perspective, which complements the existing reviews on hyperuniformity in physical systems and photonic materials. As a result, future directions and outlook are also provided, with a focus on the design and discovery of DHU quantum materials for quantum information science and engineering.

2D materials↗