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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.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Nucleus-specific expression in the multinuclear mushroom-forming fungus Agaricus bisporus reveals different nuclear regulatory programs

Many fungi are polykaryotic, containing multiple nuclei per cell. In the case of heterokaryons, there are different nuclear types within a single cell. It is unknown what the different nuclear types contribute in terms of mRNA expression levels in fungal heterokaryons. Each cell of the mushroom Agaricus bisporus contains two to 25 nuclei of two nuclear types originating from two parental strains. Using RNA-sequencing data, we assess the differential mRNA contribution of individual nuclear types and its functional impact. We studied differential expression between genes of the two nuclear types, P1 and P2, throughout mushroom development in various tissue types. P1 and P2 produced specific mRNA profiles that changed through mushroom development. Differential regulation occurred at the gene level, rather than at the locus, chromosomal, or nuclear level. P1 dominated mRNA production throughout development, and P2 showed more differentially up-regulated genes in important functional groups. In the vegetative mycelium, P2 up-regulated almost threefold more metabolism genes and carbohydrate active enzymes (cazymes) than P1, suggesting phenotypic differences in growth. We identified widespread transcriptomic variation between the nuclear types of A. bisporus. Our method enables studying nucleus-specific expression, which likely influences the phenotype of a fungus in a polykaryotic stage. Our findings have a wider impact to better understand gene regulation in fungi in a heterokaryotic state. This work provides insight into the transcriptomic variation introduced by genomic nuclear separation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Bacterial community and arsenic functional genes diversity in arsenic contaminated soils from different geographic locations

To understand how soil microbial communities and arsenic (As) functional genes respond to soil arsenic (As) contamination, five soils contaminated with As at different levels were collected from diverse geographic locations, incubated for 54 days under flooded conditions, and examined by both MiSeq sequencing of 16S rRNA gene amplicons and functional gene microarray (GeoChip 4.0). The results showed that both bacterial community structure and As functional gene structure differed among geographical locations. The diversity of As functional genes correlated positively with the diversity of 16S rRNA genes (P< 0.05). Higher diversities of As functional genes and 16S rRNA genes were observed in the soils with higher available As. Soil pH, phosphate-extractable As, and amorphous Fe content were the most important factors in shaping the bacterial community structure and As transformation functional genes. Geographic location was also important in controlling both the bacterial community and As transformation functional potential. These findings provide insights into the variation of As transformation functional genes in soils contaminated with different levels of As at different geographic locations, and the impact of environmental As contamination on the soil bacterial community.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1974

Lunar orbit determination in the presence of unmodeled accelerations

A technique for estimating the state of an artificial satellite in the presence of unmodeled accelerations is presented. The unmodeled acceleration is approximated by a first-order Gauss-Markov sequence which can be separated into a timewise-correlated component and a purely random component. Using this approximation, a sequential procedure for estimating the position, velocity, and the unmodeled acceleration is developed. The method is evaluated by reducing range-rate observations obtained by tracking the Apollo 10 and 11 spacecraft during the lunar-orbit phase of the mission. Numerical results are presented which show that the observation residual pattern lies within the observation noise standard deviation. The values of the estimated components of the unmodeled acceleration are repeatable from orbit to orbit within a given mission and from mission to mission when the same ground track is covered. Finally, the variation in the radial component of the unmodeled acceleration shows a high correlation with the reported location of the lunar surface mascons.

Ingram, D. S.↗
NASA NTRS1986

Short-term spectral variability in AB Aurigae - Clues for activity in Herbig Ae stars. I - The ultraviolet lines of Mg II and Fe II

IUE satellite monitoring of the Herbig Ae star AB Aur in 1982 and 1984, with attention to the variability of both the Mg II 2795 A wind profile and a number of Fe II UV lines, has indicated temporal variations in the Mg II blue wing velocity by 30-50 percent at both epochs. By contrast, the Fe II spectrum was constant in 1982, but variable in 1984. There is no evidence of photometric variability in AB Aur during either period. An analysis of the Mg II blue wing velocity vs time shows that the variability can be fitted with a sine curve of period 45 + or - 6 yr, which is interpreted to be the stellar rotation period. The observed rotational modulation of the blue wing velocity of Mg II 2795 A in AB Aur's wind is the first direct evidence of a nonaxisymmetric wind in an A-type premain sequence object.

Praderie, F.↗
NASA NTRS1992

Stress analysis of a rectangular implant in laminated composites using 2-D and 3-D finite elements

An analysis method using the FEM based on the Hellinger-Reissner variation principle has been developed to determine the 3-D stresses and displacements near a rectangular implant inside a laminated composite material. Three-dimensional elements are employed in regions where the interlaminar stress is considered to be significant; 2-D elements are used in other areas. Uniaxially loaded graphite-epoxy laminates have been analyzed; the implant was modeled as four plies of 3501/6 epoxy located in the middle of the laminate. It is shown that the interlaminar stresses are an order of magnitude lower than the stress representing the applied far-field load. The stress concentration factors of both the interlaminar and in-plane stresses depend on the stacking sequence of the laminate.

Chow, Wai T.↗
DOE OSTI2025

Tropical Forest Soil Microbiome Modulates Leaf Heat Tolerance More Strongly Under Warming Than Ambient Conditions

ABSTRACT It is unclear how plants respond to increasing temperatures. Leaf heat tolerance (LHT) is often at its upper limit in tropical forests, suggesting that climate change might negatively impact these forests. We hypothesized that intraspecific variation in LHT might be associated with changes in the soil microbiome, which might also respond to climate. We hypothesized that warming would increase LHT through changes in the soil microbiome: we combined an in situ tropical warming experiment with a shade house experiment in Puerto Rico. The shade house experiment consisted of growing seedlings of Guarea guidonia , a dominant forest species, under different soil microbiome treatments (reduced arbuscular mycorrhizal fungi, reduced plant pathogens, reduced microbes, and unaltered) and soil inoculum from the field experiment. Heat tolerance was determined using chlorophyll fluorescence ( F V /F m ) on individual seedlings in the field and on groups of seedlings (per pot) in the shade house. We sequenced soil fungal DNA to analyze the impacts of the treatments on the soil microbiome. In the field, seedlings from ambient temperature plots showed higher F V /F m values under high temperatures (0.648 at 46°C and 0.067 at 52°C) than seedlings from the warming plots (0.535 at 46°C and 0.031 at 52°C). In the shade house, the soil microbiome treatments significantly influenced the fungal community composition and LHT ( T crit and F V /F m ). Reduction in fungal pathogen abundance and diversity altered F V /F m before T 50 for seedlings grown with soil inoculum from the warming plots but after T 50 for seedlings grown with soil inoculum from the ambient plots. Our findings emphasize that the soil microbiome plays an important role in modulating the impacts of climate change on plants. Understanding and harnessing this relationship might be vital for mitigating the effects of warming on forests, emphasizing the need for further research on microbial responses to climate change.

Hernandes Villani, Gabriela [Department of Plant B↗
DOE OSTI2021

Surveying Grassland Islands: the genetics and performance of Appalachian switchgrass (Panicum virgatum L.) collections

The interior Southeastern United States could contain novel germplasm for the bioenergy crop switchgrass due to its diverse habitats and geographic location between genetic subpopulations (Atlantic, Midwest, and Gulf). Collections from this region could accelerate breeding progress, contribute to conservation efforts, and improve understanding of isolated grasslands in the region. This study located 22 sites in the Midsouth region and obtained 1,521,210 single nucleotide polymorphism markers of 202 individuals through genotype-by-sequencing. Here, individuals were evaluated for flowering time, winter survival and tiller number. Comparison to a national diversity panel revealed that branches of two major subpopulations occur in the region with two levels of polyploidy: Atlantic tetraploids and Midwest octoploids. Two locations contained admixed octoploid individuals with Midwest and Gulf genetics. Field performance of the Midwest octoploids conformed with prior reported performance of the Midwest subpopulation, although three sites contained promising late flowering traits. The Atlantic tetraploids had moderate winter survival, short stature, and anomalously early flowering. Atlantic populations mostly occurred in marginal sites and their morphological and flowering time adaptations may be a resource conservation strategy. Demographic inference of historical effective population size variation in a subset of tetraploid locations indicated a widespread recent decline in effective population size. This pattern is consistent with isolation of these switchgrass communities from larger populations and is further supported by evidence of inbreeding within the populations (F I = 0.18). The populations documented in this study contain novel genetic diversity and adaptations to a range of marginal habitats. Therefore, this study provides a new source of germplasm for future breeding and conservation programs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

SCEC/USGS Community Stress-Drop Validation Study: How Spectral Fitting Approaches Influence Measured Source Parameters

Spectral source parameters used to estimate an earthquake’s stress drop (⁠Δσ⁠) can vary significantly across measurement approaches. The Statewide California Earthquake Center/U.S. Geological Survey Community Stress‐Drop Validation Study was initiated to compare source parameter estimates, focusing initially on a dataset from the 2019 Ridgecrest earthquake sequence. As part of that validation effort, here we focus on one potential source of uncertainty: whether spectral fitting approaches alone, applied to a common set of spectra from the 2019 Ridgecrest sequence result in different source parameter estimates. By using a common set of benchmark spectra analyzed across a consistent frequency band of 1–40 Hz, we eliminate many sources of variability. A subgroup of validation study participants volunteered to estimate the low‐frequency displacement (⁠Ω 0 ⁠) and corner frequency (⁠ƒ c ⁠) by fitting a smooth function to benchmark displacement spectra. Participants used linear‐ or log‐sampled spectra, assumed a Brune or Boatwright spectral model, and applied different misfit criteria. We compare 17 approaches used to estimate ⁠Ω 0 ⁠, ƒ c ⁠, and Δσ for 54 earthquake spectra. Our results reveal that 35% of events have Δσ estimates within a factor of two, whereas others exhibit variations exceeding an order of magnitude. The variability in and can largely be attributed to whether a spectrum is consistent with the smooth function of an idealized simple crack model. The trade‐off between Ω 0 and ƒ c may be more pronounced when using linearly sampled spectra, as higher frequency spectral bumps control the fits. As expected, methods that assumed a Boatwright model tended to have lower Ω 0 and somewhat higher ƒ c compared to those assuming a Brune model, although resulting Δσ estimates are similar. Finally, when compared to the overall validation study results, the fitting approach alone may account for between 5% and 90% (25% on average) of the total variability in spectral Δσ⁠.

58 GEOSCIENCES↗
DOE OSTI2016

Bino variations: Effective field theory methods for dark matter direct detection

We apply effective field theory methods to compute bino-nucleon scattering, in the case where tree-level interactions are suppressed and the leading contribution is at loop order via heavy flavor squarks or sleptons. We find that leading log corrections to fixed-order calculations can increase the bino mass reach of direct detection experiments by a factor of 2 in some models. These effects are particularly large for the bino-sbottom coannihilation region, where bino dark matter as heavy as 5–10 TeV may be detected by near future experiments. For the case of stop- and selectron-loop mediated scattering, an experiment reaching the neutrino background will probe thermal binos as heavy as 500 and 300 GeV, respectively. We present three key examples that illustrate in detail the framework for determining weak scale coefficients, and for mapping onto a low-energy theory at hadronic scales, through a sequence of effective theories and renormalization group evolution. For the case of a squark degenerate with the bino, we extend the framework to include a squark degree of freedom at low energies using heavy particle effective theory, thus accounting for large logarithms through a “heavy-light current.” Finally, benchmark predictions for scattering cross sections are evaluated, including complete leading order matching onto quark and gluon operators, and a systematic treatment of perturbative and hadronic uncertainties.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1991

Recrystallization and superplasticity at 300 C in an aluminum-magnesium alloy

Variations in thermomechanical processing (TMP) which regulate the microstructural characteristics and superplastic response of an Al-10Mg-0.1Zr alloy at 300 C were evaluated. Mechanical property data revealed that the superplastic ductility can be enhanced by simultaneously increasing the total rolling strain, the reduction per pass, and the duration of reheating intervals between passes during isothermal rolling. Texture and microscopy data were consistent with the development of a refined microstructure by recovery-dominated processes, i.e., continuous recrystallization, during the processing. The mechanisms by which a refined substructure can be progressively converted into a fine-grained structure during repeated cycles of deformation and annealing are addressed. A qualitative description of the complex sequence of developments leading to a microstructure better suited to support superplastic response is presented.

Hales, S. J.↗
NASA NTRS1993

Comparison of kinetic models for atom recombination on high-temperature reusable surface insulation

Five kinetic models are compared for their ability to predict recombination coefficients for oxygen and nitrogen atoms over high-temperature reusable surface insulation (HRSI). Four of the models are derived using Rideal-Eley or Langmuir-Hinshelwood catalytic mechanisms to describe the reaction sequence. The fifth model is an empirical expression that offers certain features unattainable through mechanistic description. The results showed that a four-parameter model, with temperature as the only variable, works best with data currently available. The model describes recombination coefficients for oxygen and nitrogen atoms for temperatures from 300 to 1800 K. Kinetic models, with atom concentrations, demonstrate the influence of atom concentration on recombination coefficients. These models can be used for the prediction of heating rates due to catalytic recombination during re-entry or aerobraking maneuvers. The work further demonstrates a requirement for more recombination experiments in the temperature ranges of 300-1000 K, and 1500-1850 K, with deliberate concentration variation to verify model requirements.

Willey, Ronald J.↗
NASA NTRS1995

The Rovibrational Intensities of the (40 deg 1) and (00 deg 0) Pentad Absorption Bands of 12C16O2 Between 7284 and 7921 cm(exp-1)

Carbon dioxide is the major constituent of the atmospheres of both Mars and Venus. Correct interpretations of spectra of these atmospheres require accurate knowledge of a substantial number of absorption bands of this gas. This is especially true for Venus; many weak CO2 bands that are insignificant in the earth's atmosphere are prominent absorbers in Venus' hot, dense lower atmosphere. Yet, recent near-infrared spectra of Venus' nightside have discovered emission windows, which occur between CO2 absorption bands, at 4040-4550 cm(exp-1), 5700-5900 cm(exp-1), and several smaller ones between 7500 and 9400 cm(exp-1). This radiation is due to thermal emission from Venus' lower atmosphere, diminished by scattering and absorption within the sulfuric acid clouds on its way to space. Simulations of these data with radiative transfer models can provide improved information on the abundances of a number of constituents of the lower atmosphere (e.g. H2O, CO, HDO, HCl, HF, and OCS) and the optical properties of the clouds, whose spatial variation modulates the brightness of the emissions. However, the accuracy of these retrievals has been limited by insufficient knowledge of the opacity of some of the gas species, including CO2, at the large pathlengths and high temperatures and pressures that exist on Venus. In particular, modeling the emission spectrum did not produce a good fit for the emission window centered at 7830 cm(exp-1). In an ongoing effort to assist analyses of these Venus spectra, we have been making laboratory intensity measurements of several weak bands of CO2 which are significant absorbers in these Venus emission windows. The CO2 bands that are prominent in the 7830 cm(exp-1) region belong to the vibrational sequence 4v1+v3 and associated hot bands. Only 2 of the 5 bands of this sequence have been previously measured. Modeling Venus' emission spectrum in the 7830 cm(exp-1) region had to rely on calculated intensity values for the weak ground state band at 7921 cm-1 and the associated hot bands. Since the calculated intensities of ground state bands are known to have significant uncertainties, we decided to measure this (40 deg 1)I (left arrow) (00 deg 0) band with the Ames 25 meter multiple reflection absorption cell and Fourier transform spectrometer. We also measured the (40 deg 1) (sub IV) (left arrow) (00 deg 0) band at 7460 cm(exp-1), which also had not been previously measured. These measurements are reported in this article, and we also give our reanalysis of the prior measurements of the (40 deg 1) (sub III) (left arrow) (00 deg 0) bands. These measurements provide the basis for improving calculated intensities for related hot bands as well as simulations of Venus' spectrum.

Giver, L. P.↗
NASA NTRS2021

Decoding the effects of synonymous variants

Synonymous single nucleotide variants (sSNVs) are common in the human genome but are often overlooked. However, sSNVs can have significant biological impact and may lead to disease. Existing computational methods for evaluating the effect of sSNVs suffer from the lack of gold-standard training/evaluation data and exhibit over-reliance on sequence conservation signals. We developed synVep (synonymous Variant effect predictor), a machine learning-based method that overcomes both of these limitations. Our training data was a combination of variants reported by gnomAD (observed) and those unreported, but possible in the human genome (generated). We used positive-unlabeled learning to purify the generated variant set of any likely unobservable variants. We then trained two sequential extreme gradient boosting models to identify subsets of the remaining variants putatively enriched and depleted in effect. Our method attained 90% precision/recall on a previously unseen set of variants. Furthermore, although synVep does not explicitly use conservation, its scores correlated with evolutionary distances between orthologs in cross-species variation analysis. synVep was also able to differentiate pathogenic vs. benign variants, as well as splice-site disrupting variants (SDV) vs. non-SDVs. Thus, synVep provides an important improvement in annotation of sSNVs, allowing users to focus on variants that most likely harbor effects.

Zishuo Zeng↗
DOE OSTI2021

Arbuscular mycorrhizal fungal community responses to drought and nitrogen fertilization in switchgrass stands

Anthropogenic global change is increasing the severity and frequency of abiotic stresses such as drought that are likely to affect soil communities. Arbuscular mycorrhizal fungi (AMF) play important roles in many soil processes, so it is important to understand how drought affects AMF biodiversity. This is especially relevant in agricultural systems where crops rely on AMF associations for water and nutrient uptake, and where management decisions such as crop selection and fertilizer application may influence how the AMF community responds to drought. In this study, we examined the effects of reduced precipitation and nitrogen fertilization on AMF richness, community composition, and root and soil colonization in monocultures of two cultivars of switchgrass (Panicum virgatum) grown for bioenergy feedstock. We conducted a two-year field experiment using rain-out shelters to manipulate precipitation in mature stands of switchgrass growing in a long-term nitrogen fertilization (0 or 56 kg N ha –1 ) experiment at the W.K. Kellogg Biological Station Long-Term Ecological Research site in Michigan, USA. We expected that AMF richness and colonization would decrease due to drought, as predicted by the stress exclusion hypothesis. Contrary to our expectations, we found that drought stress increased AMF species richness in fertilized plots by 15%; there was no effect of drought on AMF richness in unfertilized plots. Drought also significantly altered AMF community composition, primarily due to increases in Rhizophagus taxa abundance, and reduced AMF root colonization in switchgrass by 6%. We also found variation in AMF richness and colonization across switchgrass cultivars as well as sampling dates. Furthermore, the changes in AMF richness and composition that we observed in this study may have implications for perennial bioenergy feedstock selection and management as changes in AMF communities may feedback to affect host plants.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Desiccation induces varied responses within a soil bacterial genus

Abstract Desiccation impacts a suite of physiological processes in microbes by elevating levels of damaging reactive oxygen species and inducing DNA strand breaks. In response to desiccation‐induced stress, microbes have evolved specialized mechanisms to help them survive. Here, we performed a 128‐day lab desiccation experiment on nine strains from three clades of an abundant soil bacterium, Curtobacterium . We sequenced RNA from each strain at three time points to investigate their response. Curtobacterium was highly resistant to desiccation, outlasting both Escherichia coli and a famously DNA damage‐resistant bacterium, Deinococcus radiodurans . However, within the genus, there were also 10‐fold differences in survival rates among strains. Transcriptomic profiling revealed responses shared within the genus including up‐regulation of genes involved in DNA damage repair, osmolyte production, and efflux pumps, but also up‐regulation of pathways and genes unique to the three clades. For example, trehalose synthesis gene otsB , the chaperone groEL , and the oxygen scavenger katA were all found in either one or two clades but not the third. Here, we provide evidence of considerable variation in closely related strains, and further elucidation of the phylogenetic conservation of desiccation tolerance remains an important goal for microbial ecologists.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Multi-strain analysis of Pseudomonas putida reveals the metabolic and genetic diversity of the species

Pseudomonas putida is a gram-negative bacterial species increasingly utilized in biotechnology due to its robust growth, ability to degrade aromatic compounds, solvent tolerance, and genetic tractability. In this study, we report a comprehensive multi-strain analysis of 164 P. putida strains based on the reconstruction of a pan-putida metabolic network and the formulation of strain-specific genome-scale metabolic models (GEMs). We performed whole-genome sequencing and hybrid assembly for 40 strains, contributing a ~8% increase to the available genomic data for P. putida . Furthermore, high-throughput phenotypic profiling using the Biolog phenotype microarray system for 24 strains on 190 unique carbon sources, along with 15 aromatic compounds not present on Biolog plates, yielded 4,920 unique strain-phenotype measurements. These data were leveraged to curate GEMs for 24 representative strains, including a refined model for strain KT2440, which comprised 1,480 genes and 2,191 metabolites, achieving a prediction accuracy of 91.2% in carbon utilization. Systematic comparison of genomes and GEMs revealed both conserved core pathways and significant allelic and functional divergence across strains, highlighting strain-specific variation in aromatic degradation. While pathways for protocatechuate and phenylacetate degradation were widely conserved, metabolic capabilities for compounds such as ferulate, phenol, and cresols varied markedly, suggesting adaptation to distinct ecological niches. Alleleome analysis of enzymes, such as PcaI and PcaJ, revealed distinct, functionally similar clades, indicating possible convergent evolution or horizontal gene transfer. These results provide computable resources and informative models for selecting P. putida strains with desired traits for biomanufacturing and bioremediation and offer insights into the evolution and phylogeny of the P. putida species.

aromatics utilization↗
DOE OSTI2020

Geology and climate influence rhizobiome composition of the phenotypically diverse tropical tree Tabebuia heterophylla

Plant-associated microbial communities have diverse phenotypic effects on their hosts that are only beginning to be revealed. We hypothesized that morpho-physiological variations in the tropical tree Tabebuia heterophylla, observed on different geological substrates, arise in part due to microbial processes in the rhizosphere. We characterized the microbiota of the rhizosphere and soil communities associated with T. heterophylla trees in high and low altitude sites (with varying temperature and precipitation) of volcanic, karst and serpentine geologies across Puerto Rico. We sampled 6 areas across the island in three geological materials including volcanic, serpentine and karst soils. Collection was done in 2 elevations (>450m and 0-300m high), that included 3 trees for each site and 4 replicate soil samples per tree of both bulk and rhizosphere. Genomic DNA was extracted from 144 samples, and 16S rRNA V4 sequencing was performed on the Illumina MiSeq platform. Proteobacteria, Actinobacteria, and Verrucomicrobia were the most dominant phyla, and microbiomes clustered by geological substrate and elevation. Volcanic samples were enriched in Verrucomicrobia; karst was dominated by nitrogen-fixing Proteobacteria, and serpentine sites harbored the most diverse communities, with dominant Cyanobacteria. Sites with similar climates but differing geologies showed significant differences on rhizobiota diversity and composition demonstrating the importance of geology in shaping the rhizosphere microbiota, with implications for the plant's phenotype. Our study sheds light on the combined role of geology and climate in the rhizosphere microbial consortia, likely contributing to the phenotypic plasticity of the trees.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

A Deep Learning Modeling Framework to Capture Mixing Patterns in Reactive-Transport Systems

Prediction and control of chemical mixing are vital for many scientific areas such as subsurface reactive transport, climate modeling, combustion, epidemiology, and pharmacology. Due to the complex nature of mixing in heterogeneous and anisotropic media, the mathematical models related to this phenomenon are not analytically tractable. Numerical simulations often provide a viable route to predict chemical mixing accurately. However, contemporary modeling approaches for mixing cannot utilize available spatial-temporal data to improve the accuracy of the future prediction and can be compute-intensive, especially when the spatial domain is large and for long-term temporal predictions. To address this knowledge gap, in this work we will present in this paper a deep learning (DL) modeling framework applied to predict the progress of chemical mixing under fast bimolecular reactions. This framework uses convolutional neural networks (CNN) for capturing spatial patterns and long short-term memory (LSTM) networks for forecasting temporal variations in mixing. By careful design of the framework—placement of non-negative constraint on the weights of the CNN and the selection of activation function, the framework ensures non-negativity of the chemical species at all spatial points and for all times. Our DL-based framework is fast, accurate, and requires minimal data for training. The time needed to obtain a forecast using the model is a fraction (≈ O(-6)) of the time needed to obtain the result using a high-fidelity simulation. To achieve an error of 10% (measured using the infinity norm) for capturing local-scale mixing features such as interfacial mixing, only 24% to 32% of the sequence data for model training is required. To achieve the same level of accuracy for capturing global-scale mixing features, the sequence data required for model training is 64% to 70% of the total spatial-temporal data. Hence, the proposed approach—a fast and accurate way to forecast long-time spatial-temporal mixing patterns in heterogeneous and anisotropic media—will be a valuable tool for modeling reactive-transport in a wide range of applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗