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Yu, Yue

Publications and source records attributed to Yu, Yue.

At least 19 records

Intermodal microwave-to-optical transduction using silicon-on-sapphire optomechanical ring resonator

Optomechanical and electro-optomechanical systems have emerged as one of the most promising approaches for quantum microwave-to-optical transduction to interconnect distributed quantum modalities for scaling the quantum systems. These systems use suspended structures to increase mode overlap and mitigate loss to achieve high efficiency. However, the suspended design’s poor heat dissipation under strong drive limits the ultimate efficiency. Here, we demonstrate an unsuspended optomechanical ring resonator (OMR) based on the silicon-on-sapphire (SOS) platform for microwave-to-optical frequency conversion. The OMR achieves a triply resonant optical-to-optical conversion with an enhanced coupling rateG b = 3.6 gigahertz per square-root milliwatt at a peak conversion efficiency of 1.2% with 3.6-milliwatt microwave drive power and a microwave-to-optical conversion efficiency of 1.5 × 10 −5 at 10-milliwatt optical drive power. Our results show that the unsuspended SOS platform, which mitigates the thermal effect and is compatible with superconducting qubits, is a promising platform for optomechanical circuitry and quantum transduction.

Science & Technology - Other Topics↗

Peridynamic neural operators: A data-driven nonlocal constitutive model for complex material responses

Neural operators, which can act as implicit solution operators of hidden governing equations, have recently become popular tools for learning the responses of complex real-world physical systems. Nevertheless, most neural operator applications have thus far been data-driven and neglect the intrinsic preservation of fundamental physical laws in data. Here, in this work, we introduce a novel integral neural operator architecture called the Peridynamic Neural Operator (PNO) that learns a nonlocal constitutive law from data. This neural operator provides a forward model in the form of state-based peridynamics, with objectivity and momentum balance laws automatically guaranteed. As applications, we demonstrate the expressivity and efficacy of our model in learning complex material behaviors from both synthetic and experimental data sets. We also compare the performances with baseline models that use predefined constitutive laws. We show that, owing to its ability to capture complex responses, our learned neural operator achieves improved accuracy and efficiency. Moreover, by preserving the essential physical laws within the neural network architecture, the PNO is robust in treating noisy data. The method shows generalizability to different domain configurations, external loadings, and discretizations.

42 ENGINEERING↗

Peridynamic Models for Random Media Found by Coarse Graining

Using coarse graining, the upscaled mechanical properties of a solid with small scale heterogeneities are derived. The method maps internal forces at the small scale onto peridynamic bond forces in the coarse grained mesh. These upscaled bond forces are used to calibrate a peridynamic material model with position-dependent parameters. These parameters incorporate mesoscale variations in the statistics of the small scale system. The upscaled peridynamic model can have a much coarser discretization than the original small scale model, allowing larger scale simulations to be performed efficiently. The convergence properties of the method are investigated for representative random microstructures. In conclusion, a bond breakage criterion for the upscaled peridynamic material model is also demonstrated.

36 MATERIALS SCIENCE↗

Conjugate Multimode Heat Transfer Analysis of Cryogenic EXLO Manipulation

Abstract In this study, a conjugate radiation/conduction multimode heat transfer analysis of cryogenic focused ion beam (FIB) milling steps necessary for producing ex situ lift out specimens under cryogenic conditions (cryo-EXLO) is performed. Using finite volume for transient heat conduction and enclosure theory for radiation heat transfer, the analysis shows that as long as the specimen is attached or touching the FIB side wall trenches, the specimen will remain vitreous indefinitely, while actively cooled at liquid nitrogen (LN2) temperatures. To simulate the time needed to perform a transfer step to move the bulk sample containing the FIB-thinned specimen from the cryo-FIB to the cryo-EXLO cryostat, the LN2 temperature active cooling is turned off after steady-state conditions are reached and the specimen is monitored over time until the critical devitrification temperature is reached. Under these conditions, the sample will remain vitreous for >3 min, which is more than enough time needed to perform the cryo-transfer step from the FIB to the cryostat, which takes only ∼10 s. Cryo-transmission electron microscopy images of a manipulated cryo-EXLO yeast specimen prepared with cryo-FIB corroborates the heat transfer analysis.

Materials Science↗

Topology stabilized fluctuations in a magnetic nodal semimetal

Abstract The interplay between magnetism and electronic band topology enriches topological phases and has promising applications. However, the role of topology in magnetic fluctuations has been elusive. Here, we report evidence for topology stabilized magnetism above the magnetic transition temperature in magnetic Weyl semimetal candidate CeAlGe. Electrical transport, thermal transport, resonant elastic X-ray scattering, and dilatometry consistently indicate the presence of locally correlated magnetism within a narrow temperature window well above the thermodynamic magnetic transition temperature. The wavevector of this short-range order is consistent with the nesting condition of topological Weyl nodes, suggesting that it arises from the interaction between magnetic fluctuations and the emergent Weyl fermions. Effective field theory shows that this topology stabilized order is wavevector dependent and can be stabilized when the interband Weyl fermion scattering is dominant. Our work highlights the role of electronic band topology in stabilizing magnetic order even in the classically disordered regime.

36 MATERIALS SCIENCE↗

Nondegenerate surface pair density wave in the kagome superconductor CsV 3 Sb 5 : Application to vestigial orders

On the Sb layer of the kagome superconductor CsV 3 ⁢Sb 5 , pair density wave states have been observed. When the high-temperature charge orderings are treated as static backgrounds, these pair density wave (PDW) states exhibit the same wave vector in the effective two-dimensional Brillouin zone. Interestingly, these PDW states break the same symmetry on the surface. Considering the presence of this nondegenerate PDW, we investigate the implications for the possible existence of a vestigial charge-4⁢ e phase with a nonzero center-of-mass momentum. To distinguish between different vestigial phases, we propose scanning tunneling microscopy experiments. Here we aim to provide insights into the nature of the vestigial phases and their distinct characteristics in CsV 3 ⁢Sb 5 . This research sheds light on the interplay between PDW states, charge orderings, and superconductivity of the kagome superconductor.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Revealing the Internal Architecture of Alkaline Fuel Cell Membranes with Cryo-4D-STEM and Cryo-STEM-EELS

Characterization of the internal architecture of polymer materials plays an important role in the development of energy devices such as fuel cells. The beam sensitivity of polymer materials coupled with their inherent low contrast makes imaging using conventional TEM and STEM techniques a challenge. Here, we demonstrate robust mapping of the internal architecture of fuel cell polymer membranes using cryo-4D-STEM and cryo-STEM-EELS. Here, we will focus on characterization of alkaline anion exchange membranes (AAEMs) used in AAEM fuel cells, a cheaper alternative to current fuel cell technologies as they allow for platinum group metal-free catalysts. In fuel cell polymer membranes, the internal architecture is critical in performance metrics such as conductivity, mechanical durability, and chemical stability.

30 DIRECT ENERGY CONVERSION↗

Towards a unified nonlocal, peridynamics framework for the coarse-graining of molecular dynamics data with fractures

Molecular dynamics (MD) has served as a powerful tool for designing materials with reduced reliance on laboratory testing. However, the use of MD directly to treat the deformation and failure of materials at the mesoscale is still largely beyond reach. In this work, we propose a learning framework to extract a peridynamics model as a mesoscale continuum surrogate from MD simulated material fracture data sets. Firstly, we develop a novel coarse-graining method, to automatically handle the material fracture and its corresponding discontinuities in the MD displacement data sets. Inspired by the weighted essentially non-oscillatory (WENO) scheme, the key idea lies at an adaptive procedure to automatically choose the locally smoothest stencil, then reconstruct the coarse-grained material displacement field as the piecewise smooth solutions containing discontinuities. Then, based on the coarse-grained MD data, a two-phase optimization-based learning approach is proposed to infer the optimal peridynamics model with damage criterion. In the first phase, we identify the optimal nonlocal kernel function from the data sets without material damage to capture the material stiffness properties. Then, in the second phase, the material damage criterion is learnt as a smoothed step function from the data with fractures. As a result, a peridynamics surrogate is obtained. As a continuum model, our peridynamics surrogate model can be employed in further prediction tasks with different grid resolutions from training, and hence allows for substantial reductions in computational cost compared with MD. We illustrate the efficacy of the proposed approach with several numerical tests for the dynamic crack propagation problem in a single-layer graphene. Our tests show that the proposed data-driven model is robust and generalizable, in the sense that it is capable of modeling the initialization and growth of fractures under discretization and loading settings that are different from the ones used during training.

97 MATHEMATICS AND COMPUTING↗

Effects of rejuvenation modes on the microstructures and mechanical properties of metallic glasses

This study systematically investigates the effects of three rejuvenation modes, namely biaxial loading, thermal pressure loading, and cryogenic thermal cycling, on the microstructures and mechanical properties of Cu 64 Zr 36 metallic glasses (MGs) using molecular dynamics (MD) simulations. The simulation results demonstrate that biaxial tension application during loading results in a rejuvenated glassy state with high strength. Specifically, we find that the yield stress, Young's modulus, and shear modulus of the rejuvenated glass obtained by biaxial tensile loading decreased by 2.8%, 2.1%, and 2.7%, respectively, compared to an as-cast MG reference. We also find that MGs achieve the greatest degree of rejuvenation, at the expense of strength, with the use of thermal pressure loading. Interestingly, the application of cryogenic thermal cycling results in a rejuvenated state with a lower strength drop compared to thermal pressure loading. Furthermore, analysis of the potential energy and medium-range-order (MRO) size indicates that the microstructures of MGs achieves a high-energy ordered glass state after thermal pressure loading, but a high-energy disordered glass state after biaxial tensile loading and cryogenic thermal cycling. Furthermore, these findings provide meaningful insights into the effect of rejuvenation modes on the microstructures and mechanical properties of MGs, as well as useful guidelines for designing MGs with high strength and superior plasticity for prospective applications in industry.

36 MATERIALS SCIENCE↗

Comparative Energetics of Various Membrane Distillation Configurations and Guidelines for Design and Operation

This paper presents a comparative performance study of single-stage desalination processes with major configurations of membrane distillation (MD) modules. MD modules covered in this study are (a) direct contact MD (DCMD), (b) vacuum MD (VMD), (c) sweeping gas MD (SGMD), and (d) air gap MD (AGMD). MD-based desalination processes are simulated with rigorous theoretical MD models supported by molecular thermodynamic property models for the accurate calculation of performance metrics. The performance metrics considered in MD systems are permeate flux and energy efficiency, i.e., gained output ratio (GOR). A general criterion is established to determine the critical length of these four MDs (at fixed width) for the feasible operation of desalination in a wide range of feed salinities. The length of DCMD and VMD is restricted by the feed salinity and permeate flux, respectively, while relatively large AGMD and SGMD are allowed. The sensitivity of GOR flux with respect to permeate conditions is investigated for different MD configurations. AGMD outperforms other configurations in terms of energy efficiency, while VMD reveals the highest permeate production. With larger MD modules, utilization of thermal energy supplied by the hot feed for evaporation is in the order of VMD > AGMD > SGMD > DCMD. Simulation results highlight that energy efficiency of the overall desalination process relies on the efficient recovery of spent for evaporation, suggesting potential improvement in energy efficiency for VMD-based desalination.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Ampere field fluctuation from acoustic phonons as a possible source of spin decoherence

Here, we present a simple theory for estimating spin decoherence due to spin–phonon coupling in a lattice, and apply the theory to the Ampere field fluctuation from acoustic phonons. The Ampere field is generated by charge current loops around each lattice site due to acoustic phonon motion of the ions. The spin decoherence time due to the Ampere field fluctuation is estimated for NV centers and Mo impurities in SiC, and quantum dot qubits in Ge, GaAs, InAs, and InSb for temperature range 2 to 300 K. For most materials the estimated decoherence time is orders of magnitude longer than reported experimental values at the same temperature. The only exception is Mo impurity in SiC, for which the experimental decoherence time at 2 K is close to that due to Ampere field fluctuation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Universal topological quantum computation with strongly correlated Majorana edge modes

Abstract Majorana-based quantum gates are not complete for performing universal topological quantum computation while Fibonacci-based gates are difficult to be realized electronically and hardly coincide with the conventional quantum circuit models. In reference Hu and Kane (2018 Phys. Rev. Lett. 120 066801), it has been shown that a strongly correlated Majorana edge mode in a chiral topological superconductor can be decomposed into a Fibonacci anyon τ and a thermal operator anyon ɛ in the tricritical Ising model. The deconfinement of τ and ɛ via the interaction between the fermion modes yields the anyon collisions and gives the braiding of either τ or ɛ . With these braidings, the complete members of a set of universal gates, the Pauli gates, the Hadamard gate and extra phase gates for one-qubit as well as controlled-NOT (CNOT) gate for two-qubits, are topologically assembled. Encoding quantum information and reading out the computation results can be carried out through electric signals. With the sparse-dense mixed encodings, we set up the quantum circuit where the CNOT gate turns out to be a probabilistic gate and design the corresponding devices with thin films of the chiral topological superconductor. As an example of the universal topological quantum computing, we show the application to Shor’s integer factorization algorithm.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗