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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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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Temporal Dynamics of DNA Methylation Patterns in Response to Rearing Juvenile Steelhead (Oncorhynchus mykiss) in a Hatchery versus Simulated Stream Environment

Genetic selection is often implicated as the underlying cause of heritable phenotypic differences between hatchery and wild populations of steelhead trout (Oncorhynchus mykiss) that also differ in lifetime fitness. Developmental plasticity, which can also affect fitness, may be mediated by epigenetic mechanisms such as DNA methylation. Our previous study identified significant differences in DNA methylation between adult hatchery- and natural-origin steelhead from the same population that could not be distinguished by DNA sequence variation. In the current study, we tested whether hatchery-rearing conditions can influence patterns of DNA methylation in steelhead with known genetic backgrounds, and assessed the stability of these changes over time. Eyed-embryos from 22 families of Methow River steelhead were split across traditional hatchery tanks or a simulated stream-rearing environment for 8 months, followed by a second year in a common hatchery tank environment. Family assignments were made using a genetic parentage analysis to account for relatedness among individuals. DNA methylation patterns were examined in the liver, a relatively homogeneous organ that regulates metabolic processes and somatic growth, of juveniles at two time points: after eight months of rearing in either a tank or stream environment and after a subsequent year of rearing in a common tank environment. Further, we analyzed DNA methylation in the sperm of mature 2-year-old males from the earlier described treatments to assess the potential of environmentally-induced changes to be passed to offspring. Hepatic DNA methylation changes in response to hatchery versus stream-rearing in yearling fish were substantial, but few persisted after a second year in the tank environment. However, the early rearing environment appeared to affect how fish responded to developmental and environmental signals during the second year since novel DNA methylation differences were identified in the livers of hatchery versus stream-reared fish after a year of common tank rearing. Furthermore, we found profound differences in DNA methylation due to age, irrespective of rearing treatment. This could be due to smoltification associated changes in liver physiology after the second year of rearing. Although few rearing-treatment effects were observed in the sperm methylome, strong family effects were observed. These data suggest limited potential for intergenerational changes, but highlight the importance of understanding the effects of kinship among studied individuals in order to properly analyze and interpret DNA methylation data in natural populations. Our work is the first to study family effects and temporal dynamics of DNA methylation patterns in response to hatchery-rearing.

Gavery, Mackenzie R. (ORCID:0000000150103399)↗
DOE OSTI2023

Mutations in the Second Alternative Oxidase Gene: A New Approach to Group Aspergillus niger Strains

Alternative oxidase is a terminal oxidase in the branched mitochondrial electron transport chain of most fungi including Aspergillus niger (subgenus Circumdati, section Nigri). A second, paralogous aox gene (aoxB) is extant in some A. niger isolates but also present in two divergent species of the subgenus Nidulantes—A. calidoustus and A. implicatus—as well as in Penicillium swiecickii. Black aspergilli are cosmopolitan opportunistic fungi that can cause diverse mycoses and acute aspergillosis in immunocompromised individuals. Amongst the approximately 75 genome-sequenced A. niger strains, aoxB features considerable sequence variation. Five mutations were identified that rationally affect transcription or function or terminally modify the gene product. One mutant allele that occurs in CBS 513.88 and A. niger neotype strain CBS 554.65 involves a chromosomal deletion that removes exon 1 and intron 1 from aoxB. Another aoxB allele results from retrotransposon integration. Three other alleles result from point mutations: a missense mutation of the start codon, a frameshift, and a nonsense mutation. A. niger strain ATCC 1015 has a full-length aoxB gene. The A. niger sensu stricto complex can thus be subdivided into six taxa according to extant aoxB allele, which may facilitate rapid and accurate identification of individual species

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Systematic identification of cis -regulatory variants that cause gene expression differences in a yeast cross

Sequence variation in regulatory DNA alters gene expression and shapes genetically complex traits. However, the identification of individual, causal regulatory variants is challenging. Here, we used a massively parallel reporter assay to measure the cis-regulatory consequences of 5832 natural DNA variants in the promoters of 2503 genes in the yeast Saccharomyces cerevisiae. We identified 451 causal variants, which underlie genetic loci known to affect gene expression. Several promoters harbored multiple causal variants. In five promoters, pairs of variants showed non-additive, epistatic interactions. Causal variants were enriched at conserved nucleotides, tended to have low derived allele frequency, and were depleted from promoters of essential genes, which is consistent with the action of negative selection. Causal variants were also enriched for alterations in transcription factor binding sites. Models integrating these features provided modest, but statistically significant, ability to predict causal variants. This work revealed a complex molecular basis for cis-acting regulatory variation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Investigation of inter- and intraspecies variation through genome sequencing of Aspergillus section Nigri

Aspergillus section Nigri comprises filamentous fungi relevant to biomedicine, bioenergy, health, and biotechnology. In order to learn more about fungal speciation, as well as potential for applications in biotechnology and biomedicine, we sequenced 23 genomes de novo, forming a full genome compendium for the section (26 species), as well as six A. niger isolates. This allowed us to quantify both inter- and intra-species genomic variation. We further predicted 17,903 CAZymes and 2,717 secondary metabolite gene clusters, which we condensed into 455 distinct families corresponding to compound classes, 49% of which are only found in single species. We performed metabolomics and genetic engineering to correlate genotypes to phenotypes, as demonstrated for the metabolite aurasperone, and by heterologous transfer of citrate production to A. nidulans. Experimental and computational analyses all supported a role in speciation for secondary metabolism and regulators and allowed us to propose a three-step model for fungal speciation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Design of diverse, functional mitochondrial targeting sequences across eukaryotic organisms using variational autoencoder

Mitochondria play a key role in energy production and metabolism, making them a promising target for metabolic engineering and disease treatment. However, despite the known influence of passenger proteins on localization efficiency, only a few protein-localization tags have been characterized for mitochondrial targeting. To address this limitation, we leverage a Variational Autoencoder to design novel mitochondrial targeting sequences. In silico analysis reveals that a high fraction of the generated peptides (90.14%) are functional and possess features important for mitochondrial targeting. We characterize artificial peptides in four eukaryotic organisms and, as a proof-of-concept, demonstrate their utility in increasing 3-hydroxypropionic acid titers through pathway compartmentalization and improving 5-aminolevulinate synthase delivery by 1.62-fold and 4.76-fold, respectively. Moreover, we employ latent space interpolation to shed light on the evolutionary origins of dual-targeting sequences. Overall, our work demonstrates the potential of generative artificial intelligence for both fundamental research and practical applications in mitochondrial biology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Data for "Design of Diverse, Functional Mitochondrial Targeting Sequences Across Eukaryotic Organisms Using Variational Autoencoder"

Mitochondria play a key role in energy production and metabolism, making them a promising target for metabolic engineering and disease treatment. However, despite the known influence of passenger proteins on localization efficiency, only a few protein-localization tags have been characterized for mitochondrial targeting. To address this limitation, we leverage a Variational Autoencoder to design novel mitochondrial targeting sequences. In silico analysis reveals that a high fraction of the generated peptides (90.14%) are functional and possess features important for mitochondrial targeting. We characterize artificial peptides in four eukaryotic organisms and, as a proof-of-concept, demonstrate their utility in increasing 3-hydroxypropionic acid titers through pathway compartmentalization and improving 5-aminolevulinate synthase delivery by 1.62-fold and 4.76-fold, respectively. Moreover, we employ latent space interpolation to shed light on the evolutionary origins of dual-targeting sequences. Overall, our work demonstrates the potential of generative artificial intelligence for both fundamental research and practical applications in mitochondrial biology.

AI/ML↗
DOE OSTI2020

Organic amendments change soil organic C structure and microbial community but not total organic matter on sub-decadal scales

Organic C has many benefits for soil, but it is depleted by tillage and crop harvest, and especially so for biofuel crops. Accordingly, strategies such as partially retaining stover or planting a cover crop can help ameliorate the negative effect of C removal. We used a long-term field experiment to study the impacts of stover retention and planting cover crop on soil organic matter (SOM), its extractable components and the soil microbial community. SOM chemical composition characterization was determined by electrospray ionization (ESI) coupled with Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) in sequential water, methanol (MeOH), and chloroform (CHCl3) extracts. The characteristics of the soil bacterial community were measured by phospholipid fatty acid (PLFA), real-time quantitative PCR, and 16S rRNA gene sequence. The variations in total SOM content, total microbial biomass, and bacterial population were slight among treatments, but SOM chemical compounds, arbuscular mycorrhizal fungi (AMF) biomass, and bacterial structure changed significantly, and especially so in the coupled application of stover retention and cover crop. Specifically, stover retention enriched more lignin-like compounds in soil, whereas cover crop enriched more condensed hydrocarbons, and had more compounds with an aromaticity index (AI) >0.5. The bacterial community was not altered by the cover crop, but the corn stover retention increased the relative abundances of Myxococcales (Deltaproteobacteria) and decreased that of Actinobacteria. Redundancy analysis (RDA) further unveiled that the bacterial community in the stover treatments had significantly positive association with CHCl3-extracted chemical classes, i.e. unsaturated hydrocarbon and lipid with the coupled application (stover and cover crop), and lignin and protein with the single corn stover treatment. Taken together, our study shows how different C addition practices influence the molecular composition of SOM and the structure of soil microbial communities.

Xu, Jiangbin↗
DOE OSTI2020

Platform for efficient large-scale storage and analysis of multi-omics data in plant and microbial systems (Final Technical Report)

Genomic variation at the sequence level fundamentally affects the phenotypic state of all organisms at all stages of development, while dynamic processes such as changes in the epigenome (e.g. DNA methylation state) and transcriptome regulate the specific phenotype expressed at any given state of development based upon that genomic variation. In plants, DNA methylation is a particularly important mechanism for both regulating transcriptomic expression and for management of genomic variations that could be deleterious to the organism due to the presence of active retrotransposons in plant genomes. While DNA methylation is heritable, it is also dynamic through a given plant’s development and life cycle, particularly during the development from seed to mature specimen suggesting variations in DNA methylation could be critical regulators of biologically and commercially important phenotypes such as time to flowering; in addition, plant DNA methylation is more complex than that of animals, with methylation of CHG and CHH trinucleotides evident in addition to the better-known CG methylation. The complexity of plant DNA methylation and its interplay with genomic sequence variation, transcriptomics and other epigenomic factors demand a storage and analysis framework that can cope with the complexity both within a single specimen and with analyses that span many individuals and even many species, such as attempts to extend models from model organisms to commercially relevant species. In addition to complexity, the rapid development and proliferation of sequencing technology has led to an explosion of data volume that conventional storage and analysis solutions will likely be unable to cope with in the long run. We proposed to study these with suitable distributed storage and computation and therefore for the application of cloud computing to biological analyses; integrate with existing data sources and compatible with virtually any interface use case, from fully automated shell scripts to notebooks and do all these at scale in this STTR grant.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Data-driven prediction of geometry- and toolpath sequence-dependent intra-layer process conditions variations in laser powder bed fusion

Geometrical features and toolpath sequence are two important factors that cause process condition variations, such as variations in the meltpool temperature or meltpool size, that might lead to undesired material properties in the laser powder bed fusion (LPBF) process. Due to the high dynamics and complex physics of the LPBF process, it is difficult to predict variations in process conditions with simulations alone. Advances in measurement technology and computational technologies open up new possibilities for smart manufacturing. In this paper, a data-driven method to predict intra-layer variations in the processing conditions that source from the toolpath sequence and part geometry is presented. The approach is demonstrated using two-color on-axis pyrometer measurements. Three demonstration cases are presented in which it is demonstrated (1) how the trained predictive model can be used as a filter to ease the interpretation of process variations and discover patterns related to toolpath and part geometry, and (2) how to generate predictions that can be used for feedforward control, i.e., for adjusting laser power or scanning speed along the toolpath using a meltpool temperature prediction model generated based on on-axis measurements. Results show that the developed prediction model is able to meaningfully predict process variations resulted from toolpath sequence and geometry. Predictions are aligned with the results from the related work of others and for the case of 180° laser path turnarounds in our high-speed X-ray imaging experiments. In conclusion, the potential issues related to the current maturity status of the process and measuring equipment that could in practice affect the performance of the proposed solutions are also discussed.

42 ENGINEERING↗
DOE OSTI2021

Adaptive pruning-based optimization of parameterized quantum circuits

Abstract Variational hybrid quantum–classical algorithms are powerful tools to maximize the use of noisy intermediate-scale quantum devices. While past studies have developed powerful and expressive ansatze, their near-term applications have been limited by the difficulty of optimizing in the vast parameter space. In this work, we propose a heuristic optimization strategy for such ansatze used in variational quantum algorithms, which we call ‘parameter-efficient circuit training (PECT)’. Instead of optimizing all of the ansatz parameters at once, PECT launches a sequence of variational algorithms, in which each iteration of the algorithm activates and optimizes a subset of the total parameter set. To update the parameter subset between iterations, we adapt the Dynamic Sparse Reparameterization scheme which was originally proposed for training deep convolutional neural networks. We demonstrate PECT for the Variational Quantum Eigensolver, in which we benchmark unitary coupled-cluster ansatze including UCCSD and k -UpCCGSD, as well as the Low-Depth Circuit Ansatz (LDCA), to estimate ground state energies of molecular systems. We additionally use a layerwise variant of PECT to optimize a hardware-efficient circuit for the Sycamore processor to estimate the ground state energy densities of the one-dimensional Fermi-Hubbard model. From our numerical data, we find that PECT can enable optimizations of certain ansatze that were previously difficult to converge and more generally can improve the performance of variational algorithms by reducing the optimization runtime and/or the depth of circuits that encode the solution candidate(s).

Physics↗
DOE OSTI2017

Salmonella enterica Serovar Typhi Lipopolysaccharide O-Antigen Modification Impact on Serum Resistance and Antibody Recognition

Salmonella enterica serovar Typhi is a human-restricted Gram-negative bacterial pathogen responsible for causing an estimated 27 million cases of typhoid fever annually, leading to 217,000 deaths, and current vaccines do not offer full protection. The O-antigen side chain of the lipopolysaccharide is an immunodominant antigen, can define host-pathogen interactions, and is under consideration as a vaccine target for some Gram-negative species. The composition of the O-antigen can be modified by the activity of glycosyltransferase (gtr) operons acquired by horizontal gene transfer. Here we investigate the role of two gtr operons that we identified in the S. Typhi genome. Strains were engineered to express specific gtr operons. Full chemical analysis of the O-antigens of these strains identified gtr-dependent glucosylation and acetylation. The glucosylated form of the O-antigen mediated enhanced survival in human serum and decreased complement binding. A single nucleotide deviation from an epigenetic phase variation signature sequence rendered the expression of this glucosylating gtr operon uniform in the population. In contrast, the expression of the acetylating gtrC gene is controlled by epigenetic phase variation. Acetylation did not affect serum survival, but phase variation can be an immune evasion mechanism, and thus, this modification may contribute to persistence in a host. In murine immunization studies, both O-antigen modifications were generally immunodominant. Our results emphasize that natural O-antigen modifications should be taken into consideration when assessing responses to vaccines, especially O-antigen-based vaccines, and that the Salmonella gtr repertoire may confound the protective efficacy of broad-ranging Salmonella lipopolysaccharide conjugate vaccines.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

The Physiological Functions and Structural Determinants of Catalytic Bias in the [FeFe]-Hydrogenases CpI and CpII of Clostridium pasteurianum Strain W5

Here, the first generation of biochemical studies of complex, iron-sulfur-cluster-containing [FeFe]-hydrogenases and Mo-nitrogenase were carried out on enzymes purified from Clostridium pasteurianum (strain W5). Previous studies suggested that two distinct [FeFe]-hydrogenases are expressed differentially under nitrogen-fixing and non-nitrogen-fixing conditions. As a result, the first characterized [FeFe]-hydrogenase (CpI) is presumed to have a primary role in central metabolism, recycling reduced electron carriers that accumulate during fermentation via proton reduction. A role for capturing reducing equivalents released as hydrogen during nitrogen fixation has been proposed for the second hydrogenase, CpII. Biochemical characterization of CpI and CpII indicated CpI has extremely high hydrogen production activity in comparison to CpII, while CpII has elevated hydrogen oxidation activity in comparison to CpI when assayed under the same conditions. This suggests that these enzymes have evolved a catalytic bias to support their respective physiological functions. Using the published genome of C. pasteurianum (strain W5) hydrogenase sequences were identified, including the already known [NiFe]-hydrogenase, CpI, and CpII sequences, and a third hydrogenase, CpIII was identified in the genome as well. Quantitative real-time PCR experiments were performed in order to analyze transcript abundance of the hydrogenases under diazotrophic and non-diazotrophic growth conditions. There is a markedly reduced level of CpI gene expression together with concomitant increases in CpII gene expression under nitrogen-fixing conditions. Structure-based analyses of the CpI and CpII sequences reveal variations in their catalytic sites that may contribute to their alternative physiological roles. This work demonstrates that the physiological roles of CpI and CpII are to evolve and to consume hydrogen, respectively, in concurrence with their catalytic activities in vitro , with CpII capturing excess reducing equivalents under nitrogen fixation conditions. Comparison of the primary sequences of CpI and CpII and their homologs provides an initial basis for identifying key structural determinants that modulate hydrogen production and hydrogen oxidation activities.

09 BIOMASS FUELS↗
DOE OSTI2017

Community detection in sequence similarity networks based on attribute clustering

Networks are powerful tools for the presentation and analysis of interactions in multi-component systems. A commonly studied mesoscopic feature of networks is their community structure, which arises from grouping together similar nodes into one community and dissimilar nodes into separate communities. Here in this paper, the community structure of protein sequence similarity networks is determined with a new method: Attribute Clustering Dependent Communities (ACDC). Sequence similarity has hitherto typically been quantified by the alignment score or its expectation value. However, pair alignments with the same score or expectation value cannot thus be differentiated. To overcome this deficiency, the method constructs, for pair alignments, an extended alignment metric, the link attribute vector, which includes the score and other alignment characteristics. Rescaling components of the attribute vectors qualitatively identifies a systematic variation of sequence similarity within protein superfamilies. The problem of community detection is then mapped to clustering the link attribute vectors, selection of an optimal subset of links and community structure refinement based on the partition density of the network. ACDC-predicted communities are found to be in good agreement with gold standard sequence databases for which the "ground truth" community structures (or families) are known. ACDC is therefore a community detection method for sequence similarity networks based entirely on pair similarity information. A serial implementation of ACDC is available from https://cmb.ornl.gov/resources/developments

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

SU-F-J-103: Assessment of Liver Tumor Contrast for Radiation Therapy: Inter-Patient and Inter-Sequence Variability

Purpose: To determine the variation in tumor contrast between different MRI sequences and between patients for the purpose of MRI-based treatment planning. Methods: Multiple MRI scans of 11 patients with cancer(s) in the liver were included in this IRB-approved study. Imaging sequences consisted of T1W MRI, Contrast-Enhanced T1W MRI, T2W MRI, and T2*/T1W MRI. MRI images were acquired on a 1.5T GE Signa scanner with a four-channel torso coil. We calculated the tumor-to-tissue contrast to noise ratio (CNR) for each MR sequence by contouring the tumor and a region of interest (ROI) in a homogeneous region of the liver using the Eclipse treatment planning software. CNR was calculated (I-Tum-I-ROI)/SD-ROI, where I-Tum and I-ROI are the mean values of the tumor and the ROI respectively, and SD-ROI is the standard deviation of the ROI. The same tumor and ROI structures were used in all measurements for different MR sequences. Inter-patient Coefficient of variation (CV), and inter-sequence CV was determined. In addition, mean and standard deviation of CNR were calculated and compared between different MR sequences. Results: Our preliminary results showed large inter-patient CV (range: 37.7% to 88%) and inter-sequence CV (range 5.3% to 104.9%) of liver tumor CNR, indicating great variations in tumor CNR between MR sequences and between patients. Tumor CNR was found to be largest in CE-T1W (8.5±7.5), followed by T2W (4.2±2.4), T1W (3.4±2.2), and T2*/T1W (1.7±0.6) MR scans. The inter-patient CV of tumor CNR was also the largest in CE-T1W (88%), followed by T1W (64.3%), T1W (56.2%), and T2*/T1W (37.7) MR scans. Conclusion: Large inter-sequence and inter-patient variations were observed in liver tumor CNR. CE-T1W MR images on average provided the best tumor CNR. Efforts are needed to optimize tumor contrast and its consistency for MRI-based treatment planning of cancer in the liver. This project is supported by NIH grant: 1R21CA165384.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Polymorphism in Self-Assembly of Short Peptoid Sequences

Due to various applications enabled by diverse morphologies of self-assembled sequence-defined polymers, controlling the self-assembly of synthetic peptidomimetics into designed morphologies has emerged as a promising route for the development of bioinspired functional materials. Herein, we report morphological control over the assembly of a series of short peptoids, or poly-N-substituted glycines, that contain asymmetric hydrophobic domains. We demonstrate that the inherent flexibility of amphiphilic peptoid bilayers drives assembly polymorphism, resulting in the coexistence of nanosheets, twisted ribbons, and nanofibers three distinct morphologies. By tuning peptoid molecular interactions through variations in sequence design, solution pH, and temperature, we demonstrate precise control over the twisting and folding of peptoid bilayers, enabling the formation of well-defined nanosheets and nanohelices. Molecular dynamics simulations further unravel how the introduction of asymmetric hydrophobic domains enables the flexibility of peptoid bilayers and results in peptoid assembly polymorphism. By tuning peptoid molecular interactions through heating, we further demonstrate the transformation of nanosheets into nanohelices. We envision that our mechanistic investigation of peptoid assembly polymorphism provides a strong foundation for leveraging peptoid sequences and chemistries to achieve controlled molecular interactions, driving the creation of biomimetic materials with tailored morphologies and functionalities.

assembly polymorphism↗
DOE OSTI2020

Lipocalin Blc is a potential heme-binding protein

Lipocalins are a superfamily of functionally diverse proteins defined by a well-conserved tertiary structure despite variation in sequence. Lipocalins bind and transport small hydrophobic molecules in organisms of all kingdoms. However, there is still uncertainty regarding the function of some members of the family, including bacterial lipocalin Blc from Escherichia coli. Here, we present evidence that lipocalin Blc may be involved in heme binding, trans-periplasmic transport, or heme storage. This conclusion is supported by a cocrystal structure, mass-spectrometric data, absorption titration, and in silico analysis. Binding of heme is observed at low micromolar range with one-to-one ligand-to-protein stoichiometry. However, the absence of classical coordination to the iron atom leaves the possibility that the primary ligand of Blc is another tetrapyrrole.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

A study of mechanistic mapping of novel SNPs to male breast cancer

Alterations in BRCA2, PALB2, CHEK2, and p53 genes have been identified for their association with male breast cancer in various studies. The incidence of male breast cancer in India is consistent with its global rate. The present study was carried out with an aim to evaluate the genetic alterations in male breast cancer patients from Malwa region of Punjab, India. Four male breast cancer patients belonging to different families were recruited from Guru Gobind Singh Medical College and Hospital, Faridkot, India. A total of 51 genes reported with implications in the pathogenesis of breast cancer were screened using next generation sequencing. Germline variations were found in BRCA1, BRCA2, PMS2, p53, and PALB2 genes, previously reported to be associated with MBC as well as FBC. In addition to these, 13 novel missense alterations were detected in eight genes including STK11, FZR1, PALB2, BRCA2, NF2, BAP1, BARD1, and CHEK2. Impact of these missense alterations on structure and function of protein was also analyzed through molecular dynamics simulation. Structural analysis of these single nucleotide polymorphisms (SNPs) revealed significant impact on the encoded protein functioning.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2017

Fast heating of fuel assembled in a spherical deuterated polystyrene shell target by counter-irradiating tailored laser pulses delivered by a HAMA 1 Hz ICF driver

Fast heating is a method of heating an assembled high-density plasma into a hot state by irradiating it with short-duration (sub-picosecond), high-intensity ($>$ $10^{18}$ W ${\rm cm}^{-2}$ ) laser pulses before the plasma expands and dissolves hydrodynamically. In this paper, we present detailed experimental results of fast heating fuel assembled in a spherical deuterated polystyrene shell target of 500 ${\mu}$ m diameter and 7 μm thickness with counterbeam illumination by using a HAMA 1 Hz, 5.9 J inertial confinement fusion laser driver with pulse tailoring. These tailored pulses contain three pulses in sequence: a 'foot' pulse of 2.4 J/25 ns, a 'spike' pulse of 0.5 J/300 ps and a 'heater' pulse of 0.4 J/110 fs; these pulses are designed to assemble the fuel and heat it. By varying the energy of the foot pulse, we find that fast heating the fuel is achieved only if the fuel is weakly ablated by the foot pulse and then shock-assembled by the spike pulse into the target centre so that the heater pulse can access the fuel with a focal intensity greater than $10^{18}$ W ${\rm cm}^{-2}$ . Without a foot pulse, the heater pulse contributes to assembling the fuel. For higher foot-pulse energies, the heater pulse drives a hydrodynamic motion with speeds of the order 107 cm ${\rm s}^{-1}$ with intensities of the order $10^{17}$ W ${\rm cm}^{-2}$ , resulting in re-assembling and additional heating of the pre-assembled fuel. Once a shock-assembled core is achieved at the target centre, we succeed qualitatively in fast heating the core for shots in sequence with variations of laser energy within 18%. The coupling efficiency from the heating laser to the core is inferred to be $(10 \pm 2)$ % in total: $(8 \pm 1.6)$ % for the ionized bulk electrons and $(2 \pm 0.4)$ % for the bulk ions. The fusion neutron spectrum detected on the laser axis exhibits peaks at 1.0 MeV, 1.7 MeV and 3.8 MeV. These peaks are attributed to the $C(d, n){\hspace{0pt}}^{13}$ N and $d(d, n){\hspace{0pt}}^3$ He reactions induced by counterpropagating fast deuterons accelerated by the photon pressure of the heating pulses.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗