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DOE OSTI2021

Bulk Photovoltaic Effect Driven by Collective Excitations in a Correlated Insulator

We investigate the bulk photovoltaic effect, which rectifies light into electric current, in a collective quantum state with correlation driven electronic ferroelectricity. We show via explicit real-time dynamical calculations that the effect of the applied electric field on the electronic order parameter leads to a strong enhancement of the bulk photovoltaic effect relative to the values obtained in a conventional insulator. The enhancements include both resonant enhancements at sub-band-gap frequencies, arising from excitation of optically active collective modes, and broadband enhancements arising from nonresonant deformations of the electronic order. The deformable electronic order parameter produces an injection current contribution to the bulk photovoltaic effect that is entirely absent in a rigid-band approximation to a time-reversal symmetric material. Furthermore, our findings establish that correlation effects can lead to the bulk photovoltaic effect and demonstrate that the collective behavior of ordered states can yield large nonlinear optical responses.

14 SOLAR ENERGY↗

DOE OSTI2024

A non-isothermal breakage-damage model for plastic-bonded granular materials incorporating temperature, pressure, and rate dependencies

Plastic-bonded granular materials (PBM) are widely used in industrial sectors, including building construction, abrasive applications, and defense applications such as plastic-bonded explosives. The mechanical behavior of PBM is highly nonlinear, irreversible, rate dependent, and temperature sensitive governed by various micromechanical attributions such as grain crushing and binder damage. This paper presents a thermodynamically consistent, microstructure-informed constitutive model to capture these characteristic behaviors of PBM. Key features of the model include a breakage internal variable to upscale the grain-scale information to the continuum level and to predict grain size evolution under mechanical loading. In addition, a damage internal state variable is introduced to account for the damage, deterioration, and debonding of the binder matrix upon loading. Temperature is taken as a fundamental external state variable to handle non-isothermal loading paths. The proposed model is able to capture with good accuracy several important aspects of the mechanical properties of PBM, such as pressure-dependent elasticity, pressure-dependent yield strength, brittle-to-ductile transition, temperature dependency, and rate dependency in the post-yielding regime. Furthermore, the model is validated against multiple published datasets obtained from confined and unconfined compression tests, covering various PBM compositions, confining pressures, temperatures, and strain rates.

Breakage↗

DOE OSTI2021

Numerical and experimental evaluation of mechanical performance of the multifunctional energy storage composites

This work presents numerical simulation methods to model the mechanical behavior of the multifunctional energy storage composites (MESCs), which consist of a stack of multiple thin battery layers reinforced with through-the-hole polymer rivets and embedded inside carbon fiber composite laminates. MESC has been demonstrated through earlier experiments on its exceptional behavior as a structural element as well as a battery. However, the inherent complex infrastructure of the MESC design has created significant challenges in simulation and modeling. A novel homogenization technique was adopted to characterize the multi-layer properties of battery material using physics-based constitutive equations combined with nonlinear deformation theories to handle the interface between the battery layers. Second, mechanical damage and failure modes among battery materials, polymer reinforcements, and carbon fiber-polymer interfaces were characterized through appropriate models and experiments. The model of MESCs has been implemented in a commercial finite element code in ABAQUS. A comparison of structural response and failure modes from numerical simulations and experimental tests are presented. The results of the study showed that the predictions of elastic and damage responses of MESCs at various loading conditions agreed well with the experimental data. © 2021

Materials Science↗

DOE OSTI2021

Spin-dependent Seebeck and Nernst effects in an ideal skyrmion gas

In this work, we theoretically and numerically study spin-dependent Seebeck and Nernst effects in 2D ferromagnetic materials with the topological spin texture (skyrmion and vortex) ideal gas. From the numerical solution of the matrix Boltzmann equation for a nonequilibrium distribution function and the Lippmann–Schwinger equation for a T-matrix we find the strong nonlinear behaviors in the thermoelectric coefficients depending on skyrmion/vortex diameters and electron concentrations. In particular, the dramatic dependences in the Seebeck and Nernst coefficients take place at larger magnetic texture sizes where the abrupt sign flip in the vortex Seebeck and Nernst coefficients occurs in the narrow region of electron concentrations. In this case the normalized Nernst coefficient changes from +5 to -7. The spin-dependent thermoelectric coefficients are proportional to T at low temperatures for all skyrmion/vortex sizes.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Spontaneously formed phonon frequency combs in van der Waals solid CrGeTe 3 and CrSiTe 3

Optical phonon engineering through nonlinear effects has been utilized in ultrafast control of material properties. However, nonlinear optical phonons typically exhibit rapid decay due to strong mode-mode couplings, limiting their effectiveness in temperature or frequency sensitive applications. Here we report the observation of long-lived nonlinear optical phonons through the spontaneous formation of phonon frequency combs in the van der Waals material CrXTe 3 (X=Ge, Si) using high-resolution Raman scattering. Unlike conventional optical phonons, the highest A g mode in CrGeTe 3 splits into equidistant, sharp peaks forming a frequency comb that persists for hundreds of oscillations and survives up to 200K. These modes correspond to localized oscillations of Ge 2 Te 6 clusters, isolated from Cr hexagons, behaving as independent quantum oscillators. Introducing a cubic nonlinear term to the harmonic oscillator model, we simulate the phonon time evolution and successfully replicate the observed comb structure. Similar frequency comb behavior is observed in CrSiTe 3 , demonstrating the generalizability of this phenomenon. Our findings demonstrate that Raman scattering effectively probes high-frequency nonlinear phonon modes, offering insight into the generation of long-lived, tunable phonon frequency combs with potential applications in ultrafast material control and phonon-based technologies.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Zr 3 Mn 3 Sn 4 Ga: A new hetero-kagome bilayer antiferromagnet

Here, we report the magnetic and electrical transport properties of single-crystalline Zr 3 Mn 3 Sn 4 Ga, featuring two distinct kagome lattices: a non-magnetic breathing Zr 3 Sn 4 lattice and a magnetic intact Mn 3 Ga lattice. The material undergoes an antiferromagnetic phase transition at T N = 87 K, with neutron diffraction confirming commensurate ordering characterized by k = (1/3,1/3,0). Transport measurements show metallic behavior, a resistivity anomaly near T N , and 12% magnetoresistance at 2 K under 9 T. Deviations from the conventional second-order power law, along with negative magnetoresistance and nonlinear Hall slope variations near T N , suggest strong magneto-electronic coupling. Resonant photoemission spectroscopy identifies Zr 4d and Mn 3d orbitals as dominant contributors to the valence band, linking the material’s unique electronic properties to its kagome layers. Zr 3 Mn 3 Sn 4 Ga offers a valuable platform to study interactions between magnetism and topological electronic bands in hetero-kagome systems using the co- existence of magnetic and non-magnetic kagome layers and its tunable electronic structure.

Crystal structure↗

DOE OSTI2025

Physics-Informed Machine Learning Model for Ceramic Matrix Composite Creep

A physics-informed recurrent neural network (RNN) based surrogate model is developed to emulate the nonlinear, time-dependent constitutive behavior of ceramic matrix composites (CMCs) driven by matrix damage and constituent creep at the microscale. Physics-informed constraints are introduced into the surrogate model through regularization to ground the prediction in physics and improve its predictive capabilities. Training data is generated using the high-fidelity generalized method of cells (HFGMC) approach which calls appropriate creep and damage models for each of the constituents. This coupling permits simulating the nonlinear behavior of CMCs based on constituent response at the microscale along with microstructural features such as fiber and porosity volume fraction and fiber radius. The microscale repeating unit cell is loaded under creep fatigue conditions to replicate the material loading experienced in a turbine engine. Therefore, the RNN-based surrogate model is tasked with predicting, as a function of variable input stress sequence, temperature, and microstructural features, the resulting strain history response while satisfying physical constraints related to creep rate, isochoric inelastic deformation, and strain energy density. The trained surrogate model is shown to effectively match the strain history over quantified distributions of microstructural features and relevant loading regimes and temperatures. Neural network based surrogate models can offer efficient alternatives to running computationally intensive multiscale material models to simulate the nonlinear response of large structural models. Therefore, the presented work provides evidence towards the feasibility of developing, training, and running such models for CMCs with complex microstructures, nonlinear time-dependent material response, and under non-monotonic loading conditions.

ceramic matrix composites↗

DOE OSTI2023

Denoising diffusion algorithm for inverse design of microstructures with fine-tuned nonlinear material properties

Here we introduce a denoising diffusion algorithm to discover microstructures with nonlinear fine-tuned properties. Denoising diffusion probabilistic models are generative models that use diffusion-based dynamics to gradually denoise images and generate realistic synthetic samples. By learning the reverse of a Markov diffusion process, we design an artificial intelligence to efficiently manipulate the topology of microstructures to generate a massive number of prototypes that exhibit constitutive responses sufficiently close to designated nonlinear constitutive behaviors. To identify the subset of microcstructures with sufficiently precise fine-tuned properties, a convolutional neural network surrogate is trained to replace high-fidelity finite element simulations to filter out prototypes outside the admissible range. Results of this study indicate that the denoising diffusion process is capable of creating microstructures of fine-tuned nonlinear material properties within the latent space of the training data. More importantly, this denoising diffusion algorithm can be easily extended to incorporate additional topological and geometric modifications by introducing high-dimensional structures embedded in the latent space. Numerical experiments are conducted on the open-source mechanical MNIST data set (Lejeune, 2020). Consequently, this algorithm is not only capable of performing inverse design of nonlinear effective media, but also learns the nonlinear structure–property map to quantitatively understand the multiscale interplay among the geometry, topology, and their effective macroscopic properties.

42 ENGINEERING↗

DOE OSTI2022

Tailoring the Thickness‐Dependent Optical Properties of Conducting Nitrides and Oxides for Epsilon‐Near‐Zero‐Enhanced Photonic Applications

Abstract The unique properties of the emerging photonic materials, conducting nitrides and oxides, especially their tailorability, large damage thresholds, and, importantly, the so‐called epsilon‐near‐zero (ENZ) behavior, have enabled novel photonic phenomena spanning optical circuitry, tunable metasurfaces, and nonlinear optical devices. This work explores direct control of the optical properties of polycrystalline titanium nitride (TiN) and aluminum‐doped zinc oxide (AZO) by tailoring the film thickness, and their potential for ENZ‐enhanced photonic applications. This study demonstrates that TiN–AZO bilayers support Ferrell–Berreman modes using the thickness‐dependent ENZ resonances in the AZO films operating in the telecom wavelengths spanning from 1470 to 1750 nm. The bilayer stacks also act as strong light absorbers in the ultraviolet regime using the radiative ENZ modes and the Fabry–Perot modes in the constituent TiN films. The studied Berreman resonators exhibit optically induced reflectance modulation of 15% with picosecond response time. Together with the optical response tailorability of conducting oxides and nitrides, using the field enhancement near the tunable ENZ regime can enable a wide range of nonlinear optical phenomena, including all‐optical switching, time refraction, and high‐harmonic generation.

Saha, Soham↗

DOE OSTI2024

Streamlined Loads Analysis of Floating Wind Turbines With Fiber Rope Mooring Lines

This paper presents an approach for more accurate yet relatively streamlined accounting for the nonlinear characteristics of synthetic fiber rope mooring lines for floating wind turbines. First, we select a minimal set of parameters that can efficiently approximate a mooring line material's quasi-static and dynamic stiffness characteristics. We also develop a set of baseline coefficients for different rope materials based on published product information and research papers. We then expand a quasi-static mooring model to include dynamic mooring line stiffness terms in a way that allows the nonlinear stiffness behavior of fiber ropes to be considered even in quasi-static analyses. For dynamic analysis, we have updated the model MoorDyn, coupled with OpenFAST, to work with the new dynamic mooring line stiffness terms. This includes the implementation of a new viscoelastic approach that allows the tension-strain relation of each mooring line segment to vary between two stiffness values, depending on the strain rate. After presenting the formulation of the approaches for modeling synthetic ropes, they are demonstrated on a floating wind turbine mooring system with taut polyester rope mooring lines. The results are compared with those of other approaches of similar fidelity, including the static-dynamic method and separate simulations with static and dynamic stiffness values. Comparing the results shows the ability of the new method to match the results of the previous methods in a more streamlined manner.

elasticity↗

DOE OSTI2024

Streamlined Loads Analysis of Floating Wind Turbines With Fiber Rope Mooring Lines: Preprint

This paper presents an approach for more accurate yet relatively streamlined accounting for the nonlinear characteristics of synthetic fiber rope mooring lines for floating wind turbines. First, we select a minimal set of parameters that can efficiently approximate a mooring line material's quasi-static and dynamic stiffness characteristics. We also develop a set of baseline coefficients for different rope materials based on published product information and research papers. We then expand a quasi-static mooring model to include dynamic mooring line stiffness terms in a way that allows the nonlinear stiffness behavior of fiber ropes to be considered even in quasi-static analyses. For dynamic analysis, we have updated the model MoorDyn, coupled with OpenFAST, to work with the new dynamic mooring line stiffness terms. This includes the implementation of a new viscoelastic approach that allows the tension-strain relation of each mooring line segment to vary between two stiffness values depending on the strain rate. After presenting the formulation of the approaches for modeling synthetic ropes, they are demonstrated on a floating wind turbine mooring system with taut polyester rope mooring lines. The results are compared with those of other approaches of similar fidelity including the static-dynamic method and separate simulations with static and dynamic stiffness values. Comparing the results shows the ability of the new method to match the results of the previous methods in a more streamlined manner.

elasticity↗

DOE OSTI2020

An interface-controlled Mott memristor in α -RuCl 3

Memristor devices have history-dependent charge transport properties that are ideal for neuromorphic computing applications. We reveal a memristor material and mechanism in the layered Mott insulator α-RuCl 3 . The pinched hysteresis loops and S-shaped negative differential resistance in bulk crystals verify memristor behavior and are attributed to a nonlinear coupling between charge injection over a Schottky barrier at the electrical contacts and concurrent Joule heating. Direct simulations of this coupling can reproduce the device characteristics.

Physics↗

DOE OSTI2020

Modular Linear Thermoviscoelastic Model

Time-dependent, viscoelastic responses of materials like polymers and glasses have long been studied. As such, a variety of models have been put forth to describe the behavior including simple rheological models (e.g. Maxwell, Kelvin), linear "fading memory" theories, and hereditary integral based linear thermal viscoelastic approaches as well as more recent nonlinear theories that are either integral, fictive temperature, or differential internal state variable based. The current work details a new LINEAR_THERMOVISCOELASTIC model that has been added to LAME. This formulation represents a viscoelastic theory that neglects some of the phenomenological details of the PEC/SPEC models in favor of efficiency and simplicity. Furthermore, this new model is a first step towards developing "modular" viscoelastic capabilities akin to those available with hardening descriptions for plasticity models in LAME. Specifically, multiple different (including user-defined) shift-factor forms are implemented with each being easily selected via parameter specification rather than requiring distinct material models.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Extremized nonlinear and linearized responses in soft metamaterials enabled by gradient-based design and grayscale digital light processing

In this study, we develop a gradient-based design approach that exploits grayscale digital light processing (DLP) 3D printing for extremizing the nonlinear and linearized response of soft metamaterials — materials that harness engineered geometric instabilities to undergo large and programmable changes in configuration. Grayscale DLP approaches modulate local mechanical properties at the pixel scale by tuning the light intensity within a single grayscale image, unlocking an exceptionally large design space. To effectively navigate this space, we develop smooth mappings between local light intensity values and global quantities of interest that characterize the behavior of soft metamaterials. Enabling these smooth mappings are robust and differentiable nonlinear finite element simulations powered by a trust region solver. A PDE-constrained optimization problem is then solved to invert these mappings and produce light intensity distributions that endow the printed part with varying stiffness and flexibility in distinctive regions. It is shown that optimizing the distribution of soft and stiff phases throughout a metamaterial structure results in markedly different buckling and self-contact configurations to drive extremized nonlinear compression and linearized vibration responses. Optimized light intensity distributions are translated to grayscale images and directly used to print soft metamaterial samples, showing remarkable agreement between the buckling and self-contact response in simulated and measured deformed configurations.

Additive manufacturing↗

DOE OSTI2022

Photophysics and Spin-Physics Studies on Persistent Upconversion Luminescence from Nonlinearly Polarizable Ferroelectric-Like Lattice Prepared by Orderly Packing Donor–Acceptor Structures under Multiphoton Excitation

The ultralong-lived upconversion luminescence with the lifetime of 0.48 s in a broad spectral range (530–650 nm) is observed in CD49 (9-(3-(5-bromopyridin-3-yl)prop-2-yn-1-yl)-9H-carbazole) crystal designed with donor–acceptor (carbazole–pyridine) structures under infrared excitation, simultaneously accompanied with second harmonic generation (SHG). This phenomenon indicates orderly packing donor–acceptor structures form a nonlinearly polarizable ferroelectric-like lattice with ultralong-lived light-emitting states, leading to much prolonged nonlinear optical behaviors. The persistent upconversion luminescence together with SHG is largely reduced when lowering crystallinity. This implies that nonlinearly polarizable ferroelectric-like lattice provides the necessary condition to generate persistent upconversion luminescence. Evidently, persistent upconversion luminescence becomes completely lacking when only using ultralong-lived light-emitting states without nonlinearly polarizable ferroelectric-like lattice, exampled by 4-(dimethylamino)benzonitrile dispersed in polyvinyl alcohol matrix. Magneto-photoluminescence shows that persistent upconversion luminescence is essentially a super-delayed fluorescence from crystalline intermolecular charge-transfer excitons formed in the nonlinearly polarizable ferroelectric-like lattice. Magnetodielectrics indicate crystalline intermolecular charge-transfer excitons are coupled with nonlinearly polarizable ferroelectric-like lattice, leading to prolonged nonlinear optical behaviors shown as persistent upconversion luminescence through super delayed fluorescence. In conclusion, therefore, crystalline intermolecular charge-transfer excitons formed in nonlinearly polarizable ferroelectric-like lattice provide an interesting platform to generate prolonged nonlinear optical behaviors toward developing persistent upconversion luminescence under multiphoton excitation.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Non-degenerate parametric mixing and Q-enhancement in ALN Lamb wave resonator

In this Letter, we explore a non-degenerate phase independent parametric quality factor (Q)-enhancement technique for aluminum nitride (AlN) Lamb wave resonators. Unlike other active Q-enhancement techniques which require precise phase control of the electronic feedback loop, this technique is implemented by parametrically pumping AlN material stiffness to realize a negative resistance seen at the signal path. The negative resistance is dependent on the nonlinear material modulation and multi-resonance coupling in the device. A nonlinear circuit model is developed to simulate the parametric coupling of each resonance and extract the nonlinearity of AlN from experimental data. With proper pump frequency and pump power, the device quality factor is boosted in both simulation and experiment. The demonstrated Q-enhancement method is simple to implement and can be applied to other types of resonators that have nonlinear behavior and support multi-resonance operation.

42 ENGINEERING↗

DOE OSTI2022

Ultrafast electron dynamics of graphene quantum dots: High harmonic generation

We study theoretically nonlinear optical properties of graphene quantum dots placed in a field of a short and strong linearly polarized optical pulse. We address the problem of high harmonic generation in quantum dots and how such nonlinear effect is affected by dephasing processes in a quantum dot. The dephasing makes the ultrafast electron dynamics more irreversible with a large residual population of the excited quantum dot levels. In relation to the high-harmonic spectrum, with increasing the dephasing time, the intensities of the low-frequency harmonics increase while the cutoff energy decreases. The dependence of the cutoff energy on the amplitude of the optical pulse is also sensitive to the frequency of the pulse. When the frequency of the optical pulse is much less than the quantum dot band gap, this dependence is almost linear, but when the frequency of the pulse is comparable to the band gap, the cutoff energy shows saturation behavior at large field amplitude, >0.4 V/Å.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Automated Experiments of Local Non–Linear Behavior in Ferroelectric Materials

An automated experiment in multimodal imaging to probe structural, chemical, and functional behaviors in complex materials and elucidate the dominant physical mechanisms that control device function is developed and implemented. Here, the emergence of non-linear electromechanical responses in piezoresponse force microscopy (PFM) is explored. Non-linear responses in PFM can originate from multiple mechanisms, including intrinsic material responses often controlled by domain structure, surface topography that affects the mechanical phenomena at the tip-surface junction, and the presence of surface contaminants. Using an automated experiment to probe the origins of non-linear behavior in ferroelectric lead titanate (PTO) and ferroelectric Al 0.93 B 0.07 N films, it is found that PTO shows asymmetric nonlinear behavior across a/c domain walls and a broadened high nonlinear response region around c/c domain walls. In contrast, for Al 0.93 B 0.07 N, well-poled regions show high linear piezoelectric responses, when paired with low non-linear responses regions that are multidomain show low linear responses and high nonlinear responses. It is shown that formulating dissimilar exploration strategies in deep kernel learning as alternative hypotheses allows for establishing the preponderant physical mechanisms behind the non-linear behaviors, suggesting that automated experiments can potentially discern between competing physical mechanisms. Furthermore, this technique can also be extended to electron, probe, and chemical imaging.

36 MATERIALS SCIENCE↗