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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Progress in Fast Modular Reactor Conceptual Design

The Fast Modular Reactor (FMR) is a 100-MW(thermal) gas-cooled fast reactor being developed by General Atomics Electromagnetic System with the goal of developing a FMR for flexible and dispatchable power to the U.S. electricity market in the mid-2030s. The conceptual design aims to develop and verify simplified design features. These include an inert helium gas coolant, pellet-loaded fuel rods, installations with air cooling as ultimate heat sink, and small and passive heat removal systems. The goal is to ensure the development of a safe, maintainable, cost-effective, and distributed nuclear energy-generating station. The baseline technologies selected to achieve this goal are a helium coolant that is an inert gas with no chemical reaction with structural components, not activated, single phase, enabling high-temperature operation and a high thermal efficiency Brayton cycle; conventional uranium dioxide (UO 2 ) fuel, which is the most widely used and well-known fuel material, capable of high burnup (100 MWd/kg) and a long fuel life; and silicon carbide composite (SiGA®) cladding and internal structures that are chemically inert in the helium environment, exceptionally radiation tolerant, and being derisked by accident tolerant fuel technology development. Further, the reactor was specifically designed with passive safety features, including high-temperature in-core materials and a reactor vessel cooling system consisting of cooling panels of naturally circulating water. The passive safety of the core was confirmed for the depressurized loss-of–forced cooling accident, which showed the peak cladding temperature at ~1600°C during the transient, which is below the current design limit of 1800°C. The conceptual design of the FMR has been conducted for the reactor system, vessel system, generator and turbomachine, instrumentation and control, residual heat removal system, plant service system, and containment, as well as pre-application licensing documents.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS2011

Reusable Solid Rocket Motor - Accomplishments, Lessons, and a Culture of Success

The Reusable Solid Rocket Motor represents the largest solid rocket motor ever flown and the only human rated solid motor. Each Reusable Solid Rocket Motor (RSRM) provides approximately 3-million lb of thrust to lift the integrated Space Shuttle vehicle from the launch pad. The motors burn out approximately 2 minutes later, separate from the vehicle and are recovered and refurbished. The size of the motor and the need for high reliability were challenges. Thrust shaping, via shaping of the propellant grain, was needed to limit structural loads during ascent. The motor design evolved through several block upgrades to increase performance and to increase safety and reliability. A major redesign occurred after STS-51L with the Redesigned Solid Rocket Motor. Significant improvements in the joint sealing systems were added. Design improvements continued throughout the Program via block changes with a number of innovations including development of low temperature o-ring materials and incorporation of a unique carbon fiber rope thermal barrier material. Recovery of the motors and post flight inspection improved understanding of hardware performance, and led to key design improvements. Because of the multidecade program duration material obsolescence was addressed, and requalification of materials and vendors was sometimes needed. Thermal protection systems and ablatives were used to protect the motor cases and nozzle structures. Significant understanding of design and manufacturing features of the ablatives was developed during the program resulting in optimization of design features and processing parameters. The project advanced technology in eliminating ozone-depleting materials in manufacturing processes and the development of an asbestos-free case insulation. Manufacturing processes for the large motor components were unique and safety in the manufacturing environment was a special concern. Transportation and handling approaches were also needed for the large hardware segments. The reusable solid rocket motor achieved significant reliability via process control, ground test programs, and postflight assessment. Process control is mandatory for a solid rocket motor as an acceptance test of the delivered product is not feasible. Process control included process failure modes and effects analysis, statistical process control, witness panels, and process product integrity audits. Material controls and inspections were maintained throughout the sub tier vendors. Material fingerprinting was employed to assess any drift in delivered material properties. The RSRM maintained both full scale and sub-scale test articles. These enabled continuous improvement of design and evaluation of process control and material behavior. Additionally RSRM reliability was achieved through attention to detail in post flight assessment to observe any shift in performance. The postflight analysis and inspections provided invaluable reliability data as it enables observation of actual flight performance, most of which would not be available if the motors were not recovered. These unique challenges, features of the reusable solid rocket motor, materials and manufacturing issues, and design improvements will be discussed in the paper.

Moore, Dennis R.↗
DOE OSTI2020

Energetics of Salt-Bearing Sodalites, Na 8 Al 6 Si 6 O 24 X 2 (X = SO 4 , ReO 4 , Cl, I): A Treatment Option for Pertechnetate-Enriched Nuclear Waste Streams

An alternative option for treating anion-enriched reprocessed nuclear waste streams is to immobilize technetium-99 ( 99 Tc, β = 293.7 keV, t 1/2 = 2.1 × 10 5 years) and other anions in micro- and mesoporous materials. Here we determine the thermodynamic stability of anion bearing sodalites, Na 8 Al 6 Si 6 O 24 X 2 (X = SO 4 , ReO 4 , Cl, I), to improve our understanding of the driving forces that control framework assembly using high temperature oxide melt solution calorimetry. Raman and FTIR spectroscopy illustrate a strong dependence for vibrational features on anion size and enabled the development of a linear model that predicted the vibrational features for numerous anion bearing sodalites to within ±20 cm –1 (i.e., OH, F, Br, ClO 4 , NO 3 , and MnO 4 ). The largest negative enthalpy of formation from elements and the lack of structural water demonstrate that the perrhenate sodalite (Na 8 Al 6 Si 6 O 24 [ReO 4 ] 2 ), a chemical analogue for pertechnetate sodalite (Na 8 Al 6 Si 6 O 24 [TcO 4 ] 2 ), is more thermodynamically stable than all other anion bearing sodalites evaluated. The enthalpies of the reaction between nepheline and the sodium salt, which provides the guest anion species, was negative only for the ReO 4 and NO 3 bearing sodalites. Overall, we report for the first time the enthalpy of the ion exchange reactions for different anion bearing sodalites relative to the perrhenate sodalite, which is a key step in gaining the ability to tune sodalite material properties and structure during treatment and the immobilization of 99 Tc in the presence of competing anions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Visualizing dispersive features in 2D image via minimum gradient method

Here, we developed a minimum gradient based method to track ridge features in a 2D image plot, which is a typical data representation in many momentum resolved spectroscopy experiments. Through both analytic formulation and numerical simulation, we compare this new method with existing DC (distribution curve) based and higher order derivative based analyses. We find that the new method has good noise resilience and enhanced contrast especially for weak intensity features and meanwhile preserves the quantitative local maxima information from the raw image. An algorithm is proposed to extract 1D ridge dispersion from the 2D image plot, whose quantitative application to angle-resolved photoemission spectroscopy measurements on high temperature superconductors is demonstrated.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Machine learning prediction of self-diffusion in Lennard-Jones fluids

In this work, different machine learning (ML) methods were explored for the prediction of self-diffusion in Lennard-Jones (LJ) fluids. Using a database of diffusion constants obtained from the molecular dynamics simulation literature, multiple Random Forest (RF) and Artificial Neural Net (ANN) regression models were developed and characterized. The role and improved performance of feature engineering coupled to the RF model development was also addressed. The performance of these different ML models was evaluated by comparing the prediction error to an existing empirical relationship used to describe LJ fluid diffusion. It was found that the ANN regression models provided superior prediction of diffusion in comparison to the existing empirical relationships.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

Reconstructing Richtmyer–Meshkov instabilities from noisy radiographs using low dimensional features and attention-based neural networks

We develop an ML-based approach for density reconstruction based on transformer neural networks. This approach is demonstrated in the setting of ICF-like double shell hydrodynamic simulations wherein the parameters related to material properties and initial conditions are varied. The new method can robustly recover the complex topologies given by the Richtmyer-Meshkoff instability (RMI) from a sequence of hydrodynamic features derived from radiographic images corrupted with blur, scatter, and noise. A noise model is developed to characterize errors in extracting features from synthetic radiographs of the simulated density field. The key component of the network is a transformer encoder that acts on a sequence of features extracted from noisy radiographs. This encoder includes numerous self-attention layers that act to learn temporal dependencies in the input sequences and increase the expressiveness of the model. This approach is shown to exhibit an excellent ability to accurately recover the RMI growth rates, despite the gas-metal interface being greatly obscured by radiographic noise. Our approach can be applied in a broad array of fields involving shock physics and material science.

47 OTHER INSTRUMENTATION↗
NASA NTRS2021

Understanding the Space Weathering of Mercury Through Laboratory Experiments

Introduction: Airless surfaces across the solar system are continually modified by energetic particles from solar wind and micrometeoroid bombardment [1,2]. This process is known as space weathering, and it alters the chemical, microstructural, and optical properties of surface regoliths on airless bodies, including Mercury. On the Moon and S-type asteroids, the reflectance spectral signatures of space weathering include reddening (increasing reflectance with increasing wavelength), darkening (lowering of reflectance), and the attenuation of characteristic absorption bands [2]. Such spectral changes are driven by the production of Fe-bearing nanoparticles(npFe) through both solar wind irradiation and micrometeoroid bombardment. While our understanding of space weathering for the Moon and near-Earth S-types asteroids is advanced, insight into how these processes operate on other planetary bodies is limited. In particular, Mercury experiences a uniquely intense space weathering environment than planetary counterparts at 1 AU, including a moreintense solar wind flux and higher velocity micrometeoroid impacts [4]. Additionally, Mercury has a surface composition unique in the inner solar system, including regions of the surface with very low albedo known as the low reflectance material (LRM), which is enriched in carbon, likely graphite, up to 4wt.% [5].In addition, the concentration of Fe across Mercury’s surface islow (<2 wt.%) compared to the Moonor S-type asteroids asteroids[6]. Our understanding of the effects of space weathering on C-rich and Fe-poor phases is limited. Since Fe plays a critical role inthe development of space weathering characteristicson other airless surfaces(e.g., npFe), its limited availability may significantly affect the development of space weathering features in Mercury surface materials. We can simulate space weathering processes in the laboratory to explore their effects on the microstructural, chemical, and spectral characteristics of Mercury surface materials[7]. Here we used pulsed laser irradiation to simulate the short duration, high-temperature events associated with micrometeoroid impacts. We performed coordinated analyses including reflectance spectroscopy and electron microscopy to investigate the spectral, chemical, and microstructural changes in these mercurian analog samples. Methods: For these experiments, we usedforsteritic olivine with varying FeOcontents, a mineral phase proposed to be abundant on the surface of Mercury. We mixed each sample with graphite to simulate LRM regions of the surface. Wesynthesized the olivinesamplesat 1-bar at NASA’s Johnson Space Centerand prepared pressed powder pellets for laser irradiation [8].We prepared three samples, each with a base layer of olivineto maintain structural integrity and topped witha surface layer containing the graphite-olivine mixture: 1) Sample SC-001 San Carlos olivine(Fo90.91),2)Sample F-S-002 with0.05 wt.% FeO olivine, and 3) F-T-004 with 0.53 wt.% FeO olivine. Each sample was mixed with 5 wt.% powdered graphite and had grain sizes ranging from 45to 125μm. We irradiated each sample usinga pulsed Nd-YAG laser, (l=1064 nm, ~6 ns pulse duration, energy of 48 mJ/pulse) while undervacuumat Northern Arizona University. The laser was rastered1x and then 5x over the surfaceof each sample to simulate progressive space weathering. We collected in situreflectance spectra from the samples after each laser pulse witha Nicolet IS50 Fourier-Transform Infrared spectrometer (lfrom 0.65-2.5 μm). We used an FEI Nova NanoSEM200scanning electron microscope (SEM) and a Hitachi TM4000 Plus benchtop SEM at Purdue University to image the surface morphology and topography of the samples. We extracted thin sections for analysis in the transmission electron microscope(TEM)using the FEI Helios NanoLab 660 focused ion beam (FIB) SEM at the University of Arizona.We performed analysis of the microstructural and chemical characteristics of the samples using the 200 keV JEOL 2500 scanning TEM at Johnson Space Center. Reflectance Spectroscopy Results:Reflectance spectra for each sample are shown in Fig. 1.SC-001:The spectrum of the unirradiated sample exhibits a weak 1.0 μm absorption feature, associated with Fe2+in the olivine,and low overall reflectance (Fig. 1a). Thereflectance and the depth of the absorption band increases after 1x laser raster but are at their lowest after 5x laser rasters.F-T-004:The unirradiated sample has a blue-sloped spectrum with low reflectance without identifiable absorption features (Fig. 1b). With progressive laser irradiation, the sample reflectance increases and becomes strongly red-sloped.F-S-002:The unirradiated sample exhibits a dark, blue-slopedspectrum. The brightness of the sample increases significantly from <0.2average reflectance over >0.8 reflectance in the most irradiated sampleand thespectral slope also becomesslightly reddened (Fig. 1c). Microstructural and Chemical Analysis: Two primary alteration textures were observed in the samples exposed to simulated space weathering: 1) fluffy C-rich,and 2) vesiculated melt. The fluffy C-rich texture is composed oflow-densitydeposits distributed across the surface of the sample(Fig. 2A). Analysis of a FIB section extracted from a low-density C-rich region in sample SC-001 reveals multiple globule-type deposits, discrete from stacked graphite, likely produced via melting from the laser irradiation [9].The vesiculated melt textureis smooth and uniformly distributed across isolated regions of the sample surface. The vesicles measure up to 100s of nmin diameter. Analysis of a FIB section from this texture was extracted from sample F-T-004 reveals a layer of amorphous melt material, close to 100 nm thick and uniform across the FIB section (Fig. 2B). Isolated regions of this melt layer contain small nanoparticles, <5 nm in diameter. Chemical analysis through energy dispersive X-ray spectroscopy reveals the composition of this layer is enriched in Si and depleted in Mg and O compared to the underlying sample. Implications for Space Weathering on Mercury: Previous experiments simulating space weathering of Mercury have showndarkening and reddening of spectra[7,10].However, our use of low-Fe materials and graphite to create a sample set more analogous to the mercurian surface. Our results indicate that sample composition plays a significant and important role in the space weathering of Mercury. In particular, our spectral data demonstrates a strong correlation between spectral slope, Fe content, and simulated space weathering. While the variation in FeO content between samples F-S-002 and F-T-004 is <0.6 wt.%, the spectra deviate from flat to strongly red-sloped(F-T-004). This reddeningmay be linked to the presence of very small nanoparticles observed in the melt textures extracted from sample F-T-004. For the SC-001 sample, the fluffy C-rich textures may be developed by the amalgamation of small graphite particles into these unique morphologies. Such observations indicate that space weathering on Mercury may result in both familiar and new microstructural and chemical characteristics. References: [1]Hapke B. (2001) J. Geophys. Res.-Planet.,106,10039–10073. [2]Pieters C.M. and Noble S.K. (2016) J. Geophys. Res-Planet., 121, 1865–1884. [3] Lucey P.G., and Riner, M.A. (2011) Icarus,212, 451-462.[4]CintalaM.J.(1992)J. Geophys. Res.-Planet.,97,947–973.[5]Klima R.L.et al.(2018)Geophys.Res.Letters, 45, 2945–2953. [6]Nittler L.R., et al. (2011) Science 333, 1847-1850.[7]Sasaki S. and Kurahashi E. (2004) Space weathering on Mercury, Adv.Space Res., 33, 2152-2155.[8] Vander KaadenK.E., et al. (2018) LPSCXLIX, Abstract 1230. [9] McGlaun M.L. et al. (2019) LPSCL, Abstract 2019. [10] TrangD.et al. (2018)LPSCXLIX,Abstract2083

M S Thompson↗
DOE OSTI2022

Analytics-at-scale of Sensor Data for Digital Monitoring in Nuclear Plants (3 rd Annual Report)

Nuclear power plants collect and store large volumes of heterogeneous data from various components and systems. With recent advances in machine learning (ML) techniques, these data can be leveraged to develop diagnostic and short-term forecasting models to better predict future equipment condition. Maintenance operations can then be planned in advance whenever degraded performance is predicted, thus resulting in fewer unplanned outages and the optimization of maintenance activities. This enables lower maintenance costs and improves the overall economics of nuclear power. This report primarily focuses on developing a short-term forecasting process that leverages a feature selection process to distill large volumes of heterogeneous data and predict specific equipment parameters. A variety of feature selection methods, including Shapley Additive Explanations (SHAP) and variance inflation factor (VIF), were used to select the optimal features as inputs for three ML methods: long short-term memory (LSTM) networks, support vector regression (SVR), and random forest (RF). Each combination of model and input features was used to predict a pump bearing temperature both 1 and 24 hours in advance, based on actual plant system data. The optimal inputs for the LSTM and SVR were selected using the SHAP values, while the optimal input for the RF consisted solely of the response variable itself. Each model produced similar 1-hour-ahead predictions, with root mean square errors (RMSEs) of roughly 0.006. For the 24-hour-ahead predictions, differences could be seen between LSTM, SVR, and RF, as reflected by model performances of 0.036 ± 0.014, 0.0026 ± 0, and 0.063 ± 0.004 RMSE, respectively. As big data and continuous online monitoring become more widely available, the proposed feature selection process can be used for many applications beyond the prediction of process parameters within nuclear infrastructure. This report summarizes the Fiscal Year 2021 research progress encompassing the (1) data cleaning and feature selection necessary for ML applications; (2) development of short-term forecasting models to predict future plant process parameters for both single and multiple time steps ahead; and (3) validation of the feature selection methods and short-term forecasting models given new data from different systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

Evaluating Support for OpenMP Offload Features

The OpenMP language features have been evolving to meet the rapid development in hardware platforms. DOE applications tend to push the bleeding edge of features ratified in the OpenMP specification and tend to expose the rough edges of the features' implementations. The software harness on DOE supercomputers such as Titan and (upcoming) Summit include Cray, Clang, Flang, XL and GCC compilers. It is critical, especially for Summit, that the compilers support OpenMP offloading features. This paper focuses on evaluating support for OpenMP 4.5 target offload directives across compiler implementations on Titan and Summitdev, an early access system, which is one generation removed from Summit's architecture enabling application teams to test the systems' architecture. Our tests not only evaluate the OpenMP implementations but also expose ambiguities in the OpenMP 4.5 specification. We also evaluate compiler implementations using kernels extracted from production DOE applications. This helps in assessing the interaction of different OpenMP directives independent of other application artifacts. We are aware that the implementations are constantly evolving and are advertised as having only partial OpenMP 4.x support. We see this as a synergistic effort to help identify and correct features that are required by DOE applications and prevent deployment delays later on. Going forward, we also plan to interact with standard benchmarking bodies like SPEC/HPG to donate our tests and mini-apps/kernels for potential inclusion in the next release versions of SPEC OMP and SPEC ACCEL benchmark suites.

Monsalve Diaz, Jose↗
DOE OSTI2017

Application of Bottlebrush Block Copolymers as Photonic Crystals

Brush block copolymers are a class of comb polymers that feature polymeric side chains densely grafted to a linear backbone. These polymers display interesting properties due to their dense functionality, low entanglement, and ability to rapidly self-assemble to highly ordered nanostructures. The ability to prepare brush polymers with precise structures has been enabled by advancements in controlled polymerization techniques. This Feature Article highlights the development of brush block copolymers as photonic crystals that can reflect visible to near-infrared wavelengths of light. Fabrication of these materials relies on polymer self-assembly processes to achieve nanoscale ordering, which allows for the rapid preparation of photonic crystals from common organic chemical feedstocks. Finally, the characteristic physical properties of brush block copolymers are discussed, along with methods for their preparation. Strategies to induce self-assembly at ambient temperatures and the use of blending techniques to tune photonic properties are emphasized.

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

Mass-preserving time second-order explicit–implicit domain decomposition schemes for solving parabolic equations with variable coefficients

In this paper, the new mass-preserving time second-order explicit–implicit domain decomposition (DD) schemes for solving parabolic equations with various coefficients are proposed. In the schemes, first, the interface values on the interfaces of sub-domains are explicitly calculated, in which two kinds of explicit difference schemes are used. Second, the interior values in sub-domains are determined by the implicit schemes. Third, the interface values are recalculated explicitly to preserve mass. The important feature is that the developed schemes are more than first order in time step and the correction operators at the third step ensure the schemes’ mass conservative. The stability and convergence are analyzed for the two schemes. The optimal error estimates are obtained in the H{sup 1} semi-norm under a stability condition. Numerical experiments confirm the theoretical results.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

A review of separation processes proposed for advanced fuel cycles based on technology readiness level assessments

The results of an international review of separation processes for spent nuclear fuel (SNF) recycling in future closed fuel cycles are reported. This study was made by the Expert Group on Fuel Recycling Chemistry (EGFRC) organised by the Nuclear Energy Agency (NEA) of the Organisation for Economic Co-operation and Development (OECD). A unique feature of this study was that processes were classified according to a hierarchy of separations aimed at different elements within spent fuel (uranium; uranium-plutonium co-recovery; minor actinides; high heat generating radionuclides) and also the Head-end processes, used to prepare the SNF for chemical separation, were included. Separation processes covered both wet (hydrometallurgical) and dry (pyro-chemical) processes. A bespoke methodology suitable for assessing the technological maturities of separation processes for SNF recycling was then designed based on the well-established Technology Readiness Level (TRL) scale but adapted for spent nuclear fuel separations. The innovative feature of this was the use of a matrix approach that enabled information on both the scale of testing and materials used in testing to be combined in the evaluation of the TRL. TRLs for the Head-end, hydrometallurgical and pyrochemical processes that had been reviewed by the study have been evaluated. It is clear that, whilst more R&D is needed in most cases to raise TRLs, suitable options exist to enable the recovery of all actinide elements plus the HHRs by wet or dry processes, even up to the extraordinarily difficult isolation of americium alone. The technology readiness levels (TRL) for most processes fall in the ‘proof of principle’ range with TRLs between 4 and 6, although this is an evaluation at the system level and some gaps in the individual process steps may still exist that strictly would reduce the overall TRL. That is, flowsheets have been proposed for processes and tested with active materials under increasingly relevant conditions, through to initial hot tests with small quantities of SNF. The results of this work were shown to be comparable to a parallel European study that evaluated TRLs for minor actinide partitioning processes.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

Recovering fine details from under-resolved electron tomography data using higher order total variation ℓ 1 regularization

Over the last decade or so, reconstruction methods using ℓ 1 regularization, often categorized as compressed sensing (CS) algorithms, have significantly improved the capabilities of high fidelity imaging in electron tomography. The most popular ℓ 1 regularization approach within electron tomography has been total variation (TV) regularization. In addition to reducing unwanted noise, TV regularization encourages a piecewise constant solution with sparse boundary regions. In this paper we propose an alternative ℓ 1 regularization approach for electron tomography based on higher order total variation (HOTV). Like TV, the HOTV approach promotes solutions with sparse boundary regions. In smooth regions however, the solution is not limited to piecewise constant behavior. We demonstrate that this allows for more accurate reconstruction of a broader class of images – even those for which TV was designed for – particularly when dealing with pragmatic tomographic sampling patterns and very fine image features. In conclusion, we develop results for an electron tomography data set as well as a phantom example, and we also make comparisons with discrete tomography approaches.

47 OTHER INSTRUMENTATION↗
DOE OSTI2017

Controlling the intermediate structure of an ionic liquid for f-block element separations

Recent research has revealed molecular structure beyond the inner coordination sphere is essential in defining the performance of separations processes, but nevertheless remains largely unexplored. Here we apply small angle neutron scattering (SANS) and x-ray absorption fine structure (XAFS) spectroscopy to investigate the structure of an ionic liquid system studied for f-block element separations. SANS data reveal dramatic changes in the ionic liquid microstructure (~150 Å) which we demonstrate can be controlled by judicious selection of counter ion. Mesoscale structural features (> 500 Å) are also observed as a function of metal concentration. XAFS analysis supports formation of extended aggregate structures, similar to those observed in traditional solvent extraction processes, and suggest additional parallels may be drawn from further study. As a result, achieving precise tunability over the intermediate features is an important development in controlling mesoscale structure and realizing advanced new forms of soft matter.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Elucidating Molecular Interactions in Glycerol Adsorption at the Metal–Water Interface with Density Functional Theory

Glycerol is an extremely versatile platform molecule for chemical and fuel production, as evidenced by successful demonstrations in electrochemical and thermochemical processes, where key catalytic chemistries occur at the solid–liquid interface. Despite the remarkable progress made in enriching the first-principles-based computational tool set to reveal and characterize solvent structures in the past decade, techniques for realistic and efficient molecular-level modeling to study aqueous-phase glycerol chemistry are still far from mature. Many aqueous-phase catalytic systems are deemed too complex for routine modeling because of their highly correlated structures at the heterogeneous solid–liquid interface. This invited feature article merges recent developments in quantum mechanical solvation models and oxygenated hydrocarbon conversion chemistry by revisiting the molecular interactions of adsorbed glycerol and its dehydrogenation intermediates at the water–metal interface. Explicit participation of water through the establishment of water–adsorbate, water–water, and water–metal interactions on Pt(111) was investigated using density functional theory. In periodic models, the adsorption favors networklike structures with adsorbates as nodal points linked by coadsorbed water molecules. We also showed that these adsorption patterns actually preserve the original bond-order-based scaling relationship framework established without the consideration of solvent. This behavior can be exploited to improve computational efficiency for future analysis of catalytic polyol conversions in the aqueous-phase environment.

Shan, Nannan↗
DOE OSTI2017

Electroreduction of CO 2 Catalyzed by a Heterogenized Zn–Porphyrin Complex with a Redox-Innocent Metal Center

Transition-metal-based molecular complexes are a class of catalyst materials for electrochemical CO2 reduction to CO that can be rationally designed to deliver high catalytic performance. One common mechanistic feature of these electrocatalysts developed thus far is an electrogenerated reduced metal center associated with catalytic CO2 reduction. Here we report a heterogenized zinc–porphyrin complex (zinc(II) 5,10,15,20-tetramesitylporphyrin) as an electrocatalyst that delivers a turnover frequency as high as 14.4 site–1 s–1 and a Faradaic efficiency as high as 95% for CO2 electroreduction to CO at -1.7 V vs the standard hydrogen electrode in an organic/water mixed electrolyte. While the Zn center is critical to the observed catalysis, in situ and operando X-ray absorption spectroscopic studies reveal that it is redox-innocent throughout the potential range. Cyclic voltammetry indicates that the porphyrin ligand may act as a redox mediator. Chemical reduction of the zinc–porphyrin complex further confirms that the reduction is ligand-based and the reduced species can react with CO2. This represents the first example of a transition-metal complex for CO2 electroreduction catalysis with its metal center being redox-innocent under working conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Ammonia pretreatment of corn stover enables facile lignin extraction

Thermochemical pretreatment of lignocellulose is often employed to render polysaccharides more digestible by carbohydrate-active enzymes to maximize sugar yields. The fate of lignin during pretreatment, however, is highly dependent on the chemistry employed and must be considered in cases where lignin valorization is targeted alongside sugar conversion—an important feature of future biorefinery development. Here, a two-step process is demonstrated in which anhydrous ammonia (AA) pretreatment is followed by mild NaOH extraction on corn stover to solubilize and fractionate lignin. As known, AA pretreatment simultaneously alters the structure of cellulose with enhanced digestibility while redistributing lignin. The AA-pretreated residue is then extracted with dilute NaOH at mild conditions to maximize lignin separation, resulting in a digestible carbohydrate-rich solid fraction and a solubilized lignin stream. Lignin removal of more than 65% with over 84% carbohydrate retention is achieved after mild NaOH extraction of AA-pretreated corn stover with 0.1 M NaOH at 25 °C. Two-dimensional nuclear magnetic resonance (2D-NMR) spectroscopy of the AA-pretreated residue shows that ammonolysis of ester bonds occurs to partially liberate hydroxycinnamic acids, and the AA-pretreated/NaOH-extracted residue exhibits a global reduction of all lignin moieties caused by reduced lignin content. A significant reduction (~70%) in the weight-average molecular weight ( M w ) of extracted lignin is also achieved. Imaging of AA-pretreated/NaOH extracted residues show extensive delamination and disappearance of coalesced lignin globules from within the secondary cell walls. Glycome profiling analyses demonstrates ultrastructural level cell wall modifications induced by AA pretreatment and NaOH extraction, resulting in enhanced extractability of hemicellulosic glycans, indicating enhanced polysaccharide accessibility. The glucose and xylose yields from enzymatic hydrolysis of AA-pretreated/NaOH-extracted corn stover were higher by ~80% and ~60%, respectively, compared to untreated corn stover at 1% solids loadings. For digestions at 20% solids, a benefit of NaOH extraction is realized in achieving ~150 g/L of total monomeric sugars (glucose, xylose, and arabinose) in the enzymatic hydrolysates from AA-pretreated/NaOH-extracted corn stover. Altogether, this process enables facile lignin extraction in tandem with a leading thermochemical pretreatment approach, demonstrating excellent retention of highly digestible polysaccharides in the solid phase and a highly depolymerized, soluble lignin-rich stream.

09 BIOMASS FUELS↗
DOE OSTI2019

Random Force Perturbations: A New Extension of the Cell Perturbation Method for Turbulence Generation in Multiscale Atmospheric Boundary Layer Simulations

Coupling between mesoscale and large eddy simulation (LES) is critically important for many atmospheric model applications, from predictions of wind energy to fire propagation. The grid-nesting technique enables bridging between vastly different scales without incurring prohibitive computational costs. Yet, the transition from coarser to finer resolutions often requires a large number of grid points from inflow boundaries for the development of fine-scale turbulence features in the LES domain. Recently, the cell perturbation method (CPM) was developed to reduce the turbulence development region with high computational efficiency. Herein, we explore a new method based on the CPM that uses force perturbations in both the horizontal and vertical directions (Force Cell Perturbation Method) instead of the potential temperature perturbations in the original CPM, as an attempt to further explore the performance of the random perturbation techniques. This method is tested for a neutral and a convective atmospheric boundary layer under idealized conditions. Overall, similar performance is found between the optimal configurations of the CPM and the Force Cell Perturbation Method pointing to the robustness of this family of perturbation methods in accelerating turbulence generation in nested domains. Vertical force perturbations performed better than horizontal force perturbations for both atmospheric stability conditions. The CPM performed best under convective stability conditions. The combination of the force and potential temperature perturbations is found to provide no additional performance improvement over the stand-alone application of the individual methods.

54 ENVIRONMENTAL SCIENCES↗