Artificial Intelligence-Assisted Design and Virtual Diagnostic for the Initial Condition of a Storage-Ring-Based Quantum Information System
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43 PARTICLE ACCELERATORS↗
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On-Chip Cavity Electroacoustics Using Lithium Niobate Phononic Crystal Resonators
Mechanical systems are pivotal in quantum technologies because of their long coherent time and versatile coupling to qubit systems. So far, the coherent and dynamic control of gigahertz-frequency mechanical modes mostly relies on optomechanical coupling and piezoelectric coupling to superconducting qubits. Here, we demonstrate on-chip cavity electroacoustic dynamics using our microwave-frequency electrically modulated phononic crystal resonators on lithium niobate. Leveraging the high dispersion of phononic crystal, our acoustic modes space unevenly in the frequency spectrum, emulating atomic energy levels. Atomiclike transitions between different acoustic modes are selectively achieved by applying electrical fields to modulate acoustic modes via the nonlinear piezoelectricity of lithium niobate. Among two modes, we demonstrate Autler-Townes splitting, ac Stark shift, and Rabi oscillation with a maximum cooperativity of 4.18. Extending to three modes, we achieve nonreciprocal frequency conversions with an isolation up to 20 dB. Nonreciprocity can be tuned by the time delay between the two modulating pulses. Finally, our cavity electroacoustic platform could find broad applications in sensing, microwave signal processing, acoustic computing, and quantum acoustics.
Rabi model↗
A generalizable machine learning-assisted fast Fourier transform algorithm to simulate the large strain phenomena in polycrystalline materials
Machine learning methods have shown initial promise in constitutive modeling for single crystals or homogenized polycrystals, delivering notable computational efficiency. However, existing machine learning-based constitutive models often lack generalizability, limiting their application across diverse boundary value problems. This study introduces a thermodynamics-informed artificial neural network model to accelerate rate-tangent crystal plasticity fast Fourier transform simulations for cross-scale deformation behaviors of polycrystals under complex loading. Our model integrates microstructural variability and local interactions effectively. To address local effects in each grain, we employ K-means clustering to group Gauss points within the microstructure into clusters assumed to be in similar mechanical states. This approach, based on self-clustering analysis, extends model scope from macroscopic stress response to the granular level, capturing mechanical responses and orientation evolution across grains. This reduces the number of nonlinear problems to solve, with cluster responses propagated throughout each group. The thermodynamics-based artificial neural network-extracted features are further processed using local material state clusters to account for history-dependent deformation and evolving microstructures. Additionally, representative volume element simulations with rate-tangent crystal plasticity fast Fourier transform provide reliable datasets for model training. The proposed model demonstrates high efficiency, accuracy, self-consistency, and enhanced generalizability in predicting strain–stress responses and orientation evolution at both individual grain and aggregate scales under complex loading conditions, such as biaxial tension and arbitrary loading scenarios.
36 MATERIALS SCIENCE↗
Liquid Crystal Orientation and Shape Optimization for the Active Response of Liquid Crystal Elastomers
Liquid crystal elastomers (LCEs) are responsive materials that can undergo large reversible deformations upon exposure to external stimuli, such as electrical and thermal fields. Controlling the alignment of their liquid crystals mesogens to achieve desired shape changes unlocks a new design paradigm that is unavailable when using traditional materials. While experimental measurements can provide valuable insights into their behavior, computational analysis is essential to exploit their full potential. Accurate simulation is not, however, the end goal; rather, it is the means to achieve their optimal design. Such design optimization problems are best solved with algorithms that require gradients, i.e., sensitivities, of the cost and constraint functions with respect to the design parameters, to efficiently traverse the design space. In this work, a nonlinear LCE model and adjoint sensitivity analysis are implemented in a scalable and flexible finite element-based open source framework and integrated into a gradient-based design optimization tool. To display the versatility of the computational framework, LCE design problems that optimize both the material, i.e., liquid crystal orientation, and structural shape to reach a target actuated shapes or maximize energy absorption are solved. Multiple parameterizations, customized to address fabrication limitations, are investigated in both 2D and 3D. The case studies are followed by a discussion on the simulation and design optimization hurdles, as well as potential avenues for improving the robustness of similar computational frameworks for applications of interest.
42 ENGINEERING↗
An Atom-Precise Approach to Damp First-Order Phase Transitions and Its Implications for Neuromorphic Signal Processing
Neuromorphic computing inspired by mammalian intelligence aims to emulate the nonlinear dynamics of biological neurons and synapses to achieve fast, low-energy, and highly efficient information processing. Brain-inspired computing relies on the design and discovery of materials exhibiting nonlinear current–voltage profiles, frequently underpinned by electronic state transitions, to achieve spiking neurons and dynamically tunable synapses. A signature challenge in the design of artificial neurons is controlling the steepness of first-order transitions in active elements, as abrupt transitions are at risk of driving unstable voltage and temperature oscillations, which result in catastrophic device failure. A critical knowledge gap is the lack of structure–function correlations mapping the composition and atomistic structure of crystalline solids to nonlinear dynamical response characteristics. Here, we address the key question of how modification of atomistic structure correlates with alteration of neuron-like functionality. Constructing oscillator circuits from millimeter-scale single crystals enables high-resolution atomic structure solutions, which we use to demonstrate that the selective positioning of Pb cations modifies charge ordering along a one-dimensional CuxV2O5 framework even at low insertion stoichiometries, thereby providing an atom-precise design parameter for damping first-order transitions. We use temperature-variant X-ray diffraction and X-ray spectroscopy to elucidate the suppression of Cu-ion shuttling based on the precise positioning of Pb ions in seven-coordinated tunnel interstitial sites as the mechanistic basis for transition broadening, thus bridging a critical gap between statistical mechanics and quantum chemical descriptions of phase transitions. Such mechanistic understanding thus paves the way to site-selective modification strategies for modulating the sharpness of first-order transitions, with an exemplary demonstration here in tuning neuronal signal processing.
Crystal structure↗
Facile and quantitative estimation of strain in nanobubbles with arbitrary symmetry in 2D semiconductors verified using hyperspectral nano-optical imaging
When layers of van der Waals materials are deposited via exfoliation or viscoelastic stamping, nanobubbles are sometimes created from aggregated trapped fluids. Though they can be considered a nuisance, nanobubbles have attracted scientific interest in their own right owing to their ability to generate large in-plane strain gradients that lead to rich optoelectronic phenomena, especially in the semiconducting transition metal dichalcogenides. Determination of the strain within the nanobubbles, which is crucial to understanding these effects, can be approximated using elasticity theory. However, the Föppl–von Kármán equations that describe strain in a distorted thin plate are highly nonlinear and often necessitate assuming circular symmetry to achieve an analytical solution. Here, we present an easily implemented numerical method to solve for strain tensors of nanobubbles with arbitrary symmetry in 2D crystals. The method only requires topographic information from atomic force microscopy and the Poisson ratio of the 2D material. We verify that this method reproduces the strain for circularly symmetric nanobubbles that have known analytical solutions. Finally, we use the method to reproduce the Grüneisen parameter of the E' mode for 1L-WS2 nanobubbles on template-stripped Au by comparing the derived strain with measured Raman shifts from tip-enhanced Raman spectroscopy, demonstrating the utility of our method for estimating localized strain in 2D crystals.
2D materials↗
Robust cycloid crossover driven by anisotropy in the skyrmion host GaV 4 S 8
We report on the anomalous magnetization dynamics of the cycloidally modulated spin textures under the influence of uniaxial anisotropy in multiferroic GaV 4 S 8 . The temperature and field dependence of the linear ac susceptibility [$χ'_{1ω}$ (T, H)], AC magnetic loss [$χ''_{1ω}$ (T, H)], and nonlinear AC magnetic response [$M_{3ω}$ (T, H)] are examined across the magnetic phase diagram in the frequency range f = 10 - 10 000 Hz. According to recent theory, skyrmion vortices under axial crystal symmetry are confined along specific orientations, resulting in enhanced robustness against oblique magnetic fields and altered spin dynamics. We characterize the magnetic response of each spin texture and find that the dynamic rigidity of the Néel skyrmion lattice appears enhanced compared to Bloch-type skyrmions in cubic systems, even in the multidomain state. Anomalous M 3 ω and strong dissipation emerge over the same phase regime where strong variations in the cycloid pitch were observed on lowering temperature in recent small-angle neutron-scattering experiments [White et al., Phys. Rev. B 97, 020401(R) (2018)]. Here, we show that strong anisotropy also drives an extended crossover of the zero-field cycloid texture in GaV 4 S 8 . The frequency dependence of these dynamic signatures is consistent with that of a robust anharmonic spin texture exhibiting a correlated domain arrangement. The results underpin the essential role of magnetic anisotropy in enhancing the rigidity of topological spin textures for diverse applications.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Dispersion Caused by the Penetration Effect in X-ray Compressors
Chirped X-ray pulse compression is a promising approach for generating ultra-short X-ray free electron laser (XFEL) pulses. The design of X-ray pulse compressors requires the careful control of group delay dispersion (GDD), which plays a critical role in achieving optimal compression. However, the penetration dispersion of crystals and multilayers can induce an extra GDD, which may result in over-compression or under-compression. In this study, we investigate the penetration dispersion of crystals and multilayers theoretically and numerically. Our results indicate that the extra GDD induced by the penetration effect increases as the bandwidth of the rocking curve decreases. Moreover, the extra GDD is nonlinear and can be mitigated by optimizing the configuration of X-ray pulse compressors. This work provides insights into the dispersion compensation and configuration optimization of X-ray pulse compressors, which are essential for generating ultra-short XFEL pulses.
47 OTHER INSTRUMENTATION↗
Berry curvature memory through electrically driven stacking transitions
In two-dimensional layered quantum materials, the interlayer stacking order determines both crystalline symmetry and quantum electronic properties such as Berry curvature, topology and electron correlation. Electrical stimuli can strongly influence quasi-particle interactions and the free energy landscape, thus making it possible to access hidden stacking orders with novel quantum properties and enabling dynamic engineering of these attributes. In this paper, we demonstrate electrically driven stacking transitions and a new type of nonvolatile memory based on Berry curvature in few-layer WTe 2 . The interplay of out-of-plane electric fields and electrostatic doping controls in-plane interlayer sliding and creates multiple polar and centrosymmetric stacking orders. In-situ nonlinear Hall transport reveals such stacking rearrangements result in a layer-parity-selective Berry curvature memory in momentum space, where the sign reversal of the Berry curvature only occurs in odd layer crystals. Our findings open an avenue towards exploring coupling between topology, electron correlations, and ferroelectricity in hidden stacking orders and demonstrate a new low energy cost, electrically-controlled topological memory in the atomically thin limit.
36 MATERIALS SCIENCE↗
Unraveling the magnetic ground state in the alkali-metal lanthanide oxide Na 2 PrO 3
Here, a comprehensive set of muon spin spectroscopy and neutron scattering measurements supported by ab initio and model Hamiltonian simulations have been used to investigate the magnetic ground state of Na 2 PrO 3 . μSR reveals a Néel antiferromagnetic order below T N ~ 4.9K, with a small static magnetic moment m static ≤ 0.22 μ B /Pr collinearly aligned along the c axis. Inelastic neutron measurements reveal the full spectrum of crystal field excitations and confirm that the Pr 4+ ground-state wave function deviates significantly from the Γ 7 limit that is relevant to the Kitaev model. Single- and two-magnon excitations are observed in the ordered state below T N =4.6K and are well described by nonlinear spin wave theory from the Néel state using a magnetic Hamiltonian with Heisenberg exchange J=1 meV and symmetric anisotropic exchange Γ/J=0.1, corresponding to an XY model. Intense two magnon excitations are accounted for by g-factor anisotropy g z /g ± = 1.29. A fluctuating moment δm 2 = 0.57 (22) μ$^2_B$/Pr extracted from the energy and momentum integrated inelastic neutron signal is reduced from expectations for a local J = 1/2 moment with average g factor g avg ≈ 1.1. Together, the results demonstrate that the small moment in Na 2 PrO 3 arises from crystal field and covalency effects and the material does not exhibit significant quantum fluctuations.
36 MATERIALS SCIENCE↗
Dual Emission Bands of a 2D Perovskite Single Crystal with Charge Transfer State Characteristics
Several hybrid halide 2D-perovskite species emit light with an emergent and controversial broadband emission Stokes-shifted down from the narrow band emission. This work uncovers the sub- and above-bandgap emission and absorption characteristics of PEA 2 PbI 4 prepared with gap states introduced during single crystal growth. Here, gap states led to coexistent intrinsic and heterostructured electronic frameworks that are selectively accessible with ultraviolet (UV) and infrared (IR) light, respectively, resulting in the phenomenon of photoluminescence (PL) switching from narrowband green to broadband red. Electron-energy dependent cathodoluminescence shows a relative increase in the broadband red PL intensity as the electron penetration depth increases from 30 nm to 2 μm, confirming the heterostructured framework is formed in the bulk of the crystal. Excitation–emission power slope of 2.5 and up-conversion pump transient absorption (TA) spectra suggest that the IR up-conversion excitation with red photoluminescence, peaked at 655 nm, is a multiphoton process occurring in the heterostructured framework through a nonlinear optical response. The energetic pathways toward the dual emission bands are revealed by pump–probe transient absorption spectroscopy, showing energetically broad gap states with high sensitivity to an IR pump are upconverted and subsequently quickly relax from high to low energy levels within 4 ps. Furthermore, the up-conversion red PL demonstrates a linear polarization with magnetic field effects, thus affirming that the band-like heterostructured framework is crystallographically aligned with characteristics of spatially extended charge-transfer states.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Advances in the photon avalanche luminescence of inorganic lanthanide-doped nanomaterials
Photon avalanche (PA)—where the absorption of a single photon initiates a ‘chain reaction’ of additional absorption and energy transfer events within a material—is a highly nonlinear optical process that results in upconverted light emission with an exceptionally steep dependence on the illumination intensity. Over 40 years following the first demonstration of photon avalanche emission in lanthanide-doped bulk crystals, PA emission has been achieved in nanometer-scale colloidal particles. The scaling of PA to nanomaterials has resulted in significant and rapid advances, such as luminescence imaging beyond the diffraction limit of light, optical thermometry and force sensing with (sub)micron spatial resolution, and all-optical data storage and processing. In this review, we discuss the fundamental principles underpinning PA and survey the studies leading to the development of nanoscale PA. Finally, we offer a perspective on how this knowledge can be used for the development of next-generation PA nanomaterials optimized for a broad range of applications, including mid-IR imaging, luminescence thermometry, (bio)sensing, optical data processing and nanophotonics.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Recent advances in computational mathematics and applications
We are honored to bring you this special issue dedicated to recent advances in computational mathematics and applications in science and engineering. The papers in this special issue were presented in ”Conference on Computational Mathematics and Applications (CCMA)” held at the University of Nevada Las Vegas (UNLV) during October 25–27, 2019. The conference has attracted about 90 attendees from six countries. The 15 papers in the special issue comprise a diverse collection of theoretical numerical analysis as well as applications in various subjects. Topics cover optimal control of PDEs, discontinuous Galerkin methods, fluid flow in porous media, turbulence flow, static and moving interface problems, complex fluids composed by the mixture of Newtonian fluid and nematic (liquid crystal) flows, modeling of ocean–atmosphere system, image segmentation algorithm, uncertainty quantification problems for turbulence model and Maxwell’s equations, iterative solver for systems resulting from mixed methods, and novel methods for solving systems of nonlinear equations. As the Guest Editors we would like to thank Dr. Leland Jameson at NSF (National Science Foundation) for kindly supporting our conference proposal which made this conference possible. We would also like to thank Darren Sugrue from Elsevier who provided partial support for our conference, and Thennarasu Gunasekaran and his production team from Elsevier who produced this nice special issue. We are grateful to many people (Dr. Zhijian Wu, Lori Ornelas, Elsa Juarez, and many Ph.D. students) at the Department of Mathematical Sciences of UNLV who provided tremendous support for the conference. Finally, we very much appreciate all authors who contributed their precious results to this special issue.
97 MATHEMATICS AND COMPUTING↗
Broadband sum-frequency generation of spectrally incoherent pulses
We study and demonstrate the nonlinear frequency conversion of broadband optical pulses from 1053 nm to 351 nm using sum-frequency generation with a narrowband pulse at 526.5 nm. The combination of angular dispersion and noncollinearity cancels out the wave-vector mismatch and its frequency derivative, yielding an order-of-magnitude increase in spectral acceptance compared to conventional tripling. This scheme can support the nonlinear frequency conversion of broadband spectrally incoherent nanosecond pulses generated by high-energy lasers and optical parametric amplifiers to mitigate laser−plasma instabilities occurring during interaction with a target. The experimental results obtained with KDP crystals are in excellent agreement with modeling, demonstrating the generation of spectrally incoherent pulses with a bandwidth larger than 10 THz at 351 nm.
47 OTHER INSTRUMENTATION↗
A machine-learning approach to measure 3D sample properties from 2D Transmission Electron Microscopy images
Transmission Electron Microscopy (TEM) is a powerful tool for the characterization of materials at the nanoscale; however, its inherent two-dimensional (2D) nature poses significant challenges to accurately measure three-dimensional (3D) properties. We introduce a supervised machine-learning model that predicts 3D structural information, such as sample thickness and curvature, from a series of conventional 2D TEM images. The model, a U-Net convolutional neural network, is trained on a large synthetic dataset generated from dynamical diffraction simulations that model TEM’s complex, nonlinear image formation, accounting for sample thickness and curvature. This physically realistic framework enables exploration of a broad parameter space impractical to sample experimentally. We demonstrate that the trained model has accurate predictions for experimental single-crystal silicon samples, achieving performance comparable to established measurement techniques. This work highlights the critical role of robust, simulation-based training in overcoming the limitations of real-world imaging artifacts and inconsistent sample geometries. By integrating machine learning with numerical simulations, we offer an efficient and scalable framework for quantitative TEM analysis, paving the way for more sophisticated 3D characterization of complex materials.
Dynamical diffraction↗
Kinetics of HCP-BCC Phase Transition Boundary in Magnesium at High Pressure
Under high pressures, many crystalline metals undergo solid–solid phase transformations. In order to accurately model the behavior of materials under extreme loading conditions, it is essential to understand the kinetics of phase transition. Using molecular dynamics simulations, this work demonstrates the feasibility of characterizing the speeds of a moving phase boundary using atomistic simulations employing a suitable empirical potential for single-crystal magnesium. The model can provide temperature- and tensorial stress-dependent velocity of a moving phase boundary as a rate-limiting contribution to the kinetics of phase transformation in continuum codes. Results demonstrate that a nonlinear interaction exists between plasticity and phase transition, facilitating a jump in the velocity of a moving phase boundary, facilitated by activated plastic deformation mechanisms.
36 MATERIALS SCIENCE↗
Noncentrosymmetric Tetrel Pnictides RuSi[subscript 4]P[subscript 4] and IrSi[subscript 3]P[subscript
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Lee, Shannon↗
Activated relaxation in supercooled monodisperse atomic and polymeric WCA fluids: Simulation and ECNLE theory
Here, we combine simulation and Elastically Collective Nonlinear Langevin Equation (ECNLE) theory to study the activated relaxation in monodisperse atomic and polymeric Weeks–Chandler–Andersen (WCA) liquids over a wide range of temperatures and densities in the supercooled regime under isochoric conditions. By employing novel crystal-avoiding simulations, metastable equilibrium dynamics is probed in the absence of complications associated with size polydispersity. Based on a highly accurate structural input from integral equation theory, ECNLE theory is found to describe well the simulated density and temperature dependences of the alpha relaxation time of atomic fluids using a single system-specific parameter, a c , that reflects the nonuniversal relative importance of local cage and collective elastic barriers. For polymer fluids, the explicit dynamical effect of local chain connectivity is modeled at the fundamental dynamic free energy trajectory level based on a different parameter, N c , that quantifies the degree of intramolecular correlation of bonded segment activated barrier hopping. For the flexible chain model studied, a physically intuitive value of N c ≈ 2 results in good agreement between simulation and theory. A direct comparison between atomic and polymeric systems reveals that chain connectivity can speed up activated segmental relaxation due to weakening of equilibrium packing correlations but can slow down relaxation due to local bonding constraints. The empirical thermodynamic scaling idea for the alpha time is found to work well at high densities or temperatures but fails when both density and temperature are low. The rich and subtle behaviors revealed from simulation for atomic and polymeric WCA fluids are all well captured by ECNLE theory.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗