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At least 1,063 records · Page 59

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DOE OSTI2020

Chapter 6: An Improved Leaf Protoplast System for Highly Efficient Transient Expression in Switchgrass (Panicum virgatum L.)

As a robust perennial C4-type monocot plant and a native species to North America, switchgrass (Panicum virgatum) has been evaluated and designated as a strong candidate bioenergy crop by the U.S. DOE. Although genetic modifications of switchgrass have been used to successfully reduce the recalcitrance of switchgrass biomass for biofuel production, the generation of transgenic switchgrass is still a slow and laborious process. A transient protoplast system can provide an excellent platform to accelerate the selection of genes-of-interest for tailoring switchgrass biomass. However, partially due to the lack of the complete genomic information, the attempts to optimize the transient protoplast system for switchgrass remain scarce. In this chapter, we provide an improved protocol for switchgrass protoplast isolation, increased transformation efficiency using CsCl gradient ultracentrifugation-derived plasmid DNA and extended application of the transient switchgrass protoplast system to analyze protein expression using western blot.

BASIC BIOLOGICAL SCIENCES,BIOMASS FUELS↗

DOE OSTI2020

Characterization of the Benefit of APS Flash Coatings in Improving TBC Lifetime

The addition of an air plasma sprayed (APS) “flash” layer on top of a high velocity oxygen fuel (HVOF) bond coating has been shown to extend the lifetime of thermal barrier coatings. A series of furnace cycle tests (FCTs) has been conducted at 1100 °C in air + 10% H 2 O to study the benefit of flash coatings on rod and disk alloy 247 specimens and provide a better mechanistic understanding of their benefit. Flash coatings of NiCoCrAlY and NiCoCrAlYHfSi both improved the FCT lifetime of rod specimens tested in 100-h cycles and disk specimens tested in 1-h cycles. In 1-h cycles, the NiCoCrAlY flash coating significantly outperformed an HVOF-only NiCoCrAlYHfSi bond coating and a NiCoCrAlYHfSi flash coating. Both flash coatings increased the bond coating roughness compared to HVOF. During exposure, the flash layer formed an intermixed alumina-metal layer that appeared to inhibit crack formation. Using a time series of observations, the lower Y + Hf content in the Y-only flash coating appeared to reduce Al consumption. The HVOF layer acted as a source of Al for the adjacent mixed zone. A second series of specimens included a fully APS bond coating where oxide had penetrated through the entire coating to the substrate after only 100, 1-h cycles and lifetime was similar to an HVOF-only bond coating. The inner HVOF layer with the outer APS flash coating prevented this complete penetration from occurring.

Pint, Bruce↗

DOE OSTI2020

Performance Improvements on SNS and HFIR Instrument Data Reduction Workflows Using Mantid

Performance of data reduction workflows at the High Flux Isotope Reactor (HFIR) and the Spallation Neutron Source (SNS) at Oak Ridge National Laboratory (ORNL) is mainly determined by the time spent loading raw measurement events stored in large and sparse datasets. This paper describes: (1) our long-term view to leverage SNS and HFIR data management needs with our experience at ORNL’s world-class high performance computing (HPC) facilities, and (2) our short-term efforts to speed up current workflows using Mantid, a data analysis and reduction community framework used across several neutron scattering facilities. We show that minimally invasive short-term improvements in metadata management have a moderate impact in speeding up current production workflows. We propose a more disruptive domain-specific solution: the No Cost Input Output (NCIO) framework, we provide an overview, the risks and challenges in NCIO’s adoption by HFIR and SNS stakeholders.

Godoy, William↗

DOE OSTI2025

Benchmarking Operators in Deep Neural Networks for Improving Performance Portability of SYCL

SYCL is a portable programming model for heterogeneous computing, so it is important to obtain reasonable performance portability of SYCL. Towards the goal of better understanding and improving performance portability of SYCL for machine learning workloads, we have been developing benchmarks for basic operators in deep neural networks (DNNs). These operators could be offloaded to heterogeneous computing devices such as graphics processing units (GPUs) to speed up computation. In this paper, we introduce the benchmarks, evaluate the performance of the operators on GPU-based systems, and describe the causes of the performance gap between the SYCL and Compute Unified Device Architecture (CUDA) kernels. We find that the causes are related to the utilization of the texture cache for read-only data, optimization of the memory accesses with strength reduction, use of local memory, and register usage per thread. We hope that the efforts of developing benchmarks for studying performance portability will stimulate discussion and interactions within the community.

Jin, Zheming [ORNL] (ORCID:000000027197780X)↗

DOE OSTI2025

Power-Capping Metric Evaluation for Improving Energy Efficiency in HPC Applications

With high-performance computing systems now running at exascale, optimizing power-scaling management and resource utilization has become more critical than ever. This paper explores runtime power-capping optimizations that leverage integrated CPU-GPU power management on architectures like the NVIDIA GH200 superchip. We evaluate energy-performance metrics that account for simultaneous CPU and GPU power-capping effects by using two complementary approaches: speedup-energy-delay and a Euclidean distance-based multi-objective optimization method. By targeting a mostly compute-bound exascale science application, the Locally Self-Consistent Multiple Scattering (LSMS), we explore challenging scenarios to identify potential opportunities for energy savings in exascale applications, and we recognize that even modest reductions in energy consumption can have significant overall impacts. Our results highlight how GPU task-specific dynamic power-cap adjustments combined with integrated CPU-GPU power steering can improve the energy utilization of certain GPU tasks, thereby laying the groundwork for future adaptive optimization strategies.

Patrou, Maria [ORNL] (ORCID:0000000339754638)↗

DOE OSTI2023

Improved coarse-graining methods for two dimensional tensor networks including fermions

We show how to apply renormalization group algorithms incorporating entanglement filtering methods and a loop optimization to a tensor network which includes Grassmann variables which represent fermions in an underlying lattice field theory. As a numerical test a variety of quantities are calculated for two dimensional Wilson-Majorana fermions and for the two flavor Gross-Neveu model. The improved algorithms show much better accuracy for quantities such as the free energy and the determination of Fisher’s zeros.

Phase transitions↗

DOE OSTI2024

Renormalization group improved photon impact factors and the high energy virtual photon scattering

We perform the renormalization group improved collinear resummation of the photon-gluon impact factors. We construct the resummed cross section for virtual photon-photon (γ ∗ γ ∗ ) scattering which incorporates the impact factors and BFKL gluon Green’s function up to the next-to-leading logarithmic accuracy in energy. The impact factors include important kinematical effects which are responsible for the most singular poles in Mellin space at next-to-leading order. Further conditions on the resummed cross section are obtained by requiring the consistency with the collinear limits. Our analysis is consistent with previous impact factor calculations at NLO, apart from a new term proportional to C F that we find for the longitudinal polarization. Finally, we use the resummed cross section to compare with the LEP data on the γ ∗ γ ∗ cross section and with previous calculations. The resummed result is lower than the leading logarithmic approximation but higher than the pure next-to-leading one, and is consistent with the experimental data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Improving the five-point bootstrap

We present a new algorithm for the numerical evaluation of five-point conformal blocks in d-dimensions, greatly improving the efficiency of their computation. To do this we use an appropriate ansatz for the blocks as a series expansion in radial coordinates, derive a set of recursion relations for the unknown coefficients in the ansatz, and evaluate the series using a Padé approximant to accelerate its convergence. We then study the 〈σσϵσσ〉 correlator in the 3d critical Ising model by truncating the operator product expansion (OPE) and only including operators with conformal dimension below a cutoff ∆ ⩽ ∆cutoff. We approximate the contributions of the operators above the cutoff by the corresponding contributions in a suitable disconnected five-point correlator. Using this approach, we compute a number of OPE coefficients with greater accuracy than previous methods.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

Modelling and computational improvements to the simulation of single vector-boson plus jet processes for the ATLAS experiment

This paper presents updated Monte Carlo configurations used to model the production of single electroweak vector bosons (W, Z/γ$^{∗}$) in association with jets in proton-proton collisions for the ATLAS experiment at the Large Hadron Collider. Improvements pertaining to the electroweak input scheme, parton-shower splitting kernels and scale-setting scheme are shown for multi-jet merged configurations accurate to next-to-leading order in the strong and electroweak couplings. The computational resources required for these set-ups are assessed, and approximations are introduced resulting in a factor three reduction of the per-event CPU time without affecting the physics modelling performance. Continuous statistical enhancement techniques are introduced by ATLAS in order to populate low cross-section regions of phase space and are shown to match or exceed the generated effective luminosity. This, together with the lower per-event CPU time, results in a 50% reduction in the required computing resources compared to a legacy set-up previously used by the ATLAS collaboration. The set-ups described in this paper will be used for future ATLAS analyses and lay the foundation for the next generation of Monte Carlo predictions for single vector-boson plus jets production.[graphic not available: see fulltext]

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

Medium-induced radiative kernel with the Improved Opacity Expansion

We calculate the fully differential medium-induced radiative spectrum at next-to-leading order (NLO) accuracy within the Improved Opacity Expansion (IOE) framework. This scheme allows us to gain analytical control of the radiative spectrum at low and high gluon frequencies simultaneously. The high frequency regime can be obtained in the standard opacity expansion framework in which the resulting power series diverges at the characteristic frequency ω c ~ q^L 2 . In the IOE, all orders in opacity are resumed systematically below ωc yielding an asymptotic series controlled by logarithmically suppressed remainders down to the thermal scale T « ω c , while matching the opacity expansion at high frequency. Furthermore, we demonstrate that the IOE at NLO accuracy reproduces the characteristic Coulomb tail of the single hard scattering contribution as well as the Gaussian distribution resulting from multiple soft momentum exchanges. Finally, we compare our analytic scheme with a recent numerical solution, that includes a full resummation of multiple scatterings, for LHC-inspired medium parameters. Furthermore, we find a very good agreement both at low and high frequencies showcasing the performance of the IOE which provides for the first time accurate analytic formulas for radiative energy loss in the relevant perturbative kinematic regimes for dense media.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2020

Improved opacity expansion at NNLO for medium induced gluon radiation

When an energetic parton propagates in a hot and dense QCD medium it loses energy by elastic scatterings or by medium-induced gluon radiation. The gluon radiation spectrum is suppressed at high frequency due to the LPM effect and encompasses two regimes that are known analytically: at high frequencies ω > ω c = q ^ L 2 , where q ^ is the jet quenching transport coefficient and L the length of the medium, the spectrum is dominated by a single hard scattering, whereas the regime ω < ωc is dominated by multiple low momentum transfers. In this paper, we extend a recent approach (dubbed the Improved Opacity Expansion (IOE)), which allows an analytic (and systematic) treatment beyond the multiple soft scattering approximation, matching this result with the single hard emission spectrum. We calculate in particular the NNLO correction analytically and numerically and show that it is strongly suppressed compared to the NLO indicating a fast convergence of the IOE scheme and thus, we conclude that it is sufficient to truncate the series at NLO. We also propose a prescription to compare the GW and the HTL potentials and relate their parameters for future phenomenological works.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2020

Comparison of improved TMD and CGC frameworks in forward quark dijet production

For studying small- x gluon saturation in forward dijet production in high-energy dilute-dense collisions, the improved TMD (ITMD) factorization formula was recently proposed. In the Color Glass Condensate (CGC) framework, it represents the leading term of an expansion in inverse powers of the hard scale. It contains the leading-twist TMD factorization formula relevant for small gluon’s transverse momentum k t , but also incorporates an all-order resummation of kinematical twists, resulting in a proper matching to high-energy factorization at large k t . In this paper, we evaluate the accuracy of the ITMD formula quantitatively, for the case of quark dijet production in high-energy proton-proton( p + p ) and proton-nucleus ( p + A ) collisions at LHC energies. We do so by comparing the quark-antiquark azimuthal angle Δ ϕ distribution to that obtained with the CGC formula. For a dijet with each quark momentum p t much larger than the target saturation scale, Q s , the ITMD formula is a good approximation to the CGC formula in a wide range of azimuthal angle. It becomes less accurate as the jet p t ’s are lowered, as expected, due to the presence of genuine higher-twists contributions in the CGC framework, which represent multi-body scattering effects absent in the ITMD formula. We find that, as the hard jet momenta are lowered, the accuracy of ITMD start by deteriorating at small angles, in the high-energy-factorization regime, while in the TMD regime near Δ ϕ = π , very low values of p t are needed to see differences between the CGC and the ITMD formula. In addition, the genuine twists corrections to ITMD become visible for higher values of p t in p + A collisions, compared to p + p collisions, signaling that they are enhanced by the target saturation scale.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

Improving Simulations of Vegetation Dynamics over the Tibetan Plateau: Role of Atmospheric Forcing Data and Spatial Resolution

The efficacy of vegetation dynamics simulations in offline land surface models (LSMs) largely depends on the quality and spatial resolution of meteorological forcing data. In this study, the Princeton Global Meteorological Forcing Data (PMFD) and the high spatial resolution and upscaled China Meteorological Forcing Data (CMFD) were used to drive the Simplified Simple Biosphere model version 4/Top-down Representation of Interactive Foliage and Flora Including Dynamics (SSiB4/TRIFFID) and investigate how meteorological forcing datasets with different spatial resolutions affect simulations over the Tibetan Plateau (TP), a region with complex topography and sparse observations. By comparing the monthly Leaf Area Index (LAI) and Gross Primary Production (GPP) against observations, we found that SSiB4/TRIFFID driven by upscaled CMFD improved the performance in simulating the spatial distributions of LAI and GPP over the TP, reducing RMSEs by 24.3% and 20.5%, respectively. The multi-year averaged GPP decreased from 364.68 gC m –2 yr –1 to 241.21 gC m –2 yr –1 with the percentage bias dropping from 50.2% to –1.7%. When using the high spatial resolution CMFD, the RMSEs of the spatial distributions of LAI and GPP simulations were further reduced by 7.5% and 9.5%, respectively. This study highlights the importance of more realistic and high-resolution forcing data in simulating vegetation growth and carbon exchange between the atmosphere and biosphere over the TP.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Development and Field Assessment of Transgenic Hybrid Switchgrass for Improved Biofuel Traits

Development of commercially relevant bioenergy switchgrass cultivars requires reducing recalcitrance for bioprocessing without compromising biomass yield. Low-lignin transgenic switchgrass has been produced via down-regulation of caffeic acid O-methyltransferase (COMT), a lignin biosynthetic enzyme, or by over-expression of the MYB4 transcription factor, a repressor of the lignin biosynthetic pathway. The aim of this study was to evaluate parents and selected hybrids obtained from COMT and MYB4 hybrid families under field conditions for agronomic performance and biomass quality. Plant height, width, number of tillers, dry weight, cell wall composition including lignin content, and sugar release were measured after the establishment year (2014) and the second growing season (2015). For COMT hybrids, biomass yield of the transgenic hybrids was similar to or greater than the wild-type parents selected for high biomass. Lignin content of COMT transgenic hybrids was reduced by 10%, S/G ratio decreased by 27%, and sugar release increased between 20% and 44% compared to their wild-type parents. These results indicate that hybridization of COMT with a high-yielding locally selected genotype resulted in both improved agronomic performance and enhanced biomass quality in the offspring. On the other hand, the MYB transgenic hybrid showed a 10% reduction in biomass yield compared with its wild-type parent in year 1, but not in year 2. The lignin S/G ratio was not reduced in MYB transgenic hybrids, nor was sugar release increased. These data indicate that the MYB transgene may not be suitable for an agronomic setting. More testing is needed of transgenic and wild-type, high-biomass selections for use as breeding parents. These results show that combining low-lignin transgenic switchgrass with a breeding and selection program for biomass yield will allow for the deployment of effective transgenes in high-yielding genetic backgrounds.

09 BIOMASS FUELS↗

DOE OSTI2022

Skinny kelp (Saccharina angustissima) provides valuable genetics for the biomass improvement of farmed sugar kelp (Saccharina latissima)

Abstract Saccharina latissima (sugar kelp) is one of the most widely cultivated brown marine macroalgae species in the North Atlantic and the eastern North Pacific Oceans. To meet the expanding demands of the sugar kelp mariculture industry, selecting and breeding sugar kelp that is best suited to offshore farm environments is becoming necessary. To that end, a multi-year, multi-institutional breeding program was established by the U.S. Department of Energy's (DOE) Advanced Research Projects Agency-Energy (ARPA-E) Macroalgae Research Inspiring Novel Energy Resources (MARINER) program. Hybrid sporophytes were generated using 203 unique gametophyte cultures derived from wild-collected Saccharina spp . for two seasons of farm trials (2019–2020 and 2020–2021). The wild sporophytes were collected from 10 different locations within the Gulf of Maine (USA) region, including both sugar kelp ( Saccharina latissima ) and the skinny kelp species ( Saccharina angustissima ). We harvested 232 common farm plots during these two seasons with available data. We found that farmed kelp plots with skinny kelp as parents had an average increased yield over the mean (wet weight 2.48 ± 0.90 kg m −1 and dry weight 0.32 ± 0.10 kg m −1 ) in both growing seasons. We also found that blade length positively correlated with biomass in skinny kelp x sugar kelp crosses or pure sugar kelp crosses. The skinny x sugar progenies had significantly longer and narrower blades than the pure sugar kelp progenies in both seasons. Overall, these findings suggest that sugar x skinny kelp crosses provide improved yield compared to pure sugar kelp crosses.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Using diverse potentials and scoring functions for the development of improved machine-learned models for protein–ligand affinity and docking pose prediction

The advent of computational drug discovery holds the promise of significantly reducing the effort of experimentalists, along with monetary cost. More generally, predicting the binding of small organic molecules to biological macromolecules has far-reaching implications for a range of problems, including metabolomics. However, problems such as predicting the bound structure of a protein–ligand complex along with its affinity have proven to be an enormous challenge. In recent years, machine learning-based methods have proven to be more accurate than older methods, many based on simple linear regression. Nonetheless, there remains room for improvement, as these methods are often trained on a small set of features, with a single functional form for any given physical effect, and often with little mention of the rationale behind choosing one functional form over another. Moreover, it is not entirely clear why one machine learning method is favored over another. Here, we endeavor to undertake a comprehensive effort towards developing high-accuracy, machine-learned scoring functions, systematically investigating the effects of machine learning method and choice of features, and, when possible, providing insights into the relevant physics using methods that assess feature importance. Here, we show synergism among disparate features, yielding adjusted R 2 with experimental binding affinities of up to 0.871 on an independent test set and enrichment for native bound structures of up to 0.913. When purely physical terms that model enthalpic and entropic effects are used in the training, we use feature importance assessments to probe the relevant physics and hopefully guide future investigators working on this and other computational chemistry problems.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Improving the Recyclability of Polymer Composites With Cellulose Nanofibrils

Cellulose nanofibers (CNFs) have been widely studied for their reinforcing potential in high-performance composites. While there are numerous publications on CNF-reinforced composites in a variety of polymer matrices, few have considered the recyclability of such thermoplastic composites and whether the incorporation of CNFs deteriorates or improves their performance upon reprocessing. In this study, two thermoplastic resins, poly(lactic acid) (PLA), and glycol-modified polyethylene terephthalate (PETg), were prepared with CNF reinforcement and thermomechanically recycled to investigate the effect of CNF inclusion on the composite properties after reprocessing as well as their effect on the composites’ number of useful life cycles. Additionally, changes in mechanical, thermal, rheological, molecular, and microstructural properties of the composites and/or base resins were monitored as a function of cycle numbers. As is typical, the polymers’ molecular weight and mechanical performance deteriorated with continued processing. However, the addition of spray dried CNF was found to better maintain the mechanical performance of both polymers throughout multiple recycling steps as compared to neat samples. For example, the tensile strength of PETg with 20 wt% CNF after 6 processing cycles was found to exceed that of virgin neat PETg, and higher loadings of CNF were found to preserve a higher yield strength during multiple rounds of reprocessing compared to PETg composites with lower CNF loadings. Ultimately this study indicates that the addition of CNF to some thermoplastic materials can increase both their sustainability by offsetting the use of high-embodied energy resins and their circularity by enabling performance retention over more use cycles.

42 ENGINEERING↗

DOE OSTI2022

Improving sustainable tropical forest management with voluntary carbon markets

Due to a rapidly changing climate, voluntary carbon markets are gaining momentum and should be leveraged to improve and expand tropical sustainable forest management plans, limiting carbon emissions and enhancing critical carbon sinks. By sequestering more carbon than any other terrestrial ecosystem — ~1 Pg C yr –1 — tropical forests provide crucial natural climate solutions and opportunities in the evolving voluntary carbon market. Here, we argue that some issues with the current sustainable management of tropical forests can be addressed using carbon-focused sustainable forest management (SFM + C) to leverage financial resources for tropical forest carbon storage and sequestration. We suggest an extended harvest cycle in SFM + C and calculate an associated potential increase in aboveground carbon stocks of commercial timber of 1.26 Mg C ha –1 after each cycle in the Brazilian Amazon. The additional carbon storage due to a longer harvest cycle can generate carbon credits worth 152.6 (SD 9.2) US dollars per hectare in 40 years. Considering an average cost of 180 BRL per m3 of commercial timber delivered to the sawmill, an SFM + C plan with a 40-year cycle could generate 28.7% (SD 2.5) more profit than 35-year cycles by combining timber and carbon revenues. A robust carbon price could incentivize the further extension of harvest cycles, providing a monetary return that offsets the opportunity cost intrinsic to harvesting under longer cycles. Lastly, we highlight research needs to support tropical SFM + C, which can be part of a global collective effort to limit global warming to below 2 °C above pre-industrial levels.

54 ENVIRONMENTAL SCIENCES↗