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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

ExactPack: A python library of exact analytic solutions

Verification of multi-physics simulation software against problems with known analytic or semi-analytic solutions is an important aspect of research into a wide variety of fields involving the motion of fluids, shock physics and other dynamic material properties. Previous work comparing simulation results against analytic solutions has been ad-hoc, with developers frequently writing their own analytic solvers. This has resulted in a large amount of duplicated effort. The python library ExactPack has been developed as a collection of analytic and semi-analytic solvers to a variety of multi-physics problems, providing a consistent API to a set of well-tested solver implementations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Advanced Materials for Energy-Water Systems: The Central Role of Water/Solid Interfaces in Adsorption, Reactivity, and Transport

The structure, chemistry, and charge of interfaces between materials and aqueous fluids play a central role in determining properties and performance of numerous water systems. Sensors, membranes, sorbents, and heterogeneous catalysts almost uniformly rely on specific interactions between their surfaces and components dissolved or suspended in the water-and often the water molecules themselves-to detect and mitigate contaminants. Deleterious processes in these systems such as fouling, scaling (inorganic deposits), and corrosion are also governed by interfacial phenomena. Despite the importance of these interfaces, much remains to be learned about their multiscale interactions. Developing a deeper understanding of the molecular- and mesoscale phenomena at water/solid interfaces will be essential to driving innovation to address grand challenges in supplying sufficient fit-for-purpose water in the future. In this Review, we examine the current state of knowledge surrounding adsorption, reactivity, and transport in several key classes of water/solid interfaces, drawing on a synergistic combination of theory, simulation, and experiments, and finally, provide an outlook for prioritizing strategic research directions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Tuning Surface Adhesion Using Grayscale Electron-beam Lithography

Surface texturing of manufactured products tailors their properties, such as friction, adhesion, biocompatibility, or fluid interactions. However, advancements in this area are largely the result of trial-and-effort testing and generally lack a science-guided framework for determining the surface topography that will optimize performance. The present investigation explores grayscale electron-beam lithography as a means to create multiscale surface patterns to control surface performance. Here, we created and characterized a set of surface textures on a silicon wafer; the textures were superpositions of sine waves of varying wavelengths and amplitudes. First, the multiscale topography of the patterned surface was characterized, using profilometry and atomic force microscopy, to understand its fidelity to the designed-in pattern. The results of this analysis demonstrated how grayscale lithography accurately controlled the lateral size of features but was less precise on the vertical height of the surface, and also introduced inherent roughness below the scale of patterning. Second, a micromechanical tester was used to characterize the adhesion of the surfaces with large-scale polished silicon spheres. The results showed that adhesion could be tailored, with significant contribution from all of the designed-in length scales of topography. The strength of adhesion did not correlate with conventional roughness parameters but could be accurately modeled using simple numerical integration. Taken together, this investigation demonstrates the promise and challenges of grayscale e-beam lithography with multiscale patterns as a method for the tailoring of surface performance.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Effect of surface properties and polymer chain length on polymer adsorption in solution

In polymer nanoparticle composites (PNCs) with attractive interactions between nanoparticles (NPs) and polymers, a bound layer of the polymer forms on the NP surface, with significant effects on the macroscopic properties of the PNCs. The adsorption and wetting behaviors of polymer solutions in the presence of a solid surface are critical to the fabrication process of PNCs. In this study, we use both classical density functional theory (cDFT) and molecular dynamics (MD) simulations to study dilute and semi-dilute solutions of short polymer chains near a solid surface. Using cDFT, we calculate the equilibrium properties of polymer solutions near a flat surface while varying the solvent quality, surface–fluid interactions, and the polymer chain lengths to investigate their effects on the polymer adsorption and wetting transitions. Using MD simulations, we simulate polymer solutions near solid surfaces with three different curvatures (a flat surface and NPs with two radii) to study the static conformation of the polymer bound layer near the surface and the dynamic chain adsorption process. Additionally, we find that the bulk polymer concentration at which the wetting transition in the poor solvent system occurs is not affected by the difference in surface–fluid interactions; however, a threshold value of surface–fluid interaction is needed to observe the wetting transition. We also find that with good solvent, increasing the chain length or the difference in the surface–polymer interaction relative to the surface–solvent interaction increases the surface coverage of polymer segments and independent chains for all surface curvatures. Finally, we demonstrate that the polymer segmental adsorption times are heavily influenced only by the surface–fluid interactions, although polymers desorb more quickly from highly curved surfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

The maintenance of coherent vortex topology by Lagrangian chaos in drift-Rossby wave turbulence

Here, this work introduces the “potential vorticity bucket brigade,” a mechanism for explaining the resilience of vortex structures in magnetically confined fusion plasmas and geophysical flows. Drawing parallels with zonal jet formation, we show how inhomogeneous patterns of mixing can reinforce, rather than destroy non-zonal flow structure. We accomplish this through an exact stochastic Lagrangian representation of vorticity transport, together with a near-integrability property, which relates coherent flow topology to fluid relabeling symmetries. We demonstrate these ideas in the context of gradient-driven magnetized plasma turbulence, though the tools we develop here are model-agnostic and applicable beyond the system studied here.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Improved first-principles equation-of-state table of deuterium for high-energy-density applications

Here, we present a first-principles equation-of-state (EOS) table of deuterium aimed at improving the previously established first-principles equation-of-state table (FPEOS). The EOS table presented here, referred to as iFPEOS, introduces (1) a universal density functional theory (DFT) treatment of all density and temperature conditions, (2) a fully consistent treatment of exchange-correlation (XC) thermal effects across the entire range of temperatures covered, and (3) quantum treatment of ions. Based on ab initio molecular dynamics driven by thermal density functional theory, iFPEOS includes density points in the range 1×10 –3 $\leqslant$ ρ $\leqslant$ 1.6×10 3 g/cm 3 and temperature points in the range 800 K $\leqslant$ T $\leqslant$ 256 MK, thus covering the challenging warm dense matter (WDM) regime. For an improved description of the electronic structure, iFPEOS employs an advanced free-energy XC density functional with explicit temperature dependence, which is at the metageneralized gradient approximation level of DFT. We use the latest orbital-free free-energy density functional for the high-temperature regime where it shows excellent agreement with standard Mermin-Kohn-Sham DFT. For quantum treatment of ions we use path-integral molecular dynamics in order to take into account nuclear quantum effects. Results are compared to other EOS models and most recent experimental measurements of deuterium properties such as the molecular-toatomic fluid transition, the principal and reshock Hugoniot, and sound speed. We find that iFPEOS provides an improved agreement with experimental data compared to other first-principles EOS models in the WDM regime for pressures up to 200 GPa and temperatures up to 60 000 K. For higher pressures and temperatures, however, iFPEOS is in agreement with other models in predicting lower compressibility and higher sound speed along the Hugoniot, compared to experiment.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Altering the Supply of Shielding Gases to Fabricate Distinct Geometry in GMA Additive Manufacturing

Wire arc additive manufacturing (WAAM) is the process by which large, metallic structures are built, layer-by-layer, using a welding arc to melt wire feedstock. In this process, the proper selection of the shielding gas plays a vital role in the achievement of structurally acceptable part geometries and quality surface finishes. In this study, the authors used either a ternary mix (He, Ar and CO 2 ) or a binary mix (Ar and CO 2 ) of shielding gases to deposit wall geometries using an open loop-controlled WAAM system developed at Oak Ridge National Laboratory’s Manufacturing Demonstration Facility. The binary blend produced a wider and shorter geometry, while the ternary blend resulted in a narrower build that was more equivalent to the CAD geometry. The data indicated that the binary blend provided a higher oxygen concentration in the weld as compared to that of the ternary blend. The results imply that the arc characteristics and heat input had a significantly higher impact on the weld penetration than the surface tension effect of surface active elements. This was further verified by developing and applying a high-fidelity computational fluid dynamics (CFD) model of the thermophysical properties of gas mixtures. The results from the model showed that, while the influence of increased oxygen concentration on the surface tension for the binary blend led to a deeper penetration, the ternary blend gave rise to heat flux to the workpiece.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Unveiling stimulation fluid-driven alterations in shale pore architecture through combined interpretation of TD-NMR and multi-component gas adsorption

The hydraulic fracturing stimulation process can alter petrophysical and flow properties of the shale matrix in unconventional reservoirs. These alterations can result from interactions with native and exogenous fluids, and can be detrimental to reservoir productivity. Different experimental procedures have been proposed to study reactive processes and thereby understand the aforementioned interactions. Most published works do not consider the rock initial saturation with formation fluid, or the effect of organic matter (OM). To gain insights into these effects, two reactive experimental sets, differing in experimental conditions, were conducted. In the first set, at 125°C and 45 MPa, a stimulation fluid surrogate was put in contact with Baxter Shale samples, previously saturated and equilibrated with synthetic formation fluid. A baseline consisted of exposure to formation fluid exclusively. In the second set, at 0.08 MPa and 25°C, contact with stimulation fluid took place as in the first set. Two additional assays in this second set either skipped the initial formation fluid saturation or removed the OM, respectively. Petrophysical properties analyses, focused on the pore architecture, relied on the combined interpretation of gas adsorption and Time-Domain Nuclear Magnetic Resonance (TD-NMR). Results show that the presence of the formation fluid significantly restricts pore space accessibility to the stimulation fluid and mitigates the pore-architecture alteration to the macro-pore region. Mineral dissolution and precipitation dominate over surface or wettability alteration. Next, results suggest that the OM restricts accessibility to some pores. Ultimately, the equilibration process with synthetic formation fluid drives mainly surface alteration, unhindered by OM.

58 GEOSCIENCES↗
DOE OSTI2020

Fast Computational Algorithms for Partial Differential Equations and Uncertainty Quantifications

This project concerned the construction, testing and analysis of computational algorithms for solving parameterized and stochastic partial differential equations. The study and understanding of equations of this type is of fundamental importance in numerous engineering and scientific applications. Examples include simulation of plasma dynamics in models of electric propulsion and nuclear fusion, simulation of multiphase flows, such as the flow of water, gas and oil in reservoirs, and structural analysis of the dependence of structures on materials. Parametrization is used in such settings when properties of the models such as viscosity of fluids or electric resistivity of materials are not precisely understood and instead are treated as random variables. The resulting solutions are themselves random, and having such solutions will enable engineers to use probabilistic methods to assess the likelihood of events, for example, whether a pollutant in a liquid will exceed a limit, and to use such analyses to develop ways to ensure positive outcomes. Construction of accurate (high resolution) computational solutions is expensive, requiring significant computer time and computational resources, and there is need to reduce computational cost to make simulation useful and effective. The aim of the project was to construct algorithms to efficiently compute surrogate solutions to parameterized problems to allow for efficient and accurate simulation. The technical approach used focused on two related strategies, based on rank-reduction methods and reduced-order models. These methods construct surrogate solutions of parameter-dependent models by projection or interpolation into low-dimensional approximation spaces. Cost savings are achieved if the low-dimensional spaces can be identified and constructed efficiently and if the resulting low-dimensional algebraic systems can be solved cheaply. Accomplishments include: Theoretical and empirical demonstration of the effectiveness of fast multigrid solution strategies for computing low-rank representations of parameter-dependent solutions to discrete partial differential equations, including the first proof establishing so-called textbook convergence properties for low-rank methods. Development of efficient solution algorithms for solving nonlinear parameter-dependent partial differential equations used in models of fluid dynamics. Developent of efficient algorithms for low-rank representation of solutions of time-dependent simulations of fluid dynamics using multi-dimensional tensor representations of solutions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

On the expansion of non-ideal copper plasma into vacuum

The expansion of non-ideal copper plasma into vacuum is analyzed for the conditions typical for explosive electron emission in vacuum arcs. The computational model solves the Euler equations with an equation of state (EoS) for weakly non-ideal plasma, taking into account the ionization energy correction due to electron–ion Coulomb coupling. We have ascertained that the EoS has insignificant influence on the plasma expansion while the plasma properties and composition change drastically. Based on our simulation results, we discuss the validity of the “frozen” state theory often used in the vacuum arc plasma diagnostics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Particle collisionality in scaled kinetic plasma simulations

Kinetic plasma processes, such as magnetic reconnection, collisionless shocks, and turbulence, are fundamental to the dynamics of astrophysical and laboratory plasmas. Simulating these processes often requires particle-in-cell (PIC) methods, but the computational cost of fully kinetic simulations can necessitate the use of artificial parameters, such as a reduced speed of light and ion-to-electron mass ratio, to decrease expense. While these approximations can preserve overall dynamics under specific conditions, they introduce nontrivial impacts on particle collisionality that are not yet well understood. In this work, we develop a method to scale particle collisionality in simulations employing an artificial speed of light and/or an artificial ion-to-electron mass ratio. By introducing species-dependent scaling factors, we independently adjust inter- and intra-species collision rates to better replicate the collisional properties of the physical system. Our approach maintains the fidelity of electron and ion transport properties while preserving critical relaxation rates, such as energy exchange timescales, within the limits of weakly collisional plasma theory. Furthermore, we demonstrate the accuracy of this scaling method through benchmarking tests against theoretical relaxation rates and connecting to fluid theory, highlighting its ability to retain key transport properties. Existing collisional PIC implementations can be easily modified to include this scaling, which will enable deeper insights into the behavior of marginally collisional plasmas across various contexts.

Totorica, S. R. [Princeton Univ., NJ (United State↗
DOE OSTI2023

Design of a novel carbon/carbon composite microvascular solar receiver

Solar thermal power tower systems are the primary technology being proposed for solar electricity from thermal energy. Operational limits on these towers are often driven by mechanical properties under significant thermal loads, particularly at the receiver where incoming flux is converted to thermal energy. While the solar receiver’s efficiency is largely driven by its optical properties, thermomechanical stresses on the receiver limits the operational envelope. One pathway to higher efficiency is greater allowable solar fluxes on the receiver but novel materials are required. The present study uses computational fluid dynamics to describe a parametric design space for a microvascular carbon/carbon composite solar receiver as a new material option for high flux solar receivers. Simulations are conducted for different microvascular geometries considering the role of material properties and heat transfer fluids, for the impact on thermal efficiency, and allowable strain. Results show that microscale receiver modules made of the proposed carbon/carbon composite could achieve thermal efficiencies over 90% and full-scale receivers can achieve up to 85% thermal efficiency for the design explored considering realistic strain limits, flux levels, and material properties. These values are highly dependent on the heat transfer fluid pairing, the through plane thermal conductivity of the carbon/carbon composite, the path architecture of the microscale receiver, and the incident solar flux profiles.

14 SOLAR ENERGY↗
DOE OSTI2022

Carbon nanofibers (CNFs) dispersed in ultra-high performance concrete (UHPC): Mechanical property, workability and permeability investigation

This paper presents experimental data on the effect of carbon nano-fiber (CNF) dispersion on mechanical behavior, workability, and permeability of ultra-high-performance concrete containing CNF (UHPC-CNF). The addition of CNFs in concrete has been shown to provide improved performance. However, an inhomogeneous distribution of CNFs in the cement matrix can result in no impact or decreased mechanical performance. Due to the van der Waal's forces and hydrophobic surface properties of the CNFs, good dispersion in mix fluids and cement paste is challenging. Experimental studies of UHPC-CNF with different dispersion methods are provided. Further mixing with optimized UHPC paste allowed for the investigation of the optimal dosage of CNFs, impact on porosity, compressive strength, flexural strength, hydration rate, and slump. Scanning electron microscopy (SEM) analysis visually revealed the effect of dispersion. Our results indicate that shear mixing and subsequent ultrasonic dispersion with chemical surfactants can provide a well-dispersion liquid admixture of CNFs resulting in high mechanical performance of UHPC-CNFs composites. The water permeability and chloride resistance of optimized UHPC-CNFs composites were further evaluated with the wicking test and ponding test to reveal improved performance for these properties as well.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Imaging viscous flow of the Dirac fluid in graphene

The electron–hole plasma in charge-neutral graphene is predicted to realize a quantum critical system in which electrical transport features a universal hydrodynamic description, even at room temperature. This quantum critical ‘Dirac fluid’ is expected to have a shear viscosity close to a minimum bound, with an interparticle scattering rate saturating1 at the Planckian time, the shortest possible timescale for particles to relax. Although electrical transport measurements at finite carrier density are consistent with hydrodynamic electron flow in graphene a clear demonstration of viscous flow at the charge-neutrality point remains elusive. In this work, we directly image viscous Dirac fluid flow in graphene at room temperature by measuring the associated stray magnetic field. Nanoscale magnetic imaging is performed using quantum spin magnetometers realized with nitrogen vacancy centres in diamond. Scanning single-spin and wide-field magnetometry reveal a parabolic Poiseuille profile for electron flow in a high-mobility graphene channel near the charge-neutrality point, establishing the viscous transport of the Dirac fluid. This measurement is in contrast to the conventional uniform flow profile imaged in a metallic conductor and also in a low-mobility graphene channel. Furthermore, via combined imaging and transport measurements, we obtain viscosity and scattering rates, and observe that these quantities are comparable to the universal values expected at quantum criticality. This finding establishes a nearly ideal electron fluid in charge-neutral, high-mobility graphene at room temperature4. Our results will enable the study of hydrodynamic transport in quantum critical fluids relevant to strongly correlated electrons in high-temperature superconductors9. This work also highlights the capability of quantum spin magnetometers to probe correlated electronic phenomena at the nanoscale.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Development of an ERT‐Based Framework for Bentonite Buffers Monitoring From Laboratory Tests: 2. Quantitative Moisture Dynamics Estimation Model

Abstract The long‐term containment of high‐level radioactive waste in geological disposal repositories relies on Engineered Barrier Systems (EBS), with bentonite clay emerging as a candidate material due to its unique properties. Understanding moisture dynamics within bentonite buffers is crucial for EBS performance, as it directly influences the material's swelling capacity, thermal and hydraulic conductivity, mechanical properties, and long‐term evolution under complex thermal‐hydrological‐mechanical (THM) processes. This study develops an advanced Electrical Resistivity Tomography (ERT)‐based framework to quantitatively monitor moisture dynamics under THM conditions. Our framework extends the Waxman‐Smits model to incorporate the coupled effects of temperature, water content, fluid chemistry, and mechanical changes on bentonite's electrical properties. Utilizing HotBENT‐Lab data from our companion paper, which includes electrical conductivity, CT density, and thermocouple measurements, this study offers a novel methodological framework bridging different scales of the model. Our results show that the extended model can estimate water content from ERT data, capturing spatial and temporal variations in moisture distribution within bentonite columns. However, the model tends to overestimate water content compared to CT density‐derived measurements. We address this discrepancy by incorporating a simplified swelling effect model, which improves agreement between ERT and CT density‐based water content estimates. We also discuss model limitations, including simplified treatment of swelling and micropore effects, and propose a conceptual framework for transitioning from laboratory to field applications, addressing challenges such as parameter scalability, field validation methods, and integration of diverse data sources. This ERT‐based framework can potentially advance real‐world moisture monitoring of bentonite‐based EBS in nuclear waste repositories. Plain Language Summary Safely containing high‐level radioactive waste depends on barriers made from materials like bentonite clay, which is effective because it swells and seals in the waste. To ensure these barriers work well over time, it's important to understand how moisture moves through the clay. Our study developed a new method using ERT to monitor moisture levels in bentonite under conditions that mimic those in actual storage sites, including changes in temperature, water content, and mechanical stress. This study improved an existing model to better account for how these factors affect the clay, allowing us to create more accurate moisture maps. Initially, the proposed model overestimated the amount of water in the clay, but its accuracy was improved by factoring in how the clay swells when wet. This study also identified some limitations of the model and suggested ways to adapt it for use in real‐world waste storage sites. This new approach could lead to better monitoring and safety checks for nuclear waste storage systems, helping to ensure long‐term containment. Key Points This work develops an ERT‐based framework extending the Waxman‐Smits model to monitor bentonite moisture dynamics during coupled THM processes The extended model accurately estimates water content from Electrical Resistivity Tomography data, incorporating swelling effects to improve precision This work proposes a conceptual framework for transitioning from laboratory to field applications, advancing EBS monitoring in nuclear waste repositories

Chen, Hang↗
DOE OSTI2022

Multi-fidelity modeling to predict the rheological properties of a suspension of fibers using neural networks and Gaussian processes

Unveiling the rheological properties of fiber suspensions is of paramount interest to many industrial applications. There are multiple factors, such as fiber aspect ratio and volume fraction, that play a significant role in altering the rheological behavior of suspensions. Three-dimensional (3D) numerical simulations of coupled differential equations of the suspension of fibers are computationally expensive and time-consuming. Machine learning algorithms can be trained on the available data and make predictions for the cases where no numerical data are available. However, some widely used machine learning surrogates, such as neural networks, require a relatively large training dataset to produce accurate predictions. Multi-fidelity models, which combine high-fidelity data from numerical simulations and less expensive lower fidelity data from resources such as simplified constitutive equations, can pave the way for more accurate predictions. Here, we focus on neural networks and the Gaussian processes with two levels of fidelity, i.e., high and low fidelity networks, to predict the steady-state rheological properties, and compare them to the single-fidelity network. High-fidelity data are obtained from direct numerical simulations based on an immersed boundary method to couple the fluid and solid motion. The low-fidelity data are produced by using constitutive equations. Multiple neural networks and the Gaussian process structures are used for the hyperparameter tuning purpose. Results indicate that with the best choice of hyperparameters, both the multi-fidelity Gaussian processes and neural networks are capable of making predictions with a high level of accuracy with neural networks demonstrating marginally better performance.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Atomic dynamics in fluids: Normal mode analysis revisited

Developing microscopic understanding of the thermal properties of liquids is challenging due to their strong dynamic disorder, which prevents characterization of the atomic degrees of freedom. There have been significant research interests in the past few decades to extend the normal mode analysis for solids to instantaneous structures of liquids. However, the nature of normal modes that arise from these unstable structures is still elusive. Here, in this paper, we explore the instantaneous eigenmodes of dynamical matrices of various Lennard-Jones argon liquid and gas systems at high temperatures and show that the normal modes can be interpreted as an interpolation of T →∞ (gas) and T=0 (solid) mode descriptions. We find that normal modes become increasingly collisional and translational, recovering atomistic gaslike behavior rather than vibrational with increase in temperature, suggesting that normal modes in liquids may be described by both solidlike and gaslike modes.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

A quantum liquid of magnetic octupoles on the pyrochlore lattice

Spin liquids are highly correlated yet disordered states formed by the entanglement of magnetic dipoles. Theories define such states using gauge fields and deconfined quasiparticle excitations that emerge from a local constraint governing the ground state of a frustrated magnet. For example, the ‘2-in–2-out’ ice rule for dipole moments on a tetrahedron can lead to a quantum spin ice in rare-earth pyrochlores. However, $f$-electron ions often carry multipole degrees of freedom of higher rank than dipoles, leading to intriguing behaviours and ‘hidden’ orders. In this paper we show that the correlated ground state of a Ce 3+ -based pyrochlore, Ce 2 Sn 2 O 7 , is a quantum liquid of magnetic octupoles. Our neutron scattering results are consistent with a fluid-like state where degrees of freedom have a more complex magnetization density than that of magnetic dipoles. The nature and strength of the octupole–octupole couplings, together with the existence of a continuum of excitations attributed to spinons, provides further evidence for a quantum ice of octupoles governed by a ‘2-plus–2-minus’ rule. Our work identifies Ce 2 Sn 2 O 7 as a unique example of frustrated multipoles forming a ‘hidden’ topological order, thus generalizing observations on quantum spin liquids to multipolar phases that can support novel types of emergent fields and excitations.

36 MATERIALS SCIENCE↗