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At least 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Progress on the reevaluation and validation of the n+233U neutron cross sections

The set of 233 U resonance parameters of the ENDF/B-VIII.0 nuclear data library was adopted from the previous ENDF/B-VII.1 evaluation using the external levels to update the thermal values. Adoption of IAEA 2017 thermal standards ( σ f = 533.0 ± 2.2 b, σ c = 44.9 ± 0.9 b, and ν ‾ tot = 2.487 ± 0.011 ) and of the IAEA-recommended thermal-neutron induced prompt fission neutron spectrum (PFNS) with average PFNS energy of 2.030 ± 0.013 MeV requires a re-evaluation of 233 U neutron cross sections in the resolved resonance region. A newly produced evaluation is being tested on benchmarks carefully selected from the Handbook of International Criticality Safety Benchmark Experiments (ICSBEP) which are highly sensitive to 233 U data. An important goal of this work was to eliminate the strong negative gradient of the calculated effective multiplication factors with respect to the epithermal fission fraction observed in the validation of the ENDF/B-VIII.0 library for those assemblies. A significant improvement in integral performance of critical 233 U solutions is observed for the newly proposed evaluation. Further work addressing the fast neutron region is needed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Development of Direct Injection/Ionization Mass Spectrometry Methods for Whole Molecule Characterization

The objective of this work is to adapt ambient ionization mass spectrometry (AMS) techniques for the rapid analysis of intact uranium complexes, stable strontium, cerium, and explosive compounds. The methods used were “soft ionization” techniques, which facilitate the detection of whole molecule complexes. The soft ionization mass spectrometry (MS) techniques that were investigated include paper spray ionization (PSI), matrix-assisted ionization (MAI), electrospray ionization (ESI) and direct analysis in real time (DART). For the first time, PSI-MS methods were successfully developed for whole molecule uranium-containing analytes (uranyl acetate, uranyl nitrate, and uranyl-tributylphosphate complexes). This was also the first demonstration of uranium complex detection and characterization and one of the few examples of inorganic analysis using MAI techniques. Proof of concept experiments also putatively identified matrix-derived ions and ion complexes that have not previously been described in the literature. Additionally, PSI-MS on cotton swipe samples doped with a multi-element standard containing μg levels of U, Bi, Pb, Cd, Fe, and Zn were directly analyzed without purification, representing a major improvement over existing methods. Both PSI and MAI methods demonstrated limits of detection (LODs) in the 10 - 100’s ng for various uranyl species within a range of 10’s ppm - 100’s ppb, dependent on analytical method and analyte species. AMS methods were also developed for other inorganics, including Ce and Sr, and organic explosive residues to address specific challenges in environmental monitoring and forensics. Further refinement and qualification of the AMS techniques developed within this effort would lead to significant cost reduction and timeliness by facilitating the triage and queueing of samples for subsequent more sensitive and time-consuming analyses.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Cosmic shear cosmology beyond two-point statistics: a combined peak count and correlation function analysis of DES-Y1

ABSTRACT We constrain cosmological parameters from a joint cosmic shear analysis of peak-counts and the two-point shear correlation functions, as measured from the Dark Energy Survey (DES-Y1). We find the structure growth parameter $S_8\equiv \sigma _8\sqrt{\Omega _{\rm m}/0.3} = 0.766^{+0.033}_{-0.038}$ which, at 4.8 per cent precision, provides one of the tightest constraints on S8 from the DES-Y1 weak lensing data. In our simulation-based method we determine the expected DES-Y1 peak-count signal for a range of cosmologies sampled in four w cold dark matter parameters (Ωm, σ8, h, w0). We also determine the joint covariance matrix with over 1000 realizations at our fiducial cosmology. With mock DES-Y1 data we calibrate the impact of photometric redshift and shear calibration uncertainty on the peak-count, marginalizing over these uncertainties in our cosmological analysis. Using dedicated training samples we show that our measurements are unaffected by mass resolution limits in the simulation, and that our constraints are robust against uncertainty in the effect of baryon feedback. Accurate modelling for the impact of intrinsic alignments on the tomographic peak-count remains a challenge, currently limiting our exploitation of cross-correlated peak counts between high and low redshift bins. We demonstrate that once calibrated, a fully tomographic joint peak-count and correlation functions analysis has the potential to reach a 3 per cent precision on S8 for DES-Y1. Our methodology can be adopted to model any statistic that is sensitive to the non-Gaussian information encoded in the shear field. In order to accelerate the development of these beyond-two-point cosmic shear studies, our simulations are made available to the community upon request.

Harnois-Déraps, Joachim↗
DOE OSTI2023

Surface Roughness Effects from Additive Manufacturing in High Efficiency Gas Turbine Combustion Systems

In the past, clean combustion systems were characterized by high system development costs due to growing complexity and escalating manufacturing costs from conventional manufacturing processes. As a result, high efficiency concepts are difficult to design and more difficult to be cost-effectively manufactured. In recent years, with the introduction of additive manufacturing (AM) technologies, the rapid prototyping and mass production processes of clean combustion systems are promising to be significantly simplified with significant reduction in terms of engine manufacturing cost and engine energy cost. Compared with conventional manufacturing built parts, the AM process enabled a simpler design to be adopted for the nozzle, reducing the number of required braze and weld joints from twenty-five to just five. The resulting nozzle was 25% lighter and five times more durable and contributed to a 15% reduction in fuel burn in comparison with the previous model produced. Applying these improvements to a fleet of 5,000 turbofan engines at 150 kN thrust would result in fuel cost savings of $ \$ $6B annually (at $ \$ $5/gallon Jet-A fuel price, 700 gallon/hour fuel consumption rate, and 2,300 operational hours per year), and reduce CO2 emissions by more than 25 million tons per year. These advances support core Department of Energy (DOE) missions in energy efficiency, improving productivity, and environmental sustainability. Maximizing the benefit of these new capabilities will require high prediction capability of high speed turbulent flow with wall modeled Large Eddy Simulation (LES). GE Aviation maintains that advanced simulation technology and supercomputing is required in order to provide the appropriate boundary conditions to realize the maximum potential of AM and Ceramic Matrix Composite to reduce cooling flow, a first order penalty on the Brayton cycle. The algorithm developed using the ANSYS/Fluent software would provide the foundation for entirely new avenues of research and development with potential multi-billion dollar impact to the US economy, and significant reduction in carbon based emissions across the aerospace and power generation industries. The formulation of this iWLES (integral wall model for LES) is generic and allows to capture the changes in flow dynamics that have a significant impact on the wall bounded flow characteristics, such as swirler effective area, bulk swirl number, local pressure distribution, exit velocity profile, and turbulence kinetic energy profile. A periodic channel flow with rough flat plate is simulated using LES (Wall-Adapting Local Eddy-viscosity) model to verify the implementation of iWLES in the Fluent User Defined Function (UDF). As the flow fields are highly sensitive due to surface roughness of the wall bounded flows in the combustion systems, there is significant potential to conduct further LES studies focusing on the turbulence boundary layer interaction. Accurately capturing near wall physics will elucidate the impact of rough surfaces on combustor flow and aero-thermal interactions.

42 ENGINEERING↗
DOE OSTI2023

Surface Roughness Effects from Additive Manufacturing in High Efficiency Gas Turbine Combustion Systems

In the past, clean combustion systems were characterized by high system development costs due to growing complexity and escalating manufacturing costs from conventional manufacturing processes. As a result, high efficiency concepts are difficult to design and more difficult to be cost-effectively manufactured. In recent years, with the introduction of additive manufacturing (AM) technologies, the rapid prototyping and mass production processes of clean combustion systems are promising to be significantly simplified with significant reduction in terms of engine manufacturing cost and engine energy cost. Compared with conventional manufacturing built parts, the AM process enabled a simpler design to be adopted for the nozzle, reducing the number of required braze and weld joints from twenty-five to just five. The resulting nozzle was 25% lighter and five times more durable and contributed to a 15% reduction in fuel burn in comparison with the previous model produced. Applying these improvements to a fleet of 5,000 turbofan engines at 150 kN thrust would result in fuel cost savings of $6B annually (at $5/gallon Jet-A fuel price, 700 gallon/hour fuel consumption rate, and 2,300 operational hours per year),and reduce CO2 emissions by more than 25 million tons per year. These advances support core Department of Energy (DOE)missions in energy efficiency, improving productivity, and environmental sustainability. Maximizing the benefit of these new capabilities will require high prediction capability of high speed turbulent flow with wall modeled Large Eddy Simulation (LES). GE Aviation maintains that advanced simulation technology and supercomputing is required in order to provide the appropriate boundary conditions to realize the maximum potential of AM and Ceramic Matrix Composite to reduce cooling flow, a first order penalty on the Brayton cycle. The algorithm developed using the ANSYS/Fluent software would provide the foundation for entirely new avenues of research and development with potential multi-billion dollar impact to the US economy, and significant reduction in carbon based emissions across the aerospace and power generation industries. The formulation of this iWLES (integral wall model for LES) is generic and allows to capture the changes in flow dynamics that have a significant impact on the wall bounded flow characteristics, such as swirler effective area, bulk swirl number, local pressure distribution, exit velocity profile, and turbulence kinetic energy profile. A periodic channel flow with rough flat plate is simulated using LES (Wall-Adapting Local Eddy-viscosity) model to verify the implementation of iWLES in the Fluent User Defined Function (UDF). As the flow fields are highly sensitive due to surface roughness of the wall bounded flows in the combustion systems, there is significant potential to conduct further LES studies focusing on the turbulence boundary layer interaction. Accurately capturing near wall physics will elucidate the impact of rough surfaces on combustor flow and aero-thermal interactions.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Prompt Gamma Analysis of ARIES Materials and Updates to the 2015 Calibration Equations

Prompt gamma (PG) analysis is a nondestructive, nuclear, elemental analysis technique that uses charged particle reactions to interrogate a sample, and elements present in the sample matrix are identified through the characteristic gamma-rays emitted from the product nuclei in alpha-p and alpha-n nuclear reactions. This technique has been applied to plutonium oxide packaged in over 4,000 individual 3013 containers, and the concentrations of certain light elements were determined from the integrated peak areas based on a calibration that was published previously. This report provides the results for a new population of 3013 containers packaged with oxide materials produced by the conversion of metal by Advanced Recovery and Integrated Extraction System (ARIES) project using the direct metal oxidation (DMO) process and muffle furnaces. New PG and analytical chemistry data collected since 2015 were added to the existing calibration data sets to refine the calibration parameters. Calibration equations were also developed for determining beryllium and fluorine at low concentrations in high-purity ARIES product oxides. The new fluorine calibration provides an order of magnitude greater sensitivity and results in an additional 1,408 containers in the original population identified as having fluorine as an impurity. Additionally, equations for calculating the lower limits of detection (LLDs) as a function of the actual counting time (live time) were obtained using WLS regression technique for samples in the calibration data set. This resulted in changes to the LLDs published previously.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Modulation of Akt vs Stat3 activity by the focal adhesion kinase in non-neoplastic mouse fibroblasts

Adhesion of cells to each other and to the extracellular matrix (ECM) are both required for cellular functions. Cell-to-cell adhesion is mediated by cadherins and their engagement triggers the activation of Stat3, which offers a potent survival signal. Adhesion to the ECM on the other hand, activates FAK which attracts and activates Src, as well as receptor tyrosine kinases (RTKs), the PI3k/Akt and Ras/Erk pathways. However, the effect of cell density upon FAK and Akt activity has not been examined. We now demonstrate that, interestingly, despite being potent Stat3 activators, Src and RTKs are unable to activate Stat3 in sparsely growing (i.e., without cadherin engagement), non-neoplastic cells attached to the ECM. In contrast, cell aggregation (i.e., cadherin engagement in the absence of adhesion to a solid substratum) was found to activate both Stat3 and Akt. Pharmacologic or genetic reduction of FAK activity abolished Akt activity at low densities, indicating that FAK is an important activator of Akt in this setting. Notably, FAK knockout increased cellular sensitivity to the Stat3 inhibitor CPA7, while FAK reintroduction restored resistance to this drug. These findings suggest a complementary role of integrin/FAK/Akt and cadherin/Stat3-mediated pro-survival pathways, which may be of significance during neoplastic transformation and metastasis.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Modelling nearest neighbour distributions of biased tracers using hybrid effective field theory

ABSTRACT We investigate the application of hybrid effective field theory (HEFT) – which combines a Lagrangian bias expansion with subsequent particle dynamics from N-body simulations – to the modelling of k-nearest neighbour cumulative distribution functions (kNN-CDFs) of biased tracers of the cosmological matter field. The kNN-CDFs are sensitive to all higher order connected N-point functions in the data, but are computationally cheap to compute. We develop the formalism to predict the kNN-CDFs of discrete tracers of a continuous field from the statistics of the continuous field itself. Using this formalism, we demonstrate how kNN-CDF statistics of a set of biased tracers, such as haloes or galaxies, of the cosmological matter field can be modelled given a set of low-redshift HEFT component fields and bias parameter values. These are the same ingredients needed to predict the two-point clustering. For a specific sample of haloes, we show that both the two-point clustering and the kNN-CDFs can be well-fit on quasi-linear scales (≳ 20h−1Mpc) by the second-order HEFT formalism with the same values of the bias parameters, implying that joint modelling of the two is possible. Finally, using a Fisher matrix analysis, we show that including kNN-CDF measurements over the range of allowed scales in the HEFT framework can improve the constraints on σ8 by roughly a factor of 3, compared to the case where only two-point measurements are considered. Combining the statistical power of kNN measurements with the modelling power of HEFT, therefore, represents an exciting prospect for extracting greater information from small-scale cosmological clustering.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Search for Heavy Neutral Leptons at the MINER$\nu$A detector

Heavy Neutral Leptons (HNL) are particles hypothesised to provide a mass generation mechanism for the active (observed) neutrino species, which are known to have nonzero mass from the definitive observation of neutrino oscillations. HNL are eigenstates of mass of the order $\mathcal{O}(0.1 − 1\,\,\mathrm{GeV}/c^{2})$, which mix into the active flavour eigenstates through the extended leptonic mixing matrix. Apart from neutrino mass, they could provide a natural dark matter candidate and a mechanism for matter-antimatter asymmetry in the early Universe, giving rise to today’s matter-dominated cosmos. Searches for HNL typically attempt to either confirm the existence of HNL through an excess in data that is most compatible with an HNL hypothesis, or by setting limits on the HNL parameter space $\left(M_{N4}, \left|U_{\alpha 4}\right|^{2}\right)$ in the case of statistically insignificant excess. Such searches are intensifying as part of a global research programme at both colliders and accelerator / atmospheric neutrino experiments. One such setting is the MINER$\nu$A experiment, located in the NuMI beamline at Fermilab. MINER$\nu$A has collected a large amount of data over seven years of operation to measure the cross-sections of neutrino-nucleus interactions necessary to drive systematic uncertainties down, in order for neutrino oscillation experiments to achieve sensitivity to CP violation in the neutrino sector. With the high-energy, high-intensity NuMI beam, and with good timing, position, and angular resolution leading to sensitivity to HNL decays, MINER$\nu$A is fertile ground for an HNL search, which is performed in this thesis. Specifically, a novel, experiment-agnostic and general simulation of HNL production and decay is presented and deployed; this simulation has been incorporated in the ubiquitous GENIE neutrino event generator for use with neutrino experiments in the future. The event selection and background characterisation is discussed in detail, including the primary background coming from charged-current coherent and diffractive pion production from neutrino-nucleus interactions, and constraints on the background using control regions from MINER$\nu$A data are derived. Finally, by means of a fake-data study given a background of $\mathcal{O}(500)$ events, the discovery potential and limit-setting capacity of MINER$\nu$A is demonstrated, and ways to improve this capacity are expounded upon.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Environmental matrix and moisture are key determinants of microbial phenotypes expressed in a reduced complexity soil-analog

Soil moisture and porosity regulate microbial metabolism by influencing factors such as redox conditions, substrate availability, and soil connectivity. However, the inherent biological, chemical, and physical heterogeneity of soil complicates laboratory investigations into microbial phenotypes that mediate community metabolism. This difficulty arises from challenges in accurately representing the soil environment and in establishing a tractable microbial community that limits confounding variables. To address these challenges in our investigation of community metabolism, we use a reduced-complexity microbial consortium grown in a soil analog using a glass-bead matrix amended with chitin. Long-read and short-read metagenomes, metatranscriptomes, metaproteomes, and metabolomes were analyzed to test the effects of soil structure and moisture on chitin degradation. Our soil structure analog system greatly altered microbial expression profiles compared to the liquid-only incubations, emphasizing the importance of incorporating environmental parameters, like pores and surfaces, for understanding microbial phenotypes relevant to soil ecosystems. These changes were mainly driven by differences in overall expression of chitin-degrading Streptomyces species and stress-tolerant Ensifer. Our findings suggest that the success of Ensifer in a structured environment is likely related to its ability to repurpose carbon via the glyoxylate shunt while potentially using polyhydroxyalkanoate granules as a C source. We also identified traits like motility, stress resistance, and biofilm formation that underlie the degradation of chitin across our treatments and inform how they may ultimately alter carbon use efficiency. Together our results demonstrate that community functions like decomposition are sensitive to environmental conditions and more complex than the multi-enzyme pathways involved in depolymerization.

Rodriguez-Ramos, Josue A↗
DOE OSTI2022

Exploring the Use of Novel Spatial Accelerators in Scientific Applications

Driven by the need to find alternative accelerators which can viably replace GPUs in next-generation Supercomputing systems, this paper proposes a methodology to enable agile application/hardware co-design. The application-first methodology provides the ability to come up with design of accelerators while working with real-world workloads, available accelerators, and system software. The iterative design process targets a set of kernels in a workload for performance estimates that can prune the design space for later phases of detailed architectural evaluations. To this effect, in this paper, a novel data-parallel device model is introduced that simulates the latency of performance-sensitive operations in an accelerator including data transfers and kernel computation using multi-core CPUs. The use of off-the-shelf simulators, such as pre-RTL simulator Aladdin or multiple tools available for exploring the design of deep neural network accelerators (e.g., Timeloop) is demonstrated for evaluation of various accelerator designs using applications with realistic inputs. Examples of multiple device configurations that are instantiable in a system are explored to evaluate the performance benefit of deploying novel accelerators. The proposed device is integrated with a programming model and system software to potentially explore the impacts of high-level programming languages/compilers and low-level effects such as task scheduling on multiple accelerators. We analyze our methodology for a set of applications that represent high-performance computing (HPC) and graph analytics. The applications include a computational chemistry kernel realized using tensor contractions, triangle counting, GraphSAGE and Breadth-first Search. These applications include kernels such as dense matrix-dense matrix multiplication, sparse matrix-spare matrix multiplication, and sparse matrix-dense vector multiplication. Our results indicate potential performance benefits and insights for system design by including accelerators that realize these kernels along-side general purpose accelerators.

AI, codesign, Accelerated Computing, Modeling and ↗
DOE OSTI2022

Fundamental Investigations into the Properties and Performance of Advanced Materials

Intelligent engineering designs require an accurate understanding of material behavior, since any uncertainties or gaps in knowledge must be counterbalanced with heightened factors of safety, leading to overdesign. Therefore, building better structures and pushing the performance of new components requires an improved understanding of the thermomechanical response of advanced materials under service conditions. This dissertation provides fundamental investigations of several advanced materials: thermoset polymers, a common matrix material for fiber-reinforced composites and nanocomposites; aluminum alloy 7075-T6 (AA7075-T6), a high-performance aerospace material; and ceramic matrix composites (CMCs), an advanced composite for extreme-temperature applications. To understand matrix interactions with various interfaces and nanoinclusions at their fundamental scale, the properties of thermoset polymers are studied at the atomistic scale. An improved proximity-based molecular dynamics (MD) technique for modeling the crosslinking of thermoset polymers is carefully established, enabling realistic curing simulations through its ability to dynamically and probabilistically perform complex topology transformations. The proximity-based MD curing methodology is then used to explore damage initiation and the local anisotropic evolution of mechanical properties in thermoset polymers under uniaxial tension with an emphasis on changes in stiffness through a series of tensile loading, unloading, and reloading experiments. Aluminum alloys in aerospace applications often require a fatigue life of over 109 cycles, which is well over ii the number of cycles that can be practically tested using conventional fatigue testing equipment. In order to study these high-life regimes, a detailed ultrasonic cycle fatigue study is presented for AA7075-T6 under fully reversed tension-compression loading. The geometric sensitivity, frequency effects, size effects, surface roughness effects, and the corresponding failure mechanisms for ultrasonic fatigue across different fatigue regimes are investigated. Finally, because CMCs are utilized in extreme environments, oxidation plays an important role in their degradation. A multiphysics modeling methodology is thus developed to address the complex coupling between oxidation, mechanical stress, and oxygen diffusion in heterogeneous carbon fiber-reinforced CMC microstructures.

Schichtel, Jacob J.↗
DOE OSTI2024

Globally optimal interferometry with lossy twin Fock probes

Parity or quadratic spin (e.g., J z 2 ) readouts of a Mach–Zehnder (MZ) interferometer probed with a twin Fock (TF) input state allow saturating the optimal sensitivity attainable among all mode-separable states with a fixed total number of particles but only when the interferometer phase θ is near zero. When more general Dicke state probes are used, the parity readout saturates the quantum Fisher information (QFI) at θ = 0, whereas better-than-standard quantum limit performance of the J z 2 readout is restricted to an o ( N ) occupation imbalance. We show that a method of moments readout of two quadratic spin observables J z 2 and J + 2 + J − 2 is globally optimal for Dicke state probes; i.e., the error saturates the QFI for all θ . In the lossy setting, we derive the time-inhomogeneous Markov process describing the effect of particle loss on TF states, showing that the method of moments readout of four at-most-quadratic spin observables is sufficient for globally optimal estimation of θ when two or more particles are lost. The analysis culminates in a numerical calculation of the QFI matrix for distributed MZ interferometry on the four-mode state | N 4 , N 4 , N 4 , N 4 〉 and its lossy counterparts, showing that an advantage for the estimation of any linear function of the local MZ phases θ 1 and θ 2 (compared to independent probing of the MZ phases by two copies of | N 4 , N 4 〉 ) appears when more than one particle is lost.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Understanding Differences in Water Adsorption Isotherms: Structural Variations, Force Fields, and Monte Carlo Simulation Approaches

Accurate prediction of water adsorption in micro- and mesoporous materials with hydrophobic pores is essential for the design and characterization of advanced adsorbent materials for separation and energy applications. Here, we assess the reproducibility and consistency of water adsorption isotherms in two microporous all-silica MFI zeolite structures (MFI-K and MFI-O) using two different zeolite force fields and three simulation approaches: grand canonical Monte Carlo (GCMC), Gibbs ensemble Monte Carlo (GEMC), and transition matrix Monte Carlo (TMMC). We demonstrate that consistent treatment of the bulk fluid phase in GCMC and TMMC simulations is critical for reconciling isotherms across methods, and we construct simulation-based equations of state for the TIP4P water model to enable rigorous fugacity-to-pressure conversions. Large shifts in the isotherms are observed for two zeolite force fields developed using different parametrization strategies, with the GCS force field representing implicitly a defect-containing all-silica zeolite, whereas the TraPPE-zeo force field accurately represents an essentially defect-free all-silica zeolite. While water in the van Koningsveld structure of MFI exhibits a first-order phase transition and condensation-like step for adsorption near room temperature, water in the Olson structure of MFI displays continuous adsorption, attributed to differences in the adsorption free energy landscapes. Structural analysis reveals that small geometric variations, particularly Si–O–Si bond angles near the strongest adsorption sites, lead to these substantial differences in adsorption behavior. Furthermore, our results highlight the sensitivity of simulated water adsorption isotherms in hydrophobic frameworks to seemingly small differences in the framework structures, force field parametrization, and simulation approaches.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A computationally-efficient method for flamelet calculations

A new open-source code for the simulation of the diffusion flamelet equations is proposed. Emphasis is placed on using an approximate Jacobian to reduce the computational cost of the matrix operations. Performance of the proposed solvers is tested by performing flamelet calculations with kinetic mechanisms of varying sizes. For the unity Lewis number equations, the present iterative Newton solver using an approximate Jacobian greatly outperforms direct Newton solvers using exact Jacobians. The computation cost scales linearly with the number of species, leading to a reduction in solution times by two orders of magnitude for mechanisms containing thousands of species. The applicability of the Jacobian approximations to the solution of the non-unity Lewis number flamelet equations is assessed. The approximations are generally inadequate to solve the full non-unity Lewis number equations but can be used in some applications depending on the balance of terms in the flamelet equations. As an example, the flamelet solver is applied to the study of sooting tendencies in laminar co-flow diffusion flames where modified non-unity Lewis number flamelet equations, previously shown to accurately reproduce experimentally-measured Yield Sooting Indices (YSI), are solved. Here, the accelerated flamelet solver is well suited for sensitivity analysis and uncertainty quantification with large detailed kinetic mechanisms, tasks for which the computational cost was previously prohibitive.

42 ENGINEERING↗
DOE OSTI2020

Extended Lagrangian Born–Oppenheimer molecular dynamics using a Krylov subspace approximation

It is shown how the electronic equations of motion in extended Lagrangian Born–Oppenheimer molecular dynamics simulations can be integrated using low-rank approximations of the inverse Jacobian kernel. This kernel determines the metric tensor in the harmonic oscillator extension of the Lagrangian that drives the evolution of the electronic degrees of freedom. The proposed kernel approximation is derived from a pseudoinverse of a low-rank estimate of the Jacobian, which is expressed in terms of a generalized set of directional derivatives with directions that are given from a Krylov subspace approximation. The approach allows a tunable and adaptive approximation that can take advantage of efficient preconditioning techniques. The proposed kernel approximation for the integration of the electronic equations of motion makes it possible to apply extended Lagrangian first-principles molecular dynamics simulations to a broader range of problems, including reactive chemical systems with numerically sensitive and unsteady charge solutions. This can be achieved without requiring exact full calculations of the inverse Jacobian kernel in each time step or relying on iterative non-linear self-consistent field optimization of the electronic ground state prior to the force evaluations as in regular direct Born–Oppenheimer molecular dynamics. We note the low-rank approximation of the Jacobian is directly related to Broyden’s class of quasi-Newton algorithms and Jacobian-free Newton–Krylov methods and provides a complementary formulation for the solution of nonlinear systems of equations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Ab initio ultrafast spin dynamics in solids

Spin relaxation and decoherence is at the heart of spintronics and spin-based quantum information science. Currently, theoretical approaches that can accurately predict spin relaxation of general solids including necessary scattering pathways and are capable of nanosecond to millisecond simulation time are urgently needed. We present a first-principles real-time density-matrix approach based on Lindblad dynamics to simulate ultrafast spin dynamics for general solid-state systems. Through the complete first-principles descriptions of pump, probe, and scattering processes including electron-phonon, electron-impurity, and electron-electron scatterings with self-consistent electronic spin-orbit couplings, our method can directly simulate the ultrafast pump-probe measurements for coupled spin and electron dynamics over nanoseconds at any temperatures and doping levels. We first apply this method to a prototypical system GaAs and obtain excellent agreement with experiments. We found that the relative contributions of different scattering mechanisms and phonon modes differ considerably between spin and carrier relaxation processes. In sharp contrast to previous work based on model Hamiltonians, we point out that the electron-electron scattering is negligible at room temperature but becomes dominant at low temperatures for spin relaxation in n-type GaAs. We further examine ultrafast dynamics in novel spin-valleytronic materials: monolayer and bilayer WSe 2 with realistic defects. We find that spin relaxation is highly sensitive to local symmetry and chemical bonds around defects. For the bilayer WSe 2 , we identify the scattering pathways in ultrafast dynamics and determine relevant dynamical properties, essential to its utilization of unique spin-valley-layer locking effects. In conclusion, our work provides a predictive computational platform for spin dynamics in solids, which has potential for designing new materials ideal for spintronics and quantum information technology.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗