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At least 289 records · Page 16

Passive radiative thermal management using phase-change metasurfaces

Abstract Realizing innovative composite materials with passive thermal management capabilities and minimal ecological footprints is a challenging but much sought-after goal that would have a transformative effect on renewable energy sciences. We demonstrate an environmentally friendly metasurface utilizing vanadium dioxide (VO 2 ) that offers responsiveness to ambient temperature and potentially long-term stability. The metasurface enables passive thermal management by self-adjusting its absorptivity and emissivity response over a broad bandwidth ranging from visible to mid-infrared (IR) wavelengths. Above the VO 2 phase transition the metasurface exhibits increased mid-IR emissivity and reduced visible/near-IR absorptivity, creating an efficient radiative emission channel in the first atmospheric transparency window with reduced absorption of solar radiation. In contrast, below VO 2 ’s transition temperature, the metasurface increasingly absorbs sun light while minimizing mid-IR radiative heat losses. Moreover, a functional silicon layer eliminates the need for an additional capping layer commonly employed to protect VO 2 from environmental degradation. The additional protective layer often impedes the use and performance of VO 2 based devices in terrestrial as well as spacecraft applications. Therefore, the proposed durable and eco-friendly metasurface will be an excellent candidate for essential passive thermal regulation systems across residential and terrestrial applications.

42 ENGINEERING↗

Machine Learning Chemical Guidelines for Engineering Electronic Structures in Half-Heusler Thermoelectric Materials

Half-Heusler materials are strong candidates for thermoelectric applications due to their high weighted mobilities and power factors, which is known to be correlated to valley degeneracy in the electronic band structure. However, there are over 50 known semiconducting half-Heusler phases, and it is not clear how the chemical composition affects the electronic structure. While all the n-type electronic structures have their conduction band minimum at either the Γ - or X -point, there is more diversity in the p-type electronic structures, and the valence band maximum can be at either the Γ -, L -, or W -point. Here, we use high throughput computation and machine learning to compare the valence bands of known half-Heusler compounds and discover new chemical guidelines for promoting the highly degenerate W -point to the valence band maximum. We do this by constructing an “orbital phase diagram” to cluster the variety of electronic structures expressed by these phases into groups, based on the atomic orbitals that contribute most to their valence bands. Then, with the aid of machine learning, we develop new chemical rules that predict the location of the valence band maximum in each of the phases. These rules can be used to engineer band structures with band convergence and high valley degeneracy.

36 MATERIALS SCIENCE↗

Highly efficient removal and sequestration of Cr(VI) in confined MoS 2 interlayer Nanochannels: Performance and mechanism

Environmental contamination by Cr(VI) is of particular concern because of its severe toxicity and high mobility. In this study, we employed two-dimensional MoS 2 nanosheets in the removal of Cr(VI), with an emphasis on revealing the removal mechanisms, and how the compositional and structural uniqueness of 2D MoS 2 nanomaterials intrinsically impact the Cr removal efficiency. Through batch experiments with dispersed nanosheets, we found that MoS 2 nanosheets exhibited a high Cr(VI) removal capacity at ~1100 mg/g via a phase-dependent mechanism. Particularly, the 1T polymorph in the MoS 2 nanosheets removed Cr(VI) through a redox-reaction mechanism, which was different from the adsorptive removal of Cr(VI) by MoS 2 reported previously, highlighting the compositional effects on the removal mechanism and performance. More importantly, the reduced product Cr(III) was concurrently removed via precipitation and adsorption onto the MoS 2 nanosheets, which could avoid the additional pH-elevation step that is typically needed in the conventional treatment. The unique 2D flake-like structure of MoS 2 nanosheets enabled the formation of aligned and ion-accessible nanochannels, where Cr(VI) species were accommodated, reduced and sequestered. The irreversible shrinking of the nanochannels under drying modified the interior of the layer-stacked structure into confined compartments preventing the release and re-oxidation of the immobilized Cr(III). In conclusion, the compiled results highlight the effects of MoS 2 composition and structure on the Cr removal efficiency and mechanism, which has substantial implications on future studies tailoring these unique features of 2D nanomaterials for various remediation scenarios.

42 ENGINEERING↗

Group-equivariant autoencoder for identifying spontaneously broken symmetries

We introduce the group-equivariant autoencoder (GE autoencoder), a deep neural network (DNN) method that locates phase boundaries by determining which symmetries of the Hamiltonian have spontaneously broken at each temperature. We use group theory to deduce which symmetries of the system remain intact in all phases, and then use this information to constrain the parameters of the GE autoencoder such that the encoder learns an order parameter invariant to these “never-broken” symmetries. This procedure produces a dramatic reduction in the number of free parameters such that the GE-autoencoder size is independent of the system size. We include symmetry regularization terms in the loss function of the GE autoencoder so that the learned order parameter is also equivariant to the remaining symmetries of the system. By examining the group representation by which the learned order parameter transforms, we are then able to extract information about the associated spontaneous symmetry breaking. We test the GE autoencoder on the 2D classical ferromagnetic and antiferromagnetic Ising models, finding that the GE autoencoder (1) accurately determines which symmetries have spontaneously broken at each temperature; (2) estimates the critical temperature in the thermodynamic limit with greater accuracy, robustness, and time efficiency than a symmetry-agnostic baseline autoencoder; and (3) detects the presence of an external symmetry-breaking magnetic field with greater sensitivity than the baseline method. Lastly, we describe various key implementation details, including a quadratic-programming-based method for extracting the critical temperature estimate from trained autoencoders and calculations of the DNN initialization and learning rate settings required for fair model comparisons.

42 ENGINEERING↗

Engineering-In Cybersecurity

Cyber-Informed Engineering is a framework which allows engineers to build resiliency to the impacts of cyber attack into engineered systems starting in the early design phases. This article introduces the framework and provides a description of some of its principles and resources for learning more.

42 ENGINEERING↗

Nuclear Technology Selection and Preliminary Integration at St. Charles and Carrollton Chemical Plants

Nuclear energy is identified as a valuable candidate for decarbonizing industrial facilities as a non-emitting baseload energy source capable of dispatching energy as needed for an integrated facility. As industrial facilities are unique, analyzing what nuclear technology is the best candidate should be evaluated on a case-by-case basis. For two identified facilities of the Dow Chemical Company, an ideal mix of nuclear energy resources is calculated, and integration strategies are put forward. This research was funded through a Gateway for Accelerated Innovation in Nuclear (GAIN) Nuclear Energy Voucher, specifically seeking near-term engineering solutions for the technical issue of introducing nuclear generated energy into the Dow chemical facilities. The research is split into four main phases: background on reactors and chemical facilities, preliminary engineering analysis determining how reactor technologies may be integrated with specific facilities, site characterization and discrete hazards analysis, and finally an optimization of reactor-facility selection through the use of Framework for Optimization of ResourCes and Economics (FORCE) tools.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

A conservative, interface-resolved, compressible framework for the modeling and simulation of liquid/gas phase change

This paper presents a method for simulating evaporation in a compressible, interface-resolved framework appropriate for modeling problems of engineering interest. In order to achieve robustness and broad applicability, the method has been designed to discretely enforce consistent mass and thermal energy transport at the phase interface, to globally conserve mass, momentum, and energy, and to be capable of modeling compressible and incompressible systems. Verification is performed via the Sod-shock test, one-dimensional heat conduction, evaporation from a planar interface, and evaporation of three-dimensional droplets. Convergence with increasing mesh resolution is demonstrated in all tested configurations, and conservation is maintained near machine precision for a translating droplet. Conservation and accurate phase change rates are preserved at the low numerical resolutions commonly encountered in engineering calculations. Following verification, the method is validated by comparison to an empirical correlation for evaporating droplets in high temperature crossflow, and the presentation concludes with the simulation of an iso-octane spray at conditions representative of gasoline direct injection. In conclusion, successful verification, validation, and demonstrated practical utility suggest the method to be an accurate, efficient, and robust approach for the study of phase change in engineering systems.

97 MATHEMATICS AND COMPUTING↗

Self-Assembled Periodic Nanostructures Using Martensitic Phase Transformations

We describe a novel approach for the rational design and synthesis of self-assembled periodic nanostructures using martensitic phase transformations. We demonstrate this approach in a thin film of perovskite SrSnO 3 with reconfigurable periodic nanostructures consisting of regularly spaced regions of sharply contrasted dielectric properties. The films can be designed to have different periodicities and relative phase fractions via chemical doping or strain engineering. The dielectric contrast within a single film can be tuned using temperature and laser wavelength, effectively creating a variable photonic crystal. Our results show the realistic possibility of designing large-area self-assembled periodic structures using martensitic phase transformations with the potential of implementing "built-to-order" nanostructures for tailored optoelectronic functionalities.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Giant energy storage and power density negative capacitance superlattices

Dielectric electrostatic capacitors, because of their ultrafast charge-discharge, are desirable for high-power energy storage applications. Along with ultrafast operation, on-chip integration can enable miniaturized energy storage devices for emerging autonomous microelectronics and microsystems. Moreover, state-of-the-art miniaturized electrochemical energy storage systems-microsupercapacitors and microbatteries-currently face safety, packaging, materials and microfabrication challenges preventing on-chip technological readiness, leaving an opportunity for electrostatic microcapacitors. Here, in this study, we report record-high electrostatic energy storage density (ESD) and power density, to our knowledge, in HfO 2 -ZrO 2 -based thin film microcapacitors integrated into silicon, through a three-pronged approach. First, to increase intrinsic energy storage, atomic-layer-deposited antiferroelectric HfO 2 -ZrO 2 films are engineered near a field-driven ferroelectric phase transition to exhibit amplified charge storage by the negative capacitance effect, which enhances volumetric ESD beyond the best-known back-end-of-the-line-compatible dielectrics (115 J cm -3 ). Second, to increase total energy storage, antiferroelectric superlattice engineering scales the energy storage performance beyond the conventional thickness limitations of HfO 2 -ZrO 2 -based (anti)ferroelectricity (100-nm regime). Third, to increase the storage per footprint, the superlattices are conformally integrated into three-dimensional capacitors, which boosts the areal ESD nine times and the areal power density 170 times that of the best-known electrostatic capacitors: 80 mJ cm -2 and 300 kW cm -2 , respectively. This simultaneous demonstration of ultrahigh energy density and power density overcomes the traditional capacity-speed trade-off across the electrostatic-electrochemical energy storage hierarchy. Furthermore, the integration of ultrahigh-density and ultrafast-charging thin films within a back-end-of-the-line-compatible process enables monolithic integration of on-chip microcapacitors, which can unlock substantial energy storage and power delivery performance for electronic microsystems.

25 ENERGY STORAGE↗

Realization of fermionic Laughlin state on a quantum processor

Strongly correlated topological phases of matter are central to modern condensed matter physics and quantum information technology but often challenging to probe and control in material systems. The experimental difficulty of accessing these phases has motivated the use of engineered quantum platforms for simulation and manipulation of exotic topological states. Among these, the Laughlin state stands as a cornerstone for topological matter, embodying fractionalization, anyonic excitations, and incompressibility. Although its bosonic analogs have been realized on programmable quantum simulators, a genuine fermionic Laughlin state has yet to be demonstrated on a quantum processor. Here, we realize the ν = 1/3 fermionic Laughlin state on IonQ’s trapped-ion quantum computer using an efficient and scalable Hamiltonian variational ansatz with 369 two-qubit gates on a 16-qubit circuit. Employing symmetry-verification error mitigation, we extract key observables that characterize the Laughlin state, including correlation hole, bulk-edge correspondence, and topological entanglement entropy, with strong agreement to exact diagonalization benchmarks. This work demonstrates an end-to-end workflow to simulate material-intrinsic topological orders and provides a starting point to explore its dynamics and excitations on digital quantum processors.

Shen, Lingnan [Univ. of Washington, Seattle, WA (U↗

Millimeter-wave electromagnetic monitoring for liquid metal droplet-on-demand printing

As new printing approaches emerge, in situ diagnostics to monitor the print quality in real-time become essential for long-term monitoring and feedback control. In this article, we present a millimeter-wave electromagnetic monitoring approach for liquid metal droplet-on-demand printing to support the high-speed and real-time evaluation of droplet ejection. An open-ended rectangular waveguide is placed perpendicular to a jetted droplet stream and operated at a continuous-wave frequency of 40 GHz. Liquid metal droplets with diameters as low as 1.2 mm are characterized, and droplet jetting events on the order of 500 μm are detected at ejection rates up to 80 Hz. The measured results demonstrate that trends at the macro-level (large-scale print variation and anomalies at the nozzle tip) as well as micro-level (droplet size, position, and dynamics) can be detected using this technique.

42 ENGINEERING↗

Finite-Temperature Quantum Matter with Rydberg or Molecule Synthetic Dimensions

Synthetic-dimension platforms offer unique pathways for engineering quantum matter. We compute the phase diagram of a many-body system of ultracold atoms (or polar molecules) with a set of Rydberg states (or rotational states) as a synthetic dimension, where the particles are arranged in real space in optical microtrap arrays and interact via dipole-dipole exchange interaction. Using mean-field theory, we find three ordered phases—two are localized in the synthetic dimension, predicted as zero-temperature ground states, and one is a delocalized phase. We characterize them by identifying the spontaneously broken discrete symmetries of the Hamiltonian. We also compute the phase diagram as a function of temperature and interaction strength for both signs of the interaction. For system sizes with more than six synthetic sites and attractive interactions, we find that the thermal phase transitions can be first or second order, which leads to a tricritical point on the phase boundary. Furthermore, by examining the dependence of the tricritical point and other special points of the phase boundary on the synthetic dimension size, we shed light on the physics for thermodynamically large synthetic dimension.

74 ATOMIC AND MOLECULAR PHYSICS↗

Twist Angle-Dependent Interlayer Exciton Lifetimes in van der Waals Heterostructures

In van der Waals (vdW) heterostructures formed by stacking two monolayers of transition metal dichalcogenides, multiple exciton resonances with highly tunable properties are formed and subject to both vertical and lateral confinement. We investigate how a unique control knob, the twist angle between the two monolayers, can be used to control the exciton dynamics. We observe that the interlayer exciton lifetimes in MoSe 2 /WSe 2 twisted bilayers (TBLs) change by one order of magnitude when the twist angle is varied from 1° to 3.5°. Additionally, using a low-energy continuum model, we theoretically separate two leading mechanisms that influence interlayer exciton radiative lifetimes. The shift to indirect transitions in the momentum space with an increasing twist angle and the energy modulation from the moiré potential both have a significant impact on interlayer exciton lifetimes. We further predict distinct temperature dependence of interlayer exciton lifetimes in TBLs with different twist angles, which is partially validated by experiments. While many recent studies have highlighted how the twist angle in a vdW TBL can be used to engineer the ground states and quantum phases due to many-body interaction, our studies explore its role in controlling the dynamics of optically excited states, thus, expanding the conceptual applications of “twistronics”.

36 MATERIALS SCIENCE↗

Quasi-Floquet Prethermalization in a Disordered Dipolar Spin Ensemble in Diamond

Floquet (periodic) driving has recently emerged as a powerful technique for engineering quantum systems and realizing nonequilibrium phases of matter. A central challenge to stabilizing quantum phenomena in such systems is the need to prevent energy absorption from the driving field. Fortunately, when the frequency of the drive is significantly larger than the local energy scales of the many-body system, energy absorption is suppressed. The existence of this so-called prethermal regime depends sensitively on the range of interactions and the presence of multiple driving frequencies. Here, we report the observation of Floquet prethermalization in a strongly interacting dipolar spin ensemble in diamond, where the angular dependence of the dipolar coupling helps to mitigate the long-ranged nature of the interaction. Moreover, we extend our experimental observation to quasi-Floquet drives with multiple incommensurate frequencies. In contrast to a single-frequency drive, we find that the existence of prethermalization is extremely sensitive to the smoothness of the applied field. In conclusion, our results open the door to stabilizing and characterizing nonequilibrium phenomena in quasiperiodically driven systems.

36 MATERIALS SCIENCE↗

Universal finite-time thermodynamics of many-body quantum machines from Kibble-Zurek scaling

We demonstrate the existence of universal features in the finite-time thermodynamics of quantum machines by considering a many-body quantum Otto cycle in which the working medium is driven across quantum critical points during the unitary strokes. Specifically, we consider a quantum engine powered by dissipative energizing and relaxing baths. We show that under very generic conditions, the output work is governed by the Kibble-Zurek mechanism; i.e., it exhibits a universal power-law scaling with the driving speed through the critical points. We also optimize the finite-time thermodynamics as a function of the driving speed. The maximum power and the corresponding efficiency take a universal form, and are reached for an optimal speed that is governed by the critical exponents. We exemplify our results by considering a transverse-field Ising spin chain as the working medium. For this model, we also show how the efficiency and power vary as the engine becomes critical.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Switching Dynamics in Vanadium Dioxide-Based Stochastic Thermal Neurons

We report on switching dynamics of individual and coupled vanadium dioxide (VO 2 ) devices subject to voltage pulses as the temperature is systematically varied from room temperature spanning the insulator–metal transition (IMT) temperature. The switching voltage of single devices has a strong relationship with both temperature and voltage pulsewidth. Two-step switching in connected VO 2 devices has been noted in current transient plots and was found to depend on temperature, pulsewidth, and pulse amplitude. Experimental switching behavior measured from VO 2 artificial neurons was implemented into a spiking neural network (SNN). During training, modulating the switching voltage via temperature affords a novel method to implement homeostasis with the coupled devices. Simulation results show the efficacy of the stochastic neuronal characteristics and the proposed homeostasis mechanism on a standard digit recognition task. As a result, these studies contribute to ongoing efforts in neuromorphic computing exploiting collective phase transitions.

42 ENGINEERING↗

A Stochastic Reduced-Order Model for Statistical Microstructure Descriptors Evolution

Integrated computational materials engineering (ICME) models have been a crucial building block for modern materials development, relieving heavy reliance on experiments and significantly accelerating the materials design process. However, ICME models are also computationally expensive, particularly with respect to time integration for dynamics, which hinders the ability to study statistical ensembles and thermodynamic properties of large systems for long time scales. To alleviate the computational bottleneck, we propose to model the evolution of statistical microstructure descriptors as a continuous-time stochastic process using a non-linear Langevin equation, where the probability density function (PDF) of the statistical microstructure descriptors, which are also the quantities of interests (QoIs), is modeled by the Fokker–Planck equation. In this work, we discuss how to calibrate the drift and diffusion terms of the Fokker–Planck equation from the theoretical and computational perspectives. The calibrated Fokker–Planck equation can be used as a stochastic reduced-order model to simulate the microstructure evolution of statistical microstructure descriptors PDF. Considering statistical microstructure descriptors in the microstructure evolution as QoIs, we demonstrate our proposed methodology in three integrated computational materials engineering (ICME) models: kinetic Monte Carlo, phase field, and molecular dynamics simulations.

97 MATHEMATICS AND COMPUTING↗