Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “model order reduction”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 217 records · Page 12

Sulfurized Polyacrylonitrile for High-Performance Lithium–Sulfur Batteries: In-Depth Computational Approach Revealing Multiple Sulfur’s Reduction Pathways and Hidden Li + Storage Mechanisms for Extra Discharge Capacity

Like no other sulfur host material, polyacrylonitrile-derived sulfurized carbon (SPAN) promises improved electrochemical performance for lithium–sulfur batteries, based on its compatibility with carbonate solvents and ability to prevent self-discharge and shuttle effect. However, a complete understanding of the SPAN’s lithiation mechanism is still missing because its structural features vary widely with synthesis conditions, and its electrochemical performance deviates from elemental sulfur. This study continues our research on the elucidation of the SPAN’s structural characteristics and lithiation mechanisms via computational approaches. Here, our models reproduce most experimental data regarding carbon’s graphitization level and conjugated ordering, sulfur–carbon covalent bonding, sulfur loading, and elemental composition. Our simulations emulate the discharge voltage observed in experiments for the first discharge, which reveals that sulfur follows multiple reduction pathways based on its interaction with the carbon backbone. Sulfur reduction takes place above 1.0 V vs Li/Li + mostly in the SPAN-like material, with no long-chain lithium polysulfide formation. Below 1.0 V vs Li/Li + , the backbone’s electrochemical activity occurs via multiple C–Li and N–Li interactions, mostly with edge carbon atoms and pyridinic nitrogen. Moreover, we identify Li + binding sites throughout the graphitized backbone that might lead to prohibited energy costs for Li + deintercalation, which may explain the irreversible capacity loss between the first and second discharges. This work improves understanding of lithiation mechanisms in sulfurized carbon, which is useful for rationally designing SPAN synthesis pathways tailored to increase sulfur loading and enhanced electrochemical performance.

25 ENERGY STORAGE↗

Multiple magnetic orders in LaFeAs 1-x P x O uncover universality of iron-pnictide superconductors

The iron-pnictide superconductors have generated tremendous excitement as the competition between magnetism and superconductivity has allowed unique in-roads towards elucidating a microscopic theory of unconventional high-temperature superconductivity. In addition to the stripe spin density wave ($C^a_{2M}$) phase observed in the parent compounds of all iron-pnictide superconductors, two novel magnetic orders have recently been discovered in different parent structures: an out-of-plane collinear double-Q ($C^c_{4M}$) structure in the hole-doped (Ca, Sr, Ba) 1-x (Na) x Fe 2 As 2 and Ba 1-x K x Fe 2 As 2 families, and a spin vortex crystal “hedgehog” ($C^{ab}_{4M}$) structure in the CaKFe 4 As 4 family. Using neutron diffraction, we demonstrate that LaFeAs 1-x P x O contains all three magnetic orders within a single-phase diagram as a function of substitution, all of which compete strongly with superconductivity. Our experimental observations combined with theoretical modeling demonstrate how the reduction in electronic correlations by chemical substitution results in larger Fermi surfaces and the sequential stabilization of multiple magnetic anisotropies. Our work presents a unified narrative for the competing magnetic and superconducting phases observed in various iron-pnictide systems with different crystal structures and chemistry.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Variations in lithium vapor cave performance predictions due to radial transport and recycling assumptions

The lithium vapor cave is a detached divertor design that uses a single private flux region baffle to contain a dense cloud of lithium vapor to dissipate heat flux. Plasma flows are created via fuel gas puffing in order to minimize lithium contamination of the main plasma. Significant modeling using the 2D edge code SOLPS-ITER has already been performed, predicting that sufficient target heat flux reductions (q$^{max}_{Target}$ MW m −2 ) with ( $n$ Li /$n$ e ) LCFS < 0.05 is possible in a case with 90 MW m −2 unmitigated heat flux in NSTX-U. Low heat flux and low upstream concentration was found with a variety of combinations of divertor geometries, target recycling coefficients, upstream plasma parameters, lithium evaporation locations and deuterium fueling locations, with variations in performance found for each design choice. However, the most universal uncertainty of SOLPS-ITER simulations has until now remained unaddressed systematically, namely the cross-field anomalous particle and heat diffusivities. This article aims to bound the uncertainty in lithium concentration prediction as a result of the assumed deuterium cross-field transport and recycling. For the simulations presented here, a factor of 2.1 increase in the upstream lithium density prediction across a factor of four decrease to the assumed deuterium radial particle diffusivity is found. This result is compared across different assumed deuterium recycling coefficients, known to reduce with lithium injection. Upstream lithium density is found to vary by a factor of 2.4 across a feasible range of recycling coefficients at similar $n$$^{OMP,sep}_{e}$.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Magnetism and its coexistence with superconductivity in CaK(Fe 0.949 Ni 0.051 ) 4 As 4 : Muon spin rotation/relaxation studies

Here, the magnetic response of Ca K ( Fe 0.949 Ni 0.051 ) 4 As 4 was investigated by means of the muon spin rotation/relaxation. The long-range commensurate magnetic order sets in below the Néel temperature T N = 50.0 ( 5 ) K. The density-functional theory calculations have identified three possible muon stopping sites. The experimental data were found to be consistent with only one type of magnetic structure, namely, the long-range magnetic spin-vortex-crystal order with the hedgehog motif within the a b plane and the antiferromagnetic stacking along the c direction. The value of the ordered magnetic moment at T ≈ 3 K was estimated to be m Fe = 0.38 ( 11 ) μ B ( μ B is the Bohr magneton). A microscopic coexistence of magnetic and superconducting phases accompanied by a reduction of the magnetic order parameter below the superconducting transition temperature T c ≃ 9 K is observed. Comparison with 11, 122, and 1144 families of Fe-based pnictides points to existence of correlation between the reduction of the magnetic order parameter at T → 0 and the ratio of the transition temperatures T c / T N . Such correlations were found to be described by Machida's model for coexistence of itinerant spin-density-wave magnetism and superconductivity [K. Machida, J. Phys. Soc. Jpn. 50 , 2195 (1981) ; S. L. Bud'ko et al. , Phys. Rev. B 98 , 144520 (2018) ].

36 MATERIALS SCIENCE↗

A reduced-order modeling of a tubular solar reactor for long duration thermochemical energy storage

The storage of solar energy in a solid form, referred to as a “solar fuel”, can be achieved through a process known as endothermic solar thermochemistry. This process transforms the absorbed solar energy into a stable and retrievable form that can be stored for extended periods of time. This paper presents a low–order heat transfer model of a counter–current tubular falling bed reactor designed to produce thermally reduced magnesium manganese oxide pellets for long duration thermochemical energy storage. The energy required for the endothermic reduction was supplied by concentrated solar energy or renewable electricity via indirect heating of the gas and solid reactants flowing in a ceramic tube. The counter-current gas flow enhances the mixing of the solid particles with the heat recuperation zone, allowing the gas and particles to enter and exit the tubular reactor close to room temperature. Further, the reactor was vertically oriented and was heated circumferentially by an adjustable level heat flux along a finite segment of its length. The temperature distribution of the reactor in response to transient changes along the tube was modeled by considering conduction, convection, and radiation heat transfer. Governing equations for the heat transfer model were solved by discretizing the reactor tube into a finite number of control volumes and using an energy balance for the heat exchange between the reactor wall, gas, and particles within the control volume. The energy absorbed during this endothermic reaction was modeled numerically by fitting the data of the chemical conversion rate with the corresponding temperature of particles in the heating zone. The numerical model has been experimentally validated using a reactor prototype made of a 121.92 cm alumina tube heated by a 7kW electric tube–furnace. The alumina tube receives magnesium manganese oxide pellets of 3.66±0.516 mm in diameter from the top, and a counter–current gas flow from the bottom. The reactor wall temperature was monitored by six thermocouples installed along the reactor tube length. The experimental procedure was numerically simulated, and the temperature variation along the reactor tube was compared with a matrix of experimental runs for a range of particles mass flowrates (0.75–1.25g/s) and corresponding gas flowrates (36–65 SLPM). The reactor system was heated gradually from room temperature to a steady state temperature of 1673K, and then cooled down to room temperature. The heating and cooling processes were simulated, and the numerical and experimental results were compared throughout processes. The numerical model showed similar trends to the experimental results, with an error of 0.69 to 7.9% for the particle inlet and 0.7 to 7.9% for the gas inlet during steady-state operation. The proposed numerical model can be implemented as a simplified physical model to design a feedback control system to regulate reactor temperature.

14 SOLAR ENERGY↗

Gate-free state preparation for fast variational quantum eigensolver simulations

Abstract The variational quantum eigensolver is currently the flagship algorithm for solving electronic structure problems on near-term quantum computers. The algorithm involves implementing a sequence of parameterized gates on quantum hardware to generate a target quantum state, and then measuring the molecular energy. Due to finite coherence times and gate errors, the number of gates that can be implemented remains limited. In this work, we propose an alternative algorithm where device-level pulse shapes are variationally optimized for the state preparation rather than using an abstract-level quantum circuit. In doing so, the coherence time required for the state preparation is drastically reduced. We numerically demonstrate this by directly optimizing pulse shapes which accurately model the dissociation of H 2 and HeH + , and we compute the ground state energy for LiH with four transmons where we see reductions in state preparation times of roughly three orders of magnitude compared to gate-based strategies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Accelerating computational modeling and design of high-entropy alloys

High-entropy alloys, with N elements and compositions {$c_{ν = 1,N}$} in competing crystal structures, have large design spaces for unique chemical and mechanical properties. In this work, to enable computational design, we use a metaheuristic hybrid Cuckoo search (CS) to construct alloy configurational models on the fly that have targeted atomic site and pair probabilities on arbitrary crystal lattices, given by supercell random approximates (SCRAPs) with S sites. Our Hybrid CS permits efficient global solutions for large, discrete combinatorial optimization that scale linearly in a number of parallel processors, and linearly in sites S for SCRAPs. For example, a four-element, 128-site SCRAP is found in seconds—a more than 13,000-fold reduction over current strategies. Our method thus enables computational alloy design that is currently impractical. We qualify the models and showcase application to real alloys with targeted atomic short-range order. Being problem-agnostic, our Hybrid CS offers potential applications in diverse fields.

36 MATERIALS SCIENCE↗

Fission with Exotic Nuclei (Abbreviated Report)

Nuclear fission is a key mechanism involved in the synthesis of heavy elements in the Cosmos and is the primary explanation for the stability of superheavy elements. Nevertheless, our knowledge of fission remains extremely fragmented. Most experiments have been conducted only on a tiny number of stable actinide nuclei and are often incomplete, leading to gaps in our basic understanding of the process. For many radioactive isotopes, basic fission data such as the charge or mass distribution of the fragments is unknown. These gaps cannot always be filled by simulation alone. Common fission models contain too many free parameters and lack predictive power. In contrast, the fundamental theory of fission under development at LLNL is much more predictive, but its current computational cost is too high to be used extensively for data evaluations. A unique window of opportunity to resolve these limitations has recently opened: the U.S. nuclear science community is ramping up major experimental programs at the Facility for Rare Isotope Beams (FRIB, the DOE flagship facility in low-energy nuclear science), and techniques from machine learning have shown great potential to simplify the use of a fundamental, quantum-mechanical theory of fission. This project has two components. On the experimental side, we acquired and deployed at the HIGS facility a new dual Frisch-Grid ionization chamber to measure correlated fragment-mass, kinetic energy, and angular distributions of fission fragments from induced fission. This new device was used to perform measurements of charge, mass and total kinetic energy of fission fragments in the photofission of 238 U and eight gamma-ray beam energies between 6.2 and 13 MeV, which allowed extracting high-precision independent yields for this reaction. The device was also used to perform measurements of the same quantities in the neutron-induced fission of 234 U with monoenergetic beams of energy between 5 and 8 MeV. In parallel, we collaborated with a team at Commissariat à l’énergie atomique et aux énergies alternatives (CEA) to perform a series of measurements of fission yields in inverse kinematics for the two isotopes of 236 U and 240 Pu. The experiment took place at the Grand Accélérateur National d’Ions Lourds in France in June 2023. The deployment of the VAMOS spectrometer with a new array called PISTA allowed determining the excitation energy of the fissioning system within 1 Mega-electronvolts. The second component of the project involved using deep neural networks to build fast and reliable emulators of our current fission models. In an invited paper published in Frontier in Physics, we showed that autoencoders could successfully compress nuclear wavefunctions in nuclear density functional theory. We achieved a dimensionality reduction of the order of two orders of magnitude while keeping the error in the total energy to less than 0.01%. In a second paper submitted to Physical Review Letters in June 2023 with our collaborators at CEA, we showed that variational autoencoders can learn the collective degrees of freedom driving the fission process.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Southeast Regional CO 2 Utilization and Storage Acceleration Partnership (SECARB-USA): Preliminary Regional Assessment of Potential Storage Complexes, Including Capacities and Costs, Based on Application of NRAP and SCO2T (Deliverable 3.3) Storage Complexes

The Recipient will assist with the field validation of one or more risk assessment toolsets through: 1) collaborative research; 2) sharing of relevant datasets, information, and technical insights from field efforts; and 3) other modeling and simulation toolsets as they are developed. Collaborative research could include, but is not limited to: 1) demonstrating use of field data for improved leakage pathway characterization, uncertainty reduction, and risk management and uncertainty workflows; 2) testing and validation of a specific National Risk Assessment Partnership (NRAP) tool using site specific data; and 3) improved modeling or reduced-order modeling of geophysical monitoring.

42 ENGINEERING↗

Interpretable Deep Learning for Advancing Field-Enhanced Catalysis

This DOE Early Career project developed a physics-informed, interpretable AI-and-modeling framework to understand and exploit electric-field effects in heterogeneous catalysis, with ammonia cracking and synthesis as a representative pathway. The team built and validated methods to map local electric fields on metal surfaces and nanoparticles, showing that low-coordination features (tips/edges/corners) can concentrate fields by several-fold relative to flat facets. Using DFT-generated datasets, the project created physics-guided machine learning models that rapidly predict local electric fields and field-dependent adsorption energetics with near-DFT accuracy while reducing computational cost by orders of magnitude. These predictions were integrated with microkinetic modeling to quantify how field-dipole interactions reshape reaction energetics and mechanisms, enabling large increases in predicted catalytic rates and substantial reductions in operating temperature under favorable field conditions. To accelerate discovery of earth-abundant catalysts, the project combined interpretable ML screening (with electronic-structure descriptors identified as key drivers) with a generative inverse-design workflow based on diffusion models and physics constraints. The resulting closed-loop approach, linking simulation, mechanistic modeling, and AI, provides reusable tools and datasets for designing catalysts and operating conditions in field-enhanced catalysis, with broad relevance to electrostatic catalysis, plasma catalysis, electrocatalysis, and other energy-related chemical transformations.

30 DIRECT ENERGY CONVERSION↗

Source term analysis of FeCrAl accident tolerant fuel using MELCOR

It has been established that incremental improvements in beyond design basis accident performance can be achieved through accident tolerant fuel (ATF). However, they have the potential to recover margin with respect to conventional fuel and therefore enhance plant economics through uprate or cycle length increase. To realize this potential, it is necessary to quantify the reduction in source term due to use of ATF, and correspondingly how this is affected by increasing the cycle length and/or burnup. This requires development of a risk informed analysis methodology for ATF under high burnup conditions, which is being developed within LWRS. To this end, a MELCOR simulation of FeCrAl ATF in a recovered Large Break LOCA (LBLOCA) scenario has been developed, using a model based on the Zion Pressurized Water Reactor (PWR). The new user defined material capability, along with the inclusion of detailed neutronics- and depletion-derived parameters such as core power distribution, decay heat behavior, and fission product inventories, allows a more detailed simulation of FeCrAl clad material properties and behavior than has previously been possible using MELCOR. These detailed FeCrAl results were compared with a zircaloy clad model to investigate the differences between the two clad types and quantify the benefits of FeCrAl ATF with an 18-month cycle. Next, the fuel cycle with ATF was extended to 24 months, to determine whether any additional safety margin provided by FeCrAl ATF could be leveraged to implement high burnup FeCrAl-clad fuel while retaining the same operating and safety limits as current zircaloy-clad fuel. For the particular scenario analyzed, the delay to fuel failure from using ATF was of the same order as the LOCA recovery time, and hence significant in reducing fission product release, with the 24-month FeCrAl core performing better than the 18-month zircaloy core. It is noted that for other transients, the reduction in release due to using FeCrAl may be less significant. Furthermore, the material model developed here can be used in such further studies in support of determining the overall source term.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Development of a High-Pressure Fuel Injection System for Use with Propane-DME

Paper details the design approach and performance of a high-pressure common rail fuel injection system used with Propane-DME mixtures targeting high injection pressures on a light duty 2.2L inline-4 compression ignition engine. The study estimates the bulk modulus of elasticity based on the hardware geometry and operating pressures to assess the compressibility of Propane and DME across a range of pressures typical of the LD engine application. The compressibility factor ranges from 500 to 3000 bar, significantly lower than the theoretical values for the conditions tested. The high-pressure pump performance is optimized via the implementation of an inlet metering valve operated on a crank-angle open/close sequence to control pressure at the common rail. The application of a model-based controller and the use of high-speed sampling of rail pressure indicate that pressure at the rail can be attained with the pump metering valve, and without use of the pressure relieve valve present in the rail. Results show a significant reduction on pumping work parasitics and of fuel heating, on the order of 40°C, at typical working conditions with the proposed approach. Injector rates of injection with Propane-DME are very similar to those of Diesel. Paper compares bench data of rates of injection versus simulation predictions across operating pressures of 200 to 1000bar and from injection commands spanning 0.20 to 2.0ms. Furthermore, the accuracy of the model predictions are attributed in part by to the updated fuel compressibility modulus descriptions attained during the testing.

42 ENGINEERING↗

A perspective on the redox properties of tetrapyrrole macrocycles

Tetrapyrrole macrocycles serve a multitude of roles in biological systems, including oxygen transport by heme and light harvesting and charge separation by chlorophylls and bacteriochlorophylls. Synthetic tetrapyrroles are utilized in diverse applications ranging from solar-energy conversion to photomedicine. Nevertheless, students beginning tetrapyrrole research, as well as established practitioners, are often puzzled when comparing properties of related tetrapyrroles. Questions arise as to why optical spectra of two tetrapyrroles often shift in wavelength/energy in a direction opposite to that predicted by common chemical intuition based on the size of a π-electron system. Gouterman's four-orbital model provides a framework for understanding these optical properties. Similarly, it can be puzzling as to why the oxidation potentials differ significantly when comparing two related tetrapyrroles, yet the reduction potentials change very little or shift in the opposite direction. In order to understand these redox properties, it must be recognized that structural/electronic alterations affect the four frontier molecular orbitals (HOMO, LUMO, HOMO-1 and LUMO+1) unequally and in many cases the LUMO+1, and not the LUMO, may track the HOMO in energy. This perspective presents a fundamental framework concerning tetrapyrrole electronic properties that should provide a foundation for rational molecular design in tetrapyrrole science.

chlorophyll↗

Forward sensitivity analysis and mode dependent control for closure modeling of Galerkin systems

Model reduction by projection-based approaches is often associated with losing some of the important features that contribute towards the dynamics of the retained scales. As a result, a mismatch occurs between the predicted trajectories of the original system and the truncated one. We put forth a framework to apply a continuous time control signal in the latent space of the reduced order model (ROM) to account for the effect of truncation. We set the control input using parameterized models by following energy transfer principles. Our methodology relies on observing the system behavior in the physical space and using the projection operator to restrict the feedback signal into the latent space. Then, we leverage the forward sensitivity method (FSM) to derive relationships between the feedback and the desired mode-dependent control. We test the performance of the proposed approach using two test cases, corresponding to viscous Burgers and vortex merger problems at high Reynolds number. Results show that the ROM trajectory with the applied FSM control closely matches its target values in both the data-dense and data-sparse regimes.

97 MATHEMATICS AND COMPUTING↗

Exploring the role of 𝑑* hexaquarks on quark deconfinement and hybrid stars

We investigate the impact of the d*( 2380) hexaquark on the equation of state (EOS) of dense matter within hybrid stars (HSs) using the chiral mean-field model (CMF). The hexaquark is included as a new degree of freedom in the hadronic phase, and its influence on the deconfinement transition to quark matter is explored. We reparametrize the CMF model to ensure compatibility with recent astrophysical constraints, including the observation of massive pulsars and gravitational wave events. Our results show that the presence of d* significantly modifies the EOS, leading to a softening at high densities and a consequent reduction in the predicted maximum stellar masses. Furthermore, we examine the possibility of a first-order deconfinement phase transition within the context of the extended stability branch of slow stable HSs (SSHSs). We find that the presence of hexaquarks can delay the deconfinement phase transition and reduce the associated energy density gap, affecting the structure and stability of HSs. Our results suggest that, as the hexaquark appearance tends to destabilize stellar configurations, fine-tuning of model parameters is required to obtain both the presence of hexaquarks and quark deconfinement in these systems. In this scenario, the SSHS branch plays a crucial role in obtaining HSs with hexaquarks that satisfy current astrophysical constraints. Our work provides new insights into the role of exotic particles like d* in dense matter and the complex interplay between hadronic and quark degrees of freedom inside compact stellar objects.

Nuclear astrophysics↗

Investigation of the Structure of Atomically Dispersed NiN x Sites in Ni and N-Doped Carbon Electrocatalysts by 61 Ni Mössbauer Spectroscopy and Simulations

Ni and nitrogen-doped carbons are selective catalysts for CO 2 reduction to CO (CO 2 R), but the hypothesized NiNx active sites are challenging to probe with traditional characterization methods. Here, we synthesize 61 Ni-enriched model catalysts, termed 61 NiPACN, in order to apply 61 Ni Mössbauer spectroscopy using synchrotron radiation ( 61 Ni-SR-MS) to characterize the structure of these atomically dispersed NiNx sites. First, we demonstrate that the CO 2 R results and standard characterization techniques (SEM, PXRD, XPS, XANES, EXAFS) point to the existence of dispersed Ni active sites. Then, 61 Ni-SR-MS reveal significant internal magnetic fields of ~5.4 T, which is characteristic of paramagnetic, high-spin Ni 2+ , in the 61NiPACN samples. Finally, theoretical calculations for a variety of Ni-N x moieties confirm that high-spin Ni 2+ is stable in non-planar, tetrahedrally distorted geometries, which results in calculated isotropic hyperfine coupling that is consistent with 61 Ni-SR-MS measurements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Elastic wave suppression through additively manufactured petal lattice metamaterials

Lattice-core sandwich structure metamaterials are lightweight alternatives to monolithic materials that can present better mechanical, thermal, and energy dampening performance. Manufacturing lattice metamaterials to follow curved surfaces can pose a challenge, as the lattices rely on their geometric orientation to the substrate for their mechanical properties. This work rationally designed a lattice structure where the surface is broken up into “petals” connected to the underlying lattice, which localizes the petals’ impact response. This design opens a pathway for implementation of lattice-core sandwich structures onto complex surface geometries. These petal structures were evaluated for their energy absorption efficiency experimentally by utilizing pressure waves generated with nanosecond lasers and computationally via finite element modeling. The lattice structures exhibited a two-orders-of-magnitude decrease in transmitted pressure compared to their constituent steel at equivalent mass. Furthermore, localizing energy absorption into petal structures provided a 44% reduction in peak load compared to a continuous “single-petal” design.

Sarracino, Alex↗

Emergent Inductance from Chiral Orbital Currents in a Bulk Ferrimagnet

Here, we report the discovery of a new form of inductance in the bulk ferrimagnet Mn 3 ⁢Si 2 ⁢Te 6 , which features strong spin-orbit coupling, large magnetic anisotropy, and pronounced magnetoelastic interactions. Below its Curie temperature (𝑇 𝐶 ≈ 78 K), Mn 3 ⁢Si 2 ⁢Te 6 hosts chiral orbital currents (COC) that circulate within the crystal lattice and give rise to collective electronic behavior [Control of chiral orbital currents in a colossal magnetoresistance material, Nature (London) 611, 467 (2022).]. By applying a magnetic field along the hard 𝑐 axis and driving the system with low-frequency currents, we uncover a giant inductive response up to millhenry scale, originating from first-order reconfigurations of COC domains. These domains act as coherent mesoscopic inductive elements that resist reversal upon current reduction, producing a large electromotive force and sharply increasing voltage. This emergent inductance defies classical models, occurs without superconductivity or engineered nanostructures, and opens a new frontier in orbital-based quantum functionality and device concepts.

complex materials↗