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At least 487 records · Page 27

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DOE OSTI2022

Piecewise interaction picture density matrix quantum Monte Carlo

The density matrix quantum Monte Carlo (DMQMC) set of methods stochastically samples the exact N-body density matrix for interacting electrons at finite temperature. We introduce a simple modification to the interaction picture DMQMC (IP-DMQMC) method that overcomes the limitation of only sampling one inverse temperature point at a time, instead allowing for the sampling of a temperature range within a single calculation, thereby reducing the computational cost. At the target inverse temperature, instead of ending the simulation, we incorporate a change of picture away from the interaction picture. The resulting equations of motion have piecewise functions and use the interaction picture in the first phase of a simulation, followed by the application of the Bloch equation once the target inverse temperature is reached. We find that the performance of this method is similar to or better than the DMQMC and IP-DMQMC algorithms in a variety of molecular test systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Progress toward hydro-equivalent ignition in OMEGA direct-drive DT-layered implosions

Considerable progress has been made in deuterium-tritium-layered implosion experiments on the OMEGA Laser System, bringing the prospects for thermonuclear ignition in direct-drive configurations with megajoule-class lasers closer to reality. Doing so has required navigating the balance between improved 1D performance and multidimensional stability. Using statistical modeling based on over 350 cryogenic implosions to identify various degradation mechanisms, and combined with multidimensional simulations and experimental techniques such as target offsets to combat residual flows, core conditions have repeatably been achieved that extrapolate to the burning-plasma state when scaled to 2.15 MJ of symmetric laser illumination. Using high implosion velocities (⁠> 450 km/s) and moderately high adiabats (⁠~5⁠), these experiments produced record-high scaled Lawson parameters in direct drive equal to 89 ± 2% of that required for ignition with expected yields of up to 1.5 ± 0.2 MJ. To improve these results still further, focused physics studies are performed to improve physics understanding and identify routes to even greater performance. Recent studies include investigations into the impact of mounting features, laser imprint, reduced fuel temperatures, and greater on-target intensities through subscale experiments. This manuscript gives a summary of the cryogenic direct-drive program on the OMEGA laser, including routes taken to achieve the current best performance, the status of recent focused physics investigations, and future designs—such as target solutions to laser imprint and reducing vapor density to increase convergence—that are expected lead to the demonstration of hydro-equivalent ignition on OMEGA.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Adaptive Client Selection in Federated Learning: A Network Anomaly Detection Use Case

Federated Learning (FL) has become a ubiquitous approach for training machine learning models on decentralized data, addressing the myriad privacy concerns inherent in traditional centralized methods. However, the efficiency of FL depends on effective client selection and robust privacy preservation mechanisms. Inadequate client selection may lead to suboptimal model performance, while insufficient privacy measures risk exposing sensitive data. This paper proposes a client selection framework for FL that integrates differential privacy and fault tolerance. Our adaptive approach dynamically adjusts the number of selected clients based on model performance and system constraints, ensuring privacy through calibrated noise addition. We evaluate our method on a network anomaly detection use case using the UNSW-NB15 and ROAD datasets. Results show up to a 7% increase in accuracy and a 25% reduction in training time compared to FedL2P. Moreover, we highlight the trade-offs between privacy budgets and model performance, with higher privacy budgets reducing noise and improving accuracy. Our fault tolerance mechanism, while causing a slight performance drop, enhances robustness to client failures. Statistical validation using Mann-Whitney U tests confirms the significance of these improvements (p < 0.05).

Marfo, William [University of Texas at El Paso,Dep↗

DOE OSTI2026

Pinned Clouds over Industrial Sources of Heat during TRACER

An analysis of stereo-camera data from the Tracking Aerosol Convection Interactions Experiment (TRACER) campaign in Houston, Texas, reveals the existence of pinned clouds sitting atop industrial heat sources. These are not plumes of vapor and condensate emanating from stacks: The pinned shallow cumuli have cloud bases at about the lifting condensation of near-surface air. On many mornings, the pinned clouds are the only shallow cumuli in the field of view of the stereo cameras, persisting by themselves for at least an hour. On those mornings, the lower atmosphere straddles the boundary between stable and unstable, and the waste heat from industrial facilities is able to pin moist convection overhead. When solar heating of the surface becomes sufficient later in the morning, those mornings transition to having widespread shallow moist convection. Occurring within the field of view of the stereo cameras and other TRACER instruments, these pinned clouds represent steady plume-like moist convection triggered by known heat sources in a well-characterized atmosphere, making them a rich target for further study. Significance Statement This article introduces steady-state cumulus clouds observed during the Tracking Aerosol Convection Interactions Experiment (TRACER) campaign that were pinned to industrial heat sources. These pinned clouds were present in the early morning only when conditions were primed for moist convection, but for which there was not yet enough solar heating to trigger widespread convection. They persist in a statistical steady state and therefore provide a natural setting to explore the mechanisms controlling convective dynamics, which play a central role in Earth’s atmospheric circulation and radiative balance.

Atmosphere↗

DOE OSTI2023

On the convergence of statistics in simulations of stationary incompressible turbulent flows

When reporting statistics from simulations of statistically stationary chaotic phenomenon, it is important to verify that the simulations are time-converged. This condition is connected with the statistical error or number of digits with which statistics can be reliably reported. In this work we consider numerical experiments of low Reynolds number incompressible homogeneous and isotropic turbulence as a model problem to investigate statistical convergence over finite simulation times. Specifically, we investigate the time integration requirements that allow meaningful reporting of the statistical error associated with finiteness of the temporal domain. We address two key questions: (1) How long should a simulation be performed in terms of large eddy time, and (2) How should the simulation time be divided among temporal windows over which a quantity of interest is estimated so that its statistical error could be reliably reported? We find that reliable reporting of statistical errors requires simulations on the order of 10 4 large eddy times, which is orders of magnitude longer than typically performed. Additionally, data post-processing should employ windows of at least ten times the large eddy time scale, with the most robust computation of statistical error of the mean requiring window sizes of an additional factor of ten. For practical simulations, we demonstrate that it is possible to estimate the statistical error within a factor of two under a less stringent condition in which a minimum of four windows with size at least ten large eddy times are used. In conclusion, our observations for homogeneous isotropic turbulence are also shown to hold in turbulent channel flow.

42 ENGINEERING↗

DOE OSTI2023

Modes and Mechanisms of Pacific Decadal-Scale Variability

The modes of Pacific decadal-scale variability (PDV), traditionally defined as statistical patterns of variance, reflect to first order the ocean's integration (i.e., reddening) of atmospheric forcing that arises from both a shift and a change in strength of the climatological (time-mean) atmospheric circulation. While these patterns concisely describe PDV, they do not distinguish among the key dynamical processes driving the evolution of PDV anomalies, including atmospheric and ocean teleconnections and coupled feedbacks with similar spatial structures that operate on different timescales. In this review, we synthesize past analysis using an empirical dynamical model constructed from monthly ocean surface anomalies drawn from several reanalysis products, showing that the PDV modes of variance result from two fundamental low-frequency dynamical eigenmodes: the North Pacific–central Pacific (NP-CP) and Kuroshio–Oyashio Extension (KOE) modes. Both eigenmodes highlight how two-way tropical–extratropical teleconnection dynamics are the primary mechanisms energizing and synchronizing the basin-scale footprint of PDV. While the NP-CP mode captures interannual- to decadal-scale variability, the KOE mode is linked to the basin-scale expression of PDV on decadal to multidecadal timescales, including contributions from the South Pacific.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Statistical Homogenization of Elastic and Fracture Properties of a Sample Selective Laser Melting Material

Selective laser melting (SLM) is an additive manufacturing technique commonly used in the rapid prototyping of components. The complexity of the SLM microstructure poses a unique challenge to deriving effective mechanical properties at different length scales. Representative volume elements (RVEs) are often used to homogenize the material properties of composites. Instead of RVEs, we use statistical volume elements (SVEs) to homogenize the elastic and fracture properties of the material. This relates the inherent variation of a material’s microstructure to the variation in its mechanical properties at different observation scales. The convergence to the RVE limit is examined from two perspectives: the stability of the mean value as the SVE size increases for the mean-based approach, and the tendency of the normalized variation in homogenized properties to zero as the SVE size increases for the variation-based approach. Fracture properties tend to make the RVE limit slower than do elastic properties from both perspectives. There are also differences between vertical (normal to printing plane) and horizontal (in-plane) properties. While the elastic properties tend to make the RVE limit faster for the horizontal direction, i.e., having a smaller variation and more stable mean value, the fracture properties exhibit the opposite effect. We attributed these differences to the geometry of the melt pools.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Quantitative measurements of dislocations in metals for advancing predictive simulations

LLNL applications require scientists to predict how materials evolve under various thermomechanical conditions. While this is achieved through physics-based simulations, uncertainty in the predictions of mechanical properties remains a serious challenge that limits the predictive capabilities of models because we lack methods to compare predictions of atomic-scale defects (dislocations) with experimental measurements. High energy X-ray diffraction (HEXRD) is the most relevant technique that can provide the necessary statistical information on dislocations. However, this technique is not yet quantitative because we lack a precise understanding of the relationship between X-ray diffraction patterns and the underlying material dislocation content and arrangements. To address this need, we used our novel computational X-ray diffraction method to simulate the effect of dislocations on the diffraction patterns. We compared virtual and experimental diffraction patterns. Results allowed us to clearly establish the relationship between X-ray diffraction patterns and the underlying dislocation structures, proving that it is feasible to quantitatively measure dislocation statistics with HEXRD. This project delivered a method that can provide the missing piece to LLNL’s mechanical property simulations in advanced metals by obtaining experimentally long-needed quantitative dislocation data, which could fully enable predictive capabilities.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Manipulation and statistical analysis of the fluid flow of polymer semiconductor solutions during meniscus-guided coating

Recent work in structure–processing relationships of polymer semiconductors have demonstrated the versatility and control of thin-film microstructure offered by meniscusguided coating (MGC) techniques. Here, we analyze the qualitative and quantitative aspects of solution shearing, a model MGC method, using coating blades augmented with arrays of pillars. The pillars induce local regions of high strain rates—both shear and extensional—not otherwise possible with unmodified blades, and we use fluid mechanical simulations to model and study a variety of pillar spacings and densities. We then perform a statistical analysis of 130 simulation variables to find correlations with three dependent variables of interest: thin-film degree of crystallinity and transistor field-effect mobilities for charge-transport parallel (Μ para ) and perpendicular (Μ perp ) to the coating direction. Our study suggests that simple fluid mechanical models can reproduce substantive correlations between the induced fluid flow and important performance metrics, providing a methodology for optimizing blade design.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Tuning the Mechanical Properties of Crosslinked Copolymers via Sequence and Solvent‐Selective Swelling for Vat Photopolymerization

Block copolymers (BCPs) offer distinct advantages for vat photopolymerization by enabling mechanically programmable network structures through microphase-separated morphologies that can be kinetically trapped during curing, yielding properties unattainable in homogeneous resins. However, the respective roles of repeat-unit sequence and solvent environment, together with their interplay in directing network formation and mechanical performance, remain unclear. Here, we synthesize a series of CO 2 -based polycarbonate copolymers comprising a crosslinkable glassy poly(vinyl cyclohexene carbonate) (PVCHC, A block) and a non-crosslinkable soft poly(propylene carbonate) (PPC, B block). The polymer sequence is systematically varied (ABA, BAB, and statistical), and solvent choice controls block-selective swelling to jointly control gelation behavior, microphase morphology, and mechanical response through changes in the accessibility and local environment of photocrosslinkable vinyl groups during network formation, as revealed by photorheology and small angle x-ray scattering. By tuning polymer sequence and curing solvent, we transform nominally identical formulations from brittle to highly ductile materials, achieving a three-orders-of-magnitude range in toughness (0.003 to 9.1 MJ m −3 ). These results establish clear structure–processing–property relationships and identify polymer sequence and selective solvation as powerful strategies for programming both printability and performance of block copolymer resins for additive manufacturing.

additive manufacturing↗

DOE OSTI2024

Size-Resolved Shape Evolution in Inorganic Nanocrystals Captured via High-Throughput Deep Learning-Driven Statistical Characterization

Precise size and shape control in nanocrystal synthesis is essential for utilizing nanocrystals in various industrial applications, such as catalysis, sensing, and energy conversion. However, traditional ensemble measurements often overlook the subtle size and shape distributions of individual nanocrystals, hindering the establishment of robust structure–property relationships. In this study, we uncover intricate shape evolutions and growth mechanisms in Co 3 O 4 nanocrystal synthesis at a subnanometer scale, enabled by deep-learning-assisted statistical characterization. By first controlling synthetic parameters such as cobalt precursor concentration and water amount then using high resolution electron microscopy imaging to identify the geometric features of individual nanocrystals, this study provides insights into the interplay between synthesis conditions and the sizedependent shape evolution in colloidal nanocrystals. Utilizing population-wide imaging data encompassing over 441,067 nanocrystals, we analyze their characteristics and elucidate previously unobserved size-resolved shape evolution. This high-throughput statistical analysis is essential for representing the entire population accurately and enables the study of the size dependency of growth regimes in shaping nanocrystals. Our findings provide experimental quantification of the growth regime transition based on the size of the crystals, specifically (i) for faceting and (ii) from thermodynamic to kinetic, as evidenced by transitions from convex to concave polyhedral crystals. Additionally, we introduce the concept of an “onset radius,” which describes the critical size thresholds at which these transitions occur. This discovery has implications beyond achieving nanocrystals with desired morphology; it enables finely tuned correlation between geometry and material properties, advancing the field of colloidal nanocrystal synthesis and its applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2025

DOUBLY-STRANGE BARYON SPECTROSCOPY WITH THE GLUEX EXPERIMENT: GROUND STATE ¿(1320) PHOTOPRODUCTION CROSS SECTION AND PROPERTIES

In the light-quark sector, traditional quark models and, more recently, lattice QCD calculations have predicted many more baryon states than have been experimentally observed. The hyperons, baryons with strange-quark content, in particular abundantly lack these observed states, and past observations are statistically limited. For multi-strange hyperons the matter is much worse and the production mechanisms of these states in photoproduction are very poorly understood. By capitalizing on the narrow peaks, as compared to the broad and overlapping N* and ¿* states, characteristic of the lowest lying ¿ resonances, the systematic aspects of the spectrum can be analyzed. In addition, we can measure experimental observables such as the production cross section to study the production mechanisms of the ¿ resonances. By accumulating various experimental observables, this goal could be accomplished through Partial Wave Analysis (PWA). The main body of work presented in this dissertation is the physics analysis and systematic study of the production cross section for the doubly strange octet ground state baryon (¿(1320)) in the exclusive t-channel photoproduction reaction ¿p ¿ K+Y* ¿ K+(K+¿-)Y* where ¿- ¿ ¿p- and ¿ ¿ pp-. The spin quantum number of ¿(1320) is also extracted and discussed. A preliminary result to extract the mass of ¿(1320) is also explored as a result of the statistical limitations of current measurements. Furthermore, the spectrum of the excited ¿* baryons are explored and discussed in the ¿*- ¿ K-¿ decay channel. The studies on the ground state and excited ¿ baryon are performed using the GlueX Phase-I (GlueX-I) data set. We have extracted differential cross sections from seven beam photon energy bins for E¿ ¿ [6.4,11.4] GeV1 and for -t < 2.4 GeV2 in the production of K+Y*. 1Natural units (c = 1) are used for the entire body of work.

Hernandez, Jesse [Florida State Univ., Tallahassee↗

DOE OSTI2021

Significant disparity of non-basal dislocation activities in hot-rolled highly-textured Mg and Mg-3Al-1Zn alloy under tension

It is well-established that Mg-3Al-1Zn (AZ31) alloy exhibits much better tensile ductility than pure Mg. However, the underlying mechanisms for such difference still remain relatively unexplored at the dislocation level. In this work, we deformed hot-rolled highly-textured pure Mg and AZ31 samples with similar initial microstructures (i.e., grain size and texture) under tension along the rolling direction. Apparent shear banding was only observed in the pure Mg samples from the early stage of the deformation. Shear bands could act as easy paths for crack propagation, leading to low ductility in pure Mg. Apparent shear banding was not noted in deformed AZ31 samples. We then investigated the deformation mechanisms at the dislocation level using transmission electron microscopy. Systematic tilting experiments and statistical analyses of multiple grains at different strain levels revealed a significant disparity of non-basal dislocation activities between pure Mg and AZ31. For pure Mg, dislocations were activated since the early stage of plastic deformation. For AZ31, dislocations were mostly absent at all strain levels, even in the strain-to-failure samples. Non-basal dislocations, including prismatic and pyramidal dislocations, were observed. The promotion of the non-basal dislocation activities and the suppression of dislocations in AZ31 are expected to offer more sustainable hardening, which could elucidate the absence of apparent shear banding and much-improved ductility in AZ31 compared to pure Mg.

Zhao, Dexin↗

DOE OSTI2022

Observation of a multiplicity dependence in the $\mathcal{p}_T$-differential charm baryon-to-meson ratios in proton–proton collisions at $\sqrt{s}$ = 13 TeV

The production of prompt D 0 , D$^+_s$, and Λ$^+_c$ hadrons, and their ratios, D$^+_s$/D 0 and Λ$^+_c$/D 0 , are measured in proton–proton collisions at $\sqrt{s}$ = 13 TeV at midrapidity (|y| < 0.5) with the ALICE detector at the LHC. The measurements are performed as a function of the charm-hadron transverse momentum (p T ) in intervals of charged-particle multiplicity, measured with two multiplicity estimators covering different pseudorapidity regions. While the strange to non-strange D$^+_s$/D 0 ratio indicates no significant multiplicity dependence, the baryon-to-meson p T -differential Λ$^+_c$/D 0 ratio shows a multiplicity-dependent enhancement, with a significance of 5.3σ for 1 < p T < 12 GeV/c, comparing the highest multiplicity interval with respect to the lowest one. The measurements are compared with a theoretical model that explains the multiplicity dependence by a canonical treatment of quantum charges in the statistical hadronisation approach, and with predictions from event generators that implement colour reconnection mechanisms beyond the leading colour approximation to model the hadronisation process. The Λ$^+_c$/D 0 ratios as a function of p T present a similar shape and magnitude as the Λ/K$^0_s$ ratios in comparable multiplicity intervals, suggesting a potential common mechanism for light- and charm-hadron formation, with analogous multiplicity dependence. The p T -integrated ratios, extrapolated down to p T = 0, do not show a significant dependence on multiplicity within the uncertainties.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

Enantioselective Allenoate-Claisen Rearrangement Using Chiral Phosphate Catalysts

Herein we report the first highly enantioselective allenoate-Claisen rearrangement using doubly axially chiral phosphate sodium salts as catalysts. This synthetic method provides access to β-amino acid derivatives with vicinal stereocenters in up to 95% ee. We also investigated the mechanism of enantioinduction by transition state (TS) computations with DFT as well as statistical modeling of the relationship between selectivity and the molecular features of both the catalyst and substrate. The mutual interactions of charge-separated regions in both the zwitterionic intermediate generated by reaction of an amine to the allenoate and the Na + -salt of the chiral phosphate leads to an orientation of the TS in the catalytic pocket that maximizes favorable noncovalent interactions. Crucial arene-arene interactions at the periphery of the catalyst lead to a differentiation of the TS diastereomers. Finally, these interactions were interrogated using DFT calculations and validated through statistical modeling of parameters describing noncovalent interactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

A method to fuse multiphysics waveforms and improve predictive explosion detection: theory, experiment and performance

Natural and human-made sources of transient energy often emit multiple geophysical signatures that include mechanical and electromagnetic waveforms. We present a constructive method to fuse and evaluate statistics that we derive from such multiphysics waveforms that improves our capability to detect small, near-ground explosions over similar methods that consume single signature waveforms. Our method advances Fisher's Combined Probability Test (Fisher's Method) to operate under both hypotheses of a binary test on noisy data and provide researchers with the density functions required to forecast the ability of Fisher's Method to screen fused explosion signatures from noise. We apply this method against 12 d, multisignature explosion and noise records to show (1) that a fused multiphysics waveform statistic that combines radio, acoustic and seismic waveform data can identify explosions roughly 0.8 magnitude units lower than an acoustic emission, STA/LTA detector for the same detection probability and (2) that we can quantitatively predict how this fused, multiphysics statistic performs with Fisher's Method. Our work thereby offers a baseline method for predictive waveform fusion that supports multiphenomenological explosion monitoring (multiPEM) and is applicable to any binary testing problem in observational geophysics.

58 GEOSCIENCES↗

DOE OSTI2024

Towards revealing intrinsic vortex-core states in Fe-based superconductors through statistical discovery

Abstract In type-II superconductors, electronic states within magnetic vortices hold crucial information about the paring mechanism and can reveal non-trivial topology. While scanning tunneling microscopy/spectroscopy (STM/S) is a powerful tool for imaging superconducting vortices, it is challenging to isolate the intrinsic electronic properties from extrinsic effects like subsurface defects and disorders. Here we combine STM/STS with basic machine learning to develop a method for screening out the vortices pinned by embedded disorder in iron-based superconductors. Through a principal component analysis of large STS data within vortices, we find that the vortex-core states in Ba(Fe 0.96 Ni 0.04 ) 2 As 2 start to split into two categories at certain magnetic field strengths, reflecting vortices with and without pinning by subsurface defects or disorders. Our machine-learning analysis provides an unbiased approach to reveal intrinsic vortex-core states in novel superconductors and shed light on ongoing puzzles in the possible emergence of a Majorana zero mode.

Guo, Yueming↗

DOE OSTI2021

Prediction of Probabilistic Shock Initiation Thresholds of Energetic Materials Through Evolution of Thermal-Mechanical Dissipation and Reactive Heating

The ignition threshold of an energetic material (EM) quantifies the macroscopic conditions for the onset of self-sustaining chemical reactions. The threshold is an important theoretical and practical measure of material attributes that relate to safety and reliability. Historically, the thresholds are measured experimentally. In this work, we present a new Lagrangian computational framework for establishing the probabilistic ignition thresholds of heterogeneous EM out of the evolutions of coupled mechanical-thermal-chemical processes using mesoscale simulations. Furthermore, the simulations explicitly account for microstructural heterogeneities, constituent properties, and interfacial processes and capture processes responsible for the development of material damage and the formation of hotspots in which chemical reactions initiate. The specific mechanisms tracked include viscoelasticity, viscoplasticity, fracture, post-fracture contact, frictional heating, heat conduction, reactive chemical heating, gaseous product generation, and convective heat transfer. To determine the ignition threshold, the minimum macroscopic loading required to achieve self-sustaining chemical reactions with a rate of reactive heat generation exceeding the rate of heat loss due to conduction and other dissipative mechanisms is determined. Probabilistic quantification of the processes and the thresholds are obtained via the use of statistically equivalent microstructure sample sets (SEMSS). The predictions are in agreement with available experimental data.

36 MATERIALS SCIENCE↗