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At least 163 records · Page 9

Estimating Electron Temperature and Density Using Van Allen Probe Data: Typical Behavior of Energetic Electrons in the Inner Magnetosphere

Abstract The Earth's inner magnetosphere contains multiple electron populations influenced by different factors. The cold electrons of the plasmasphere, warm plasma that contributes to the ring current, and the relativistic plasma of the radiation belts often seem to behave independently. Using omni‐directional flux and energy measurements from the HOPE and Magnetic Electron Ion Spectrometer instruments aboard the Van Allen Probes, we provide a detailed density and temperature description of the inner magnetosphere, offering a comprehensive statistical analysis of the entire Van Allen Probe era. While number density and temperature data at geosynchronous orbit are available, this study focuses on the warm plasma in the inner magnetosphere . Values of density and temperature are extracted by fitting energy and phase space density to obtain the distribution function. The fitted distributions are related to the zeroth and second moments to estimate the number density and temperature. Analysis has indicated that a two Maxwellian fit is sufficient over a wide range of and that there are two independent plasma populations. The more energetic population has a median number density of approximately and a temperature of around 130 keV, with a temperature peak observed between L * = 4 and L * = 4.5. This population is relatively uniform in magnetic local time (MLT). In contrast, the less energetic warm electron population has a median number density of about and a temperature of 7.4 keV. Strong statistical trends in density and temperature across both L * and MLT are presented, along with potential sources driving these variations.

58 GEOSCIENCES↗

Ensemble Effects on Hydroxide Bond Dissociation Free Energies in Polyoxovanadate Clusters

Understanding structure-property relationships is foundational to numerous modern chemistries, such as proton-coupled electron transfer (PCET). However, an experimentally measured property is the result of the behavior from an ensemble of molecules. Neglecting ensemble effects, especially under complex chemical environments, may obfuscate these relationships and lead to discrepancies between theory and experiment. In this work, we demonstrate the impact of configurational entropy and local chemical environments on hydroxide bond dissociation free energies [BDFE- (O−H)] for a set of polyoxovanadate nanoclusters, at ambient conditions. The O−H bond strengths are investigated via density functional theory (DFT) coupled with statistical thermodynamic analysis and bilinear modeling, and compared with previous experimental results on the same systems, namely electrochemical solutions of: [V 6 O 13−x (OH) x (TRIOL R ) 2 ] −2 (x = 2, 4, 6; R = NO 2 , Me) and [V 6 O 11−x (OMe) 2 (OH) x (TRIOL NO 2 ) 2 ] −2 (x = 2, 4). Interestingly, we find that ensemble effects, even at room temperature, can account for a significant portion of the BDFE(O−H) trend with the degree of reduction via H atom binding, which cannot be fully captured by single-structure, static DFT calculations. Moreover, we find that the ensemble effects may be replicated statistically, requiring only enumeration of energetically accessible H-binding sites. With the ensemble effects resolved, we present a simple bilinear model to reconcile remaining biases between experiment and ensemble-informed theory, which corelate with clusterspecific electronic environment differences. The bilinear model achieves outstanding accuracy vs experiments with a root-mean squared error of 0.4 kcal/mol. Finally, based on the physicochemical characteristics of hydrogen interaction with polyoxometalates, we present a simple methodology that captures the BDFE(O−H) trend while dramatically reducing required DFT calculations by 98% and achieving accuracy within 1 kcal/mol. Overall, this work elucidates the roles and structural origins of configurational entropy and chemical effects on polyoxometalate hydroxide bond energies, with potential applicability to various atomically precise metal oxide systems. Importantly, it introduces models for rapid and highly accurate property calculations in connection with experiments.

Cluster chemistry↗

Enhanced spectral purity of WSe 2 quantum emitters via conformal organic adlayers

Quantum emitters in solid-state materials are typically embedded in the bulk of their hosts, making their electronic transitions inaccessible to surface modification. In contrast, two-dimensional materials, with their all-surface nature, offer a platform for tuning quantum emitters via chemical functionalization. Because of its semiconducting properties that enable electrical addressability, monolayer WSe 2 is a promising candidate for quantum emission, although the complex interplay between point defects and the localized strain needed to activate quantum emission leads to poor spectral purity. Here, we demonstrate that functionalizing monolayer WSe 2 with conformal adlayers of 3,4,9,10-perylenetetracarboxylic dianhydride (PTCDA) improves quantum emission spectral purity. Optical spectroscopy reveals that PTCDA functionalization lowers defect activation energies by 10 meV and induces a 30 nm redshift in quantum emission wavelength, while preserving the bright and dark exciton energies of monolayer WSe 2 . First-principles calculations corroborate these findings, thus providing molecular-level insight into the underlying mechanism of enhanced spectral purity.

Ananth, Riddhi [Northwestern Univ., Evanston, IL (↗

Interplay between electron localization, magnetic order, and Jahn-Teller distortion dictates LiMnO2 phase stability

The development of manganese (Mn)-rich cathodes for Li-ion batteries promises to alleviate potential supply chain bottlenecks in battery manufacturing. Fundamental challenges in Mn-rich cathodes arise from phenomena such as structural changes due to cooperative Jahn-Teller (JT) distortions of in octahedral environments, Mn migration, and phase transformations to spinel-like order, all of which affect the electrochemical performance. These physically complex phenomena motivate an re-examination of the Li-Mn-O rock-salt space, with a focus on the thermodynamics of the prototypical, polymorphs. It is found that the generalized gradient approximation (GGA-PBEsol) and meta-GGA ( ) density functionals with empirically fitted on-site Hubbard corrections yield spurious stable phases for , such as predicting a phase with -like order ( ) to be the ground state instead of the orthorhombic (Pmmn) phase, which is the experimentally known ground state. Accounting for antiferromagnetic order in each structure is shown to have a substantial effect on the total energies and resulting phase stability. By using hybrid-GGA (HSE06) and GGA with self-consistent Hubbard parameters (on-site and inter-site ) calculated from linear response theory, the experimentally observed phase stability trends are recovered. The calculated on-site between Mn- states in the experimentally observed orthorhombic, layered, and spinel phases are significantly smaller than in and disordered layered structures, by within GGA. The smaller values of are shown to be correlated with a collinear ordering of JT distortions, in which all orbitals are oriented in the same direction. This cooperative JT effect can lead to greater electron delocalization from Mn along the states due to increased Mn-O covalency, which contributes to the greater electronic stability compared to the phases with noncollinear JT arrangements. The structures with collinear ordering of JT distortions also generate greater vibrational entropy, which helps stabilize these phases at high temperature. These phases are shown to be strongly insulating with large calculated band gaps , which are computed using HSE06 and .

Kam, Ronald L↗

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials

Atomic disorder can strongly influence material properties such as charge transport, optical response, and catalytic activity. However, efficiently modeling these disorder effects remains challenging for first-principles methods due to the cost of sampling large configurational spaces and computing complex physical quantities. Recent advances of machine learning techniques, particularly graph neural networks (GNNs), has enabled the efficient and accurate predictions of complex material properties, offering promising tools for studying disordered systems. In this work, we present a general machine-learning-assisted computational framework that integrates equivariant GNNs with Monte Carlo simulations to compute the thermodynamic and ensemble-averaged functional properties of disordered materials. Using the surface-termination-disordered MXene monolayer Ti 3 C 2 T 2–x as a representative system, we find that electrical conductivity exhibits an emergent peak near the order–disorder phase transition temperature due to the interplay between electron scattering and doping. In contrast, optical conductivity remains largely insensitive to local atomic disorder and reflects the global surface chemical composition. These results highlight the role of atomic disorder in affecting material properties and demonstrate the potential of our approach for statistically modeling disorder effects in a wide range of materials such as high-entropy alloys and spin liquids.

MXene↗

Toward an Understanding of Linear Scaling Relations through Energy Decomposition Analysis

The discovery of linear scaling relations has fundamentally changed the field of heterogeneous catalysis. The scaling relations have been rationalized based on the d-band theory, specifically a separation of sp and d electron contributions to adsorption energies. Within the framework of energy decomposition analysis, a full understanding of such a separation would require one to further break down the adsorption energy into distinct energy components such as electrostatics, polarization, charge transfer, and van der Waals interactions, and to examine the sp and d contributions to each of them. As a step in this direction, we analyzed the interaction energy between CH x (x = 1–4) adsorbates and fcc(100) transition metal surfaces (M = Cu, Ag, Au, Rh, and Pt), with the surfaces represented both as slabs in plane-wave density functional theory (pw-DFT) calculations and as atomic clusters in atomic-orbital basis density functional theory (ao-DFT) calculations. Through an absolutely localized molecular orbital (ALMO) based energy decomposition analysis of the ao-DFT adsorption energy, each of the interaction energy components (electrostatics, polarization, van der Waals, and charge transfer) was found to follow its own scaling relations, with an intricate interplay among these energy components yielding the overall scaling relations for the total adsorption energies. Using the recently introduced ALMO-based polarization and charge-transfer analysis schemes, we further dissected polarization into metal surface and adsorbate contributions, and charge transfer into metal → adsorbate and adsorbate → metal contributions. The contributions from the sp and d electrons of the metal to these terms were further quantified, and the dominant role of the metal d electrons was reaffirmed. These results shed light on how CHx adsorbates interact with metal surfaces and further reveal the physical origin of the scaling relations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Assessment of thermally driven local structural phase changes in 1⁢𝑇′−MoTe 2

The role of layer disorder is important in establishing the topological phases of MoTe 2 . A rich tapestry of atomic ordering influences the structural phase transitions (SPTs), but there is little understanding of the mechanistic details of the phase transition. An atomistic level study was conducted to investigate the local structure of the 1⁢𝑇′ and 𝑇 𝑑 phases of MoTe 2 by using the pair distribution function (PDF) technique. While the average structure exhibits an SPT and coexistence of phases as a function of temperature, the local structure showed the suppression of SPT. The sample retained its monoclinic structure at all temperatures in short-range order. A sharp PDF peak observed at short distances indicated a strong atom-atom correlation between the Mo and Te atoms within the Mo octahedra. In addition, a large-box modeling of the PDF data indicated a preferential motion of Te atoms towards 𝑐 axis at all temperatures. Structural defects, such as stacking faults, likely result in the coexistence of phases in the average structure and suppress the local SPT of MoTe 2 . These results are stepping stones to understand the long-debated origins of structural, vibrational, and electronic properties of MoTe 2 and similar transition metal dichalcogenides.

2-dimensional systems↗

Switching of electrochemical selectivity due to plasmonic field-induced dissociation

Electrochemical reactivity is known to be dictated by the structure and composition of the electrocatalyst–electrolyte interface. Here, we show that optically generated electric fields at this interface can influence electrochemical reactivity insofar as to completely switch reaction selectivity. We study an electrocatalyst composed of gold–copper alloy nanoparticles known to be active toward the reduction of CO 2 to CO. However, under the action of highly localized electric fields generated by plasmonic excitation of the gold–copper alloy nanoparticles, water splitting becomes favored at the expense of CO 2 reduction. Real-time time-dependent density functional tight binding calculations indicate that optically generated electric fields promote transient-hole-transfer-driven dissociation of the O─H bond of water preferentially over transient-electron-driven dissociation of the C─O bond of CO 2 . These results highlight the potential of optically generated electric fields for modulating pathways, switching reactivity on/off, and even directing outcomes.

Alcorn, Francis M.↗

Spectroscopic and Theoretical Studies of Ruthenium Complexes with a Noninnocent N 2 S 2 Ligand in Different Redox States

Herein we report an electronic structure investigation of neutral and oxidized Ru complexes containing a redox noninnocent N 2 S 2 ligand derived from o-phenylenediamide (L1). UV–vis spectroelectrochemistry (SEC) studies were conducted on the square pyramidal complex [Ru I I(L1)(PPh 3 )] (1) and the six-coordinate complexes [Ru I I(μ-BH 3 )(L1)(PPh 3 )] (2) – which has BH 3 bound in a metal–ligand cooperative (MLC) fashion across Ru and L1 – and [Ru II (L1)(PPh 3 )(MeCN)] (3). The SEC results yielded spectra assigned to singly and doubly oxidized 1 and 3, revealing electronic structure changes as a function of oxidation state and in response to the presence and absence of bound MeCN. By contrast, the SEC results of 2 showed that it rapidly loses MLC-bound BH 3 upon oxidation. The SEC results for 1 and 3 were compared to single-crystal XRD data and UV–vis, EPR, and P K-edge, S K-edge, and Ru L 3 -edge X-ray absorption spectroscopy (XAS) data collected on isolated samples of chemically oxidized 3. The data revealed that the first two oxidations are primarily localized on the ligand, which was supported by DFT and TDDFT calculations. DFT calculations for the doubly oxidized species revealed a singlet ground state with a singlet–triplet gap of 8.9 kcal/mol. CASPT2 calculations corroborated the DFT calculations and further revealed that the singlet ground state is multiconfigurational with 21% radical character. Collectively, the results establish redox formalisms and the underlying electronic structure of Ru complexes containing a noninnocent tetradentate ligand in different oxidation states.

electronic structure↗

Facet-Dependent Cold Welding of Au Nanorods Revealed by Liquid Cell Transmission Electron Microscopy

Cold welding of metals at the nanoscale has been demonstrated to play a significant role in bottom-up manufacturing and self-healing processes of nanostructures and nanodevices. However, the welding mechanism at the nanoscale is not well understood. In this study, a comprehensive demonstration of the cold welding process of gold nanorods with different modes is presented through in situ liquid cell transmission electron microscopy. The experimental results and molecular dynamics simulations reveal that the nanorods are welded through the facet-dependent atomic surface diffusion and rearrangement along {100} facets. The density functional theory calculations indicate that the preferred coalescence of two {100} surfaces is thermodynamically favorable. Unlike the prevalent “oriented attachment” in the nanoparticle coalescence, the misalignment of nanorod orientations and local stresses can induce grain boundaries and stacking faults in the welded interface.

42 ENGINEERING↗

Unveiling X-ray absorption signatures of boron nitride via first-principles simulation and machine learning

Boron nitride (BN) allotropes hold great promise in many advanced applications ranging from optical and photonic devices to energy storage and battery systems to tribological components. The diverse functionalities of this material stem from BN’s highly tunable structural and electronic properties, which are governed by the versatile boron–nitrogen bonding configurations. Exploring the structural landscape of BN can unveil novel structures possessing unique properties suited for specific applications, therefore accelerating the design of next-generation advanced functional materials. In this work, we leverage boron K-edge X-ray absorption spectroscopy (XAS) as an effective probe for local structural features and chemical environments. A total of 210 BN crystal structures are generated via analogies to the extensive array of carbon allotropes, and XAS is simulated for each unique local motif within the resulting collection of structures. A mapping between structural features and spectral signatures was established by synergizing first-principle simulations with data-driven based post-analysis approaches. Specifically, we developed a neural network model that can satisfactorily predict spectra line shapes from local structural descriptors. Toward automatic spectroscopic interpretation of any new BN structures, supervised machine learning models, trained on this structure–spectrum dataset, can accurately infer local coordination environments from simulated XAS, highlighting the strength of this unique approach of combining high-fidelity first-principles simulation and machine-learning to accelerate target design of novel BN materials via rational understanding of local structure-spectrum correlations.

36 MATERIALS SCIENCE↗

Generalized approach for rapid entropy calculation of liquids and solids

We build a comprehensive methodology for the fast computation of entropy across both solid and liquid phases. The proposed method utilizes a single trajectory of molecular dynamics (MD) to facilitate the calculation of entropy, which is composed of three components. The electronic entropy is determined through the temporal average acquired from density functional theory MD simulations. The vibrational entropy, typically the predominant contributor to the total entropy, even within the liquid state, is evaluated by computing the phonon density of states via the velocity autocorrelation function. The most arduous component to quantify, the configurational entropy, is assessed by probability analysis of the local structural arrangement and atomic distribution. We illustrate, through a variety of examples, that this method is both a versatile and valid technique for characterizing the thermodynamic states of both solids and liquids. Furthermore, this method is employed to expedite the calculation of melting temperatures, demonstrating its practical utility in computational thermodynamics.

36 MATERIALS SCIENCE↗

Echo state network for coarsening dynamics of charge density waves

An echo state network (ESN) is a type of reservoir computer that uses a recurrent neural network with a sparsely connected hidden layer. Compared with other recurrent neural networks, one great advantage of ESN is the simplicity of its training process. Yet, despite the seemingly restricted learnable parameters, ESN has been shown to successfully capture the spatial-temporal dynamics of complex patterns. Here we build an ESN to model the coarsening dynamics of charge-density waves (CDWs) in a semiclassical Holstein model, which exhibits a checkerboard electron density modulation at half-filling stabilized by a commensurate lattice distortion. The inputs to the ESN are local CDW order parameters in a finite neighborhood centered around a given site, while the output is the predicted CDW order of the center site at the next time step. Special care is taken in the design of couplings between hidden layer and input nodes to ensure lattice symmetries are properly incorporated into the ESN model. Since the model predictions depend only on CDW configurations of a finite domain, the ESN is scalable and transferrable in the sense that a model trained on dataset from a small system can be directly applied to dynamical simulations on larger lattices. Furthermore, our work opens avenues for efficient dynamical modeling of pattern formations in functional electron materials.

2-dimensional systems↗

Hyperfine interactions for small systems including transition-metal elements using self-interaction corrected density-functional theory

The interactions between the electronic magnetic moment and the nuclear spin moment, i.e., magnetic hyperfine (HF) interactions, play an important role in understanding electronic properties of magnetic systems and in realizing platforms for quantum information science applications. We investigate the HF interactions for atomic systems and small molecules, including Ti or Mn, by using Fermi–Löwdin orbital (FLO) based self-interaction corrected (SIC) density-functional theory. We calculate the Fermi contact (FC) and spin-dipole terms for the systems within the local density approximation (LDA) in the FLO-SIC method and compare them with the corresponding values without SIC within the LDA and generalized-gradient approximation (GGA), as well as experimental data. For the moderately heavy atomic systems (atomic number Z ≤ 25), we find that the mean absolute error of the FLO-SIC FC term is about 27 MHz (percentage error is 6.4%), while that of the LDA and GGA results is almost double that. Therefore, in this case, the FLO-SIC results are in better agreement with the experimental data. For the non-transition-metal molecules, the FLO-SIC FC term has the mean absolute error of 68 MHz, which is comparable to both the LDA and GGA results without SIC. For the seven transition-metal-based molecules, the FLO-SIC mean absolute error is 59 MHz, whereas the corresponding LDA and GGA errors are 101 and 82 MHz, respectively. Therefore, for the transition-metal-based molecules, the FLO-SIC FC term agrees better with experiment than the LDA and GGA results. We observe that the FC term from the FLO-SIC calculation is not necessarily larger than that from the LDA or GGA for all the considered systems due to the core spin polarization, in contrast to the expectation that SIC would increase the spin density near atomic nuclei, leading to larger FC terms.

Chemistry↗

Understanding the superconductivity and charge density wave interaction through quasi-static lattice fluctuations

In unconventional superconductors, coupled charge and lattice degrees of freedom can manifest in ordered phases of matter that are intertwined. In the cuprate family, fluctuating short-range charge correlations can coalesce into a longer-range charge density wave (CDW) order which is thought to intertwine with superconductivity, yet the nature of the interaction is still poorly understood. Here, by measuring subtle lattice fluctuations in underdoped YBa 2 Cu 3 O 6+y on quasi-static timescales (thousands of seconds) through X-ray photon correlation spectroscopy, we report sensitivity to both superconductivity and CDW. The atomic lattice shows remarkably faster relaxational dynamics upon approaching the superconducting transition at T c ≈ 65 K. By tracking the momentum dependence, we show that the intermediate scattering function almost monotonically scales with the relaxation distance of atoms away from their average positions above T c and in the presence of the CDW state, while this peculiar trend is reversed for other temperatures. These observations are consistent with an incipient CDW stabilized by local strain. This work provides insights into the crucial role of relaxational atomic fluctuations for understanding the electronic physics cuprates, which are inherently disordered due to carrier doping.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Ferrimagnetic Order in Tetragonal Antiperovskite Mn3GeN

The crystal and magnetic structures of the nitride antiperovskite M⁢n3⁢GeN reveals ferrimagnetic order stemming from a distorted kagome-derived lattice of the Mn atoms. Polycrystalline M⁢n3⁢GeN was synthesized via a solid-state reaction and characterized using neutron powder diffraction, dc magnetometry, and first-principles calculations. Rietveld refinement reveals near-stoichiometric composition (M⁢n3⁢Ge⁢N0.992⁢(7)) adopting a tetragonal 𝐼⁢4/𝑚⁢𝑐⁢𝑚 structure at 𝑇=500K and below, featuring axially distorted and tilted [NM⁢n6] octahedra that result in a buckled Mn kagome lattice. On heating, the tetragonal distortion and octahedral tilt angle decrease continuously before transitioning to the cubic 𝑃⁢𝑚⁢3⁢𝑚 antiperovskite phase at 𝑇≈527K. Neutron diffraction and magnetometry together reveal noncollinear ferrimagnetic ordering. For 30K≤𝑇≤500K, the magnetic structure is described by magnetic space group 𝐼⁢𝑏⁢𝑎′⁢𝑚′ (72.544), with inequivalent Mn1 and Mn2 sublattices that couple antiferromagnetically to yield a net moment. Density-functional theory-based calculations show that the different local moments originate from the bandwidths associated with distinct Mn–N bond lengths. Temperature-dependent refinements reveal distinct differences in the thermal disordering profiles of the Mn1 and Mn2 sublattices. These findings reveal a subtlety in the magnetic and structural behavior of M⁢n3⁢GeN, highlighting the interplay between structural distortions, magnetic ordering, and electronic structure in kagome-derived antiperovskite materials.

36 MATERIALS SCIENCE↗

Formalism for Local Correction of Vertical Crabbing in Hadron Storage Ring

The Electron-Ion Collider (EIC) incorporates crab cavities in both the Electron Storage Ring (ESR) and the Hadron Storage Ring (HSR) to achieve unprecedented luminosity goals. This technical note presents a formalism for the local correction of vertical crabbing in the HSR, addressing the complexities introduced by the integration of crab cavities and the interplay between betatron coupling and crabbing dispersion. Various strategies, including the use of skew quadrupoles and adjustments of Twiss functions, are explored to compensate vertical crabbing to achieve optimal beam-beam performance. The derived theoretical formulas offer practical guidance for minimizing the required vertical crabbing corrections, and will be implemented in the HSR lattice design.

43 PARTICLE ACCELERATORS↗

Electrically‐Driven Metal‐Insulator Transitions Emerging from Localizing Current Density and Temperature

Negative differential resistance (NDR) is a key electronic response enabling two‐terminal artificial neurons that can be achieved through different physical phenomena, including phase‐homogeneous current density and temperature (electro‐thermal) localizations and spatially‐localized metal‐insulator phase transitions (MITs). These two effects have been observed to occur sequentially in select electrically‐biased transition metal oxides. However, it is unknown why and under what conditions localizing behaviors precede MITs, particularly as a function of device length scale. To this end, the interplay between phase‐homogeneous electro‐thermal localizations and MITs is investigated in a 3D multiphysics simulation of a lateral thin film device, using the material properties of the prototype MIT material VO 2 . These findings demonstrate that the MIT is nucleated through dynamically localizing current density and temperature. A critical device width (≈0.7 µm in this study) is identified, below which both the electrically‐induced electro‐thermal and phase inhomogeneities cease to appear. It is demonstrated that the formation of spatial inhomogeneities directly relates to device dimensions, and demonstrate the decoupling of NDR from the MIT through device scaling relationships. These results provide insight into the material phenomena underlying the material's electrical responses, clarifying conditions under which spatial inhomogeneities form in electrically‐biased MIT materials.

artificial neuron↗