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NASA NTRSDate not supplied

Progress on the Reduced Gravity Cryogenic Transfer (RGCT) Project

Reduced gravity transfer of cryogenic propellants is crucial to being able to perform planned extended-duration space exploration missions. However, the transfer of cryogenic propellants under reduced gravity conditions has never been demonstrated in a mass-efficient fashion. Efficient cryogenic fluid transfer methods will reduce the transfer time or amount of propellant consumed for chilldown of transfer lines and tanks and ensure successful engine restart or fill of a customer receiver tank. The purpose of the Reduced Gravity Cryogenic Transfer (RGCT) project is to enhance line chilldown, tank chilldown, and tank fill/transfer in a reduced gravity environment through (1) ground and reduced gravity cryogenic testing and (2) numerical model development and validation, which includes empirical, lumped capacitance, and computational fluid dynamics modeling. Technologies developed, data gathered, and models developed and validated under RGCT have played a critical role in enabling longer duration in-space missions. This presentation will provide a description of the ongoing cryogenic propellant transfer ground and reduced gravity testing, numerical modeling, and technology development to-date.

Boiling↗
NASA NTRSDate not supplied

Implementation of a Hybrid Edge Node-Centroid Node Approach for the Generation of Reduced Thermal Models

Reduced thermal models are often required for delivery to organizations that manage observatory or launch models at the highest levels of assembly. However, the effort to generate reduced models, and verify against their detailed counterparts, is a challenge that has not yet been conclusively solved. Higher level organizations often place a limit on the number of nodes for delivered models with the assumption that smaller models generally result in less computation time. However, the burden of producing and verifying the accuracy of the reduced models is placed primarily on the lower-level organizations, which in turn consumes resources needed to produce these models. Limiting the total number of allowable nodes may also prevent users from taking full advantage of software capabilities that allow for faster generation of models, such as finite elements, which generally require more nodes than older centroid based models. A methodology using Thermal Desktop was described in 2010 which used: (1) finite elements and edge nodes for a conduction matrix, (2) centroid nodes for capacitance and radiative computations, and (3) the super network feature to produce a conduction matrix based only on the centroid nodes. At that time, the methodology was clear, but the implementation would have had to be done manually; however, with the inclusion of the OpenTD API, this methodology can now be implemented programmatically and for the first time, be a viable approach for the generation of reduced models. The approach was implemented and developed at the NASA Goddard Space Flight Center (GSFC) for the Capture, Containment, and Return System (CCRS) payload on the Earth Return Orbiter (ERO) as part of the Mars Sample Return (MSR) mission, resulting in the TCYEE tool. ERO features a spacecraft bus provided by Airbus through the European Space Agency (ESA) with node limitations on the delivered CCRS model provided by GSFC. TCYEE was used to generate the reduced model for this delivery and the predictions compared favorably to the detailed model currently in use for the thermal performance evaluation. Furthermore, TCYEE is being explored for potential use on the Roman Space Telescope (RST) for the generation of reduced models for delivery to the launch provider, which also has node limit requirements on the RST observatory model for use in launch simulation analyses. This paper describes the methodology, its implementation, and compares the performance of reduced models generated by TCYEE to their detailed counterparts.

Hume L. Peabody↗
DOE OSTI2017

Facile synthesis of highly active reduced graphene oxide-CuI catalyst through a simple combustion method for photocatalytic reduction of CO{sub 2} to methanol

We report a facile combustion method synthesis of reduced graphene oxide/CuI composites as a photocatalyst, in which CuI nanoparticles were homogeneously distributed on the surface of reduced graphene oxide (rGO), showing a good visible light response. The rGO-supported and unsupported CuI hybrids were tested over the photocatalytic reduction of CO{sub 2} for methanol evolution in visible light. In the current study rGO-CuI composites have shown excellent yields (19.91 μmol g-cat{sup −1}). rGO provides a light-weight, charge complementary and two-dimensional material that interacts effectively with the CuI nanoparticles. - Graphical abstract: A facile reduced graphene oxide（rGO）/ CuI nanoparticles complexes hybrid material was prepared by a naked flame. This method can be simple and rapid preparation of composite materials which exhibit excellent catalytic performance. It is not only can improve the light absorption but also can be highly efficient reduction of CO{sub 2} to methanol in visible light. So the rGO-CuI composite will find potential applications as catalysts in organic photosynthetic reaction. Display Omitted - Highlights: • Reduced graphene oxide-CuI composites have been prepared by a facile method. • This method can produce reduced graphene oxide from graphene oxide without any reducing agent. • The absorption efficiency of rGO-CuI composites is significantly higher than rGO and CuI.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2023

AMORE-Isoprene v1.0: A New Reduced Mechanism for Gas-Phase Isoprene Oxidation

Gas-phase oxidation of isoprene by ozone (O 3 ) and the hydroxyl (OH) and nitrate (NO 3 ) radicals significantly impacts tropospheric oxidant levels and secondary organic aerosol formation. The most comprehensive and up-to-date chemical mechanism for isoprene oxidation consists of several hundred species and over 800 reactions. Therefore, the computational expense of including the entire mechanism in large-scale atmospheric chemical transport models is usually prohibitive, and most models employ reduced isoprene mechanisms ranging in size from ∼ 10 to ∼ 200 species. We have developed a new reduced isoprene oxidation mechanism using a directed-graph path-based automated model reduction approach, with minimal manual adjustment of the output mechanism. The approach takes as inputs a full isoprene oxidation mechanism, the environmental parameter space, and a list of priority species which are protected from elimination during the reduction process. Our reduced mechanism, AMORE-Isoprene (where AMORE stands for Automated Model Reduction), consists of 12 species which are unique to the isoprene mechanism as well as 22 reactions. We demonstrate its performance in a box model in comparison with experimental data from the literature and other current isoprene oxidation mechanisms. AMORE-Isoprene's performance with respect to predicting the time evolution of isoprene oxidation products, including isoprene epoxydiols (IEPOX) and formaldehyde, is favorable compared with other similarly sized mechanisms. When AMORE-Isoprene is included in the Community Regional Atmospheric Chemistry Multiphase Mechanism 1.0 (CRACMM1AMORE) in the Community Multiscale Air Quality Model (CMAQ, v5.3.3), O 3 and formaldehyde agreement with Environmental Protection Agency (EPA) Air Quality System observations is improved. O 3 bias is reduced by 3.4 ppb under daytime conditions for O 3 concentrations over 50 ppb. Formaldehyde bias is reduced by 0.26 ppb on average for all formaldehyde measurements compared with the base CRACMM1. There was no significant change in computation time between CRACMM1AMORE and the base CRACMM. AMORE-Isoprene shows a 35 % improvement in agreement between simulated IEPOX concentrations and chamber data over the base CRACMM1 mechanism when compared in the Framework for 0-D Atmospheric Modeling (F0AM) box model framework. This work demonstrates a new highly reduced isoprene mechanism and shows the potential value of automated model reduction for complex reaction systems.

Automated Model Reduction↗
DOE OSTI2015

A trust region algorithm for PDE-constrained optimization with bound constraints using reduced order modeling

This paper presents a novel trust region algorithm that relies on proper orthogonal de-composition techniques to construct accurate reduced order models during optimization.The algorithm samples high fidelity snapshots to compute the POD functions that are used to generate reduced order models. The reduced order models are used to replace the computationally intensive high fidelity finite element evaluations during optimization.The proposed algorithm employs a trust region framework to detect loss in predictive ac-curacy in the reduced order model and automatically update the POD functions during optimization. The trust region framework allows the algorithm to use sound mathematical metrics to effectively improve the accuracy and robustness of the reduced order models during optimization. The algorithm also employs a projected gradient algorithm to model bound constraints and compute optimal and feasible controls.This paper also presents an accurate Hessian formulation for topology optimization problems. The proposed trust region framework relies on a quadratic model to update the control. This quadratic model needs reliable second order derivative information to predict the behavior of the objective function within a suitable trust region. If a nonlinear Hessian formulation is used, the computational effort increases due to additional finite element evaluations. The proposed linear Hessian formulation reduces the computational effort and enables the calculation of the second order derivative information without additional finite element model evaluations. Examples in topology optimization are presented to demonstrate the applicability of the proposed algorithm and linear Hessian formulation for large-scale PDE-constrained optimization.

bound constraints↗
DOE OSTI2024

Long-term drought promotes invasive species by reducing wildfire severity

Anthropogenic climate change has increased the frequency of drought, wildfire, and invasions of non-native species. Although high-severity fires linked to drought can inhibit recovery of native vegetation in forested ecosystems, it remains unclear how drought impacts the recovery of other plant communities following wildfire. We leveraged an existing rainfall manipulation experiment to test the hypothesis that reduced precipitation, fuel load, and fire severity convert plant community composition from native shrubs to invasive grasses in a Southern California coastal sage scrub system. We measured community composition before and after the 2020 Silverado wildfire in plots with three rainfall treatments. Drought reduced fuel load and vegetation cover, which reduced fire severity. Native shrubs had greater prefire cover in added water plots compared to reduced water plots. Native cover was lower and invasive cover was higher in postfire reduced water plots compared to postfire added and ambient water plots. Our results demonstrate the importance of fuel load on fire severity and plant community composition on an ecosystem scale. Management should focus on reducing fire frequency and removing invasive species to maintain the resilience of coastal sage scrub communities facing drought. In these communities, controlled burns are not recommended as they promote invasive plants.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Progressive construction of a parametric reduced‐order model for PDE‐constrained optimization

Summary An adaptive approach to using reduced‐order models (ROMs) as surrogates in partial differential equations (PDE)‐constrained optimization is introduced that breaks the traditional offline‐online framework of model order reduction. A sequence of optimization problems constrained by a given ROM is defined with the goal of converging to the solution of a given PDE‐constrained optimization problem. For each reduced optimization problem, the constraining ROM is trained from sampling the high‐dimensional model (HDM) at the solution of some of the previous problems in the sequence. The reduced optimization problems are equipped with a nonlinear trust‐region based on a residual error indicator to keep the optimization trajectory in a region of the parameter space where the ROM is accurate. A technique for incorporating sensitivities into a reduced‐order basis is also presented, along with a methodology for computing sensitivities of the ROM that minimizes the distance to the corresponding HDM sensitivity, in a suitable norm. The proposed reduced optimization framework is applied to subsonic aerodynamic shape optimization and shown to reduce the number of queries to the HDM by a factor of 4‐5, compared with the optimization problem solved using only the HDM, with errors in the optimal solution far less than 0.1%. Copyright © 2014 John Wiley & Sons, Ltd.

Zahr, Matthew J.↗
DOE OSTI2023

The effect of reducing dietary lipid and food availability on precocious male maturation in Chinook Salmon: A production-scale hatchery experiment

Abstract Objective Age of maturation in Chinook Salmon Oncorhynchus tshawytscha is phenotypically plastic, influenced by both genotype and environmental factors, including the availability and composition of the diet. Salmon hatchery programs often rear fish under accelerated growth regimes using high-lipid diets that can result in earlier age at maturity, including increased prevalence of age-2 males (minijacks). The goal of this investigation was to compare alternative dietary regimes to mitigate for this shift in age at maturity in hatchery-reared Umatilla River fall Chinook Salmon. Methods Juvenile fish were reared at Bonneville Hatchery, Oregon, under four dietary treatments across four replicate brood years. Dietary treatments included two feeding frequencies (standard [fed 7 days/week] and reduced [fed 4 days/week]) and two dietary lipid levels (standard [18%] and reduced [12%]) in a 2 × 2 factorial design. Dietary treatments were applied for approximately 9 months, beginning in March (a month after fry emergence) and lasting until December of the first year, after which all fish were reared on the standard feeding regime (7 days–18%) until the time of release the following spring as yearlings. Result We observed significant interannual variation in the proportion of minijacks produced among dietary treatments. For all brood years, decreasing the feeding frequency from 7 to 4 days/week reduced the proportion minijacks by 35.9%, and lowering dietary lipid from 18% to 12% reduced the proportion minijacks by 30%. The combined effects of reducing the feeding frequency and lowering dietary lipid were additive, reducing the proportion minijacks by 65.5% compared to the standard rearing regime. Growth and energetic indices were monitored throughout and confirmed findings from previous laboratory-based studies indicating that physiological status 10–12 months prior to spawn timing is important for the “decision” to mature. Conclusion Results of this investigation provide useful insights for optimizing rearing regimes for the Umatilla River program and other Chinook Salmon hatchery programs.

Harstad, Deborah L. (ORCID:0000000202676085)↗
DOE OSTI2022

National-scale impacts on wind energy production under curtailment scenarios to reduce bat fatalities

Wind energy often plays a major role in meeting renewable energy policy objectives; however, increased deployment can raise concerns regarding the impacts of wind plants on certain wildlife. Particularly, estimates suggest hundreds of thousands of bat fatalities occur annually at wind plants across North America, with potential implications for the viability of several bat species. One approach to reducing bat fatalities is shutting down (or curtailing) turbines when bats are most at risk, such as at night during relatively low wind speed periods throughout summer and early autumn. While curtailment has consistently been shown to reduce bat fatalities, the lost power production reduces revenues for wind plants. This study conducted simulations with a range of curtailment scenarios across the contiguous United States to examine sensitivities of annual energy production (AEP) loss and potential impacts on economic metrics for future wind energy deployment. We found that AEP reduction can vary across the country from less than 1% to more than 10% for different curtailment scenarios. From an estimated 2891 gigawatts (GW) of simulated economically viable wind capacity (measured by a positive net present value), we found the mid curtailment scenario (6.0 m/s wind speed cut-in from July 1 through October 31) reduced the quantity of economic wind capacity by 274 GW or 9.5%. Our results indicate that high levels of curtailment could substantially reduce the future footprint of financially viable wind energy. In this context, future work that illuminates cost-effective strategies to minimize curtailment while reducing bat fatalities would be of value.

17 WIND ENERGY↗
DOE OSTI2015

Reducing conditions, reactive metals, and their interactions can explain spatial patterns of surface soil carbon in a humid tropical forest

Humid tropical forests support large stocks of surface soil carbon (C) that exhibit high spatial variability over scales of meters to landscapes (km). Reactive minerals and organo-metal complexes are known to contribute to C accumulation in these ecosystems, although potential interactions with environmental factors such as oxygen (O 2 ) availability have received much less attention. Reducing conditions can potentially contribute to C accumulation, yet anaerobic metabolic processes such as iron (Fe) reduction can also drive substantial C losses. We tested whether these factors could explain variation in soil C (0–10 and 10–20 cm depths) over multiple spatial scales in the Luquillo Experimental Forest, Puerto Rico, using reduced iron (Fe(II)) concentrations as an index of reducing conditions across sites differing in vegetation, topographic position, and/or climate. Fine root biomass and Fe(II) were the best overall correlates of site (n = 6) mean C concentrations and stocks from 0 to 20 cm depth (r = 0.99 and 0.98, respectively). Litterfall decreased as reducing conditions, total and dead fine root biomass, and soil C increased among sites, suggesting that decomposition rates rather than C inputs regulated soil C content at the landscape scale. Strong relationships between Fe(II) and dead fine root biomass suggest that reducing conditions suppressed particulate organic matter decomposition. The optimal mixed-effects regression model for individual soil samples (n = 149) showed that aluminum (Al) and Fe in citrate/ascorbate and oxalate extractions, Fe(II), fine root biomass, and interactions between Fe(II) and Al explained most of the variation in C concentrations (pseudo R 2 = 0.82). The optimal model of C stocks was similar but did not include fine root biomass (pseudo R 2 = 0.62). In these models, soil C concentrations and stocks increased with citrate/ascorbate-extractable Al and oxalate-extractable Fe. However, soil C decreased with citrate/ascorbate-extractable Fe, an index of Fe susceptible to anaerobic microbial reduction. At the site scale (n = 6), ratios of citrate/ascorbate to oxalate-extractable Fe consistently decreased across a landscape O 2 gradient as C increased. Finally, we suggest that the impact of reducing conditions on organic matter decomposition and the presence of organo-metal complexes and C sorption by short-range order Fe and Al contribute to C accumulation, whereas the availability of an Fe pool to sustain anaerobic respiration in soil microsites partially attenuates soil C accumulation in these ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Soybean fallow and nitrification inhibitors: Strategies to reduce N 2 O emission intensities and N losses in Australian sugarcane cropping systems

The Australian sugar industry is facing mounting pressure to reduce the nitrogen (N) losses and nitrous oxide (N 2 O) emissions associated with N fertiliser use. Research has shown that N 2 O emissions from sugarcane (Saccharum officinarum L.) cropping systems can be reduced with the use of fertilisers coated with nitrification inhibitors, or by sowing legume crops in the fallows between sugarcane crop cycles. However, the efficacy of these two N management strategies across different climatic zones is still unclear, as results from field studies have been contradictory. The objectives of this study were therefore to use the DayCent model to assess the long-term effects of the two strategies (separately or in combination) on N 2 O emissions, N losses and yields. The model was parameterised using data from eight field experiments (39 treatments) conducted across four of the five main districts of the Australian sugarcane industry. A series of long-term scenarios embracing a range of N fertiliser rates (0- 160 kg N ha -1 applied as urea), climatic regions (Tropics and Subtropics), soil textures (fine- and coarse-textured soils) and N-loss risk scenarios (crop fertilised well before or close to the on-set of the wet season) were tested for both N management strategies. Simulations identified that the combined use of soybean (Glycine max L.) fallows and N fertiliser coated with the 3,4-dimethylpyrazole phosphate (DMPP) nitrification inhibitor was the most effective strategy to maintain or even increase current yields while significantly reducing N 2 O and cumulative N (mainly due to nitrate) losses. When used alone, the soybean fallow strategy on average reduced N losses over the entire crop cycle by 29 % compared with current industry best practice. However, this strategy showed a limited capacity to reduce N 2 O emissions over the entire cane crop cycle (median: -3% compared with current industry best practice), or even increased them in scenarios at high-risk of N losses in the Tropics. The use of urea coated with DMPP alone allowed current fertiliser N rates to be reduced by 30 % without any substantial yield penalty. In environments prone to high N losses, DMPP urea abated overall N losses and N 2 O emissions by 41 % and 30 %, respectively. This was the first study to use such an extensive dataset to parameterise a biogeochemical model for yields, N 2 O emissions and N losses in sugarcane cropping systems. Finally, the findings will be instrumental in guiding future research and policies designed to improve the profitability and environmental sustainability of this industry.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Unfolding of IgG domains detected by non-reducing SDS-PAGE

Highlights: • Aberrant artefactual mAb masses and size heterogeneity noted by non-reducing SDS-PAGE. • This effect depends on pre-electrophoresis sample heating temperatures and conditions. • These phenomena are also observed for a commercial human IgG{sub 1} polyclonal antibody. • Multiple observed bands hypothesized to reflect IgG domain thermal unfolding in SDS. • These results are likely relevant to analyses of many monoclonal and polyclonal Abs. Monoclonal antibodies are very important in modern therapeutics and constitute a substantial percentage of newly approved drugs. Every therapeutic monoclonal antibody must be analyzed for structural and functional integrity, and all protein heterogeneities need to be identified and quantified. The conformational stabilities of the monoclonal antibodies are also important for antibody storage and handling stabilities. One of the first and simplest of the structural analysis techniques utilized is SDS-PAGE, which can be performed both with and without prior reduction to break disulfide bonds. This permits sizing of both heavy and light chains in the reduced condition, and sizing of the intact antibody and any disulfide aggregates in the non-reduced condition. Analyzing our human anti-cocaine monoclonal antibody, we noted unexpectedly larger apparent molecular weights and apparent protein size heterogeneities using non-reducing SDS-PAGE. These apparent molecular weight heterogeneities are not consistent with other analysis techniques. Heterogeneities were noted using several heating and pre-electrophoretic sample preparation protocols, and are modified by the inclusion of small concentrations of certain alcohols such as propanol and butanol. All of these unexpected results were also observed for a commercial human IgG{sub 1} antibody, suggesting that these observations are applicable to IgGs in general. Thus, careful attention must be paid to the interpretation of non-reducing SDS-PAGE results for IgGs. It is hypothesized that differential thermal unfolding of the Fab, CH2 and CH3 domains of the IgGs in SDS give rise to the stable, discrete bands observed using different heating protocols prior to non-reducing SDS-PAGE.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Learning high-dimensional parametric maps via reduced basis adaptive residual networks

We propose a scalable framework for the learning of high-dimensional parametric maps via adaptively constructed residual network (ResNet) maps between reduced bases of the inputs and outputs. When just few training data are available, it is beneficial to have a compact parametrization in order to ameliorate the ill-posedness of the neural network training problem. By linearly restricting high-dimensional maps to informed reduced bases of the inputs, one can compress high-dimensional maps in a constructive way that can be used to detect appropriate basis ranks, equipped with rigorous error estimates. A scalable neural network learning framework is thus to learn the nonlinear compressed reduced basis mapping. Unlike the reduced basis construction, however, neural network constructions are not guaranteed to reduce errors by adding representation power, making it difficult to achieve good practical performance. Inspired by recent approximation theory that connects ResNets to sequential minimizing flows, we present an adaptive ResNet construction algorithm. This algorithm allows for depth-wise enrichment of the neural network approximation, in a manner that can achieve good practical performance by first training a shallow network and then adapting. We prove universal approximation of the associated neural network class for $L^2_v$ functions on compact sets. Our overall framework allows for constructive means to detect appropriate breadth and depth, and related compact parametrizations of neural networks, significantly reducing the need for architectural hyperparameter tuning. Numerical experiments for parametric PDE problems and a 3D CFD wing design optimization parametric map demonstrate that the proposed methodology can achieve remarkably high accuracy for limited training data, and outperformed other neural network strategies we compared against.

42 ENGINEERING↗
DOE OSTI2012

Role of a reducing environment in disassembly of the herpesvirus tegument

Initiation of infection by herpes family viruses involves a step in which most of the virus tegument becomes detached from the capsid. Detachment takes place in the host cell cytosol near the virus entry site and it is followed by dispersal of tegument proteins and disappearance of the tegument as a distinct entity. Here we describe the results of experiments designed to test the idea that the reducing environment of the cytosol may contribute to tegument detachment and disassembly. Non-ionic detergent was used to remove the membrane of purified herpes simplex virus under control and reducing conditions. The effects on the tegument were then examined by SDS-PAGE and electron microscopy. Protein analysis demonstrated that most major tegument proteins were removed under both oxidizing and reducing conditions except for UL49 which required a reducing environment. It is proposed therefore that the reducing conditions in the cytosol are involved in removal of UL49 protein. Electron microscopic analysis revealed that capsids produced under oxidizing conditions contained a coating of protein that was absent in reduced virions and which correlated uniquely with the presence of UL49. This capsid-associated layer is suggested to be the location of UL49 in the extracted virion.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2012

Mercury reduction and oxidation by reduced natural organic matter in anoxic environments

Natural organic matter (NOM)-mediated redox cycling of elemental mercury Hg(0) and mercuric Hg(II) is critically important in affecting inorganic mercury transformation and bioavailability. However, these processes are not well understood, particularly in anoxic water and sediments where NOM can be reduced and toxic methylmercury is formed. We show that under dark anoxic conditions reduced organic matter (NOMre) simultaneously reduces and oxidizes Hg via different reaction mechanisms. Reduction of Hg(II) is primarily caused by reduced quinones. However, Hg(0) oxidation is controlled by thiol functional groups via oxidative complexation, which is demonstrated by the oxidation of Hg(0) by low-molecular-weight thiol compounds, including glutathione and mercaptoacetic acid under reducing conditions. Depending on the NOM source, oxidation state, and NOM:Hg ratio, NOM reduces Hg(II) at initial rates ranging from 0.4 to 5.5 h-1, which are about 2 to 6 times higher than observed for photochemical reduction of Hg(II) in open surface waters. However, rapid reduction of Hg(II) by NOMre can be offset by oxidation of Hg(0) with an estimated initial rate as high as 5.4 h-1. This dual role of NOMre is expected to strongly influence the availability of reactive Hg and thus to have important implications for microbial uptake and methylation in anoxic environments.

Zheng, Wang↗
DOE OSTI2017

Effect of reducible oxide–metal cluster charge transfer on the structure and reactivity of adsorbed Au and Pt atoms and clusters on anatase TiO 2

We carried out density functional theory calculations to study the influence of oxide–metal charge transfers on the structure, energetics, and reactivity of Au and Pt atoms, dimers, and trimers adsorbed on the (101) surface of reduced anatase TiO 2 . Pt clusters interact much more strongly with the TiO 2 support than Au clusters, and, with the exception of single Pt adatoms, generally behave as electron acceptors on reduced TiO 2 , whereas Au clusters can both accept and donate charge on the reduced surface. The reactivity of the supported clusters was probed by considering their interaction with CO and co-adsorbed O 2 . The effect of surface reduction on the interaction with CO is particularly significant when the CO adsorption site is an interfacial metal atom directly in contact with the TiO 2 surface and/or in the presence of co-adsorbed O 2 . Pt clusters interact strongly with co-adsorbed O 2 and form Pt–O 2 complexes that can easily accept electrons from reduced surfaces. In contrast, Au clusters donate charge to co-adsorbed O 2 even in the presence of excess electrons from a reduced support. In conclusion, the computed differences in the properties of the supported Pt and Au clusters are consistent with several experimental observations and highlight the important role of excess surface electrons in the behavior of supported metal catalysts on reducible oxides

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

Construction of Energy-Stable Galerkin Reduced Order Models

This report aims to unify several approaches for building stable projection-based reduced order models (ROMs). Attention is focused on linear time-invariant (LTI) systems. The model reduction procedure consists of two steps: the computation of a reduced basis, and the projection of the governing partial differential equations (PDEs) onto this reduced basis. Two kinds of reduced bases are considered: the proper orthog onal decomposition (POD) basis and the balanced truncation basis. The projection step of the model reduction can be done in two ways: via continuous projection or via discrete projection. First, an approach for building energy-stable Galerkin ROMs for linear hyperbolic or incompletely parabolic systems of PDEs using continuous projec tion is proposed. The idea is to apply to the set of PDEs a transformation induced by the Lyapunov function for the system, and to build the ROM in the transformed variables. The resulting ROM will be energy-stable for any choice of reduced basis. It is shown that, for many PDE systems, the desired transformation is induced by a special weighted L 2 inner product, termed the “symmetry inner product”. Atten tion is then turned to building energy-stable ROMs via discrete projection. A discrete counterpart of the continuous symmetry inner product, a weighted L 2 inner product termed the “Lyapunov inner product”, is derived. The weighting matrix that defines the Lyapunov inner product can be computed in a black-box fashion for a stable LTI system arising from the discretization of a system of PDEs in space. It is shown that a ROM constructed via discrete projection using the Lyapunov inner product will be energy-stable for any choice of reduced basis. Connections between the Lyapunov inner product and the inner product induced by the balanced truncation algorithm are made. Comparisons are also made between the symmetry inner product and the Lyapunov inner product. The performance of ROMs constructed using these inner products is evaluated on several benchmark test cases.

Kalashnikova, Irina↗
DOE OSTI2013

Large-scale Manufacturing of Nanoparticulate-based Lubrication Additives for Improved Energy Efficiency and Reduced Emissions

This project was funded under the Department of Energy (DOE) Lab Call on Nanomanufacturing for Energy Efficiency and was directed toward the development of novel boron-based nanocolloidal lubrication additives for improving the friction and wear performance of machine components in a wide range of industrial and transportation applications. Argonne's research team concentrated on the scientific and technical aspects of the project, using a range of state-of-the art analytical and tribological test facilities. Argonne has extensive past experience and expertise in working with boron-based solid and liquid lubrication additives, and has intellectual property ownership of several. There were two industrial collaborators in this project: Ashland Oil (represented by its Valvoline subsidiary) and Primet Precision Materials, Inc. (a leading nanomaterials company). There was also a sub-contract with the University of Arkansas. The major objectives of the project were to develop novel boron-based nanocolloidal lubrication additives and to optimize and verify their performance under boundary-lubricated sliding conditions. The project also tackled problems related to colloidal dispersion, larger-scale manufacturing and blending of nano-additives with base carrier oils. Other important issues dealt with in the project were determination of the optimum size and concentration of the particles and compatibility with various base fluids and/or additives. Boron-based particulate additives considered in this project included boric acid (H 3 BO 3 ), hexagonal boron nitride (h-BN), boron oxide, and borax. As part of this project, we also explored a hybrid MoS 2 + boric acid formulation approach for more effective lubrication and reported the results. The major motivation behind this work was to reduce energy losses related to friction and wear in a wide spectrum of mechanical systems and thereby reduce our dependence on imported oil. Growing concern over greenhouse gas emissions was also a major reason. The transportation sector alone consumes about 13 million barrels of crude oil per day (nearly 60% of which is imported) and is responsible for about 30% of the CO 2 emission. When we consider manufacturing and other energy-intensive industrial processes, the amount of petroleum being consumed due to friction and wear reaches more than 20 million barrels per day (from official energy statistics, U.S. Energy Information Administration). Frequent remanufacturing and/or replacement of worn parts due to friction-, wear-, and scuffing-related degradations also consume significant amounts of energy and give rise to additional CO 2 emission. Overall, the total annual cost of friction- and wear-related energy and material losses is estimated to be rather significant (i.e., as much as 5% of the gross national products of highly industrialized nations). It is projected that more than half of the total friction- and wear-related energy losses can be recovered by developing and implementing advanced friction and wear control technologies. In transportation vehicles alone, 10% to 15% of the fuel energy is spent to overcome friction. If we can cut down the friction- and wear-related energy losses by half, then we can potentially save up to 1.5 million barrels of petroleum per day. Also, less friction and wear would mean less energy consumption as well as less carbon emissions and hazardous byproducts being generated and released to the environment. New and more robust anti-friction and -wear control technologies may thus have a significant positive impact on improving the efficiency and environmental cleanliness of the current legacy fleet and future transportation systems. Effective control of friction in other industrial sectors such as manufacturing, power generation, mining and oil exploration, and agricultural and earthmoving machinery may bring more energy savings. Therefore, this project was timely and responsive to the energy and environmental objectives of DOE and our nation. In this project, most of the boron-based materials with known and potential anti-friction and -wear properties have been manufactured as colloidal additives and tested for their effectiveness in controlling friction and wear. Unlike other anti-friction and -wear additives, which consist of zinc, molybdenum, sulfur, phosphorus, and even chlorine, lubricious boron compounds considered in this project are made of boron, oxygen, nitrogen, and hydrogen, which are more environmentally benign. Among others, boric acid is a natural mineral (known in mineralogy as "sassolite"). Based on our earlier exploratory research, it was found to offer the best overall prospect in terms of performance improvements, environmental friendliness, and ease of manufacturing and, hence, cost effectiveness. Hexagonal boron nitride and borax also offered good prospects for improving the tribological properties of lubricated sliding surfaces. Boron oxide particles were found to be rather hard and somewhat abrasive and, hence, were not considered beyond the initial screening studies. In our bench-top tribological evaluation, we also demonstrated that those additives which worked well with engine oils could work equally well with very common gear oils. When added at appropriate concentrations, such gear oils were found to provide significant resistance to micropitting and scuffing failures in bench-top tribological test systems. Their traction coefficients were also reduced substantially and their scuffing limits were improved considerably. Such impressive tribological behavior of boron-based additives may have been due to their high chemical affinities to interact with sliding contact surfaces and to form slick and protective boundary films. Indeed, our surface studies have confirmed that most of the boron-based nanoparticulate additives prepared in our project possess a strong tendency to form a boron-rich boundary film on sliding contact surfaces. It is believed that the formation of such slick and highly durable boundary films is perhaps one of the fundamental reasons for their superior anti-friction, -wear, and -scuffing performance. Boron-based additives developed under this project have shown potential to reduce or replace the uses of environmentally unsafe sulfur- and phosphorus-bearing anti-wear and friction additives, such as zinc dialkyl dithiophosphate (ZDDP) and molybdenum dialkyl dithiocarbamate (MoDTC), in current lubricating oils. Because ZDDP and MoDTC were suspected of adversely impacting the performance of after-treatment catalysts in current engines, the Environmental Protection Agency (EPA) and other regulatory agencies are demanding that the concentrations of these catalysts in current oils be curtailed drastically. The boron-based nano-additives developed in this project may help reduce the use of ZDDP and MoDTC additives and, hence, help ease the poisoning effects on after-treatment catalysts. When used as lubricity additives, these boron additives can chemically interact with sliding or contacting surfaces and form a protective and slick boundary film, which can, in turn, help reduce friction and wear and increase resistance to scuffing. In the cases of traditional anti-friction and -wear additives mentioned, such protective boundary films result from phosphorus, sulfur, and other elements in the additive package, and again they have been under increased scrutiny in recent years, mainly because of their adverse effects on after-treatment devices. Overall, the boron-based nano-additive technology of this project was shown to hold promise for a broad range of industrial and transportation applications where lower friction and higher resistance to wear and scuffing are needed. Due to more stringent operating conditions of modern machinery, rolling, rotating, and sliding components have been failing to meet the projected lifetimes, mainly because of failures related to mechanical wear, corrosion, and scuffing. The novel boron-based additive technology developed under this project may help such machine components to function reliably by cutting down the friction and wear losses and by increasing resistance to scuffing.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗