SEARCH · Search NASA

Results for “sequential dependencies”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2

All sources NASA NTRS DOE OSTI

DOE OSTI2020

Antimicrobial Properties of Corn Stover Lignin Fractions Derived from Catalytic Transfer Hydrogenolysis in Supercritical Ethanol with a Ru/C Catalyst

Converting lignin to value-added products at high yields provides an avenue for making ethanol biorefineries more profitable while reducing the carbon footprint of products generally derived from petroleum. In this study, corn stover lignin was depolymerized by catalytic transfer hydrogenolysis (CTH) in supercritical ethanol with a Ru/C catalyst. The lignin-derived bio-oil was then sequentially extracted utilizing hexane, petroleum ether, chloroform, and ethyl acetate as solvents in order of less polar to polar, and the subsequent bio-oils were characterized using GPC, GC/MS, and HSQC NMR. In this work, results show that the monomers in the bio-oil fractions contained primarily alkylated phenols, hydrogenated hydroxycinnamic acid derivatives, syringol and guaiacol-type lignins created from reductive cleavages of ether linkages, which were sequentially extracted into groups depending on the solvent polarity. The antimicrobial properties of the bio-oils were screened against Gram-positive (Bacillus subtilis, Lactobacillus amylovorus, and Staphylococcus epidermidis) and Gram-negative (Escherichia coli) bacteria and yeast (Saccharomyces cerevisiae) by examining microbial growth inhibition. Results show that CTH-derived bio-oils inhibited all tested organisms at concentrations less than 3 mg/mL. Total monomer concentration and the presence of specific monomers (i.e., syringyl propane) showed correlations to antimicrobial activity, likely due to cell death or membrane damage. This study provides insights into using sequential extraction to fractionate lignin-derived compounds and correlations between the properties of the extracted compounds and their antimicrobial activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2018

Optimal Linear Responses for Markov Chains and Stochastically Perturbed Dynamical Systems

The linear response of a dynamical system refers to changes to properties of the system when small external perturbations are applied. We consider the little-studied question of selecting an optimal perturbation so as to (i) maximise the linear response of the equilibrium distribution of the system, (ii) maximise the linear response of the expectation of a specified observable, and (iii) maximise the linear response of the rate of convergence of the system to the equilibrium distribution. We also consider the inhomogeneous, sequential, or time-dependent situation where the governing dynamics is not stationary and one wishes to select a sequence of small perturbations so as to maximise the overall linear response at some terminal time. We develop the theory for finite-state Markov chains, provide explicit solutions for some illustrative examples, and numerically apply our theory to stochastically perturbed dynamical systems, where the Markov chain is replaced by a matrix representation of an approximate annealed transfer operator for the random dynamical system.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2021

Ellipticity controlled dissociative double ionization of ethane by strong fields

We report the yields of all dissociation channels of ethane dications produced by strong field double ionization were measured. It was found that the branching ratios can be controlled by varying the ellipticity of laser pulses. The CH 3 + formation and H + formation channels show a clear competition, producing the highest and lowest branching ratios at ellipticity of ~0.6, respectively. With the help of theoretical calculations, such a control was attributed to the ellipticity dependent yields of different sequential ionization pathways.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2016

A Performance Model for Allocating the Parallelism in a Multigrid-in-Time Solver

The traditional way to numerically solve time-dependent problems is to sequentially march through time, solving for one time step and then the next. The parallelism in this approach is limited to the spatial dimension, which is quickly exhausted, causing the gain from using more processors to solve a problem to diminish. One approach to overcome this barrier is to use methods that are parallel in time. These methods have the potential to achieve dramatically better performance compared to time-stepping approaches, but achieving this performance requires carefully choosing the amount of parallelism devoted to space versus the amount devoted to time. Here, we present a performance model that, for a multigrid-in-time solver, makes the decision on when to switch to parallel-in-time and on how much parallelism to devote to space vs. time. In our experiments, the model selects the best parallel configuration in most of our test cases and a configuration close to the best one in all other cases.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

Tracking of enzymatic biomass deconstruction by fungal secretomes highlights markers of lignocellulose recalcitrance

Background:Lignocellulose biomass is known as a recalcitrant material towards enzymatic hydrolysis, increasing the process cost in biorefinery. In nature, filamentous fungi naturally degrade lignocellulose, using an arsenal of hydrolytic and oxidative enzymes. Assessment of enzyme hydrolysis efficiency generally relies on the yield of glucose for a given biomass. To better understand the markers governing recalcitrance to enzymatic degradation, there is a need to enlarge the set of parameters followed during deconstruction. Results:Industrially-pretreated biomass feedstocks from wheat straw, miscanthus and poplar were sequentially hydrolysed following two steps. First, standard secretome from Trichoderma reesei was used to maximize cellulose hydrolysis, producing three recalcitrant lignin-enriched solid substrates. Then fungal secretomes from three basidiomycete saprotrophs ( Laetisaria arvalis , Artolenzites elegans and Trametes ljubarskyi ) displaying various hydrolytic and oxidative enzymatic profiles were applied to these recalcitrant substrates, and compared to the T. reesei secretome. As a result, most of the glucose was released after the first hydrolysis step. After the second hydrolysis step, half of the remaining glucose amount was released. Overall, glucose yield after the two sequential hydrolyses was more dependent on the biomass source than on the fungal secretomes enzymatic profile. Solid residues obtained after the two hydrolysis steps were characterized using complementary methodologies. Correlation analysis of several physico-chemical parameters showed that released glucose yield was negatively correlated with lignin content and cellulose crystallinity while positively correlated with xylose content and water sorption. Water sorption appears as a pivotal marker of the recalcitrance as it reflects chemical and structural properties of lignocellulosic biomass. Conclusions:Fungal secretomes applied to highly recalcitrant biomass samples can further extend the release of the remaining glucose. The glucose yield can be correlated to chemical and physical markers, which appear to be independent from the biomass type and secretome. Overall, correlations between these markers reveal how nano-scale properties (polymer content and organization) influence macro-scale properties (particle size and water sorption). Further systematic assessment of these markers during enzymatic degradation will foster the development of novel cocktails to unlock the degradation of lignocellulose biomass.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

Precise algorithm to generate random sequential adsorption of hard polygons at saturation

Random sequential adsorption (RSA) is a time-dependent packing process, in which particles of certain shapes are randomly and sequentially placed into an empty space without overlap. In the infinite-time limit, the density approaches a "saturation'' limit. Although this limit has attracted particular research interest, the majority of past studies could only probe this limit by extrapolation. We have previously found an algorithm to reach this limit using finite computational time for spherical particles, and could thus determine the saturation density of spheres with high accuracy. Here in this paper, we generalize this algorithm to generate saturated RSA packings of two-dimensional polygons. We also calculate the saturation density for regular polygons of three to ten sides, and obtain results that are consistent with previous, extrapolation-based studies.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2024

Labeling sequential data from noisy annotations

Crowdsourcing algorithms often work under the assumption that the data samples are independent. Recent work has shown that data dependence, such as temporal correlations in sequential data, can be leveraged to improve the label quality. Existing methods that exploit this special structure rely on third-order statistics of the annotator outputs to ensure the identifiability of key latent parameters, which are costly to acquire. This work proposes an approach for integrating crowdsourced annotations under the Dawid-Skene/Hidden Markov Model (DS-HMM) for sequential data based on second-order statistics, which naturally enjoys a lower sample complexity. An effective algorithm is proposed to tackle the challenging optimization problem associated with the proposed estimator. Numerical experiments showcase the effectiveness of the data labeling paradigm.

Marrinan, Timothy P.↗

DOE OSTI2025

Active learning path-dependent properties using a cloud-based materials acceleration platform

Solid state materials are central to many modern technologies in which a given material may be exposed to a variety of environments. The material properties often vary with the sequence of environments in an irreversible manner, resulting in a quintessential path-dependency in experimental observables. While sequential learning techniques have been effectively deployed for accelerating learning of state properties of materials, they often use a consistent environment path in all experiments. To elevate such techniques for making optimal decisions in experimental investigations of path-dependent properties, we introduce an iterated expected information gain acquisition function that optimizes over entire experimental trajectories. This approach is implemented within a cloud-based Materials Acceleration Platform architecture utilizing an event-driven stateful broker coupled with remote HELAO (Hierarchical Experimental Laboratory Automation and Orchestration) instances and an AI science manager. The platform's efficacy was demonstrated through a case study optimizing multi-step spectro-electrochemical experiments to identify optically stable potential windows in (Co–Ni–Sb)O z metal oxides. The system successfully integrated AI-driven experiment design, remote laboratory automation, and cloud-based data infrastructure, validating the platform's capability for managing complex, adaptive, path-dependent workflows in materials discovery.

Guevarra, Dan [California Institute of Technology ↗

DOE OSTI2018

Defining lignin nanoparticle properties through tailored lignin reactivity by sequential organosolv fragmentation approach (SOFA)

Sustainable biorefinery heavily depends on the generation of value-added products, particularly from lignin. Despite considerable efforts, the production of fungible lignin bioproducts is still hindered by the poor fractionation and low reactivity of lignin. To address these challenges, the sequential organosolv fragmentation approach (SOFA) using ethanol plus different-stage catalysts was explored to selectively dissolve lignin for producing multiple uniform lignin streams, and to tailor its chemistry and reactivity for fabricating lignin nanoparticles (LNPs) with desired quality features. In a biorefinery concept, the carbohydrate output is taken into consideration. SOFA significantly increased the glucose and xylose yields, suggesting an improved monomer-sugar release. The fractionated lignin was used to fabricate LNPs via self-assembly. Although these LNPs were derived from the same substrate, they exhibited different properties. The effective diameter almost followed the order of stage 1, stage 3, and stage 2 in each SOFA, and the smallest effective diameter was approximately 130 nm from SOFA using ethanol plus sulfuric acid. The polydispersity index and zeta potential were less than 0.08 and –50 mV, respectively, suggesting good uniformity and stability of the LNPs. Lignin characterization results suggested that SOFA using ethanol plus sulfuric acid produced high-molecular-weight lignin, decreased S/G ratio, and β-O-4 and β–β linkage abundance, yet produced the condensed lignin and enhanced its hydrophobicity. More importantly, it exposed more phenolic OH groups and enhanced the stability of LNPs, likely due to the hydrogen bond networks. Together with enriched COOH groups, it promoted the formation of electrical double layers and increased the zeta potential of LNPs. In conclusion, by tailoring the lignin chemistry using SOFA to enhance the self-assembling process, high-quality LNPs of a spherical shape, small effective diameters, and good stability have been fabricated, which represents a sustainable means for upgrading the low-value lignin and thus contributes to the profitability of biorefineries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2018

Phase diagram of the SU(2) Kondo lattice

We examine the SU(2) Kondo Lattice Model, for simple cubic lattices with various magnitudes of the localized spins j and numbers of conduction electrons, nc. For j=1/2, the system undergoes transitions from the paramagnetic to magnetically ordered states. The sequence of low-temperature magnetic states found on increasing n c is symmetric about half-filling and exhibits a preference for commensurate phases over incommensurate phases. On increasing nc from small values, the sequence of magnetic orderings consists of: ferromagnetic phases, planes of ferromagnetically spins which are sequentially twisted by nc-dependent angles, ferromagnetic planes of spins that are aligned antiferromagnetically, antiferromagnetic planes of spins in which the Neel order parameters are twisted through incommensurate angles. Neel order is most stable around half-filling. Magnetic ordered phases are found to be more stable than the Kondo phase for j=1/2, but larger j values may stabilize the Kondo phase. For j=3/2 the sequence of magnetic ordering with increasing nc is the same but, depending on the value of the strength of the Kondo interaction, the Kondo phase may be stabilized in a window 4 ≥ n c ≥ 2. In accordance with Nozieres’s arguments, we find that magnetic ordering is dominant for almost filled and almost empty bands.

36 MATERIALS SCIENCE↗

DOE OSTI2015

A time-parallel method for the solution of PDE-constrained optimization problems

We study a time-parallel approach to solving quadratic optimization problems with linear time-dependent partial differential equation (PDE) constraints. These problems arise in formulations of optimal control, optimal design and inverse problems that are governed by parabolic PDE models. They may also arise as subproblems in algorithms for the solution of optimization problems with nonlinear time-dependent PDE constraints, e.g., in sequential quadratic programming methods. We apply a piecewise linear finite element discretization in space to the PDE constraint, followed by the Crank-Nicolson discretization in time. The objective function is discretized using finite elements in space and the trapezoidal rule in time. At this point in the discretization, auxiliary state variables are introduced at each discrete time interval, with the goal to enable: (i) a decoupling in time; and (ii) a fixed-point iteration to recover the solution of the discrete optimality system. The fixed-point iterative schemes can be used either as preconditioners for Krylov subspace methods or as smoothers for multigrid (in time) schemes. We present promising numerical results for both use cases.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

Receptor Activation of HIV-1 Env Leads to Asymmetric Exposure of the gp41 Trimer

Structural rearrangements of HIV-1 glycoprotein Env promote viral entry through membrane fusion. Env is a symmetric homotrimer with each protomer composed of surface subunit gp120 and transmembrane subunit gp41. Cellular CD4- and chemokine receptor-binding to gp120 coordinate conformational changes in gp41, first to an extended prehairpin intermediate (PHI) and, ultimately, into a fusogenic trimer-of-hairpins (TOH). HIV-1 fusion inhibitors target gp41 in the PHI and block TOH formation. To characterize structural transformations into and through the PHI, we employed asymmetric Env trimers containing both high and low affinity binding sites for individual fusion inhibitors. Asymmetry was achieved using engineered Env heterotrimers composed of protomers deficient in either CD4- or chemokine receptor-binding. Linking receptor engagement to inhibitor affinity allowed us to assess conformational changes of individual Env protomers in the context of a functioning trimer. We found that the transition into the PHI could occur symmetrically or asymmetrically depending on the stoichiometry of CD4 binding. Sequential engagement of multiple CD4s promoted progressive exposure of individual fusion inhibitor binding sites in a CD4-dependent fashion. By contrast, engagement of only a single CD4 molecule led to a delayed, but symmetric, exposure of the gp41 trimer. This complex coupling between Env-CD4 interaction and gp41 exposure explained the multiphasic fusion-inhibitor titration observed for a mutant Env homotrimer with a naturally asymmetric gp41. Our results suggest that the spatial and temporal exposure of gp41 can proceed in a nonconcerted, asymmetric manner depending on the number of CD4s that engage the Env trimer. The findings have important implications for the mechanism of viral membrane fusion and the development of vaccine candidates designed to elicit neutralizing antibodies targeting gp41 in the PHI.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Parallel-in-Time Multigrid Methods for Hyperbolic Problems, with a Focus on the Shallow Water Equations

The coming massive parallelism of exascale computing presents a pressing challenge for the many DOE simulations of time-dependent partial differential equations, which typically use traditional sequential time stepping methods. Since this traditional approach is inherently serial, it presents a sequential bottleneck when moving to exascale computing, because future performance gains will come through greater concurrency, not faster clock speeds. Thus, the goal of this work is to research parallelism in time, i.e., methods that compute multiple time values simultaneously, not sequentially. The focus will be on hyperbolic problems of programmatic interest to DOE, with the goal of enabling scalable simulations of time-dependent hyperbolic problems on future architectures. The difficulty lies in the fact that hyperbolic problems are well-known to be difficult for parallel-in-time methods, with the most common parallel-in-time method, Parareal, diverging in many cases. Here, the chosen methodology for scalably solving these hyperbolic space-time equations is multigrid-reductionin-time (MGRIT), because multigrid (when it works) is a powerful, optimal, and scalable solver for discretized PDEs. To further research in this area, this project will explore a model hyperbolic problem (the shallow water equations) in the context of recent advances (e.g., by Wingate and Haut) in constructing improved coarse time-grid time-propagators by using the slow asymptotic structure of the equations. In particular, we will investigate if such coarse time-propagators offer significant advantages in an MGRIT setting, and explore any broader insights gained into parallel-in-time for hyperbolic problems.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Influence of sequential stimulation practices on geochemical alteration of shale

Water-based hydraulic fracturing fluids (HFFs) can chemically interact with formation shale, resulting in altered porosity and permeability of the host rock. Experimental investigations of spatial and temporal shale-HFF interactions are helpful in interpreting chemical compositions of the injectate, as well as predicting alteration of hydraulic properties in the reservoir due to mineral dissolution and precipitation. Most bench-top experiments designed to study shale-HFF chemical interactions, either using batch reactors or flow-through setups, are carried out assuming that the acid spearhead has already become mixed with neutral HFFs. During operations, however, HFFs are typically injected according to a sequenced pumping schedule, starting with a concentrated acid spearhead, followed by multiple additions of near-neutral pH HFFs containing chemical amendments and proppant. In this study, we use geochemical modeling to consider whether this pre-mixed experimental protocol provides results directly comparable to a sequential discrete fluid-shale interaction protocol. Our results show that for the batch system, the transient evolution in major ion concentrations is faster with the sequential procedure. After 2 h of reaction time, the two protocols converge to the same aqueous concentrations. In a flow-through geometry, the pre-mixed model predicts extensive chemical alteration close to the injection point but negligible alteration downstream. In contrast, the sequential model predicts mineral reactions over hundreds of meters along the flow path. The extent of shale alteration in the sequential model at a given location depends on shale mineralogy and where the acid spearhead resides during the shut-in period. The predictive model developed in this study can help experimentalists to design bench-top tests and operators to better translate the results of laboratory experiments into practical applications.

Li, Qingyun↗

DOE OSTI2021

Parallel Multigrid in Time and Space for Extreme-Scale Computational Science

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

General Kinetic Model for pH Dependence of Proton-Coupled Electron Transfer: Application to an Electrochemical Water Oxidation System

The pH dependence of proton-coupled electron transfer (PCET) reactions, which are critical to many chemical and biological processes, is a powerful probe for elucidating their fundamental mechanisms. Herein, a general, multichannel kinetic model is introduced to describe the pH dependence of both homogeneous and electrochemical PCET reactions. According to this model, a weak pH dependence can arise from the competition among multiple sequential and concerted PCET channels involving different forms of the redox species, such as protonated and deprotonated forms, as well as different proton donors and acceptors. The contribution of each channel is influenced by the relative populations of the reactant species, which often depend strongly on pH, leading to complex pH dependence of PCET apparent rate constants. This model is used to explain the origins of the experimentally observed weak pH dependence of the electrochemical PCET apparent rate constant for a ruthenium-based water oxidation catalyst attached to a tin-doped In2O3 (ITO) surface. The weak pH dependence is found to arise from the intrinsic differences in the rate constants of participating channels and the dependence of their relative contributions on pH. This model predicts that the apparent maximum rate constant will become pH-independent at higher pH, which is confirmed by experimental measurements. Our analysis also suggests that the dominant channels are electron transfer at lower pH and sequential PCET via electron transfer followed by fast proton transfer at higher pH. Furthermore, this work highlights the importance of considering multiple competing channels simultaneously for PCET processes.

Catalysts↗

DOE OSTI2022

Parallel Multigrid in Time and Space for Extreme-Scale Computational Science: Chaotic and Hyperbolic Problems

The coming massive parallelism of exascale computing presents a pressing challenge for the many DOE simulations of time-dependent partial differential equations (PDEs), which typically use traditional sequential time stepping methods. Since this traditional approach is inherently serial, it presents a sequential bottleneck when moving to exascale computing, because future performance gains will come through greater concurrency, not faster clock speeds. Thus, the goal of this work is to research parallelism in time, i.e., methods that compute multiple time values simultaneously, not sequentially. The focus will be on hyperbolic and chaotic problems of interest to DOE, with the goal of enabling scalable simulations of time-dependent hyperbolic and chaotic problems on future architectures. The chosen methodology for solving these problems parallel-in-time is multigrid, because multigrid (when it works) is a powerful, optimal, and scalable solver for discretized PDEs. Multigrid is already commonly used in many DOE simulations for scalably and optimally solving space-only PDE problems. The areas of hyperbolic and chaotic problems are chosen because of their relevance to problems of programmatic interest to DOE. However, these problems are also well-known to be difficult for parallelin-time methods, with the most common method, parareal, diverging in many cases. The current stateof-the-art for parallel-in-time at LLNL is the multigrid reduction in time (MGRIT) XBraid package, which also struggles for such problems, while still showing some improvement over parareal. In summary, new methods are needed for an efficient parallel-in-time scheme for hyperbolic and chaotic problems, and this work shall research promising new multigrid methods in this area. In particular, we take inspiration from the Least Squares Shadowing (LSS by Wang) approach for solving chaotic problems. Here, an optimization approach is able to find “well-conditioned” shadow trajectories/solutions to the original “ill-conditioned” chaotic problem. Thus, the new multigrid methods researched here also arise in an optimization context.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Multigrid Reduction in Time for Chaotic and Hyperbolic Problems (Final Report)

The coming massive parallelism of exascale computing presents a pressing challenge for the many DOE simulations of time-dependent partial differential equations (PDEs), which typically use traditional sequential time stepping methods. Since this traditional approach is inherently serial, it presents a sequential bottleneck when moving to exascale computing, because future performance gains will come through greater concurrency, not faster clock speeds. Thus, the goal of this work is to research parallelism in time, i.e., methods that compute multiple time values simultaneously, not sequentially. The focus will be on hyperbolic and chaotic problems of interest to DOE, with the goal of enabling scalable simulations of time-dependent hyperbolic and chaotic problems on future architectures. The chosen methodology for solving these problems parallel-in-time is multigrid, because multigrid (when it works) is a powerful, optimal, and scalable solver for discretized PDEs. Multigrid is already commonly used in many DOE simulations for scalably and optimally solving space-only PDE problems. The areas of hyperbolic and chaotic problems are chosen because of their relevance to problems of programmatic interest to DOE. However, these problems are also well-known to be difficult for parallelin-time methods, with the most common method, parareal, diverging in many cases. The current state-of-the-art for parallel-in-time at LLNL is the multigrid reduction in time (MGRIT) XBraid package, which also struggles for such problems, while still showing some improvement over parareal. In summary, new methods are needed for an efficient parallel-in-time scheme for hyperbolic and chaotic problems, and this work shall research promising new multigrid methods in this area. In particular, this work shall continue researching the directions from the current collaboration with Dr. Falgout, which are laid out in the work Toward Parallel in Time for Chaotic Dynamical Systems and showed the first known results of a parallel-in-time speedup for a chaotic problem. This work outlines two key improvements to XBraid for chaotic problems, the so-called “theta” and “delta-correction” methods. Here, these two improvements will be implemented in a high-performance but general way in XBraid and explored for more complicated problems. We will additionally research, as time allows, improvements to these techniques, as well as multigrid relaxation techniques based on Least Squares Shadowing (LSS by Wang) and a nonintrusive block tridiagonal solver based on MGRIT, called TriMGRIT.

97 MATHEMATICS AND COMPUTING↗