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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 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

A plant genetic network for preventing dysbiosis in the phyllosphere

The aboveground parts of terrestrial plants, collectively called the phyllosphere, have a key role in the global balance of atmospheric carbon dioxide and oxygen. The phyllosphere represents one of the most abundant habitats for microbiota colonization. Whether and how plants control phyllosphere microbiota to ensure plant health is not well understood. Here we show that the Arabidopsis quadruple mutant (min7 fls2 efr cerk1; hereafter, mfec)1, simultaneously defective in pattern-triggered immunity and the MIN7 vesicle-trafficking pathway, or a constitutively activated cell death1 (cad1) mutant, carrying a S205F mutation in a membrane-attack-complex/perforin (MACPF)-domain protein, harbour altered endophytic phyllosphere microbiota and display leaf-tissue damage associated with dysbiosis. The Shannon diversity index and the relative abundance of Firmicutes were markedly reduced, whereas Proteobacteria were enriched in the mfec and cad1S205F mutants, bearing cross-kingdom resemblance to some aspects of the dysbiosis that occurs in human inflammatory bowel disease. Bacterial community transplantation experiments demonstrated a causal role of a properly assembled leaf bacterial community in phyllosphere health. Here, the pattern-triggered immune signalling, MIN7 and CAD1 are found in major land plant lineages and are probably key components of a genetic network through which terrestrial plants control the level and nurture the diversity of endophytic phyllosphere microbiota for survival and health in a microorganism-rich environment.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Identification of mobile genetic elements with geNomad

Identifying and characterizing mobile genetic elements in sequencing data is essential for understanding their diversity, ecology, biotechnological applications and impact on public health. Here we introduce geNomad, a classification and annotation framework that combines information from gene content and a deep neural network to identify sequences of plasmids and viruses. geNomad uses a dataset of more than 200,000 marker protein profiles to provide functional gene annotation and taxonomic assignment of viral genomes. Using a conditional random field model, geNomad also detects proviruses integrated into host genomes with high precision. In benchmarks, geNomad achieved high classification performance for diverse plasmids and viruses (Matthews correlation coefficient of 77.8% and 95.3%, respectively), substantially outperforming other tools. Leveraging geNomad’s speed and scalability, we processed over 2.7 trillion base pairs of sequencing data, leading to the discovery of millions of viruses and plasmids that are available through the IMG/VR and IMG/PR databases. geNomad is available at https://portal.nersc.gov/genomad.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Genetic dissection of interspecific differences in yeast thermotolerance

Some of the most unique and compelling survival strategies in the natural world are fixed in isolated species. To date, molecular insight into these ancient adaptations has been limited, as classic experimental genetics has focused on interfertile individuals in populations. Here we use a new mapping approach, which screens mutants in a sterile interspecific hybrid, to identify eight housekeeping genes that underlie the growth advantage of Saccharomyces cerevisiae over its distant relative Saccharomyces paradoxus at high temperature. Pro-thermotolerance alleles at these mapped loci were required for the adaptive trait in S. cerevisiae and sufficient for its partial reconstruction in S. paradoxus . The emerging picture is one in which S. cerevisiae improved the heat resistance of multiple components of the fundamental growth machinery in response to selective pressure. Our study lays the groundwork for the mapping of genotype to phenotype in clades of sister species across Eukarya.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Effects of timber harvesting on the genetic potential for carbon and nitrogen cycling in five North American forest ecozones

Forest ecosystems are critical to global biogeochemical cycles but under pressure from harvesting and climate change. We investigated the efects of organic matter (OM) removal during forest harvesting on the genetic potential of soil communities for biomass decomposition and nitrogen cycling in fve ecozones across North America. We analyzed 107 samples, representing four treatments with varied levels of OM removal, at Long-Term Soil Productivity Study sites. Samples were collected more than ten years after harvesting and replanting and were analyzed via shotgun metagenomics. High-quality short reads totaling 1.2 Tbp were compared to the Carbohydrate Active Enzyme (CAZy) database and a custom database of nitrogen cycle genes. Gene profle variation was mostly explained by ecozone and soil layer. Eleven CAZy and nine nitrogen cycle gene families were associated with particular soil layers across all ecozones. Treatment efects on gene profles were mainly due to harvesting, and only rarely to the extent of OM removal. Harvesting generally decreased the relative abundance of CAZy genes while increasing that of nitrogen cycle genes, although these efects varied among ecozones. Our results suggest that ecozone-specifc nutrient availability modulates the sensitivity of the carbon and nitrogen cycles to harvesting with possible consequences for long-term forest sustainability.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Using genetic algorithms to systematically improve the synthesis conditions of Al-PMOF

The synthesis of metal-organic frameworks (MOFs) is often complex and the desired structure is not always obtained. In this work, we report a methodology that uses a joint machine learning and experimental approach to optimize the synthesis conditions of Al-PMOF (Al 2 (OH) 2 TCPP) [H 2 TCPP = meso-tetra(4-carboxyphenyl)porphine], a promising material for carbon capture applications. Al-PMOF was previously synthesized using a hydrothermal reaction, which gave a low throughput yield due to its relatively long reaction time (16 hours). Here, we use a genetic algorithm to carry out a systematic search for the optimal synthesis conditions and a microwave-based high-throughput robotic platform for the syntheses. We show that, in just two generations, we could obtain excellent crystallinity and yield close to 80% in a much shorter reaction time (50 minutes). Moreover, by analyzing the failed and partially successful experiments, we could identify the most important experimental variables that determine the crystallinity and yield.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Formation mechanism of chalcogenide nanocrystals confined inside genetically engineered virus-like particles

Engineered virus-like particles (VLP) are attractive for fabricating nanostructured materials for applications in diverse areas such as catalysis, drug delivery, biomedicine, composites, etc. Basic understanding of the interaction between the inorganic guest and biomolecular host is thus important for the controlled synthesis of inorganic nanoparticles inside VLP and rational assembly of ordered VLP-based hierarchical nanostructures. We have investigated in detail the formation mechanism and growth kinetics of semiconducting nanocrystals confined inside genetically engineered bacteriophage P22 VLP using semiconducting CdS as a prototypical example. The selective nucleation and growth of CdS at the engineered sites is found to be uniform during the early stage, followed by a more stochastic growth process. Furthermore, kinetic studies reveal that the presence of an engineered biotemplate helps in significantly retarding the reaction rate. These findings provide guidance for the controlled synthesis of a wide range of other inorganic materials confined inside VLP, and are of practical importance for the rational design of VLP-based hierarchical nanostuctures.

PHOTOCATALYSIS↗
DOE OSTI2012

Repeat variation in the human PER2 gene as a new genetic marker associated with cocaine addiction and brain dopamine D2 receptor availability

Low dopamine D2 receptor (D2R) levels in the striatum are consistently reported in cocaine abusers; inter-individual variations in the degree of the decrease suggest a modulating effect of genetic makeup on vulnerability to addiction. The PER2 (Period 2) gene belongs to the clock genes family of circadian regulators; circadian oscillations of PER2 expression in the striatum was modulated by dopamine through D2Rs. Aberrant periodicity of PER2 contributes to the incidence and severity of various brain disorders, including drug addiction. Here we report a newly identified variable number tandem repeat (VNTR) polymorphism in the human PER2 gene (VNTR in the third intron). We found significant differences in the VNTR alleles prevalence across ethnic groups so that the major allele (4 repeats (4R)) is over-represented in non-African population (4R homozygosity is 88%), but not in African Americans (homozygosity 51%). We also detected a biased PER2 genotype distribution among healthy controls and cocaine addicted individuals. In African Americans, the proportion of 4R/three repeat (3R) carriers in healthy controls is much lower than that in cocaine abusers (23% vs 39%, P ¼ 0.004), whereas among non-Africans most 3R/4R heterozygotes are healthy controls (10.5% vs 2.5%, P ¼ 0.04). Analysis of striatal D2R availability measured with positron emission tomography and [11C]raclopride revealed higher levels of D2R in carriers of 4R/4R genotype (Po0.01). Taken together, these results provide preliminary evidence for the role of the PER2 gene in regulating striatal D2R availability in the human brain and in vulnerability for cocaine addiction.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

Structures and stabilities of alkaline earth metal peroxides XO2 (X=Ca, Be, Mg) studied by a genetic algorithm

The structures and stabilities of alkaline earth metal peroxides XO2 (X = Ca, Be, Mg) were studied using an adaptive genetic algorithm (GA) for global structure optimization in combination with first-principles calculations. From the adaptive GA search, we obtained an orthorhombic structure for CaO2 with 12 atoms in the unit cell, which is energetically more favorable than the previously proposed structures. Reaction energy of the decomposition CaO2 → CaO + 1/2O2 determined by density functional theory (DFT) calculation shows that this orthorhombic calcium peroxide structure is thermodynamically stable. The simulated X-ray diffraction (XRD) pattern using our predicted structure is in excellent agreement with experimental data. We also show that crystal phase BeO2 is unlikely to exist under normal conditions. MgO2 has a cubic pyrite structure, but it is not stable against decomposition: MgO2 → MgO + 1/2O2.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Pd n Ag (4-n) and Pd n Pt (4-n) clusters on MgO (100): a density functional surface genetic algorithm investigation

We employed the novel surface mode of the Birmingham Cluster Genetic Algorithm (S-BCGA) for the global optimisation of noble metal tetramers upon an MgO(100) substrate at the GGA-DFT level of theory. The effect of element identity and alloying in surface-bound neutral subnanometre clusters is determined by energetic comparison between all compositions of Pd n Ag (4-n) and Pd n Pt (4-n) . And while the binding strengths to the surface increase in the order Pt > Pd > Ag, the excess energy profiles suggest a preference for mixed clusters for both cases. The binding of CO is also modelled, showing that the adsorption site can be predicted solely by electrophilicity. Comparison to CO binding on a single metal atom shows a reversal of the 5s-d activation process for clusters, weakening the cluster surface interaction on CO adsorption. Charge localisation determines homotop, CO binding and surface site preferences. Furthermore, the electronic behaviour, which is intermediate between molecular and metallic particles allows for tunable features in the subnanometre size range.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Using genetic algorithms to discover novel ground-state triplet conjugated polymers

Stable ground-state triplet π-conjugated copolymers have many interesting electronic and optoelectronic properties. However, the large number of potential monomer combinations makes it impractical to synthesize or even just use density functional theory (DFT) to calculate their triplet ground-state stability. Furthermore, we present a genetic algorithm implementation that uses the semi-empirical GFN2-xTB to find ground-state triplet polymer candidates. We find more than 1400 polymer candidates with a triplet ground-state stability of up to 4 eV versus the singlet. Additionally, we explore the properties of the monomers of those candidates in order to understand the design rules which promote the formation of a stable ground-state triplet in π-conjugated polymers.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Rational design of a genetically encoded NMR zinc sensor

Elucidating the biochemical roles of the essential metal ion, Zn 2+ , motivates detection strategies that are sensitive, selective, quantitative, and minimally invasive in living systems. Fluorescent probes have identified Zn 2+ in cells but complementary approaches employing nuclear magnetic resonance (NMR) are lacking. Recent studies of maltose binding protein (MBP) using ultrasensitive 129 Xe NMR spectroscopy identified a switchable salt bridge which causes slow xenon exchange and elicits strong hyperpolarized 129 Xe chemical exchange saturation transfer (hyper-CEST) NMR contrast. To engineer the first genetically encoded, NMR-active sensor for Zn 2+ , we converted the MBP salt bridge into a Zn 2+ binding site, while preserving the specific xenon binding cavity. The zinc sensor (ZS) at only 1 μM achieved ‘turn-on’ detection of Zn 2+ with pronounced hyper-CEST contrast. This made it possible to determine different Zn 2+ levels in a biological fluid via hyper-CEST. ZS was responsive to low-micromolar Zn 2+ , only modestly responsive to Cu 2+ , and nonresponsive to other biologically important metal ions, according to hyper-CEST NMR spectroscopy and isothermal titration calorimetry (ITC). Protein X-ray crystallography confirmed the identity of the bound Zn 2+ ion using anomalous scattering: Zn 2+ was coordinated with two histidine side chains and three water molecules. Penta-coordinate Zn 2+ forms a hydrogen-bond-mediated gate that controls the Xe exchange rate. Metal ion binding affinity, 129 Xe NMR chemical shift, and exchange rate are tunable parameters via protein engineering, which highlights the potential to develop proteins as selective metal ion sensors for NMR spectroscopy and imaging.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Hybrid feature selection approach for power transformer fault diagnosis based on support vector machine and genetic algorithm

To further improve fault diagnosis accuracy, a new hybrid feature selection approach combined with a genetic algorithm (GA) and support vector machine (SVM) is presented in this study. Adaptive synthetic technique and arctangent transformation method are adopted to improve the statistical property of the training set (IEC TC10 dataset). Five filter methods based on different evaluation metrics are employed to rank 48 input features derived from dissolved gas analysis (DGA). Then, feature combination methods are applied to aggregate feature ranks and form a lower-dimension candidate feature subset. The GA-SVM model is implemented to optimise parameters and select optimal feature subsets. 5-fold cross-validation accuracy of the GA-SVM is used to evaluate fault diagnosis capability of feature subsets and finally, a novel subset is determined as the optimal feature subset. Accuracy comparison manifests the superiority of the optimal feature subsets over that of conventional approaches. Besides, generalisation and robustness of the optimal subset are validated by testing DGA samples from the local power utility. Results indicate that the optimal feature subset obtained by the proposed method can significantly improve the accuracies of power transformer fault diagnosis.

Kari, Tusongjiang↗
DOE OSTI2018

Effect of Genetic Diagnosis on Patients with Previously Undiagnosed Disease

Background. Despite extensive medical evaluation many patients with chronic disease remain without a diagnosis. The Undiagnosed Diseases Network (UDN) was established to embrace the most challenging cases in medicine and to characterize the biology of newly discovered diseases. Methods. The UDN was formed in 2014 as a National Institutes of Health (NIH)-funded network of seven clinical sites, two sequencing cores, and a coordinating center. Later a central biorepository, metabolomics core, and model organisms screening center were added. We undertook a retrospective evaluation of the patients referred since the network formed to evaluate the efficacy of this approach. Results. Between September 16, 2015 and May 23, 2017, 1519 patients were referred to the network (53% female). Six hundred and one cases (40%) were accepted for evaluation (53% female). Of those accepted, 192 (32%) had previously undergone exome sequencing. The most common primary symptom categories of accepted patients were neurological (40%), musculoskeletal (9.7%), immunological (6.8%), gastrointestinal (6.5%), and rheumatological (5.7%). The number of completed evaluations on May 23, 2017, was 365, at which time, 100 patients had received diagnoses. In the intervening period, a further 25 received a diagnosis indicating a network diagnosis rate of 34%. Some diagnoses were made from clinical review alone (10%). Many were informed through sequencing the exomes or genomes of the patient or family (72%). A majority of diagnoses (83%) were deemed medically actionable by the clinical team. Indeed, of the total, 30% led to changes in therapy, 24% led to changes in the diagnostic workup, and 28% allowed variant-specific genetic counseling. Through the combined work of the network, a total of 24 new syndromes were defined. Conclusions. A collaborative network with access to state-of-the-art diagnostic tools can expand the medical record of human disease providing actionable clinical diagnoses to a substantial majority of those patients.

Splinter, Kimberly↗
DOE OSTI2012

Multi channel thermal hydraulic analysis of gas cooled fast reactor using genetic algorithm

There are three analyzes to be done in the design process of nuclear reactor i.e. neutronic analysis, thermal hydraulic analysis and thermodynamic analysis. The focus in this article is the thermal hydraulic analysis, which has a very important role in terms of system efficiency and the selection of the optimal design. This analysis is performed in a type of Gas Cooled Fast Reactor (GFR) using cooling Helium (He). The heat from nuclear fission reactions in nuclear reactors will be distributed through the process of conduction in fuel elements. Furthermore, the heat is delivered through a process of heat convection in the fluid flow in cooling channel. Temperature changes that occur in the coolant channels cause a decrease in pressure at the top of the reactor core. The governing equations in each channel consist of mass balance, momentum balance, energy balance, mass conservation and ideal gas equation. The problem is reduced to finding flow rates in each channel such that the pressure drops at the top of the reactor core are all equal. The problem is solved numerically with the genetic algorithm method. Flow rates and temperature distribution in each channel are obtained here.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2012

Genetic algorithms applied to reconstructing coded imaging of neutrons and analysis of residual watermark

Monte-Carlo simulation of neutron coded imaging based on encoding aperture for Z-pinch of large field-of-view with 5 mm radius has been investigated, and then the coded image has been obtained. Reconstruction method of source image based on genetic algorithms (GA) has been established. 'Residual watermark,' which emerges unavoidably in reconstructed image, while the peak normalization is employed in GA fitness calculation because of its statistical fluctuation amplification, has been discovered and studied. Residual watermark is primarily related to the shape and other parameters of the encoding aperture cross section. The properties and essential causes of the residual watermark were analyzed, while the identification on equivalent radius of aperture was provided. By using the equivalent radius, the reconstruction can also be accomplished without knowing the point spread function (PSF) of actual aperture. The reconstruction result is close to that by using PSF of the actual aperture.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

Genetic algorithm applied to the optimization of quantum cascade lasers with second harmonic generation

A computational model for the optimization of the second order optical nonlinearities in GaInAs/AlInAs quantum cascade laser structures is presented. The set of structure parameters that lead to improved device performance was obtained through the implementation of the Genetic Algorithm. In the following step, the linear and second harmonic generation power were calculated by self-consistently solving the system of rate equations for carriers and photons. This rate equation system included both stimulated and simultaneous double photon absorption processes that occur between the levels relevant for second harmonic generation, and material-dependent effective mass, as well as band nonparabolicity, were taken into account. The developed method is general, in the sense that it can be applied to any higher order effect, which requires the photon density equation to be included. Specifically, we have addressed the optimization of the active region of a double quantum well In{sub 0.53}Ga{sub 0.47}As/Al{sub 0.48}In{sub 0.52}As structure and presented its output characteristics.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2014

Genetically designed L3 photonic crystal nanocavities with measured quality factor exceeding one million

We report on the experimental realization of ultra-high quality factor (Q) designs of the L3-type photonic crystal nanocavity. Based on genetic optimization of the positions of few nearby holes, our design drastically improves the performance of the conventional L3 as experimentally confirmed by direct measurement of Q ≃ 2 × 10{sup 6} in a silicon-based photonic crystal membrane. Our devices rank among the highest Q/V ratios ever reported in photonic crystal cavities, holding great promise for the realization of integrated photonic platforms based on ultra-high-Q resonators.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2014

A genetic algorithm for first principles global structure optimization of supported nano structures

We present a newly developed publicly available genetic algorithm (GA) for global structure optimisation within atomic scale modeling. The GA is focused on optimizations using first principles calculations, but it works equally well with empirical potentials. The implementation is described and benchmarked through a detailed statistical analysis employing averages across many independent runs of the GA. This analysis focuses on the practical use of GA’s with a description of optimal parameters to use. New results for the adsorption of M{sub 8} clusters (M = Ru, Rh, Pd, Ag, Pt, Au) on the stoichiometric rutile TiO{sub 2}(110) surface are presented showing the power of automated structure prediction and highlighting the diversity of metal cluster geometries at the atomic scale.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗