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At least 271 records · Page 15

Twists and turns: stacking and structure-dependent optical response in MoS 2 nanoscrolls

Transition metal dichalcogenide (TMD) nanoscrolls (NSs), specifically MoS 2 NSs, present unique structural and optical properties, exhibiting prominent photoluminescence (PL) signals despite their multilayer nature. Here, this study investigates the structural and spectroscopic characteristics of MoS 2 NSs, correlating them to show the effects of reduced interlayer interactions on excitons of MoS 2 NSs. The reduction in interlayer interaction arises from two main factors: (1) symmetry-broken mixed stacking due to misalignment between layers and (2) a highly inhomogeneous strain profile generated by the Archimedean spiral geometry with positive eccentricity. Transmission electron microscopy, field emission scanning electron microscopy, atomic force microscopy, Raman spectroscopy, and second harmonic generation measurements confirm these findings. Low-temperature PL spectroscopy explores the impact of reduced interlayer interactions on exciton properties such as exciton–phonon coupling and oscillator strength. This study provides crucial insights into the structure, stacking and unique optical properties of TMD NSs, advancing the understanding of interlayer interactions and their impacts in complex quasi-one-dimensional nanostructures.

25 ENERGY STORAGE↗

Restoration of weak localization in bilayer graphene by a molecular thin film

Quantum coherent effects can be probed in multilayer graphene through electronic transport measurements at low temperatures. In particular, bilayer graphene (BLG) is known to be susceptible to quantum interference corrections of the conductivity, presenting weak localization at all electronic densities, and dependent on different scattering mechanisms such as those related to the trigonal warping of the electron dispersion near the K and K′ valleys. Proximity effects with a molecular thin film influence these scattering mechanisms, which can be quantified through the known theory of magnetoconductance for BLG. Here, we present electronic transport measurements in a copper-phthalocyanine (CuPc) / BLG / hexagonal boron nitride (h-BN) heterostructure that suggest the restoration of weak localization in BLG, associated to a reduction of trigonal warping effects, that are known to suppress weak localization in BLG. Additionally, we observe a charge transfer of 3.6×10 12 cm −2 from the BLG to the molecules, as well as a very small degradation of the mobility of the BLG/h-BN heterostructure upon the deposition of CuPc. The molecular arrangement of the CuPc thin film is characterized in a control sample through transmission electron microscopy, that we relate to the electronic transport results.

bilayer graphene↗

Tropical Cyclone Super Resolution using conditional diffusion denoising probabilistic model from mesoscale simulation to LES

Accurate modeling of tropical cyclone wind fields is essential for the design, risk assessment, and operational planning of offshore energy infrastructure. While mesoscale simulations are widely used thanks to their computational efficiency, they lack the necessary resolution to capture key features such as wind shear and veer profiles as well as the distribution turbulent kinetic energy (TKE). High-fidelity large-eddy simulation (LES) models on the other hand, can resolve turbulent structures and provide a more accurate representation of the complex wind field, albeit at a higher computational cost. To address this modeling gap, we introduce a two-part generative framework to enhance the resolution and physics-capturing ability of mesoscale simulations. First, a reduced-order model based on Karhunen–Loève (KL) decomposition is used to extract dominant spatial modes from one-dimensional mean wind profiles. A multilayer perceptron (MLP) is trained to map mesoscale mode weights to their LES counterparts, enabling accurate reconstruction of vertical velocity profiles. Second, a conditional Diffusion Denoising Probabilistic Model (DDPM) is developed to super-resolve coarse and low-fidelity mesoscale velocity fields, recovering fine-scale turbulence structures and stress distributions. The framework is evaluated across different tropical cyclone intensity categories defined by the Saffir–Simpson scale and demonstrates strong performance in both interpolation and extrapolation tasks. The generated fields accurately reproduce spatial coherence, stress distributions, and spectral energy characteristics observed in LES data. By bridging the fidelity gap between mesoscale and LES outputs, this approach offers a scalable, data-driven solution for enhancing the representation of tropical cyclone wind fields, enabling more robust offshore energy infrastructure systems design in tropical-cyclone-prone areas.

17 WIND ENERGY↗

SPIKANs: separable physics-informed Kolmogorov–Arnold networks

Physics-Informed Neural Networks (PINNs) have emerged as a promising method for solving partial differential equations (PDEs) in scientific computing. While PINNs typically use multilayer perceptrons (MLPs) as their underlying architecture, recent advancements have explored alternative neural network structures. One such innovation is the Kolmogorov–Arnold Network (KAN), which has demonstrated benefits over traditional MLPs, including faster neural scaling and better interpretability. The application of KANs to physics-informed learning has led to the development of Physics-Informed KANs (PIKANs), enabling the use of KANs to solve PDEs. However, despite their advantages, KANs often suffer from slower training speeds, particularly in higher-dimensional problems where the number of collocation points grows exponentially with the dimensionality of the system. To address this challenge, we introduce Separable Physics-Informed Kolmogorov–Arnold Networks (SPIKANs). This novel architecture applies the principle of separation of variables to PIKANs, decomposing the problem such that each dimension is handled by an individual KAN. This approach drastically reduces the computational complexity of training without sacrificing accuracy, facilitating their application to higher-dimensional PDEs. Through a series of benchmark problems, we demonstrate the effectiveness of SPIKANs, showcasing their superior scalability and performance compared to PIKANs and highlighting their potential for solving complex, high-dimensional PDEs in scientific computing.

Kolmogorov-Arnold networks↗

Superfluid weight of strongly inhomogeneous superconductors

In this study, we obtain the superfluid weight of strongly inhomogeneous superconductors. We find that, in general, the response of the superconductor’s pairing potential to the perturbing vector potential is essential to obtain the correct value of the superfluid weight. We consider two exemplary cases: the case when strong inhomogeneities in the pairing potential are induced by a periodic potential, and the case when superconducting vortices are induced by an external magnetic field. For both cases we show that the correction to the superfluid weight due to the response of the paring potential to the perturbing vector potential can be significant, it must be included to obtain quantitatively correct results, and that for the case when vortices are present the expression of the superfluid weight that does not include such correction returns qualitatively wrong results. The results are directly relevant for superconducting states in moiré multilayer where the almost inevitable spatial variations of the magic angle and the proximity of superconductivity to anisotropic phases induce inhomogeneities in the pairing potential, and to the efforts to optimally pin superconducting vortices to achieve large superconducting critical currents.

Bogoliubov-de Gennes equations↗

Time-Domain Extreme-Ultraviolet Diffuse Scattering Spectroscopy of Nanoscale Surface Phonons

Here, we report the observation of dynamic fringe patterns in the diffuse scattering of extreme ultraviolet light from surfaces, following femtosecond optical excitation. At each point on the detector, the diffuse scattering intensity exhibits oscillations at well-defined frequencies that correspond to surface phonons with wave vectors determined by the scattering geometry, indicating that the optical excitation generates coherent surface phonons propagating in all directions and spanning a wavelength range from 60 to 300 nm. This phenomenon is observed on a variety of samples, including single-layer and multilayer metal films, as well as bulk semiconductors. The measured surface phonon dispersions show good agreement with theoretical calculations. By comparing signal amplitudes from samples with different surface morphologies, we find that the excitation mechanism is linked to the natural surface roughness of the samples. However, the signal is still detectable on extremely smooth surfaces with subnanometer roughness. Our findings demonstrate a simple and effective method for optically exciting coherent surface phonons with nanoscale wavelengths on a wide range of solid samples and establish a foundation for surface phonon spectroscopy in a wave vector range well beyond the limit of conventional surface Brillouin scattering.

Capotondi, F. [Elettra-Sincrotrone Trieste (Italy)↗

Parameter extraction for a SPICE model of an hTron superconducting thermal switch

Efficiently simulating large circuits is crucial to the development of superconducting nanowire-based electronics. However, current simulation tools for this technology are not adapted to the scaling of circuit size and complexity. We focus on the multilayered heater-nanocryotron (hTron), a promising superconducting nanowire-based switch used in applications such as superconducting nanowire single-photon detector readout. Previously, the hTron was modeled using traditional finite-element methods, which fall short in simulating systems at a larger scale. An empirical-based method would be better adapted to this task, enhancing both simulation speed and agreement with experimental data. In this work, we perform switching current and activation delay measurements on 17 hTron devices. We then develop a method for extracting physical fitting parameters used to characterize the devices. We build a SPICE behavioral model that reproduces the static and transient device behavior using these parameters, and validate it by comparing its performance to a model developed in prior work, showing an improvement in simulation time by several orders of magnitude. Furthermore, our model provides circuit designers with a tool to help understand the hTron’s behavior during all design stages, thus enabling broader use of the hTron across various new areas of application.

Caloritronics↗

Reconstruction of beam parameters and betatron radiation spectra measured with a Compton spectrometer

The photon flux resulting from high-energy electron beam interactions with high-field systems, such as those found in the upcoming FACET-II experiments at the SLAC National Accelerator Laboratory, yields deep insight into the electron beam’s underlying dynamics during the interaction. However, extracting this information is an intricate process. To demonstrate how to approach this challenge using modern methods, this paper utilizes simulated data that models plasma wakefield acceleration-derived betatron radiation in experiments to determine reliable methods of reconstructing key beam and beam-plasma interaction properties. For betatron radiation measurements, translating the observed 200⁢ keV to 30⁢ MeV photon double-differential energy-angle spectra obtained from an advanced Compton spectrometer requires testing multiple methods to optimize the pipeline from its response to incident electron beam information. The paper compares maximum likelihood estimation and machine learning to refine the translation of photon spectra into precise electron beam metrics, such as spot size, energy, and emittance, enhancing the understanding of beam behavior within these dense, high-field environments. We also introduce machine learning and the expected maximization algorithm to reconstruct the primary photon spectrum, employing a multilayer neural network for regression analysis of the energy and angle spectra. With appropriate modifications, the advanced methods reproduce relevant incident beam parameters with high accuracy, even for beam sizes in the <10 μ⁢m range. This capacity is critical to understanding intense beam propagation and its optimization in plasma.

Beam code development & simulation techniques↗

Electronic structure and magnetic tendencies of trilayer La 4 Ni 3 O 10 under pressure: Structural transition, molecular orbitals, and layer differentiation

Motivated by the recent observation of superconductivity in the pressurized trilayer Ruddlesden-Popper (RP) nickelate La 4 Ni 3 O 10 , we explore its structural, electronic, and magnetic properties as a function of hydrostatic pressure from first-principles calculations. We find that an orthorhombic (monoclinic)-to-tetragonal transition under pressure takes place concomitantly with the onset of superconductivity. The electronic structure of La 4 Ni 3 O 10 can be understood using a molecular trimer basis wherein n molecular subbands arise as the d z 2 orbitals hybridize strongly along the c axis within the trilayer. The magnetic tendencies indicate that the ground state at ambient pressure is formed by nonmagnetic inner planes and stripe-ordered outer planes that are antiferromagnetically coupled along the c axis, resulting in an unusual ↑, 0, ↓ stacking that is consistent with the spin density wave model previously suggested by neutron diffraction. Such a state is destabilized at the pressure where superconductivity arises. Despite the presence of d z 2 states at the Fermi level, the d x 2 –y 2 orbitals also play a key role in the electronic structure of La4Ni3O10. Finally, this active role of the d x 2 –y 2 states in the low-energy physics of the trilayer RP nickelate, together with the distinct electronic behavior of the inner and outer planes, resembles the physics of multilayer cuprates.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Protected fermionic zero modes in periodic gauge fields

It is well known that macroscopically normalizable zero-energy wave functions of spin-$\frac{1}{2}$ particles in a two-dimensional inhomogeneous magnetic field are spin-polarized and exactly calculable with degeneracy equaling the number of flux quanta linking the whole system. Here, extending this argument to massless Dirac fermions subjected to magnetic fields that have zero net flux but are doubly periodic in real space, we show that there exist only two Bloch-normalizable zero-energy eigenstates, one for each spin flavor. This result is immediately relevant to graphene multilayer systems subjected to doubly periodic strain fields, which at low energies enter the Hamiltonian as periodic pseudogauge vector potentials. Furthermore, we explore various related settings including nonlinearly dispersing band structure models and systems with singly periodic magnetic fields.

36 MATERIALS SCIENCE↗

Surface acoustic waves and lattice vibrations in two-dimensional Ti 3 ⁢C 2 ⁢𝑇 𝑥 (𝑇 =O, F) MXene films

We investigated surface acoustic wave (SAW) propagation and lattice vibrations in two-dimensional (2D) titanium carbide (Ti 3 ⁢C 2 ⁢𝑇 x ) MXene films as a function of surface termination and layer stacking, using atomistic simulations. We found that SAW propagation velocity is highly sensitive to both single-layer properties and interlayer bonding. Surface terminations significantly modulate wave behavior, with oxygen and fluorine terminations producing distinct effects on wave propagation, with oxygen-terminated monolayers exhibiting 20% higher wave speeds than fluorine counterparts due to strengthened intralayer bonds. Key observations include the transition from one to two layers causing wave speed variations, and the development of interlayer modes that generate more dispersed lattice vibrations. As the film layer thickness increases, SAW propagation becomes predominantly confined to the upper surface, with coherence of vibrational modes diminishing in multilayer structures. These findings suggest MXene terminations and layer stacking are crucial parameters for controlling SAW behavior, offering promising avenues for novel acoustic wave device applications.

2-dimensional systems↗

Tunable atomically enhanced moiré Berry curvatures in twisted triple bilayer graphene

We report a twisted triple bilayer graphene platform consisting of three units of Bernal bilayer graphene consecutively twisted at 1.49° and 1.68°. We demonstrate the atomic reconstruction between the two competing moiré superlattices strongly enhances the Berry curvature of each moiré band insulator state, characterized by measured strong nonlocal valley Hall effect that sensitively depends on the intermoiré competition strength, tunable by manipulating the out-of-plane carrier distribution. Our study sheds light on the microscopic mechanism of atomic and electronic reconstruction in twisted multilayer systems, by systematically investigating transport signatures of moiré Berry curvature and its enhancement from moiré-of-moiré lattice reconstruction. In conclusion, we show that the reconstructed electronic band can be versatilely tuned by electrostatics, providing an approach toward engineering the band structure and its topology for a quantum material platform with designer electrical and optical properties.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Gravitational form factors of charmonia

We investigate the gravitational form factors of charmonium. Our method is based on a Hamiltonian formalism on the light front known as basis light-front quantization. The charmonium mass spectrum and light-front wave functions were obtained from diagonalizing an effective Hamiltonian that incorporates confinement from holographic QCD and one-gluon exchange interaction from light-front QCD. We proposed a quantum many-body approach to construct the hadronic matrix elements of the energy momentum tensor T + + and T + − , which are used to extract the gravitational form factors A ( Q 2 ) and D ( Q 2 ) . The obtained form factors satisfy the known constraints, e.g., the von Laue condition. From these quantities, we also extract the energy, pressure and light-front energy distributions of the system. We find that hadrons are multilayer systems. Published by the American Physical Society 2024

Astronomy & Astrophysics↗

Observation of a Giant Goos-Hänchen Shift for Matter Waves

The Goos-Hänchen (GH) shift describes a phenomenon in which a specularly reflected beam is translated along the reflecting surface such that the incident and reflected rays no longer intersect at the surface. Using a neutron spin-echo technique and a specially designed magnetic multilayer mirror, we have measured the relative phase between the reflected up and down neutron spin states in total reflection. The relative GH shift calculated from this phase shows a strong resonant enhancement at a particular incident neutron wave vector, which is due to a waveguiding effect in one of the magnetic layers. Calculations based on the observed phase difference between the neutron states indicate a propagation distance along the waveguide layer of 0.65 mm for the spin-down state, which we identify with the magnitude of the giant GH shift. The existence of a physical GH shift is confirmed by the observation of neutron absorption in the waveguide layer. Here, we propose ways in which our experimental method may be exploited for neutron quantum-enhanced sensing of thin magnetic layers.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Modular Quantum Processor with an All-to-All Reconfigurable Router

Superconducting qubits provide a promising approach to large-scale fault-tolerant quantum computing. However, qubit connectivity on a planar surface is typically restricted to only a few neighboring qubits. Achieving longer-range and more flexible connectivity, which is particularly appealing in light of recent developments in error-correcting codes, however, usually involves complex multilayer packaging and external cabling, which is resource intensive and can impose fidelity limitations. Here, we propose and realize a high-speed on-chip quantum processor that supports reconfigurable all-to-all coupling with a large on-off ratio. We implement the design in a four-node quantum processor, built with a modular design comprising a wiring substrate coupled to two separate qubit-bearing substrates, each including two single-qubit nodes. We use this device to demonstrate reconfigurable controlled-𝑍 gates across all qubit pairs, with a benchmarked average fidelity of 96.00% ± 0.08% and best fidelity of 97.14% ± 0.07%, limited mainly by dephasing in the qubits. We also generate multiqubit entanglement, distributed across the separate modules, demonstrating GHZ-3 and GHZ-4 states with fidelities of 88.15% ± 0.24% and 75.18% ± 0.11%, respectively. This approach promises efficient scaling to larger-scale quantum circuits and offers a pathway for implementing quantum algorithms and error-correction schemes that benefit from enhanced qubit connectivity.

Quantum circuits↗

Defect Complexes in CrSBr Revealed Through Electron Microscopy and Deep Learning

Atomic defects underpin the properties of van der Waals materials, and their understanding is essential for advancing quantum and energy technologies. Scanning transmission electron microscopy is a powerful tool for defect identification in atomically thin materials, and extending it to multilayer and beam-sensitive materials would accelerate their exploration. Here, we establish a comprehensive defect library in a bilayer of the magnetic quasi-1D semiconductor CrSBr by combining atomic-resolution imaging, deep learning, and calculations. We apply a custom-developed machine learning work flow to detect, classify, and average point vacancy defects. This classification enables us to uncover several distinct Cr interstitial defect complexes, combined Cr and Br vacancy defect complexes, and lines of vacancy defects that extend over many unit cells. We show that their occurrence is in agreement with our computed structures and binding energy densities, reflecting the intriguing layer interlocked crystal structure of CrSBr. Our ab initio calculations show that the interstitial defect complexes give rise to highly localized electronic states. These states are of particular interest due to the reduced electronic dimensionality and magnetic properties of CrSBr and are, furthermore, predicted to be optically active. Our results broaden the scope of defect studies in challenging materials and reveal new defect types in bilayer CrSBr that can be extrapolated to the bulk and to over 20 materials belonging to the same FeOCl structural family.

deep learning↗

Nucleation and growth of polar clusters with in-phase tilts into a long-range ferroelectric matrix in a sodium niobate based complex relaxor

In this study, we have investigated the temperature dependence of atomic ordering at multiple length scales in a lead-free sodium niobate-based relaxor, i.e., 0.75 NaNbO 3 -0.25 Ba 0.9⁢ Ca 0.1⁢ TiO 3 (NN-25BCT) via synchrotron x-ray diffraction, Raman spectroscopy, and pair distribution function analysis. High-resolution synchrotron x-ray powder diffraction (SXRD) measurements reveal a ferroelectric phase transition in the relaxor ferroelectric NN-25BCT below the Vogel-Fulcher freezing temperature (𝑇 VF ≈ 270 K). In addition, SXRD analysis demonstrates the competition between in-phase octahedral tilting and ferroelectric order at the long-range scale using mode crystallography. On the other hand, Raman spectroscopic analysis provides evidence of polar ordering for 𝑇 > 𝑇 VF (with tetragonal symmetry) persisting up to the Burns temperature (𝑇 B ). Furthermore, pair distribution function (PDF) analysis reveals the presence of a polar antiferrodistortive tetragonal phase with 𝑃⁢4⁢𝑏𝑚 space group at short ranges throughout the studied temperatures (i.e., 110 K ≤ 𝑇 ≤500 K), irrespective of nonpolar long-range ordering above 𝑇 VF . Therefore, our measurements provide direct evidence for the presence of polar ordering at short ranges and their gradual transformation into long-range polar ordering using an integrated multiscale structural analysis. In conclusion, as a result of a transition from relaxor to a ferroelectric phase in the vicinity of room temperature, NN-25BCT can be exploited for applications in pyroelectric detectors, electrocaloric devices, and multilayered ceramic capacitors.

36 MATERIALS SCIENCE↗

Dispersive X-ray absorption spectroscopy using independent grazing-incidence focusing and convexly bent Bragg-crystal dispersing optics

We present a modular instrument for dispersive X-ray absorption spectroscopy (DXAS) developed for the Advanced Spectroscopy Beamline at Sector 25 of the Advanced Photon Source. The setup employs a double-multilayer monochromator to provide X-rays with a broad energy bandwidth, Kirkpatrick–Baez mirrors for focusing, a convexly bent Bragg-crystal polychromator for energy dispersion, and a pixel-array detector to resolve all X-ray energies and collect their intensity simultaneously, thereby enabling acquisition of a full X-ray absorption spectrum in a single shot. The use of separate optics for X-ray focusing and energy dispersion provides high spatial resolution and avoids chromatic aberrations inherent in focusing bent-crystal optics, and a modular design makes implementation of the technique at other beamlines possible without requiring modifications to the upstream beamline configurations. Theoretical calculations are performed to determine optimal instrument operating parameters and demonstrate that an energy resolution better than the K-edge core-hole lifetime broadening can be maintained while providing a sufficient bandwidth for X-ray absorption near-edge structure spectroscopy through the full operating range of 5–11 keV. Additionally, instrument design, data analysis methods, and initial DXAS results on lithium–manganese–nickel oxide laminates are presented.

47 OTHER INSTRUMENTATION↗