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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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pH-Dependent Vibrational Dynamics Drives Excited-State Quenching in the Phycobiliprotein Complex PC645
Phycocyanin 645 (PC645) is a closed-form lightharvesting complex found in the lumen of the photosynthetic membrane of cryptophyte algae. These peripheral antenna complexes contain bilin chromophores that absorb sunlight and transfer excitation energy to the core antenna complexes embedded in the thylakoid membrane. The location of cryptophyte antenna complex on the luminal side of the membrane is unusual. During photosynthetic activity, the pH of the lumen drops, by up to two pH units. There is little known about how this pH-change affects the light-harvesting complexes. In this study, we report multiscale simulations using a computationally efficient density functional tight-binding framework to investigate the spectroscopy and excitation energy transfer in the PC645 complex. Complementary experiments were conducted using both steady-state and time-resolved spectroscopic measurements at low, neutral, and high pH values. Our study shows that (de)protonation of specific bilin pigments, namely, the mesobiliverdins (MBVs), modulates the excitation energies, excitonic couplings, and spectral densities. These changes cause excitation transfer rates to increase by up to a factor of two to three, leading to pH-dependent energy transfer pathways in the complex. Using this model, we calculated the pH-dependent fluorescence quantum yield of the system, obtaining quantitative agreement with the experimental results. These computational simulations, supported by experiments, identify MBVs as a more prominent excitation sink than previously realized, and that this role is tuned by pH.
Oxygen Storage Incorporated Into Net Power and the Allam–Fetvedt Oxy-Fuel sCO2 Power Cycle—Techno-Economic Analysis
Abstract With the planned future reliance on variable renewable energy, the ability to store energy for prolonged time periods will be required to reduce the disruption of market fluctuations. This paper presents a method to analyze a hybrid liquid-oxygen (LOx) storage/direct-fired supercritical carbon dioxide (sCO2) power cycle and optimize the economic performance over a diverse range of scenarios. The system utilizes a modified version of the NET Power process to produce energy when energy demand exceeds the supply while displacing much of the cost of the air separation unit (ASU) energy requirements through cryogenic storage of oxygen. The model uses marginal cost of energy data to determine the optimal times to charge and discharge the system over a given scenario. The model then applies ramp rates and other time-dependent factors to generate an economic model for the system without storage considerations. The size of the storage system is then applied to create a realistic model of the plant operation. From the real plant operation model, the amount of energy charged and discharged, the capital expenditures (CAPEX) of each system, energy costs and revenue and other parameters can be calculated. The economic parameters are then combined to calculate the net present value (NPV) of the system for the given scenario. The model was then run through the SMPSO genetic algorithm in Python for a variety of geographic regions and large-scale scenarios (high solar penetration) to maximize the NPV based on multiple parameters for each subsystem. The LOx storage requirements will also be discussed.
ML Pipeline (Machine Learning Pipeline) [SWR-22-35]
The Machine Learning Pipeline (ML Pipeline) allows the user to fit a model to predict a dependent variable, y, based on a feature set, X. ML Pipeline gives the ability to automatically generate features with its Feature Engineering function, automatically select the most important features with its Feature Selection function, fit the model with its Fit function, and evaluate the model with its Evaluate function. ML Pipeline's functionality can not only help the user predict values for the desired variable it also gives the user a better understanding of which features are important and how effective the model is. ML Pipeline accomplishes all this, while remaining simple to use and interpret.
Failure Criteria and Temperature Dependent Elastic Constants in the 3-D Elastic Orthotropic Model
Recent points of emphasis in the Library of Advanced Materials for Engineering (LAMÉ) have been to enable flexibility in formulations via the adoption of a variety of modular frameworks. While more established phenomenologies such as plasticity and viscoelasticity have been considered, elastically orthotropic models (e.g. elastic_3D_orthotropic) have not. For the elasticity component, not much can be modularized. However, a potential feature of interest would be the evaluation of failure criteria to consider the possibility of damage. Many such forms exist in the literature providing a good basis for modularity.
Characterization of nonlinear ultrasonic waves behavior while interacting with poor interlayer bonds in large-scale additive manufactured materials
Over the past decades, researchers have developed several nonlinear ultrasonic techniques for quality control of materials commonly used in different applications. Owing to the superior sensitivity of nonlinear ultrasound waves to small defects such as micro-cracks, their applicability in different nondestructive testing (NDT) problems has been investigated in numerous studies. These studies utilize frequency domain analysis to detect the generation of higher harmonics because of the formation of defects in the inspected medium. Frequency domain analysis based on the Fourier transform is a significant approach used in linear systems; however, it may not perform adequately on nonlinear systems. Hence, studies on nonlinear dynamics and physics consider analyzing systems' behavior in the phase-space domain. In contrast to the frequency domain analysis, which can result in information loss, analysis in the phase-space domain retains all the information regarding a system's states. Here, we investigate the nonlinearities induced by poor interlayer bonding in polymer-based additive manufactured parts in the phase-space domain. It is convenient to characterize the nonlinearity in the phase-space domain because it provides a geometrical representation of a system's states. Two types of low quality interlayer bond are considered. The first type is simulated artificially while the second type is manufactured by reducing the bond quality during the printing process. The analysis verified that the received ultrasonic signals exhibit classical nonlinear behavior in the phase-space domain while interacting with simulated poor interlayer bonds. In addition, the results showed that the behavior of ultrasonic waves is amplitude-dependent and evolves into models that have not been previously reported. Furthermore, Largest Lyapunov Exponent (LLE) is used to quantify the behavior of nonlinear ultrasonic waves while interacting with poor interlayer bonds. Using LLE, it was observed that the divergence rate of the phase-space trajectories depends on the amplitude of the excitation. This observation quantitatively proves that nonlinear behavior of ultrasound while interacting with poor interlayer bonds can be amplitude-dependent. The results of both simulated and inherent poor interlayer bond cases showed that LLE can be used as a reliable quantitative damage-sensitive feature to detect and potentially characterize weak bonds, which are difficult to detect using conventional approaches. Additionally, the reported results in the phase-space domain provide a basis for proposing a new mathematical model for ultrasonic waves interacting with poor interlayer bonds.
3D multi-system Bayesian calibration with energy conservation to study rapidity-dependent dynamics of nuclear collisions
Considerable information about the early-stage dynamics of heavy ion collisions is encoded in the rapidity dependence of measurements. To leverage the large amount of experimental data, we perform a systematic analysis using three-dimensional hydrodynamic simulations of multiple collision systems — large and small, symmetric and asymmetric. Specifically, we perform fully 3D multi-stage hydrodynamic simulations initialized by a parameterized model for rapidity-dependent energy deposition, which we calibrate on the hadron multiplicity and anisotropic flow coefficients. We utilize Bayesian inference to constrain properties of the early- and late-time dynamics of the system, and highlight the impact of enforcing global energy conservation in our 3D model.
The right conditions for high-precision dynamic temperature and heat capacity measurement via pyrometry and conductivity
The pursuit of accurate bulk temperature T under extreme conditions has been a long-standing goal of the high pressure science community, complicated by a lack of data to inform models. To reach these extremely high-pressure, high-temperature (high P − T) conditions, a combination of dynamic and heated static experiments (e.g., diamond or gem anvil cel experiments) are used. For example, in a diamond anvil cell (DAC) experiment, a sample placed in the DAC is first pressurized. Following pressurization, the sample T is increased either by heating the entire DAC (usually using resistive heating, and limited to ∼1000K) or by applying intense laser power to the sample surfaces. In a dynamic experiment, the process of pressurizing the sample also heats it. In the case of shock physics experiments, such heating is substantial, easily reaching thousands of Kelvin; in our work we have seen T ∼17000K. Most methods of measuring temperature at ambient are not compatible with experiments under these high-pressure, high-temperature conditions: thermocouples break, melt, or have conductivity properties that differ from ambient where they are calibrated; thermometers would melt; both are too slow. As a result most methods are based on non-contact techniques such as x-ray diffraction broadening, neutron scattering, or optical methods. Of these, optical methods using the visible and near-infrared region of the spectrum are the most commonly used as the sources and detectors are readily available. In the case of optical methods the optical depth, and therefore the measurement location, is limited to the surface. When a window or anvil material is used, heat flows from the sample into the window/anvil. Likewise, if the sample undergoes a change in thermodynamic state, such as expansion upon release, different T may be expected. As a result, the surface or apparent temperature T app measurement will differ from the bulk or interior temperature that is desired. This surface measurement must be related to the bulk measurement using thermal transport models and material models. While it is tempting to conclude that one should just use x-ray methods that directly probe the interior, even these methods have been shown to depend on thermal transport and material models. Regardless of the method used to create the high P − T condition, therefore, we must understand the role of thermal transport and material models upon our interpretation of the T measurement, as well as the errors and uncertainties associated with the choice of models used in the analysis. This is a substantial area of research and this paper is by no means a complete survey of the relevant sources of uncertainty. For example, we have yet to begin to address alternate transport models in a detailed manner (e.g., Tan-Ahrens), or the many models that use additional layers to approximate melting, turbulence, or epitaxial phenomena). Likewise, we have not explored the impact upon uncertainty of thermal models that use temperature-dependent thermal transport coefficients, or the wide range of material models that can be applied. Instead, this paper focuses on using one simple model, the Urtiew-Grover model, to understand the sources of error in T measurement so that we may identify how best to focus future research efforts to return the best improvements and avoid working on over-optimizing a single type of measurement. To this end, we work through some of the best and worst case scenarios for T measurement.
Nonlinear model of infection wavy oscillation of COVID-19 in Japan based on diffusion kinetics
The infectious propagation of SARS-CoV-2 is continuing worldwide, and specifically, Japan is facing severe circumstances. Medical resource maintenance and action limitations remain the central measures. An analysis of long-term follow-up reports in Japan shows that the infection number follows a unique wavy oscillation, increasing and decreasing over time. However, only a few studies explain the infection wavy oscillation. This study introduces a novel nonlinear mathematical model of the new infection wavy oscillation by applying the macromolecule diffusion theory. In this model, the diffusion coefficient that depends on population density gives nonlinearity in infection propagation. As a result, our model accurately simulated infection wavy oscillations, and the infection wavy oscillation frequency and amplitude were closely linked with the recovery rate of infected individuals. In conclusion, our model provides a novel nonlinear contact infection analysis framework.
Bayesian inference of nuclear incompressibility from collective flow in mid-central Au+Au collisions at 400–1500 MeV/nucleon
The incompressibility K of symmetric nuclear matter (SNM) is determined through a Bayesian analysis of collective flow data from Au + Au collisions at beam energies $E = 400 -1500$ MeV/nucleon. This analysis utilizes a Gaussian process (GP) emulator applied to the isospin-dependent quantum molecular dynamics (IQMD) model for heavy-ion collisions, both with and without incorporating the momentum dependence of the single-nucleon potentials. Specifically, at the 68% confidence level, using rapidity and transverse velocity dependence of proton elliptic flow data with and without consideration of the momentum dependence, the inferred incompressibility values are $K=188.9^{+2.9}_{-4.5}$ MeV and $256.1^{+8.2}_{-8.7}$ MeV at $E = 400$ MeV/nucleon, respectively. When the transverse momentum dependence of proton-like directed flow data is included, the inferred incompressibility values become $K=222.3^{+9.0}_{-9.9}$ MeV and $K=285.5^{+6.7}_{-7.3}$ MeV, respectively. Furthermore, we found that the value of K derived from observables of proton elliptic flow increases with beam energy. Finally, this indicates that the equation of state (EoS) of nuclear matter hardens at higher densities and temperatures in reactions with higher beam energies.
A robust and efficient generalized real cascade model
This paper describes a new separation cascade model that allows for arbitrary cascade connectivity and includes the effects of mixing, material losses and generalized separation element performance. The model also accommodates mixtures with an arbitrary number of component species. The mathematical and numerical framework of this model includes both time-dependent and steady state cascade simulation. Robust numerical approximations of the continuous mathematical model are accomplished using the Sundials suite of nonlinear algebraic and differential-algebraic equation solvers. Verification of the model is accomplished using manufactured solutions while validation is demonstrated by comparison to published experimental results and benchmarks.
Evaluation of Mechanistic and Empirical Models against Existing FFRD and LOCA Experimental Databases
The desire of the nuclear industry to improve the economics of existing nuclear power plants has necessitated research into the potential of a phenomenon known as fuel fragmentation, relocation, and dispersal (FFRD). This phenomenon is possible during a loss-of-coolant accident (LOCA) at relatively high burnup. The Nuclear Energy Advanced Modeling and Simulation program has been developing simulation capabilities for FFRD and LOCA in the BISON fuel performance code for multiple years. This year, the effort has been focused on evaluating new lower length scale informed pulverization thresholds as well as updating and adding new empirical models for various phenomena. Models added or updated this year include a preliminary transient fission gas release model, new high-temperature Zircaloy creep models, a Zircaloy rupture opening area model, and a temperature-dependent emissivity during radiation from the fuel rod to the surrounding atmosphere. The models are verified through implementation tests to demonstrate code correctness after addition to BISON. The models are then assessed against a subset of the existing BISON validation suite for LOCA and FFRD cases. Two new cases, Studsvik Rods 192 and 193, have been added. The results indicate that the inclusion of a bubble pressure evolution model in the bubbles in the high-burnup structure has the largest impact compared to the 3D fracture criterion on reducing the calculated amount of pulverized fuel.
Surface-sensitive photon avalanche behavior revealed by single-avalanching-nanoparticle imaging
Avalanching nanoparticles (ANPs) are a new class of lanthanide-based upconverting material demonstrating steep optical nonlinearities with the potential to advance applications ranging from subwavelength bioimaging to neuromorphic computing, nanothermometry, and pressure transduction. Here, we use single-nanocrystal imaging to uncover design-dependent heterogeneity in ANP threshold intensity (I th ). Quantitative comparisons between distributions of I th and ANP shell properties reveal correlations between mean I th values, histogram widths, and nanocrystal shell thickness. Evaluating avalanching behaviors using an established model of shell-dependent surface energy transfer shows that variations in shell thickness-and the resultant energy transfer through the shell to the surface and environment-are likely the primary contributor to ANP-to-ANP I th heterogeneity. Further, nanocrystals with an ~6 nm average shell thickness show I th heterogeneity beyond the extent expected from statistical measurements of shell size and variability using transmission electron microscopy (TEM). Here these results provide a principal guide for the design and application of ANPs to environmental sensing.
Dynamic embedding of effective harmonic normal mode vibrations in all-atomistic energy gap fluctuations: Case study of light harvesting 2 complex
Environmental effects in excitation energy transfer have mostly been modeled by baths of harmonic oscillators, but to what extent such modeling provides a reliable description of actual interactions between molecular systems and environments remains an open issue. Here, we address this issue by investigating fluctuations in the excitation energies of the light harvesting 2 complex using a realistic all-atomistic simulation of the potential energy surface. Our analyses reveal that molecular motions exhibit significant anharmonic features, even for underdamped intramolecular vibrations. In particular, we find that the anharmonicity contributes to the broadening of spectral densities and substantial overlaps between neighboring peaks, which complicates the meaning of mode frequencies constituting a bath model. Thus, we develop a strategy to construct a minimally underdamped harmonic bath that has a clear connection to all-atomistic dynamics by utilizing actual normal modes of molecules but optimizing their frequencies such that the resulting bath model can best reproduce the all-atomistic simulation results. By subtracting the underdamped contribution from the entire fluctuations, we also show that identifying a residual spectral density representing all other contributions with overdamped behavior is possible. We find that this can be fitted well with a well-established analytic form of a spectral density function or, alternatively, modeled as explicit time dependent fluctuations with muti-exponential or power law type correlation functions. We provide an assessment and the implications of these possibilities. The approach presented here can also serve as a general strategy to construct a simplified bath model that can effectively represent the underlying all-atomistic bath dynamics.
Mid-Infrared Nonlinear Frequency Conversion Using Monolithic Barium Titanate on Silicon-on-Insulator
In this work, efficient nonlinear frequency conversion in the mid-infrared (mid-IR) region was demonstrated by a barium titanate (BTO) on a silicon-on-insulator (SOI) substrate. The BTO thin film was epitaxially grown by pulsed-laser deposition (PLD). The tensorial second order optical nonlinearity and the ferroelectric domain property of the BTO were characterized by the polarimetric mid-IR second harmonic generation (SHG) measurements. Azimuthal-dependent polarized SHG was modeled at different combinations of the nonlinear coefficient $d_{ij}$ and the domain fraction factor $ΔD^Y/ΔD^X$. Strong SHG intensity was experimentally observed over a broad spectrum at λ = 3.1 μm - 3.7 μm. A characteristic linear dependence between the SHG signal and the square of the pumping laser intensity was observed. The monolithic integration between the epitaxial BTO and the Si provides a compact platform for efficient on-chip light generation and quantum photonic technologies.
Development of a creep model informed by lower-length scale simulations to simulate creep in doped UO 2
Using molecular dynamics, we predict information at the atomistic scale used to develop a mechanistic UO 2 creep model for use in higher length-scale fuel performance codes. The ultimate objective of the model is to better describe the grain size dependence and therefore impact of doping on creep rates in UO 2 . In a previous NEAMS milestone, we found that Nabarro-Herring (bulk diffusional) creep was too low to capture the experimentally observed creep rates in standard UO 2 . Moreover, in that milestone, other mechanisms were explored, such as Coble (grain boundary) creep and dislocation climb, with each mechanism exhibiting different grain size dependencies. Again, these were orders of magnitude too low to describe the experimental creep rates. In this work, we address the previous assumptions made for the Coble creep mechanism by investigating the diffusivity of various defects at grain boundaries in UO 2 and, critically, to determine if enhanced grain boundary diffusivity allows the model to better reproduce experimental results. The diffusivity as a function of temperature for different concentrations of uranium vacancies and interstitials for bulk UO 2 have also been examined using cluster dynamics. Furthermore, using a concentration dependent segregation model, the concentration of defects at the grain boundary were predicted. This atomistic data was then input into the various creep mechanisms and the creep rates compared to the empirical MATPRO correlation (used in BISON) and experiment.
Probing New physics with high-redshift quasars: axions and non-standard cosmology
The Hubble diagram of quasars, as candidates to “standardizable” candles, has been used to measure the expansion history of the Universe at late times, up to very high redshifts ( z ~ 7). It has been shown that this history, as inferred from the quasar dataset, deviates at ≳ 3 σ level from the concordance (ΛCDM) cosmology model preferred by the cosmic microwave background (CMB) and other datasets. In this article, we investigate whether new physics beyond ΛCDM (BΛCDM) or beyond the Standard Model (BSM) could make the quasar data consistent with the concordance model. We first show that an effective redshift-dependent relation between the quasar UV and X-ray luminosities, complementing previous phenomenological work in the literature, can potentially remedy the discrepancy. Such a redshift dependence can be realized in a BSM model with axion-photon conversion in the intergalactic medium (IGM), although the preferred parameter space is in tension with various other astrophysical constraints on axions, at a level depending on the specific assumptions made regarding the IGM magnetic field. We briefly discuss a variation of the axion model that could evade these astrophysical constraints. On the other hand, we show that models beyond ΛCDM such as one with a varying dark energy equation of state ( w CDM) or the phenomenological cosmographic model with a polynomial expansion of the luminosity distance, cannot alleviate the tension. The code for our analysis, based on emcee [1] and corner.py [2], is publicly available at github.com/ChenSun-Phys/high_z_candles.
Modeling Coupled Chemo-Mechanical Behavior of Randomly Oriented NMC811 Polycrystalline Li-Ion Battery Cathodes
This paper develops a three-dimensional, transient, chemo-mechanical model that predicts the performance of single secondary particle Li-ion battery cathodes. The secondary particles are composed of numerous (approximately 60) randomly oriented single-crystal primary particles. The model incorporates concentration-dependent and anisotropic material properties. As much as possible, electrochemical, transport, and structural properties for crystalline NMC811 (Li x Ni 0.8 Mn 0.1 Co 0.1 O 2 ) are taken from prior publications. Weak Van der Waals bonding between primary particles is modeled empirically using a spring analogy, which enables local primary-particle separations (disintegration) and subsequent reattachments. The model fully couples Li diffusion and the mechanical response. Results include predictions of local Li-concentrations and stresses. High stresses are found near grain boundaries, especially when the lattice orientations are greatly misaligned. Particle separations are characterized in terms of a damage parameter. The model is used to predict the effects of design and operating conditions, including charge/discharge rates, cycling scenarios, and particle sizes.