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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 343 records · Page 19

Accuracy of finite-difference harmonic frequencies in density functional theory

Analytic Hessians are often viewed as essential for the calculation of accurate harmonic frequencies, but the implementation of analytic second derivatives is nontrivial and solution of the requisite coupled-perturbed equations engenders a sizable memory footprint for large systems, given that these equations are not required for energy and gradient calculations in density functional theory. Here, we benchmark the alternative approach to harmonic frequencies based on finite differences of analytic first derivatives, a procedure that is amenable to large-scale parallelization. Not only for absolute frequencies but also for isotopic and conformer-dependent frequency shifts in flexible molecules, we find that the finite-difference approach exhibits mean errors < 0.1 cm -1 as compared to results based on an analytic Hessian. For very small frequencies corresponding to nonbonded vibrations in noncovalent complexes (for which the harmonic approximation is questionable anyway), the finite-difference error can be larger, but even in these cases the errors can be reduced below 0.1 cm -1 by judicious choice of the displacement step size and a higher-order finite-difference approach. Finally, the surprising accuracy and robustness of the finite-difference results suggests that availability of the analytic Hessian is not so important in today's era of commodity processors that are readily available in large numbers.

74 ATOMIC AND MOLECULAR PHYSICS↗

The effect of polymer grafting on the mechanical properties of PEG-grafted cellulose nanocrystals in poly(lactic acid)

Poly(lactic acid) (PLA) is a commercially available bio-based polymer that is a potential alternative to many commodity petrochemical-based polymers. However, PLA's thermomechanical properties limit its use in many applications. Incorporating polymer-grafted cellulose nanocrystals (CNCs) is one potential route to improving these mechanical properties. One key challenge in using these polymer-grafted nanoparticles is to understand which variables associated with polymer grafting are most important for improving composite properties. In this work, poly(ethylene glycol)-grafted CNCs are used to study the effects of polymer grafting density and molecular weight on the properties of PLA composites. All CNC nanofillers are found to reinforce PLA above the glass transition temperature, but non-grafted CNCs and CNCs grafted with short PEG chains (<2 kg mol –1 ) are found to cause significant embrittlement, generally resulting in less than 3% elongation-at-break. By grafting higher molecular weight PEG (10 kg mol –1 ) onto the CNCs at a grafting density where the polymer chains are predicted to be in the semi-dilute polymer brush conformation (~0.1 chains nm –2 ), embrittlement can be avoided.

36 MATERIALS SCIENCE↗

Coupled‐cluster singles, doubles and perturbative triples with density fitting approximation for massively parallel heterogeneous platforms

Abstract A high‐performance implementation of the coupled‐cluster singles, doubles, and perturbative triples [CCSD(T)] is developed in the Massively Parallel Quantum Chemistry program. Novel features include: (1) reduced memory requirements via a density‐fitting (DF) CCSD implementation utilizing distributed lazy evaluation for tensors with more than two unoccupied indices and (2) the ability to utilize efficiently many‐core nodes (Intel Xeon Phi) and heterogeneous nodes with multiple NVIDIA GPUs on each node. All data that are greater than quadratic in the system size are distributed among processes. Excellent strong scaling is observed on distributed‐memory computers equipped with conventional CPUs, Intel Xeon Phi processors, and heterogeneous nodes with multiple NVIDIA GPUs Canonical CCSD(T) energies can be evaluated for systems containing 200 electrons and 1000 basis functions in a few days using a small size commodity cluster, with even larger computations possible on leadership‐class computing resources.

Peng, Chong↗

Thought Leaders during Crises in Massive Social Networks

The vast amount of social media data that can be gathered from the internet coupled with workflows that utilize both commodity systems and massively parallel supercomputers, such as the Cray XMT, open new vistas for research to support health, defense, and national security. Computer technology now enables the analysis of graph structures containing more than 4 billion vertices joined by 34 billion edges along with metrics and massively parallel algorithms that exhibit near-linear scalability according to number of processors. The challenge lies in making this massive data and analysis comprehensible to an analyst and end-users that require actionable knowledge to carry out their duties. Simply stated, we have developed language and content agnostic techniques to reduce large graphs built from vast media corpora into forms people can understand. Specifically, our tools and metrics act as a survey tool to identify thought leaders' -- those members that lead or reflect the thoughts and opinions of an online community, independent of the source language.

97 MATHEMATICS AND COMPUTING↗

Framework for assessing land‐management effects on at‐risk species: Example of SE USA wood pellet production and gopher tortoise ( Gopherus polyphemus )

Abstract Land‐management choices made for economic and societal gains intrinsically influence landscapes and species that are dependent upon them. We propose a simple analysis framework to examine critical intersections between land‐management choices and the life‐history conditions of selected species of concern, thereby facilitating the identification of mitigation practices that can reduce negative impacts on species at risk. We test the proposed framework through application to gopher tortoise ( Gopherus polyphemus ), a keystone species that is the focus of conservation efforts across the southeastern region of United States of America, where wood pellets are being produced for bioenergy. Production of these wood pellets for export to Europe and Asia has drastically increased in the past decade, raising concerns about potential harm to biodiversity since many species in the forests sourcing pellet production were already at risk prior to the development of this new commodity. Identifying the mechanisms of potential impacts of wood pellet production on species of concern is essential to establishing meaningful management recommendations that can enhance conservation efforts while supporting sustainable bioenergy. By considering the intersections between life‐history conditions of gopher tortoise and forest‐management practices related to woody biomass extraction for pellet production, we identify several mechanisms by which the wood‐pellet industry might affect this species of concern, both positively and negatively. We then identify mitigation practices that can help offset the potential impacts of logging, thinning, and dead wood removal on gopher tortoise. Our analysis framework may be transferable to other species of concern and land‐management practices across diverse landscapes. This article is categorized under: Bioenergy > Economics and Policy Bioenergy > Climate and Environment

54 ENVIRONMENTAL SCIENCES↗

Wind power costs driven by innovation and experience with further reductions on the horizon

The costs of wind power have declined to levels on par with or below those of conventional sources in many parts of the world. Wind power has become one of the fastest-growing sources of new electricity generation. We take stock of wind power cost evolution over the past 20 years, review methodologies commonly used for cost assessment, discuss the potential for continued cost reduction, and identify anticipated cost and value drivers. Our scope includes both onshore and offshore wind technologies. We draw from a vast body of literature on these topics to highlight key trends, approaches, and limitations. Furthermore, we discuss strategies for wind power assets to enhance their marginal economic value to the broader power system and consumers. We identify a myriad of factors that are expected to influence the future cost and value of wind power, including siting, project scale, turbine size, operational synergies, commodity prices, advancements in turbine technologies, enhanced management of the wind resource, and novel control technologies that provide value for the electricity grid. Because the common methods for forecasting future costs each have their own strengths and weaknesses, we find the best insights are elicited from a combination of methods. Overall, researchers and analysts anticipate further sizable cost reductions for onshore and offshore wind. Midrange forecasts for levelized cost of energy in 2050 are generally between $20 and $30/MWh for onshore wind and $40 and $60/MWh for offshore wind, a reduction to approximately half of today's levels. Optimistic forecasts anticipate these levels as early as 2030.

17 WIND ENERGY↗

Formally Verified ZTA Requirements for OT/ICS Environments with Isabelle/HOL

The clean energy transformation includes the integration of distributed energy resources with the power grid, which has led to a substantial increase in the complexity of power grids infrastructure and the underlying operational technology environment. Power grids infrastructure represents an operational technology environment that has become a system of systems, integrating heterogeneous devices which are both software-and hardware-intensive; as a result, there are increasing demands to exploit advances in the commodity of software-hardware infrastructures to improve energy systems requirements such as cybersecurity and resilience. In such a setting, system requirements at different levels mix, which leads to vulnerabilities and undesirable outcomes. The use of formal methods to characterize and prove system requirements removes ambiguity, increases automation, and provides high levels of assurance and reliability. In this paper, we contribute a methodology and a framework for the system-level verification of zero trust architecture requirements in operational technology environments. We define a formal specification for the core functionalities of operational technology environments, the corresponding invariants, and security proofs. Of particular note is our modular approach for the formal verification of asynchronous interactions in operational technology environments. The formal specification and the proofs have been mechanized using the interactive theorem proving environment Isabelle/HOL.

formal methods↗

Fast Multiresolution Reads of Massive Simulation Datasets

Today’s massively parallel simulation codes can produce output ranging up to many terabytes of data. Utilizing this data to support scientific inquiry requires analysis and visualization, yet the sheer size of the data makes it cumbersome or impossible to read without computational resources similar to the original simulation. We identify two broad classes of problems for reading data and present effective solutions for both. The first class of data reads depends on user requirements and available resources. Tasks such as visualization and user-guided analysis may be accomplished using only a subset of variables with a restricted spatial extent at a reduced resolution. The other class of reads requires full resolution multivariate data to be loaded, for example to restart a simulation. We show that utilizing the hierarchical multiresolution IDX data format enables scalable and efficient serial and parallel read access on a variety of hardware from supercomputers down to portable devices. Here, we demonstrate interactive view-dependent visualization and analysis of massive scientific datasets using low-power commodity hardware, and we compare read performance with other parallel file formats for both full and partial resolution data.

97 MATHEMATICS AND COMPUTING↗

GoFFish: A Sub-Graph Centric Framework for Large-Scale Graph Analytics1

Large scale graph processing is a major research area for Big Data exploration. Vertex centric programming models like Pregel are gaining traction due to their simple abstraction that allows for scalable execution on distributed systems naturally. However, there are limitations to this approach which cause vertex centric algorithms to under-perform due to poor compute to communication overhead ratio and slow convergence of iterative superstep. In this paper we introduce GoFFish a scalable sub-graph centric framework co-designed with a distributed persistent graph storage for large scale graph analytics on commodity clusters. We introduce a sub-graph centric programming abstraction that combines the scalability of a vertex centric approach with the flexibility of shared memory sub-graph computation. We map Connected Components, SSSP and PageRank algorithms to this model to illustrate its flexibility. Further, we empirically analyze GoFFish using several real world graphs and demonstrate its significant performance improvement, orders of magnitude in some cases, compared to Apache Giraph, the leading open source vertex centric implementation. We map Connected Components, SSSP and PageRank algorithms to this model to illustrate its flexibility. Further, we empirically analyze GoFFish using several real world graphs and demonstrate its significant performance improvement, orders of magnitude in some cases, compared to Apache Giraph, the leading open source vertex centric implementation.

Simmhan, Yogesh↗

High-performance Computing Applied to Semantic Databases

To-date, the application of high-performance computing resources to Semantic Web data has largely focused on commodity hardware and distributed memory platforms. In this paper we make the case that more specialized hardware can offer superior scaling and close to an order of magnitude improvement in performance. In particular we examine the Cray XMT. Its key characteristics, a large, global shared-memory, and processors with a memory-latency tolerant design, offer an environment conducive to programming for the Semantic Web and have engendered results that far surpass current state of the art. We examine three fundamental pieces requisite for a fully functioning semantic database: dictionary encoding, RDFS inference, and query processing. We show scaling up to 512 processors (the largest configuration we had available), and the ability to process 20 billion triples completely in-memory.

99 GENERAL AND MISCELLANEOUS↗

Equilibrium in a Production Economy

Consider a closed production-consumption economy with multiple agents and multiple resources. The resources are used to produce the consumption good. The agents derive utility from holding resources as well as consuming the good produced. They aim to maximize their utility while the manager of the production facility aims to maximize profits. With the aid of a representative agent (who has a multivariable utility function) it is shown that an Arrow-Debreu equilibrium exists. In so doing we establish technical results that will be used to solve the stochastic dynamic problem (a case with infinite dimensional commodity space so the General Equilibrium Theory does not apply) elsewhere.

97 MATHEMATICS AND COMPUTING↗

Conversion of lignin into value-added materials and chemicals via laccase-assisted copolymerization

With today’s environmental concerns and the diminishing supply of the world’s petroleum-based chemicals and materials, much focus has been directed toward alternative sources. Woody biomass presents a promising option due to its sheer abundance, renewability, and biodegradability. Lignin, a highly irregular polyphenolic compound, is one of the major chemical constituents of woody biomass and is the second most abundant biopolymer on Earth, surpassed only by cellulose. The pulp and paper and cellulosic ethanol industries produce lignin on the scale of millions of tons each year as a by-product. Traditionally, lignin has been viewed as a waste material and burned as an inefficient fuel. However, in recent decades, research has focused on more economical ways to convert lignin into value-added commodities, such as biofuels, biomaterials, and biochemicals, thus developing and strengthening the concept of fully integrated biorefineries. Owing to the phenolic structure of lignin, it is possible to enzymatically graft molecules onto its surface using laccases (benzenediol:oxygen oxidoreductases, EC 1.10.3.2) to create exciting novel biomaterials. These environmentally friendly enzymes use oxygen as their only co-substrate and produce water as their sole by-product, and have thus found great industrial application. Furthermore, this mini-review highlights recent advances in the field of laccase-facilitated functionalization of lignin as well as promising future directions for lignin-based polymers.

09 BIOMASS FUELS↗

Laccase-mediated synthesis of lignin-core hyperbranched copolymers

Lignin, one of the major chemical constituents of woody biomass, is the second most abundant biopolymer found in nature. The pulp and paper industry has long produced lignin on the scale of millions of tons annually as a by-product of the pulping process, and the dawn of cellulosic ethanol production has further contributed to this amount. Historically, lignin has been perceived as a waste material and burned as a fuel for the pulping process. But, recent research has been geared toward developing cost-effective technologies to convert lignin into valuable commodities. Attributing to the polyphenolic structure of lignin, enzymatic modification of its surface using laccases (benzenediol:oxygen oxidoreductases, EC 1.10.3.2) has demonstrated to be highly successful. The current study aims at developing lignin-core hyperbranched copolymers via the laccase-assisted copolymerization of kraft lignin with methylhydroquinone and a trithiol. Based on the physical properties of the resulting material, it is likely that crosslinking reactions have taken place during the drying process to produce a copolymeric network rather than discrete hyperbranched copolymers, with NMR data providing evidence of covalent bonding between monomers. A preliminary thermal analysis data reveals that the copolymeric material possesses a moderate glass transition temperature and exhibits good thermostability, thus may have potential application as a lignin-based thermoplastic. Scanning electron microscopy images confirm the smooth, glossy surface of the material and that it is densely packed. Our results are a sustainable, ecofriendly, economic method to create an exciting novel biomaterial from a renewable feedstock while further enhancing lignin valorization.

09 BIOMASS FUELS↗

Metabolic engineering of non-pathogenic microorganisms for 2,3-butanediol production

2,3-Butanediol (2,3-BDO) is a promising commodity chemical with various industrial applications. While petroleum-based chemical processes currently dominate the industrial production of 2,3-BDO, fermentation-based production of 2,3-BDO pro- vides an attractive alternative to chemical-based processes with regards to economic and environmental sustainability. The achievement of high 2,3-BDO titer, yield, and productivity in microbial fermentation is a prerequisite for the production of 2,3-BDO at large scales. Also, enantiopure production of 2,3-BDO production is desirable because 2,3-BDO stereoisomers have unique physicochemical properties. Pursuant to these goals, many metabolic engineering strategies to improve 2,3-BDO pro- duction from inexpensive sugars by Klebsiella oxytoca, Bacillus species, and Saccharomyces cerevisiae have been developed. Furthermore, this review summarizes the recent advances in metabolic engineering of non-pathogenic microorganisms to enable efficient and enantiopure production of 2,3-BDO.

2,3-BDO stereoisomers↗

Integrated energy-water-land nexus planning in the Colorado River Basin (Argentina)

Integrated energy-water-land (EWL) planning promotes synergies and avoids conflicts in ways that sector-specific planning approaches cannot. Many important decisions that influence emerging EWL nexus issues are implemented at regional (e.g., large river basin, electricity grid) and sub-regional (e.g., small river basin, irrigation district) scales. However, actual implementation of integrated planning at these scales has been limited. Simply collecting and visualizing data and interconnections across multiple sectors and sub-regions in a single modeling platform is a unique endeavor in many regions. This study introduces and applies a novel approach to linking together multiple sub-regions in a single platform to characterize and visualize EWL resource use, EWL system linkages within and among sub-regions, and the EWL nexus implications of future policies and investments. This integrated planning methodology is applied in the water-stressed Colorado River Basin in Argentina, which is facing increasing demands for agricultural and fossil fuel commodities. Guided by stakeholders, this study seeks to inform basin planning activities by characterizing and visualizing (1) the basin’s current state of EWL resources, (2) the linkages between sectors within and among basin sub-regions, and (3) the EWL nexus implications of planned future agricultural development activities. Results show that water scarcity, driven in part by human demands that have historically reached 60% of total surface water supply, poses a substantial constraint to economic development in the basin. The Colorado basin has the potential to serve as a testbed for crafting novel and generalizable sub-regional EWL planning approaches capable of informing the EWL planning dialogue globally.

54 ENVIRONMENTAL SCIENCES↗

Modulation of FadR Binding Capacity for Acyl-CoA Fatty Acids Through Structure-Guided Mutagenesis

FadR is a versatile global regulator in Escherichia coli that controls fatty acid metabolism and thereby modulates the ability of this bacterium to grow using fatty acids or acetate as the sole carbon source. FadR regulates fatty acid metabolism in response to intra-cellular concentrations of acyl-CoA lipids. The ability of FadR to bind acyl-CoA fatty acids is hence of significant interest for the engineering of biosynthetic pathways for the production of lipid-based biofuels and commodity chemicals. Based on the available crystal structure of E. coli bound to myristoyl- CoA, we predicted amino acid positions within the effector binding pocket that would alter the ability of FadR to bind acyl-CoA fatty acids without affecting DNA binding. We utilized fluorescence polarization to characterize the in-vitro binding properties of wild type and mutant FadR. We found that a Leu102Ala mutant enhanced binding of the effector, likely by increasing the size of the binding pocket for the acyl moiety of the molecule. Conversely, the elimination of the guanidine side chain (Arg213Ala and Arg213Met mutants) of the CoA moiety binding site severely diminished the ability of FadR to bind the acyl-CoA effector. These results demonstrate the ability to fine tune FadR binding capacity. The validation of an efficient method to fully characterize all the binding events involved in the specific activity (effector and DNA operator binding) of FadR has allowed us to increase our understanding of the role of specific amino acids in the binding and recognition of acyl-CoA fatty acids and will greatly facilitate efforts aimed at engineering tunable FadR regulators for synthetic biology.

59 BASIC BIOLOGICAL SCIENCES↗

Evaluation of Impact of Potential Extreme Rainfall Events on Mining in Peru

The impact that climate change may play in the future sustainability of mining projects has become increasingly important for the mining industry and its stakeholders. The most significant areas of concern are mine infrastructure, supply chains, health and safety conditions, environmental management, community relations and exploration. This is particularly relevant to mining in a country as climatically vulnerable as Peru. This study focuses on the identification of mining regions and main commodities in Peru that are potentially vulnerable to future extreme rainfall events associated with climate change. From a mine design and planning perspective, this study is a first step to illustrate the importance of considering the impacts of different climatic scenarios on mining in Peru. Based on HadGEM2-ES global climate model projections, mining regions across Peru were clustered into “super-regions” with differing potentials of extreme rainfall events during the next three decades. Five indices for precipitation extremes were used, and their variations between 1971–2000 and 2015–2034 were computed. Current and future metallic mining projects expected to take place across Peru in the next 30 years were retrieved from a mining database and subsequently exported into a geographical information systems software to represent their location and interpolate the variation for each precipitation extreme index. The results of this study point out at a decreasing trend in rainfall extremes intensity and frequency in regions of southern Peru. For copper projects located in these regions, a decrease in rainfall events could also imply an eventual decrease in total precipitation and consequently a deficit in water availability during the next three decades. Mining regions in central Peru, with significant number of zinc projects, are likely to experience a marked increase in overall annual precipitation, average daily precipitation intensity, consecutive days of precipitation and number of heavy precipitation days. At a lesser extent than in central Peru, gold projects in northern Peru are also likely to experience an overall increase in precipitation extremes. The approach used for this research could be extended to other mining regions around the world with extreme weather events.

58 GEOSCIENCES↗

Uncertainties in estimating global potential yields and their impacts for long-term modeling

Estimating realistic potential yields by crop type and region is challenging; such yields depend on both biophysical characteristics (e.g., soil characteristics, climate, etc.), and the crop management practices available in any site or region (e.g., mechanization, irrigation, crop cultivars). A broad body of literature has assessed potential yields for selected crops and regions, using several strategies. In this study we first analyze future potential yields of major crop types globally by two different estimation methods, one of which is based on historical observed yields (“Empirical”), while the other is based on biophysical conditions (“Simulated”). Potential yields by major crop and region are quite different between the two methods; in particular, Simulated potential yields are typically 200% higher than Empirical potential yields in tropical regions for major crops. Applying both of these potential yields in yield gap closure scenarios in a global agro-economic model, GCAM, the two estimates of future potential yields lead to very different outcomes for the agricultural sector globally. In the Simulated potential yield closure scenario, Africa, Asia, and South America see comparatively favorable outcomes for agricultural sustainability over time: low land use change emissions, low crop prices, and high levels of self-sufficiency. In contrast, the Empirical potential yield scenario is characterized by a heavy reliance on production and exports in temperate regions that currently practice industrial agriculture. At the global level, this scenario has comparatively high crop commodity prices, and more land allocated to crop production (and associated land use change emissions) than either the baseline or Simulated potential yield scenarios. This study highlights the importance of the choice of methods of estimating potential yields for agro-economic modeling.

60 APPLIED LIFE SCIENCES↗