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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Day-Case Treatment of Peripheral Arterial Disease: Results from a Multi-Center European Study

PurposeThe purpose of the study was to investigate safety and feasibility of day-case endovascular procedures for the management of peripheral arterial disease.Materials and MethodsThis was a multi-center, retrospective study including all patients treated over a 30-month period with endovascular angioplasty or stenting for intermittent claudication (IC) or critical limb ischemia (CLI) on a day-case basis, in Interventional Radiology (IR) departments of three European tertiary hospitals. Exclusion criteria were not related to the type of lesion and included unavailability of an adult able to take care of patient overnight; high bleeding risk and ASA score ≥4. Primary efficacy outcome was the rate of procedures performed on an outpatient basis requiring no further hospitalization and primary safety outcome was freedom from 30-day major complications’ rate.ResultsThe study included 652 patients (male 75 %; mean age 68 ± 10 years; range: 27–93), 24.6 % treated for CLI. In 53.3 % of the cases a 6Fr sheath was used. Technical success was 97.1 %. Haemostasis was obtained by manual compression in 52.4 % of the accesses. The primary efficacy outcome occurred in 95.4 % (622/652 patients) and primary safety outcome in 98.6 % (643/652 patients). Major complications included five (0.7 %) retroperitoneal hematomas requiring transfusion; one (0.1 %) common femoral artery pseudoaneurysm successfully treated with US-guided thrombin injection, two cases of intra-procedural distal embolization treated with catheter-directed local thrombolysis and one on-table cardiac arrest necessitating >24 h recovery. No major complication was noted after same-day discharge.ConclusionsDay-case endovascular procedures for the treatment of IC or CLI can be safely and efficiently performed in experienced IR departments of large tertiary hospitals.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2023

Downward quantum learning from element 118: Automated generation of Fermi–Löwdin orbitals for all atoms

A new algorithm based on a rigorous theorem and quantum data computationally mined from element 118 guarantees automated construction of initial Fermi–Löwdin-Orbital (FLO) starting points for all elements in the Periodic Table. It defines a means for constructing a small library of scalable FLOs for universal use in molecular and solid-state calculations. The method can be systematically improved for greater efficiency and for applications to excited states such as x-ray excitations and optically silent excitations. FLOs were introduced to recast the Perdew–Zunger self-interaction correction (PZSIC) into an explicit unitarily invariant form. The FLOs are generated from a set of N quasi-classical electron positions, referred to as Fermi-Orbital descriptors (FODs), and a set of N-orthonormal single-electron orbitals. FOD positions, when optimized, minimize the PZSIC total energy. However, creating sets of starting FODs that lead to a positive definite Fermi orbital overlap matrix has proven to be challenging for systems composed of open-shell atoms and ions. The proof herein guarantees the existence of a FLOSIC solution and further guarantees that if a solution for N electrons is found, it can be used to generate a minimum of N – 1 and a maximum of 2 N – 2 initial starting points for systems composed of a smaller number of electrons. As a result, applications to heavy and super-heavy atoms are presented. All starting solutions reported here were obtained from a solution for element 118, Oganesson.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Testing the LSST Difference Image Analysis Pipeline Using Synthetic Source Injection Analysis

Abstract We evaluate the performance of the Legacy Survey of Space and Time Science Pipelines Difference Image Analysis (DIA) on simulated images. By adding synthetic sources to galaxies on images, we trace the recovery of injected synthetic sources to evaluate the pipeline on images from the Dark Energy Science Collaboration Data Challenge 2. The pipeline performs well, with efficiency and flux accuracy consistent with the signal-to-noise ratio of the input images. We explore different spatial degrees of freedom for the Alard–Lupton polynomial-Gaussian image subtraction kernel and analyze for trade-offs in efficiency versus artifact rate. Increasing the kernel spatial degrees of freedom reduces the artifact rate without loss of efficiency. The flux measurements with different kernel spatial degrees of freedom are consistent. We also here provide a set of DIA flags that substantially filter out artifacts from the DIA source table. We explore the morphology and possible origins of the observed remaining subtraction artifacts and suggest that given the complexity of these artifact origins, a convolution kernel with a set of flexible bases with spatial variation may be needed to yield further improvements.

Liu, S. (ORCID:0000000244612143)↗
DOE OSTI2012

Transportation Energy Data Book: Edition 31

The Transportation Energy Data Book: Edition 31 is a statistical compendium prepared and published by Oak Ridge National Laboratory (ORNL) under contract with the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Vehicle Technologies Program. Designed for use as a desk-top reference, the Data Book represents an assembly and display of statistics and information that characterize transportation activity, and presents data on other factors that influence transportation energy use. The purpose of this document is to present relevant statistical data in the form of tables and graphs. The latest edition of the Data Book is available to a larger audience via the Internet (cta.ornl.gov/data). This edition of the Data Book has 12 chapters which focus on various aspects of the transportation industry. Chapter 1 focuses on petroleum; Chapter 2 energy; Chapter 3 highway vehicles; Chapter 4 light vehicles; Chapter 5 heavy vehicles; Chapter 6 alternative fuel vehicles; Chapter 7 fleet vehicles; Chapter 8 household vehicles; Chapter 9 nonhighway modes; Chapter 10 transportation and the economy; Chapter 11 greenhouse gas emissions; and Chapter 12 criteria pollutant emissions. The sources used represent the latest available data. There are also three appendices which include detailed source information for some tables, measures of conversion, and the definition of Census divisions and regions. A glossary of terms and a title index are also included for the reader s convenience.

02 PETROLEUM↗
DOE OSTI2025

ComStock Measure Scenario Documentation: Laboratory-Informed Modeling of Standard Performance Heat Pump Rooftop Units

This measure scenario replaces gas and electric resistance RTUs in the U.S. commercial building stock with standard efficiency commercial off the shelf heat pump rooftop units. This study uses performance data informed by NREL laboratory testing of a standard efficiency 7.5-ton heat pump RTU. This is the key distinction between this measure scenario and a similar ComStock measure scenario - Standard Performance Heat Pump Rooftop Units - that uses published manufacturer data tables to inform performance. These two scenarios are compared in this report.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2011

Transportation Energy Data Book: Edition 30

The Transportation Energy Data Book: Edition 30 is a statistical compendium prepared and published by Oak Ridge National Laboratory (ORNL) under contract with the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Vehicle Technologies Program. Designed for use as a desk-top reference, the Data Book represents an assembly and display of statistics and information that characterize transportation activity, and presents data on other factors that influence transportation energy use. The purpose of this document is to present relevant statistical data in the form of tables and graphs. The latest edition of the Data Book is available to a larger audience via the Internet (cta.ornl.gov/data). This edition of the Data Book has 12 chapters which focus on various aspects of the transportation industry. Chapter 1 focuses on petroleum; Chapter 2 energy; Chapter 3 highway vehicles; Chapter 4 light vehicles; Chapter 5 heavy vehicles; Chapter 6 alternative fuel vehicles; Chapter 7 fleet vehicles; Chapter 8 household vehicles; Chapter 9 nonhighway modes; Chapter 10 transportation and the economy; Chapter 11 greenhouse gas emissions; and Chapter 12 criteria pollutant emissions. The sources used represent the latest available data. There are also three appendices which include detailed source information for some tables, measures of conversion, and the definition of Census divisions and regions. A glossary of terms and a title index are also included for the reader s convenience.

02 PETROLEUM↗
DOE OSTI2024

GraphTango: A Hybrid Representation Format for Efficient Streaming Graph Updates and Analysis

Abstract Streaming graph processing performs batched updates and analytics on a time-evolving graph. The underlying representation format of the graph largely determines the throughputs of these updates and analytics phases. Existing representation formats usually employ variations of hash tables or adjacency lists. However, a recent study showed that the adjacency-list-based approaches perform poorly on heavy-tailed graphs, and the hash table-based approaches suffer on short-tailed graphs. We propose GraphTango, a hybrid representation format that provides excellent update and analytics throughput regardless of the graph’s degree distribution. GraphTango dynamically switches among three different formats based on a vertex’s degree: (i) Low-degree vertices store the edges directly with the neighborhood metadata, confining accesses to a single cache line, (2) Medium-degree vertices use adjacency lists, and (3) High-degree vertices use hash tables as well as adjacency lists. In this case, the adjacency list provides fast traversal during the analytics phase, while the hash table provides constant-time lookups during the update phase. We further optimized the performance by designing an open-addressing-based hash table that fully utilizes every fetched cache line. In addition, we developed a thread-local lock-free memory pool that allows fast growing/shrinking of the adjacency lists and hash tables in a multi-threaded environment. We evaluated GraphTango with the help of the SAGA-Bench framework and compared it with four other representation formats: Stinger, Degree-aware Robin Hood Hashing, and two adjacency list-based formats with different workload balancing scheme. On average, GraphTango provides 4.5x higher insertion throughput, 3.2x higher deletion throughput, and 1.1x higher analytics throughput over the next best format. Furthermore, we integrated GraphTango with the state-of-the-art graph processing frameworks DZiG and RisGraph. Compared to the vanilla DZiG and vanilla RisGraph , [ GraphTango + DZiG ] and [ GraphTango + RisGraph ] reduces the average batch processing time by 2.3x and 1.5x, respectively.

Ahmed, Alif↗
DOE OSTI2022

Designing for Zero Energy and Zero Carbon on a Multi-Building Scale Using URBANopt: Preprint

Groundbreaking efforts are necessary to mitigate contributors increasing impacts of climate change. In parallel to inventing pioneering clean energy technologies it is even more fundamental to rethink designing energy systems within a singular facility and collectively to function as a district. Facilities should not be continuously passive by just consuming; there is a need to shift to perform more dynamically. Designing for zero energy and zero carbon on a multi-building scale can uncover opportunities for building energy efficiency, decarbonization, demand flexibility, and resiliency that are not accessible at an individual building scale. This approach can be challenging without innovative tools to evaluate the multitude of possibilities. As an investigated result, we highlight the use of a campus-scale energy modeling platform - URBANopt™ - for the expansion of the National Renewable Energy Laboratory's (NREL's) South Table Mountain campus in Golden, Colorado. Programmatic growth included the design of three new all-electric, zero-energy, and zero-carbon, mixed used buildings (a combination of research laboratories and office space). This investigation is critical to NREL reaching net-zero emissions for its operational footprint, which will occur in phases over the next decade. Leveraging URBANopt's capabilities, we evaluate 1) high-performance building energy efficiency and decarbonization measures, 2) 4th generation district heating and cooling (4th GDHC) systems, 3) optimized onsite generation and energy storage assets that meet zero-energy and zero-carbon targets at minimum life-cycle costs, and 4) cost-optimal distributed energy technology mixes, dispatch strategies, and associated capacities that increase resiliency to grid outages. This work demonstrates the use and capabilities of URBANopt through a real-world case study on a multi-building scale.

community energy model↗
DOE OSTI2022

Characterizing Tradeoffs in Memory, Accuracy, and Speed for Chemistry Tabulation Techniques

Chemistry tabulation is a common approach in practical simulations of turbulent combustion at engineering scales. Linear interpolants have traditionally been used for accessing precomputed multidimensional tables but suffer from large memory requirements and discontinuous derivatives. Higher-degree interpolants address some of these restrictions but are similarly limited to relatively low-dimensional tabulation. Artificial neural networks (ANNs) can be used to overcome these limitations but cannot guarantee the same accuracy as interpolants and introduce challenges in reproducibility and reliable training. These challenges are enhanced as the physics complexity to be represented within the tabulation increases. Here, we assess the efficiency, accuracy, and memory requirements of Lagrange polynomials, tensor product B-splines, and ANNs as tabulation strategies. We analyze results in the context of nonadiabatic flamelet modeling where higher dimension counts are necessary. While ANNs do not require structuring of data, providing benefits for complex physics representation, interpolation approaches often rely on some structuring of the table. Interpolation using structured table inputs that are not directly related to the variables transported in a simulation can incur additional query costs. This is demonstrated in the present implementation of heat losses. We show that ANNs, despite being difficult to train and reproduce, can be advantageous for high-dimensional, unstructured datasets relevant to nonadiabatic flamelet models. Furthermore we demonstrate that Lagrange polynomials show significant speedup for similar accuracy compared to B-splines.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Extending Parsimonious Bayesian Inference

Parsimonious Bayesian inference is a theoretical framework for efficient data assimilation that seeks to balance increased consistency between predictions and training data against corresponding increases in model complexity. Within this framework, over-training is understood as optimization that encodes excessive information within model parameters while only achieving small improvements between predictions and training data. This project aims to develop practical methods of limiting excess model information during optimization. One key observation is that practical heuristics for parsimonious learning in high-dimensions must balance expressivity, i.e. the ability of the model to capture diverse predictions with only a few non-zero parameters, against discoverability, i.e. the ability to train the model with gradient-based optimization and drive parameters to low information states. As such, we developed logical activation functions that are able to adaptively approximate arbitrary truth tables that define Boolean logic operations within a probabilistic framework. These functions have demonstrated the ability to learn exclusive disjunction (XOR) and conditioned disjunction (if [condition] then [result_if_true] else [result_if_false]) within a single layer of a neural network. To efficiently exploit these activation functions to drive parsimonious learning required several other advances within the domain of variational inference. The most efficient form of complexity suppression is structured sparsification, driving most model parameters to zero while achieving the structural coherence among nonzeros needed for bandwidth reduction. Such models are not only far more efficient at suppressing information-theoretic complexity, they also reduce the other forms of complexity (computations, communication, storage, and the number of dependencies needed to evaluate predictions). Aiming to support enhanced sparsification, this project examined new approaches to high-dimensional variational inference that allow us to calibrate and control parameter uncertainty during optimization. By identifying which parameters can sustain sparsifying perturbations with little impact on prediction quality, we can develop better pruning strategies by framing them as approximate Bayesian inference. These advances also open paths to mitigate concerns with deploying advanced learning methods in resource-constrained environments, such as running models on power-limited or communication-limited devices.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Single shot ultrafast all optical magnetization switching of ferromagnetic Co/Pt multilayers

A single femto-second optical pulse can fully reverse the magnetization of a film within picoseconds. Such fast operation hugely increases the range of application of magnetic devices. However, so far, this type of ultrafast switching has been restricted to ferri-magnetic GdFeCo films. In contrast, all optical switching of ferro-magnetic films require multiple pulses, thereby being slower and less energy efficient. In this study, we demonstrate magnetization switching induced by a single laser pulse in various ferromagnetic Co/Pt multilayers grown on GdFeCo, by exploiting the exchange coupling between the two magnetic films. Table-top depth-sensitive time-resolved magneto-optical experiments show that the Co/Pt magnetization switches within 7 ps. Lastly, this coupling approach will allow ultrafast control of a variety of magnetic films, which is critical for applications.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Bioprocessing Separations Consortium Three-Year Overview: Technical Advances, Process Economics Influence, and State of the Science

The Bioprocessing Separations Consortium solves separations challenges that are unique to bioprocessing. To do this, the Consortium uses two methods: applying existing technologies to new challenges and developing new technologies that may address these unique challenges better than today’s commercial technologies. In its research and development, the Consortium leverages its three core capabilities: materials development and evaluation, process development, and analysis and computation. In its first three years, from 2016 to 2019, the Consortium addressed four critical challenges in biochemical and thermochemical processing. First, the Consortium targeted the fractionation of lignin to enable valorization of this portion of biomass that offers diverse, complex, and valuable building blocks and products. Second, Consortium researchers developed technologies to enable process intensification, which can reduce equipment needs, energy consumption, and waste generation, thereby cutting bioprocessing capital costs and rendering processes more efficient. Third, the Consortium sought to recover carbon from dilute aqueous streams that are common to bioprocessing; recovering dilute carbon can improve process efficiency and economics. Finally, Consortium researchers designed and developed new materials and catalysts to reduce targeted foulants and poisons in bioprocessing streams that can limit the lifetime of downstream catalysts or fermenting microorganisms. Table 1 lists the technologies that were examined and places them in the context of the Consortium’s capabilities, types of bioprocesses, and critical challenges in bioprocessing separations. Overall, across these projects, we have developed separations technologies for 10 bioprocesses, addressed 9 target compounds in bioprocessing, developed 10 materials, and evaluated 4 processes for cost and sustainability.

09 BIOMASS FUELS↗
DOE OSTI2020

Bioprocessing Separations Consortium Three-Year Overview: Technical Advances Process Economics Influence, and State of the Science

The Bioprocessing Separations Consortium solves separations challenges that are unique to bioprocessing. To do this, the Consortium uses two methods: applying existing technologies to new challenges and developing new technologies that may address these unique challenges better than today’s commercial technologies. In its research and development, the Consortium leverages its three core capabilities: materials development and evaluation, process development, and analysis and computation. In its first three years, from 2016 to 2019, the Consortium addressed four critical challenges in biochemical and thermochemical processing. First, the Consortium targeted the fractionation of lignin to enable valorization of this portion of biomass that offers diverse, complex, and valuable building blocks and products. Second, Consortium researchers developed technologies to enable process intensification, which can reduce equipment needs, energy consumption, and waste generation, thereby cutting bioprocessing capital costs and rendering processes more efficient. Third, the Consortium sought to recover carbon from dilute aqueous streams that are common to bioprocessing; recovering dilute carbon can improve process efficiency and economics. Finally, Consortium researchers designed and developed new materials and catalysts to reduce targeted foulants and poisons in bioprocessing streams that can limit the lifetime of downstream catalysts or fermenting microorganisms. Table 1 lists the technologies that were examined and places them in the context of the Consortium’s capabilities, types of bioprocesses, and critical challenges in bioprocessing separations. Overall, across these projects, we have developed separations technologies for 10 bioprocesses, addressed 9 target compounds in bioprocessing, developed 10 materials, and evaluated 4 processes for cost and sustainability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Federal Resilience Resources for State Energy Offices

The Weatherization and Intergovernmental Programs Office, through the U.S. Department of Energy’s Office of Energy Efficiency and Renewable Energy, has compiled federally funded and publicly available qualitative and quantitative resources that support energy resilience and disaster mitigation planning. This handout is accompanied by the downloadable Resilience Valuation Tools Table that offers more detailed specifications on each quantitative tool.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Bioprocessing Separations Consortium: Three-Year Overview - Technical Advances, Process Economics Influence, and State of the Science

The Bioprocessing Separations Consortium solves separations challenges that are unique to bioprocessing. To do this, the Consortium uses two methods: applying existing technologies to new challenges and developing new technologies that may address these unique challenges better than today’s commercial technologies. In its research and development, the Consortium leverages its three core capabilities: materials development and evaluation, process development, and analysis and computation. In its first three years, from 2016 to 2019, the Consortium addressed four critical challenges in biochemical and thermochemical processing. First, the Consortium targeted the fractionation of lignin to enable valorization of this portion of biomass that offers diverse, complex, and valuable building blocks and products. Second, Consortium researchers developed technologies to enable process intensification, which can reduce equipment needs, energy consumption, and waste generation, thereby cutting bioprocessing capital costs and rendering processes more efficient. Third, the Consortium sought to recover carbon from dilute aqueous streams that are common to bioprocessing; recovering dilute carbon can improve process efficiency and economics. Finally, Consortium researchers designed and developed new materials and catalysts to reduce targeted foulants and poisons in bioprocessing streams that can limit the lifetime of downstream catalysts or fermenting microorganisms. Table 1 lists the technologies that were examined and places them in the context of the Consortium’s capabilities, types of bioprocesses, and critical challenges in bioprocessing separations. Overall, across these projects, we have developed separations technologies for 10 bioprocesses, addressed 9 target compounds in bioprocessing, developed 10 materials, and evaluated 4 processes for cost and sustainability.

09 BIOMASS FUELS↗
DOE OSTI2019

Evaluation of High Rotor Pole Switched Reluctance Motors to Control Condenser Fans in a Commercial Refrigeration System

A high rotor pole switched reluctance motor (HRSRM) designed by Software Motor Corporation was evaluated for use as a condenser fan motor due to its reported high motor efficiency over a broad range of speeds and added advanced control potential. The project was split into two phases; the first of which was to determine the direct energy savings due to the increased motor efficiency, the second was to leverage the additional benefits of the energy efficiency measure (EEM) to create additional energy savings. This report only discusses results from the first phase of the project. Nine 1.5hp HRSRMs were installed parallel to the same number of legacy induction motors of a supermarket commercial refrigeration system located in Lakeside, Colorado. At this site, the 1.5 hp legacy motors had historically adjusted condenser fan speed from 200-870 rpm based on outdoor air temperature and compressor discharge pressure. This type of control is known as variable head pressure control (VHPC). These nine new motors were given a signal from the legacy variable frequency drive (VFD) to match the motor speed of the legacy motors. Determination of the energy savings of the EEM was performed over a two-month period, at which time a correlation between legacy and EEM power consumption was developed based on motor speed. Annual data that had been collected from 2016-2017 (before the two-month test period) was then leveraged to predict the annual energy savings of the EEM for a complete retrofit using both VHPC and constant fan speed control. Table 1 displays the quantitative results. The EEM saved 27% of total energy consumption of the condenser fan motors for constant fan speed control, while the energy savings increased to 32% when using VHPC. This was due to the improved motor efficiency of the HRSR motor at low speeds. While the constant speed fan control kept the motors running at 870 rpm, VHPC adjusted fan speed between 200-870rpm based on the outdoor air temperature and the compressor discharge pressure. These savings are assuming a direct replacement with no additional controls. Retrofitting a constant speed fan control system with HRSRMs and switching to VHPC would provide significant energy savings looking at the condenser alone. Additional considerations of the EEM were noted during the project as well. The HRSRM system made it possible to identify and remotely shutdown an individual motor when a piece of foam locked the fan and thereby the motor. With the traditional system, a locked rotor could have caused motor damage unless a breaker or fuse was activated. Furthermore, due to vibration complaints from the installation technicians, the ramp-up time of the HRSRM had to be increased to a minute. After implementing this change no complaints for excessive vibration were recorded.

15 GEOTHERMAL ENERGY↗
DOE OSTI2018

ORCHIDEE-PEAT (revision 4596), a model for northern peatland CO 2 , water, and energy fluxes on daily to annual scales

Peatlands store substantial amounts of carbon and are vulnerable to climate change. We present a modified version of the Organising Carbon and Hydrology In Dynamic Ecosystems (ORCHIDEE) land surface model for simulating the hydrology, surface energy, and CO 2 fluxes of peatlands on daily to annual timescales. The model includes a separate soil tile in each 0.5° grid cell, defined from a global peatland map and identified with peat-specific soil hydraulic properties. Runoff from non-peat vegetation within a grid cell containing a fraction of peat is routed to this peat soil tile, which maintains shallow water tables. The water table position separates oxic from anoxic decomposition. The model was evaluated against eddy-covariance (EC) observations from 30 northern peatland sites, with the maximum rate of carboxylation ( V cmax ) being optimized at each site. Regarding short-term day-to-day variations, the model performance was good for gross primary production (GPP) ( r 2 = 0.76; Nash–Sutcliffe modeling efficiency, MEF =0.76) and ecosystem respiration (ER, r 2 = 0.78, MEF = 0.75), with lesser accuracy for latent heat fluxes (LE, r 2 2 exchange (NEE, r 2 = 0.38, MEF = 0.26). Seasonal variations in GPP, ER, NEE, and energy fluxes on monthly scales showed moderate to high r 2 values (0.57–0.86). For spatial across-site gradients of annual mean GPP, ER, NEE, and LE, r 2 values of 0.93, 0.89, 0.27, and 0.71 were achieved, respectively. Water table (WT) variation was not well predicted ( r 2 < 0.1), likely due to the uncertain water input to the peat from surrounding areas. However, the poor performance of WT simulation did not greatly affect predictions of ER and NEE. We found a significant relationship between optimized V cmax and latitude (temperature), which better reflects the spatial gradients of annual NEE than using an average V cmax value

58 GEOSCIENCES↗
DOE OSTI2012

First-Principles Prediction of Intermediate Products in the Decomposition of Metal Amidoboranes

The non-volatile products remaining after the thermal decomposition of metal amidoboranes ([M]n+[NH2BH3] - , M = alkali or alkaline metal atom) are amorphous and incompletely characterized increasing the complexity of devising regeneration strategies for these potential hydrogen storage materials. Utilizing the combined prototype electrostatic ground state search (PEGS) and density-functional theory (DFT) methodology (PEGS+DFT), we have searched for crystal structures of possible intermediate phases with [NHBH2] - , [NBH] - , [N3H2B3H3] - , and polymer-M[NHBH2] anion groups in the decomposition of lithium amidoborane (LiAB) and calcium amidoborane (CaAB). All these potential reaction products are calculated to be significantly endothermic, in contrast to the experimentally measured nearly thermo neutral values [3 to 5 kJ/(mol H2) in LiAB and 3.5 kJ/(mol H2) in CaAB] suggesting that there are alternative products formed. The dianion group [NHBHNHBH3] 2- has recently been suggested to form in the decomposition of a calcium amidoborane complex in solution. In LiAB and CaAB, we use PEGS+DFT calculations to predict intermediate metal-dianion compounds, and the static H2 release enthalpy is 27.4 kJ/(mol H2) in LiAB and 27.3 kJ/(mol H2) in CaAB, respectively. Introducing vibrational effects by phonon calculations, the enthalpies are shifted down by a roughly constant amount, _25 kJ/(mol H2) at 0 K and _22 kJ/(mol H2) at 300 K. Thus, our theoretical H2 release enthalpies agree with the experimentally measured nearly thermo-neutral data in the decomposition of LiAB and CaAB. This agreement supports the existence of the dianion phases as products in the decomposition of metal amidoboranes. Then, using the dianion compound as an intermediate in the decomposition of MAB, we further study the stability trends of a series of MAB (M=Li, Na, K, Ca), and find that the reaction enthalpies generally obey the following trend: The amidoborane becomes more stable, i.e., MAB stability increases as the metal cation moves down in the periodic table along a given column (LiAB>NaAB>KAB), or as metal cation moves to the left along a given row (KAB>CaAB). T.A. acknowledges the Fuel Cell Technology Program at USDOE, Office of Energy Efficiency and Renewable Energy. Pacific Northwest National Laboratory is operated by Battelle for the US Department of Energy.

36 MATERIALS SCIENCE↗