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DOE OSTI2019

Quantifying Soil Phosphorus Dynamics: A Data Assimilation Approach

The dynamics of soil phosphorus (P) control its bioavailability. Yet it remains a challenge to quantify soil P dynamics. In this work we developed a soil P dynamics (SPD) model. We then assimilated eight data sets of 426-day changes in Hedley P fractions into the SPD model, to quantify the dynamics of six major P pools in eight soil samples that are representative of a wide type of soils. The performance of our SPD model was better for labile P, secondary mineral P, and occluded P than for nonoccluded organic P (Po) and primary mineral P. All parameters describing soil P dynamics were approximately constrained by the data sets. The average turnover rates were labile P 0.040 g g -1 day-1, nonoccluded Po 0.051 g g -1 day -1 , secondary mineral P 0.023 g g -1 day -1 , primary mineral P 0.00088 g g -1 day -1 , occluded Po 0.0066 g g -1 day -1 , and occluded inorganic P 0.0065 g g -1 day -1 , in the greenhouse environment studied. Labile P was transferred on average more to nonoccluded Po (transfer coefficient of 0.42) and secondary mineral P (0.38) than to plants (0.20). Soil pH and organic C concentration were the key soil properties regulating the competition for P between plants and soil secondary minerals. The turnover rate of labile P was positively correlated with that of nonoccluded Po and secondary mineral P. The pool size of labile P was most sensitive to its turnover rate. Overall, we suggest data assimilation can contribute significantly to an improved understanding of soil P dynamics.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

Dynamical regimes of vortex flow in type-II superconductors with parallel twin boundaries

We explore the dynamics of driven magnetic flux lines in disordered type-II superconductors in the presence of twin boundaries oriented parallel to the direction of the applied magnetic field, using a three-dimensional elastic line model simulated with Langevin molecular dynamics. The lines are driven perpendicular to the planes to model the effect of an electric current applied parallel to the planes and perpendicular to the magnetic field. A study of the long-time non-equilibrium steady states for varying sample orientation and thickness reveals a rich collection of dynamical regimes spanning the depinning crossover region that separates the pinned and moving-lattice states of vortex matter. We observe the emergence of a preferred direction for the ordering of the Abrikosov lattice in the free- owing vortex regime due to asymmetric pinning by the planar defects. Furthermore, we have performed novel direct measurements of flux line excitations such as half-loops and double kinks to aid the characterization of the topologically rich flux flow profile.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2021

Rare Event Sampling Improves Mercury Instability Statistics

Due to the chaotic nature of planetary dynamics, there is a non-zero probability that Mercury's orbit will become unstable in the future. Previous efforts have estimated the probability of this happening between 3 and 5 billion years in the future using a large number of direct numerical simulations with an N-body code, but were not able to obtain accurate estimates before 3 billion years in the future because Mercury instability events are too rare. In this paper we use a new rare-event sampling technique, Quantile Diffusion Monte Carlo (QDMC), to estimate that the probability of a Mercury instability event in the next 2 billion years is approximately 10 –4 in the REBOUND N-body code. We show that QDMC provides unbiased probability estimates at a computational cost of up to 100 times less than direct numerical simulation. QDMC is easy to implement and could be applied to many problems in planetary dynamics in which it is necessary to estimate the probability of a rare event.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

Accelerating Ab Initio Simulation via Nested Monte Carlo and Machine Learned Reference Potentials

As a corollary of the rapid advances in computing, ab initio simulation is playing an increasingly important role in modeling materials at the atomic scale. Two strategies are possible, ab initio Monte Carlo (AIMC) and molecular dynamics (AIMD) simulation. The former benefits from exact sampling from the correct thermodynamic distribution, while the latter is typically more efficient with its collective all-atom coordinate updates. In this study, using a relatively simple test model comprised of helium and argon, we show that AIMC can be brought up to, and even above, the performance levels of AIMD via a hybrid nested sampling/machine learning (ML) strategy. Here, ML provides an accurate classical reference potential (up to three-body explicit interactions) that can pilot long collective Monte Carlo moves that are accepted or rejected in toto à la nested Monte Carlo (NMC); this is in contrast to the single move nature of a naive implementation. Our proposed method only requires a small up front expense from evaluating the ab initio energies and forces of (100) random configurations for training. Importantly, our method does not totally rely on the trained, assuredly imperfect, interaction. We show that high performance and exact sampling at the desired level of theory can be realized even when the trained interaction has appreciable differences from the ab initio potential. Remarkably, at the highest levels of performance realized via our approach, a pair of statistically uncorrelated atomic configurations can be generated with (1) ab initio calculations.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2022

Accurate quantification of lattice temperature dynamics from ultrafast electron diffraction of single-crystal films using dynamical scattering simulations

In ultrafast electron diffraction (UED) experiments, accurate retrieval of time-resolved structural parameters, such as atomic coordinates and thermal displacement parameters, requires an accurate scattering model. Unfortunately, kinematical models are often inaccurate even for relativistic electron probes, especially for dense, oriented single crystals where strong channeling and multiple scattering effects are present. This article introduces and demonstrates dynamical scattering models tailored for quantitative analysis of UED experiments performed on single-crystal films. As a case study, we examine ultrafast laser heating of single-crystal gold films. Comparison of kinematical and dynamical models reveals the strong effects of dynamical scattering within nm-scale films and their dependence on sample topography and probe kinetic energy. Applying to UED experiments on an 11 nm thick film using 750 keV electron probe pulses, the dynamical models provide a tenfold improvement over a comparable kinematical model in matching the measured UED patterns. Also, the retrieved lattice temperature rise is in very good agreement with predictions based on previously measured optical constants of gold, whereas fitting the Debye–Waller factor retrieves values that are more than three times lower. Altogether, these results show the importance of a dynamical scattering theory for quantitative analysis of UED and demonstrate models that can be practically applied to single-crystal materials and heterostructures.

36 MATERIALS SCIENCE↗

DOE OSTI2016

Ab initio molecular dynamics with nuclear quantum effects at classical cost: Ring polymer contraction for density functional theory

Path integral molecular dynamics simulations, combined with an ab initio evaluation of interactions using electronic structure theory, incorporate the quantum mechanical nature of both the electrons and nuclei, which are essential to accurately describe systems containing light nuclei. However, path integral simulations have traditionally required a computational cost around two orders of magnitude greater than treating the nuclei classically, making them prohibitively costly for most applications. Here we show that the cost of path integral simulations can be dramatically reduced by extending our ring polymer contraction approach to ab initio molecular dynamics simulations. By using density functional tight binding as a reference system, we show that our ring polymer contraction scheme gives rapid and systematic convergence to the full path integral density functional theory result. We demonstrate the efficiency of this approach in ab initio simulations of liquid water and the reactive protonated and deprotonated water dimer systems. We find that the vast majority of the nuclear quantum effects are accurately captured using contraction to just the ring polymer centroid, which requires the same number of density functional theory calculations as a classical simulation. Combined with a multiple time step scheme using the same reference system, which allows the time step to be increased, this approach is as fast as a typical classical ab initio molecular dynamics simulation and 35× faster than a full path integral calculation, while still exactly including the quantum sampling of nuclei. This development thus offers a route to routinely include nuclear quantum effects in ab initio molecular dynamics simulations at negligible computational cost.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2019

Continuous-time quantum walks on dynamic graphs

Continuous-time quantum walks (CTQWs) on static graphs provide efficient methods for search and sampling as well as a model for universal quantum computation. We consider an extension of CTQWs to the case of dynamic graphs, in which an ordered sequence of graphs governs free evolution of the quantum walk. We then consider how perfect state transfer during the quantum walk can be used to design dynamic graphs that implement a universal set of quantum logic gates. We give explicit examples for a complete logical basis, and we validate implementations using numerical simulations for quantum teleportation and addition circuits. Lastly, we discuss the potential for realizing CTQWs on dynamic graphs using actively controlled quantum optical waveguides.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

DOE OSTI2022

High-Throughput Microfluidics Platform for Intracellular Delivery and Sampling of Biomolecules from Live Cells

Nondestructive cell membrane permeabilization systems enable the intracellular delivery of exogenous biomolecules for cell engineering tasks as well as the temporal sampling of cytosolic contents from live cells for the analysis of dynamic processes. Here, in this paper, we report a microwell array format live-cell analysis device (LCAD) that can perform localized-electroporation induced membrane permeabilization, for cellular delivery or sampling, and directly interfaces with surface-based biosensors for analyzing the extracted contents. We demonstrate the capabilities of the LCAD via an automated high-throughput workflow for multimodal analysis of live-cell dynamics, consisting of quantitative measurements of enzyme activity using self-assembled monolayers for MALDI mass spectrometry (SAMDI) and deep-learning enhanced imaging and analysis. By combining a fabrication protocol that enables robust assembly and operation of multilayer devices with embedded gold electrodes and an automated imaging workflow, we successfully deliver functional molecules (plasmid and siRNA) into live cells at multiple time-points and track their effect on gene expression and cell morphology temporally. Furthermore, we report sampling performance enhancements, achieving saturation levels of protein tyrosine phosphatase activity measured from as few as 60 cells, and demonstrate control over the amount of sampled contents by optimization of electroporation parameters using a lumped model. Lastly, we investigate the implications of cell morphology on electroporation-induced sampling of fluorescent molecules using a deep-learning enhanced image analysis workflow.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

A combined static-dynamic single-dose imaging protocol to compare quantitative dynamic SPECT with static conventional SPECT

Background: SPECT myocardial perfusion imaging (MPI) is a clinical mainstay that is typically performed with static imaging protocols and visually or semi-quantitatively assessed for perfusion defects based upon the relative intensity of myocardial regions. Dynamic cardiac SPECT presents a new imaging technique based on time-varying information of radiotracer distribution, which permits the evaluation of regional myocardial blood flow (MBF) and coronary flow reserve (CFR). In this work, a preliminary feasibility study was conducted in a small patient sample designed to implement a unique combined static-dynamic single-dose one-day visit imaging protocol to compare quantitative dynamic SPECT with static conventional SPECT for improving the diagnosis of coronary artery disease (CAD). Methods: Fifteen patients (11 males, four females, mean age 71 ± 9 years) were enrolled for a combined dynamic and static SPECT (Infinia Hawkeye 4, GE Healthcare) imaging protocol with a single dose of {sup 99m}Tc-tetrofosmin administered at rest and a single dose administered at stress in a one-day visit. Out of 15 patients, eleven had selective coronary angiography (SCA), 8 within 6 months and the rest within 24 months of SPECT imaging, without intervening symptoms or interventions. The extent and severity of perfusion defects in each myocardial region was graded visually. Dynamically acquired data were also used to estimate the MBF and CFR. Both visually graded images and estimated CFR were tested against SCA as a reference to evaluate the validity of the methods. Results: Overall, conventional static SPECT was normal in ten patients and abnormal in five patients, dynamic SPECT was normal in 12 patients and abnormal in three patients, and CFR from dynamic SPECT was normal in nine patients and abnormal in six patients. Among those 11 patients with SCA, conventional SPECT was normal in 5, 3 with documented CAD on SCA with an overall accuracy of 64%, sensitivity of 40% and specificity of 83%. Dynamic SPECT image analysis also produced a similar accuracy, sensitivity, and specificity. CFR was normal in 6, each with CAD on SCA with an overall accuracy of 91%, sensitivity of 80%, and specificity of 100%. The mean CFR was significantly lower for SCA detected abnormal than for normal patients (3.86±1.06 vs 1.94±0. 0.67, P < 0.001). Conclusions: The visually assessed image findings in static and dynamic SPECT are subjective, and may not reflect direct physiologic measures of coronary lesion based on SCA. The CFR measured with dynamic SPECT is fully objective, with better sensitivity and specificity, available only with the data generated from the dynamic SPECT method.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2011

Mobility-Dependent Low-Frequency Noise in Graphene Field-Effect Transistors

We have investigated the low-frequency 1/f noise of both suspended and on-substrate graphene field-effect transistors and its dependence on gate voltage, in the temperature range between 300 and 30 K. We have found that the noise amplitude away from the Dirac point can be described by a generalized Hooge's relation in which the Hooge parameter {alpha}{sub H} is not constant but decreases monotonically with the device's mobility, with a universal dependence that is sample and temperature independent. The value of {alpha}{sub H} is also affected by the dynamics of disorder, which is not reflected in the DC transport characteristics and varies with sample and temperature. We attribute the diverse behavior of gate voltage dependence of the noise amplitude to the relative contributions from various scattering mechanisms, and to potential fluctuations near the Dirac point caused by charge carrier inhomogeneity. The higher carrier mobility of suspended graphene devices accounts for values of 1/f noise significantly lower than those observed in on-substrate graphene devices and most traditional electronic materials.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2016

Modelling economic losses of historic and present-day high-impact winter windstorms in Switzerland

This study investigates the wind gusts and associated economic loss patterns of high-impact winter windstorms in Switzerland between 1871 and 2011. A novel approach for simulating windstorm-related gusts and losses at regional to local scales is applied to a sample of 84 windstorms. The approach involves the dynamical downscaling of the Twentieth Century Reanalysis (20CR) ensemble mean to 3-km horizontal grid size using the Weather Research and Forecasting (WRF) model. Economic losses are simulated at municipal level for present-day asset distribution based on the downscaled (parameterised) wind gusts at high spatiotemporal resolution using the open-source impact model climada. A comparison with insurance loss data for two recent windstorms (“Lothar” in 1999, “Joachim” in 2011) indicates that the loss simulation allows to realistically simulate the spatial patterns of windstorm losses. The loss amplitude is strongly underestimated for ‘Lothar’, while it is in reasonable agreement for ‘Joachim’. Possible reasons are discussed. Uncertainties concerning the loss simulation arise from the wind gust estimation method applied; estimates can differ considerably among the different methods, in particular over high orography. Furthermore, the quality of the loss simulation is affected by the underlying simplified assumptions regarding the distribution of assets and their susceptibilities to damage. For the whole windstorm sample, composite averages of simulated wind gust speed and loss are computed. Both composites reveal high values for the densely populated Swiss Plateau and lower values for south-eastern Switzerland; metropolitan areas stand out in the loss composite. Eight of the top 10 events concerning the losses simulated for present-day asset distribution and summed over all Swiss municipalities occurred after 1950. It remains uncertain whether this is due to decadal-scale changes of winter windstorms in Switzerland or merely due to a possible bias of the 20CR ensemble mean towards lower wind speeds in the period before around 1950.

20CR↗

DOE OSTI2020

An Improved Genetic Algorithm approach to the Unit Commitment/Economic Dispatch problem

The deployment of new technologies, the importance of accurately modeling the dynamics of the generating units and the introduction of new policies are making the solution of the Unit Commitment/Economic Dispatch problem more and more complicated.In the present scenario, traditionally followed scheduling criteria might not lead to the optimal fleet configuration any more. In addition, most of the widely used techniques have limited capabilities at modeling the nonlinear dynamics of committed power plants. When realistic power systems comprising of several tens of generating units are modeled, the resulting optimization problem turns to be computationally intensive for the current computing capabilities. In this paper, an improved version of a GA-based optimization algorithm is presented. A detailed methodology aimed at obtaining a more efficient version of the GA, and a more detailed and accurate description of the flexible operation flexibility of the power plants is described.

genetic algorithm↗

DOE OSTI2016

Warming Alters Expressions of Microbial Functional Genes Important to Ecosystem Functioning

Soil microbial communities play critical roles in ecosystem functioning and are likely altered by climate warming. However, so far, little is known about effects of warming on microbial functional gene expressions. Here, we applied functional gene array (GeoChip 3.0) to analyze cDNA reversely transcribed from total RNA to assess expressed functional genes in active soil microbial communities after nine years of experimental warming in a tallgrass prairie. Our results showed that warming significantly altered the community wide gene expressions. Specifically, expressed genes for degrading more recalcitrant carbon were stimulated by warming, likely linked to the plant community shift toward more C 4 species under warming and to decrease the long-term soil carbon stability. In addition, warming changed expressed genes in labile C degradation and N cycling in different directions (increase and decrease), possibly reflecting the dynamics of labile C and available N pools during sampling. However, the average abundances of expressed genes in phosphorus and sulfur cycling were all increased by warming, implying a stable trend of accelerated P and S processes which might be a mechanism to sustain higher plant growth. Furthermore, the expressed gene composition was closely related to both dynamic (e.g., soil moisture) and stable environmental attributes (e.g., C 4 leaf C or N content), indicating that RNA analyses could also capture certain stable trends in the long-term treatment. Overall, this study revealed the importance of elucidating functional gene expressions of soil microbial community in enhancing our understanding of ecosystem responses to warming.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Characterizing laser-heated polymer foams with simultaneous x-ray fluorescence spectroscopy and Thomson scattering at the Matter in Extreme Conditions Endstation at LCLS

Understanding the behavior of polymer foams at high energy density conditions is crucial to advance inertial fusion energy research. Here, we present a new experimental platform designed to measure the thermodynamic state of these materials at megabar pressures. At the Matter in Extreme Conditions Endstation of the Linac Coherent Light Source, we heat samples using an optical, high-intensity, femtosecond laser and dynamically probe them with ultra-short, coherent x-ray pulses of high peak brightness. We perform x-ray Thomson scattering measurements in forward and backward scattering geometries to capture both collective and non-collective electron behavior in the sample. Simultaneously, x-ray fluorescence spectroscopy is used to measure the emission from a mid-Z dopant, providing complementary information on the plasma conditions. By combining these techniques, we obtain temporally resolved temperature measurements of the transient warm dense matter states. Our initial experiments designed to benchmark the platform with carbon samples yielded data resolving the ultrafast response to laser heating with sub-picosecond resolution, measuring plasma temperatures exceeding 50 eV. These findings lay the foundation for precision studies of the dynamic evolution of laser-heated polymer foams.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Importance Sampling Model-Based Diffusion for Trajectory Optimization

Trajectory optimization for robotic systems remains a challenging problem. This is especially true for robotic systems featuring nonlinear dynamics and many degrees of freedom. Data-based or model-free diffusion has recently been popularized in the fields of artificial intelligence and trajectory optimization. Model-Based Diffusion provides a data-free method of trajectory optimization, trained at runtime on a system dynamics model, suitable for high-dimensional models. This paper examines how importance sampling can enhance the performance of Model-Based Diffusion for trajectory optimization. Here, we quantify the benefits of importance sampling across three long horizon planning tasks. These results show as much as a 13x improvement in sample efficiency depending on environment and optimization parameters.

Golembeski, Seth [Georgia Institute of Technology,↗

DOE OSTI2017

Stacking caustic masses from galaxy clusters

Ongoing and future spectroscopic surveys will measure numerous galaxy redshifts within tens of thousands of galaxy clusters. However, the sampling within these clusters will be low, 15 1000 galaxies per ensemble phase space, the escape-velocity edge becomes readily identifiable and the presence of interloping galaxies is minimized. We develop and test an algorithm to trace the projected phase-space surface directly, which results in minimally biased dynamical mass estimates. We then quantify how binning and sampling affect the phase-space-based mass estimates when using an observational proxy that incorporates realistic mass scatter, like richness, and find the added uncertainty in the binning procedure has minimal influence on the resulting bias and scatter of the stacked mass estimates.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2014

Dynamic compressive and tensile strengths of spark plasma sintered alumina

Fully dense submicron grain size alumina samples were manufactured from alumina nano-powder using Spark Plasma Sintering and tested in two kinds of VISAR-instrumented planar impact tests. In the first kind, samples were loaded by 1-mm tungsten impactors, accelerated to a velocity of about 1 km/s. These tests were aimed at studying the Hugoniot elastic limit (HEL) of Spark Plasma Sintering (SPS)-processed alumina and the decay, with propagation distance, of the elastic precursor wave. In the tests of the second kind, alumina samples of 3-mm thickness were loaded by 1-mm copper impactors accelerated to 100–1000 m/s. These tests were aimed at studying the dynamic tensile (spall) strength of the alumina specimens. The tensile fracture of the un-alloyed alumina shows a monotonic decline of the spall strength with the amplitude of the loading stress pulse. Analysis of the decay of the elastic precursor wave allowed determining the rate of the irreversible (inelastic) strains in the SPS-processed alumina at the initial stages of the shock-induced inelastic deformation and to clarify the mechanisms responsible for the deformation. The 1-% addition of Cr{sub 2}O{sub 3} decreases the HEL of the SPS-processed alumina by 5-% and its spall strength by 50% but barely affects its static properties.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2022

Sensitive Measures of Soil Health Reveal Carbon Stability Across a Management Intensity and Plant Biodiversity Gradient

Soil carbon (C) is a major driver of soil health, yet little is known regarding how sensitive measures of soil C shift temporally within a single growing season in response to short-term weather perturbations. Our study aimed to i) Examine how long-term management impacts soil C cycling and stability across a management intensity and plant biodiversity gradient and ii) Assess how sensitive soil health indicators change temporally over the course of a single growing season in response to recent weather patterns. Here we quantify a variety of sensitive soil C measures at four time points across the 2021 growing season at the W.K. Kellogg Biological Station’s Long Term Ecological Research Trial (LTER) located in southwest Michigan, USA. The eight systems sampled included four annual soybean ( Glycine max ) systems that ranged in management intensity (conventional, no-till, reduced input, and biologically-based), two perennial biofuel cropping systems (switchgrass ( Panicum virgatum) and hybrid poplars ( Populus nigra x P.maximowiczii )), and two unmanaged systems (early successional system and a mown but never tilled grassland). We found that unmanaged systems with increased perenniality enhanced mineralizable C (Min C) and permanganate oxidizable C (POXC) values. Additionally, all soil health indicators were found to be sensitive to changes in short-term weather perturbations over the course of the growing season. The implications of this study are threefold. First, this study assess indicators of labile and stable C pools over the course of the growing season and reflects the stability of soil C in different systems. Second, POXC, Min C, and ß-glucosidase (GLU) activity are sensitive soil health indicators that fluctuate temporally, which means that these soil health indicators could help elucidate the impact that weather patterns have on soil C dynamics. Lastly, for effective monitoring of soil C, sampling time and frequency should be considered for a comprehensive understanding of soil C cycling within a system.

Martin, Tvisha↗