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At least 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Interpreting strain tensor data to characterize and monitor reservoirs for CO2 storage and other applications

Recent advances in instrumentation have made it feasible to measure the transient strain tensor caused by small changes in fluid volume or pressure in the subsurface and this has opened the door to new opportunities for characterization and monitoring. We have deployed strainmeters and then conducted injection well tests in an underlying reservoir at 530m depth. The resulting data indicated that the horizontal strain at shallow strainmeters (30 to 40m depth) was tensile and the vertical strain was compressive. The radial strain was less than the horizontal strain, and the strain rates decreased from 100 nanostrain/day to roughly 10 n/d over a few days. The signal at two strainmeters at shallow depth were consistent, although the magnitude of the horizontal strains were different reflecting the different radial directions from the well. The signal at a deep strainmeter deployed at reservoir depth was much different, with tensile vertical strains and compressive horizontal strains. These data can be interpreted by inverting poroelastic forward models developed using numerical and analytical methods. The average horizontal strain in the caprock resembles the transient pressure in the underlying reservoir and classic type-curve methods from transient well testing can be used for preliminary interpretations of strain data. We have developed closed-form analytical solutions to a pressurized poroelastic inclusion and inhomogeneity in a half-space. This model is fast and can be inverted to estimate reservoir stiffness and geometry. Numerical models developed using finite element methods allow more details of the subsurface to be included in the inversion, but they require much longer run times and this makes inversion cumbersome using standard methods. We have developed an inversion approach that uses a proxy model created using machine learning to do most of the forward calculations. The proxy model is periodically updated and refined using the finite element model to ensure accuracy. This approach significantly reduces the computational requirements and makes it feasible to use Bayesian inversion with large numerical models. We have shown that the strain tensor in the caprock is sensitive to pressure in the reservoir, boundaries in the reservoir, and pressure in the caprock caused by leaks. These results indicate that coupling strain tensor data with inversion has the potential to help evaluate reservoirs during initial characterization, and to monitor them during the CO2 injection and storage process.

Murdoch, Larry↗
DOE OSTI2022

3D simulations of spinlike flames in Co/Al multilayers with enhanced conduction losses

Reactive Co/Al multilayers are uniformly structured materials that may be ignited to produce rapid and localized heating. Prior studies varying the bilayer thickness (i.e., sum of two individual layers of Co and Al) have revealed different types of flame morphologies, including: (a) steady/planar, (b) wavy/periodic, and (c) transverse bands, originating in the flame front. These instabilities resemble the “spin waves” first observed in the early studies of solid combustion (i.e., Ti cylinder in a N 2 atmosphere), and are likewise thought to be due to the balance of heat released by reaction and heat conduction forward into the unreacted multilayer. However, the multilayer geometry and three-dimensional (3D) edge effects are relatively unexplored. In this work, a new diffusion-limited reaction model for Co/Al multilayers was implemented in large, novel 3D finite element analysis (FEA) simulations, in order to study the origins of these spinlike flames. This reaction model builds upon previous work by introducing three new phase-dependent property models for: (1) the diffusion coefficient, (2) anisotropic thermal conductivity tensor, and (3) bulk heat capacity, as well as one additional model for the bilayer-dependent heat of reaction. These novel 3D simulations are the first to predict both steady and unsteady flames in Co/Al multilayers. Moreover, two unsteady modes of flame propagation are identified, which depend on the enhanced conduction losses with slower flames, as well as flame propagation around notched edges. Finally, future work will consider the generality of the current modeling approach and also seek to define a more generalized set of stability criteria for additional multilayer systems.

42 ENGINEERING↗
DOE OSTI2020

Structural modeling and dynamic analysis of condensate storage tanks in nuclear power plants

Condensate storage tanks (CSTs) in nuclear power plants (NPPs) are classified as critical equipment capable of surviving strong shaking in a design basis earthquake to assure the ability to subsequently provide cooling water. Structural modeling and dynamic analysis of CSTs are complicated due to fluid-structure interaction (FSI) and coupling issues, which could have significant effects on seismic response. The capability of a number of approximate models to capture seismic response is investigated using dynamic analysis results from detailed finite element models. Modal analyses and time history analyses are carried out using both 2D and 3D models to predict the dynamic behavior of CSTs as a function of ground motion intensity. Although 2D simplified models can be used to quickly evaluate the dynamic response of CSTs when there is substantial margin to failure, a detailed 3D model is required when it is necessary to examine a limit state associated with the failure mode of the tank. The findings show good agreement between the natural frequencies of convective modes determined from the 2D and 3D CST models. The difference between the frequencies of impulsive modes were found to be equal to or less than 25%.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

MPAS-Seaice (v1.0.0): sea-ice dynamics on unstructured Voronoi meshes

Abstract. We present MPAS-Seaice, a sea-ice model which uses the Model for Prediction Across Scales (MPAS) framework and spherical centroidal Voronoi tessellation (SCVT) unstructured meshes. As well as SCVT meshes, MPAS-Seaice can run on the traditional quadrilateral grids used by sea-ice models such as CICE. The MPAS-Seaice velocity solver uses the elastic–viscous–plastic (EVP) rheology and the variational discretization of the internal stress divergence operator used by CICE, but adapted for the polygonal cells of MPAS meshes, or alternatively an integral (“finite-volume”) formulation of the stress divergence operator. An incremental remapping advection scheme is used for mass and tracer transport. We validate these formulations with idealized test cases, both planar and on the sphere. The variational scheme displays lower errors than the finite-volume formulation for the strain rate operator but higher errors for the stress divergence operator. The variational stress divergence operator displays increased errors around the pentagonal cells of a quasi-uniform mesh, which is ameliorated with an alternate formulation for the operator. MPAS-Seaice shares the sophisticated column physics and biogeochemistry of CICE and when used with quadrilateral meshes can reproduce the results of CICE. We have used global simulations with realistic forcing to validate MPAS-Seaice against similar simulations with CICE and against observations. We find very similar results compared to CICE, with differences explained by minor differences in implementation such as with interpolation between the primary and dual meshes at coastlines. We have assessed the computational performance of the model, which, because it is unstructured, runs with 70 % of the throughput of CICE for a comparison quadrilateral simulation. The SCVT meshes used by MPAS-Seaice allow removal of equatorial model cells and flexibility in domain decomposition, improving model performance. MPAS-Seaice is the current sea-ice component of the Energy Exascale Earth System Model (E3SM).

58 GEOSCIENCES↗
DOE OSTI2021

Characterize traction–separation relation and interfacial imperfections by data-driven machine learning models

Abstract Interfacial mechanical properties are important in composite materials and their applications, including vehicle structures, soft robotics, and aerospace. Determination of traction–separation (T–S) relations at interfaces in composites can lead to evaluations of structural reliability, mechanical robustness, and failures criteria. Accurate measurements on T–S relations remain challenging, since the interface interaction generally happens at microscale. With the emergence of machine learning (ML), data-driven model becomes an efficient method to predict the interfacial behaviors of composite materials and establish their mechanical models. Here, we combine ML, finite element analysis (FEA), and empirical experiments to develop data-driven models that characterize interfacial mechanical properties precisely. Specifically, eXtreme Gradient Boosting (XGBoost) multi-output regressions and classifier models are harnessed to investigate T–S relations and identify the imperfection locations at interface, respectively. The ML models are trained by macroscale force–displacement curves, which can be obtained from FEA and standard mechanical tests. The results show accurate predictions of T–S relations ( R 2 = 0.988) and identification of imperfection locations with 81% accuracy. Our models are experimentally validated by 3D printed double cantilever beam specimens from different materials. Furthermore, we provide a code package containing trained ML models, allowing other researchers to establish T–S relations for different material interfaces.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Effect of deposition rate on microstructure and mechanical properties of 17-4 PH stainless steel fabricated by laser engineered net shaping

Laser engineered net shaping (LENS) is an additive manufacturing technique for fabricating and repairing metallic components. However, the relationships between its process parameters and the resulting mechanical properties of alloys such as 17-4 precipitation-hardening (PH) stainless steel require further investigation to enable reliable application. This study examines the specific effect of LENS deposition rate on the microstructure and mechanical properties of 17-4 PH stainless steel. Specimens were fabricated at two different deposition rates (8.47 and 9.31 mm s−1), subjected to subsequent solution and H900 aging treatment, and then evaluated via tensile testing, hardness measurements, and microscopy. A higher deposition rate results in a finer grain structure but increased porosity, leading to greater ultimate tensile strength (∼1294 MPa) yet lower ductility (strain at failure ∼5.8%) compared to the slower deposition rate (∼1266 MPa, ∼9.0% strain). Hardness follows the same trend as tensile strength. Tensile fracture surfaces for both conditions exhibited a mixed mode of ductile dimples and brittle quasi-cleavage regions, with chromium/silicon oxide particles identified within dimples. Complementary finite element modeling indicates that small void fractions primarily reduce ductility by enhancing localized plasticity, with only a marginal decrease in tensile strength. These integrated experimental and numerical results elucidate the mechanical properties linked to deposition rate, providing insight into tailoring LENS processes to achieve desired properties of 17-4 PH stainless steel.

17-4 PH stainlesssteel↗
DOE OSTI2023

Regional infrasonic observations from surface explosions – influence of atmospheric variations and realistic terrain

SUMMARY A pair of 1-ton, conventional surface explosions were conducted at the Nevada National Security Site in the fall of 2020 producing seismoacoustic signatures observable hundreds of kilometres from the source location. Regional infrasonic observations include tropospheric ducting at large distances to the south, a wide stratospheric waveguide with signals observed more than 700 km to the east, and anomalous arrivals in the stratospheric shadow zone. Notable differences in propagation between the events are identified despite the explosions being conducted just two days apart due to a sharp temporal shift in the tropospheric winds as well as structural changes in the stratospheric winds. Propagation simulations of the two events have been completed using a combination of ray tracing and parabolic equation (PE) methods. Simulations have been conducted to quantify the impact of the temporal variations in the atmosphere as well as the influence of terrain on propagation. Temporal variations in reflection locations are found to produce notable changes in downrange propagation due to spatially varying terrain features. Finite frequency effects modelled by the PE are found to predict ensonification not included in corresponding 2D ray tracing simulations. Notable variations in predicted signal amplitude are found due to focusing by along-path and cross-path terrain gradients; though, the later of these is only modelled using fully 3D ray tracing analysis.

58 GEOSCIENCES↗
DOE OSTI2022

Transport coefficients of the quark-gluon plasma at the critical point and across the first-order line

A bottom-up Einstein-Maxwell-dilaton holographic model is used to compute, for the first time, the behavior of several transport coefficients of the hot and baryon-rich strongly coupled quark-gluon plasma at the critical point and also across the first-order phase transition line in the phase diagram. The observables under study are the shear and bulk viscosities, the baryon and thermal conductivities, the baryon diffusion, the jet quenching parameter $\hat{q}$, as well as the heavy-quark drag force and the Langevin diffusion coefficients. These calculations provide a phenomenologically promising estimate for these coefficients, given that our model quantitatively reproduces lattice QCD thermodynamics results, both at zero and finite baryon density, besides naturally incorporating the nearly perfect fluidity of the quark-gluon plasma. Here we find that the diffusion of baryon charge, and also the shear and bulk viscosities, are suppressed with increasing baryon density, indicating that the medium becomes even closer to perfect fluidity at large densities. On the other hand, the jet quenching parameter and the heavy-quark momentum diffusion are enhanced with increasing density. The observables display a discontinuity gap when crossing the first-order phase transition line, while developing an infinite slope at the critical point. The transition temperatures associated with different transport coefficients differ in the crossover region but are found to converge at the critical point.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Exploring interlayer coupling in the twisted bilayer PtTe 2

We have investigated interlayer interactions in the bilayer PtTe 2 system, which influence the electronic energy bands near the Fermi level. Our diffusion Monte Carlo (DMC) calculations for the high-symmetry bilayer stackings (AA, AB, AC) manifest distinct interlayer binding characteristics among the stacking modes by revealing significantly different interlayer separations depending on the stacking, which is critical to understanding the interlayer coupling of the twisted bilayers consisting of various local stacking arrangements. Furthermore, a comparison between the interlayer separations obtained from DMC and density functional theory (DFT) shows that meta-generalized gradient approximation (GGA)-based van der Waals–DFT results agree with DMC for different layer stackings, including twisted bilayers, but only the ground-state AA stacking matches well with GGA-based DFT predictions. This underscores the importance of accurate exchange-correlation potentials even for capturing the stacking-dependent interlayer binding properties. We further show that the variability in DFT-predicted interlayer separations is responsible for the large discrepancy of band structures in the 21 . 79 ∘ twisted bilayer PtTe 2 , affecting its classification as metallic or insulating. These results demonstrate the importance of obtaining a correct description of stacking-dependent interlayer coupling in modeling delicate bilayer systems at finite twists. Published by the American Physical Society 2024

36 MATERIALS SCIENCE↗
DOE OSTI2021

A Continuum Dislocation Dynamics Crystal Plasticity Approach to Irradiated Body-Centered Cubic α-Iron

Radiation-induced embrittlement of reactor pressure vessel (RPV) steels can potentially limit the operating life of nuclear power plants. Over extended exposure to radiation doses, these body-centered cubic (BCC) irons demonstrate irradiation damage. Here, we present a continuum dislocation density (CDD) crystal plasticity model to capture the interaction among dislocations and self-interstitial atom (SIA) loops in α-iron. We demonstrate the importance of modeling cross slip using a combined stochastic Monte Carlo approach and the role of slip system strength anisotropy in capturing stochastic cross slip interactions. Through these captured interactions, the CDD crystal plasticity model can capture both the stress response and the physical evolution of dislocations on different slip system planes. Single-crystal verification experiments are used to calibrate the CDD crystal plasticity model, and a set of simplified polycrystalline simulations demonstrates the model’s ability to capture the stress response from tensile experiments on α-iron.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Poincaré beams from a free electron laser

Poincaré beams are light beams that have spatially inhomogeneous polarization structure that spans a finite portion of the Poincaré sphere. This feature bestows the beams with intriguing topological properties and has led to a surge in research on their fundamental characteristics, their controlled generation and on emerging applications. Here we present an experimental demonstration of a Poincaré beam generated in the extreme ultraviolet (16.7 nm) at the FERMI free electron laser (FEL). The ‘star’ type Poincaré beam is generated by exploiting the phase and intensity structure intrinsic to FEL radiation without relying on optical elements. Here, we controlled the spatial polarization distribution through a precise overlap and power balance between two FEL pulses, each with different transverse phase distributions and orthogonal circular polarizations. The spatial polarization structure was mapped in detail and shows extensive coverage of the Poincaré sphere, in agreement with analytic predictions. This method of in situ Poincaré beam production in FELs enables straightforward flexibility in the orientation and balance of polarization states, and can readily be extended to other vector beams and to shorter wavelengths enabling novel science applications in modern light sources.

Morgan, Jenny [SLAC National Accelerator Laborator↗
DOE OSTI2020

Flow-based likelihoods for non-Gaussian inference

We investigate the use of data-driven likelihoods to bypass a key assumption made in many scientific analyses, which is that the true likelihood of the data is Gaussian. In particular, we suggest using the optimization targets of flow-based generative models, a class of models that can capture complex distributions by transforming a simple base distribution through layers of nonlinearities. We call these flow-based likelihoods (FBL). We analyze the accuracy and precision of the reconstructed likelihoods on mock Gaussian data, and show that simply gauging the quality of samples drawn from the trained model is not a sufficient indicator that the true likelihood has been learned. We nevertheless demonstrate that the likelihood can be reconstructed to a precision equal to that of sampling error due to a finite sample size. We then apply FBLs to mock weak lensing convergence power spectra, a cosmological observable that is significantly non-Gaussian (NG). We find that the FBL captures the NG signatures in the data extremely well, while other commonly used data-driven likelihoods, such as Gaussian mixture models and independent component analysis, fail to do so. This suggests that works that have found small posterior shifts in NG data with data-driven likelihoods such as these could be underestimating the impact of non-Gaussianity in parameter constraints. By introducing a suite of tests that can capture different levels of NG in the data, we show that the success or failure of traditional data-driven likelihoods can be tied back to the structure of the NG in the data. Here, unlike other methods, the flexibility of the FBL makes it successful at tackling different types of NG simultaneously. Because of this, and consequently their likely applicability across datasets and domains, we encourage their use for inference when sufficient mock data are available for training.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Theoretical Description of Pump-Probe Experiments in Charge-Density-Wave Materials out to Long Times

We describe coupled nonequilibrium electron-phonon systems semiclassically—Ehrenfest dynamics for the phonons and quantum mechanics for the electrons—using a classical Monte Carlo approach that determines the nonequilibrium response to a large pump field. The semiclassical approach is expected to be accurate, because the phonons are excited to average energies much higher than the phonon frequency, eliminating the need for a quantum description. The numerical efficiency of this method allows us to perform a self-consistent time evolution out to very long times (tens of picoseconds), enabling us to model pump-probe experiments of a charge-density-wave (CDW) material. Our system is a half-filled, one-dimensional (1D) Holstein chain that exhibits CDW ordering due to a Peierls transition. The chain is subjected to a time-dependent electromagnetic pump field that excites it out of equilibrium, and then a second probe pulse is applied after a time delay. By evolving the system to long times, we capture the complete process of lattice excitation and subsequent relaxation to a new equilibrium, due to an exchange of energy between the electrons and the lattice, leading to lattice relaxation at finite temperatures. We employ an indirect (impulsive) driving mechanism of the lattice by the pump pulse due to the direct driving of the electrons. We identify two driving regimes, where the pump can either cause small perturbations or completely invert the initial CDW order. Our work successfully describes the ringing of the amplitude mode in CDW systems that has long been seen in experiment but never successfully explained by microscopic theory. We also describe the fluence-dependent crossover that inverts the CDW order parameter and changes the phonon dynamics. Finally, we illustrate how this method can examine a number of different types of experiments including photoemission, x-ray diffraction, and two-dimensional (2D) spectroscopy. Published by the American Physical Society 2024

Physics↗
DOE OSTI2025

Observation of anomalous thermal Hall effect in a Kagome superconductor

Broken time-reversal symmetry (TRS) in superconductors can induce not only spontaneous magnetization by the finite angular momentum of Cooper pairs but also the anomalous thermal Hall effects (ATHEs), whose detection has been extremely challenging. Here, we report the successful observation of an ATHE developing below the superconducting transition temperature at zero magnetic field in the kagome-lattice superconductor CsV 3 Sb 5 . This finding is verified by the absence of a signal in a conventional type-II superconductor using the same setup and by ruling out the trapped-vortex effects through micro-Hall array measurements. Both the temperature dependence and the magnitude of the observed anomalous thermal Hall conductivity are quite different from those expected for the quantized thermal edge current of an intrinsic ATHE but consistent with extrinsic impurity-induced ATHEs in chiral superconductivity. Our study of ATHE offers an alternative approach to probe TRS breaking in the superconducting states.

Yoshida, Hiroki [Univ. of Tokyo, Chiba (Japan)] (O↗
DOE OSTI2021

A Multiscale Modeling Approach to Cryocompressed Hydrogen Storage Pressure Vessels – Part II: Constitutive Modeling and Finite Element Analysis

Subjected to thermomechanical cycling, composite cryogenic hydrogen (H2) storage pressure vessels experience high stresses in the carbon fiber (CF)/epoxy overwrap which can lead to vessel failure due to a combination of degradation mechanisms such as matrix cracking, fiber/matrix debonding, delamination, and fiber rupture. The present paper is the second part of a set of two articles on this subject that addresses analysis and design of these pressure vessels. Predictive finite element (FE) modeling capabilities have been used to support a material acceptance process that aims at providing guidance to evaluate specialty resins, vessel liner options, and CF composites through thermomechanical testing. We have applied a multiscale modeling approach recently developed (B.N. Nguyen et al., International Journal of Hydrogen Energy, 2019, https://doi.org/10.1016/j.ijhydene.2019.09.200) to perform three-dimensional (3D) FE analysis and design of a cryo-compressed H2 storage pressure vessel for its operation in a large temperature range from room to cryogenic temperatures. The developed approach termed the micro-meso-macro approach determines the laminar stresses in different layers of the vessel in addition to constituent (i.e., fiber and matrix) stresses that are important to the design of the composite overwrap for its layup and material combination to reduce the risk of vessel failure.

Nguyen, Ba Nghiep↗
DOE OSTI2025

Multi-objective surrogate-assisted calibration of CPFEM models using macroscopic response and in situ EBSD measurements of grain reorientation trajectories

Crystal plasticity finite element method (CPFEM) models are widely used to simulate the deformation behaviour of polycrystalline materials, but their calibration is often limited by their high computational cost and the non-convexity of the optimisation landscape. Here, this study develops a multi-objective surrogate-assisted calibration workflow that couples a multi-objective genetic algorithm (MOGA) with an adaptively trained deep neural network (DNN) surrogate model to efficiently identify CPFEM parameters from experimental data. The workflow is demonstrated on three crystal plasticity (CP) formulations of increasing complexity — Voce hardening (VH), two-coefficient latent hardening (LH2), and six-coefficient latent hardening (LH6) — using in situ electron backscatter diffraction (EBSD) measurements of Alloy 617 under uniaxial tensile loading. The CPFEM models are calibrated against the experimentally observed stress–strain response and reorientation trajectories of eight grains, then validated against eight additional trajectories and overall texture evolution. Across the CP formulations, the macroscopic response was reproduced reliably, while differences emerged in the robustness and accuracy of the grain-scale predictions. Including grain reorientation trajectories in the multi-objective calibration improved texture evolution predictions and filtered out physically inconsistent parameter sets that can arise from calibrating against only the stress–strain data. The workflow also demonstrates good transferability of calibrated parameters from a low- to a high-fidelity microstructural model. These results provide practical guidance for integrating in situ microstructural data into CPFEM through efficient, repeatable, and physically meaningful multi-objective calibration.

Crystal plasticity finite element method↗
DOE OSTI2021

Probing the properties and mechanisms of failure waves in soda-lime glass

Soda-lime glass (SLG) and other silica glasses exhibit the failure wave phenomenon under shock compression. The mechanism responsible for this peculiar behavior of glasses is still unresolved. In this study, a series of plate impact experiments was performed at three different impact stresses of 6.4, 8.3, and 10.8 GPa to better understand the mechanisms underlying the failure wave phenomenon. Specifically, spall experiments were conducted to probe the speed and existence of failure waves at different stresses in SLG. A layered glass target was used to probe the possibility of a “renucleation” of the wave at the SLG–SLG interface. When it existed, the failure wave was inferred to propagate at a speed of 1.3 km/s. However, it was observed that the failure wave phenomenon ceases to exist for impact stresses higher than 10 GPa. In experiments with a 6.4 GPa impact stress, the peak free surface velocity was significantly less than what is predicted by stress-Hugoniot calculations. This velocity deficit and other important features of the measured free surface velocity profiles were simulated using finite element analysis by incorporating an abrupt densification of SLG at a critical stress in the equation of state. Furthermore, this densification feature is similar to what would be expected of a phase transition. Although unable to unambiguously reveal the mechanism causing the failure wave phenomenon, the results of the present work clearly indicate that the failure wave causes a secondary compression and densification in SLG.

36 MATERIALS SCIENCE↗
DOE OSTI2020

DMFT Reveals the Non-Hermitian Topology and Fermi Arcs in Heavy-Fermion Systems

When a strongly correlated system supports well-defined quasiparticles, it allows for an elegant one-body effective description within the non-Hermitian topological theory. While the microscopic many-body Hamiltonian of a closed system remains Hermitian, the one-body quasiparticle Hamiltonian is non-Hermitian due to the finite quasiparticle lifetime. We use such a non-Hermitian description in the heavy-fermion two-dimensional systems with the momentum-dependent hybridization to reveal a fascinating phenomenon which can be directly probed by the spectroscopic measurements, the bulk “Fermi arcs.” Starting from a simple two-band model, we first combine the phenomenological approach with the perturbation theory to show the existence of the Fermi arcs and reveal their connection to the topological exceptional points, special points in the Brillouin zone where the Hamiltonian is nondiagonalizable. The appearance of such points necessarily requires that the electrons belonging to different orbitals have different lifetimes. This requirement is naturally satisfied in the heavy-fermion systems, where the itinerant c electrons experience much weaker interaction than the localized f electrons. We then utilize the dynamical mean field theory to numerically calculate the spectral function and confirm our findings. We show here that the concept of the exceptional points in the non-Hermitian quasiparticle Hamiltonians is a powerful tool for predicting new phenomena in strongly correlated electron systems.

36 MATERIALS SCIENCE↗