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DOE OSTI2017

Black carbon emissions in Russia: A critical review

Russia has a particularly important role regarding black carbon (BC) emissions given the extent of its territory above the Arctic Circle, where BC emissions have a particularly pronounced effect on the climate. This study presents a comprehensive review of BC estimates from a range of studies. We assess underlying methodologies and data sources for each major emissions source based on their level of detail, accuracy and extent to which they represent current conditions. We then present reference values for each major emissions source. In the case of flaring, the study presents new estimates drawing on data on Russian associated petroleum gas and the most recent satellite data on flaring. We also present estimates of organic carbon (OC) for each source, either based on the reference studies or from our own calculations. In addition, the study provides uncertainty estimates for each source. Total BC emissions are estimated at 689 Gg in 2014, with an uncertainty range between (407-1,416), while OC emissions are 9,228 Gg (with uncertainty between 5,595 and 14,728). Wildfires dominated and contributed about 83% of the total BC emissions, however the effect on radiative forcing is mitigated by OC emissions. We also present an adjusted estimate of Arctic forcing from Russian OC and BC emissions. In recent years, Russia has pursued policies to reduce flaring and limit particulate emissions from on-road transport, both of which appear to significantly contribute to the lower emissions and forcing values found in this study.

Black carbon↗

DOE OSTI2025

Machine learning modeling and model predictive control of a closed-circuit reverse osmosis system

Closed-circuit reverse osmosis (CCRO) offers a flexible and energy-efficient alternative to conventional reverse osmosis by operating in a semi-batch mode that recycles brine, enabling higher recovery rates and reduced specific energy consumption (SEC). However, developing accurate, system-level dynamic models for CCRO remains challenging due to its nonlinear, multi-phase operation and sensitivity to variable feed water conditions. Traditional modeling approaches, such as NARMAX (nonlinear autoregressive moving average with exogenous inputs), often struggle to generalize across varying inlet feed concentrations, necessitating frequent parameter re-estimation and limiting their utility for real-time control applications. To address these limitations, we developed a long short-term memory (LSTM) neural network model trained on an extensive experimental data set from a CCRO pilot plant. The model accepts three inputs, feed flow rate, recirculation flow rate, and initial feed conductivity, and predicts three key outputs: reject conductivity, feed pump power draw, and recirculation pump power draw. We validated the LSTM model against experimental data, demonstrating its ability to distinguish between different feed conductivities and adapt to variable flow rates. Subsequently, we incorporated the LSTM model within a nonlinear model predictive control (MPC) scheme and conducted closed-loop simulations to optimize the integrated SEC (iSEC). In conclusion, the results project up to a 6% reduction in iSEC by using MPC to optimize performance over the entire experiment duration, without requiring any random excitation for data collection or parameter re-estimation.

Desalination↗

DOE OSTI2017

Polyacrylonitrile nanocomposite fibers from acrylonitrile-grafted carbon nanofibers

For the first time, uniform distribution of surface functionalized carbon nanofibers (CNFs) has been achieved in low molecular weight (≈120,000 g/mol) textile grade-polyacrylonitrile (PAN)-based composite filaments. Furthermore, surface grafting of CNFs with acrylonitrile enhances the dispersion of nanofibers in PAN fiber matrix. XPS study reveals high atomic nitrogen content (7%) on the CNF surface due to the grafting reaction. The solution-spun filaments have been characterized for distribution of CNFs in the PAN matrix by electron microscopy. PAN composite filaments containing 3.2 wt.% CNF and processed at draw ratio of ≈6.3 exhibit enhanced tensile strength and modulus by more than three folds compared to the control PAN filament. Because of chemically compatible surface modification of the nanofibers, better dispersion and improved mechanical properties were accomplished in the reinforced PAN fibers. This should then allow the production of CNF reinforced carbon fibers with improved tensile properties. An increase in CNF loading (6.4 wt.%), however, reduced performance due to inefficient alignment of CNF along the fiber axis. Nevertheless, hot stretching (at draw ratio ≈ 10) of the filaments enhanced tensile strength and elastic modulus of PAN composite filaments by 20–30% compared to the control hot stretched PAN filaments.

36 MATERIALS SCIENCE↗

DOE OSTI2020

High performance Nb/TiNi nanocomposites produced by packaged accumulative roll bonding

Taking full advantage of intrinsic high strength of nano-reinforcements has been proven difficult in a composite until the concept of strain matching was experimental verified in a nanowire Nb/TiNi in-situ composite, which was obtained via solidifying eutectic Nb/TiNi and subsequent severe wire drawing. However, the volume fraction of the nano-reinforcement was dictated by eutectic reaction, which severely limited the development of high-performance composites. Here, the martensitic transformation nanocomposites were successfully acquired with increased volume fraction and changeable morphology of the nano-reinforcement through hot packaged ARB (PARB) and subsequent wire drawing. The nano-reinforcement with lamellar configuration in the composite could exhibit a large lattice strain of similar to 3.8%, which demonstrated the applicability and effectiveness of the strain matching principle in nano-lamellar composite. The obtained composites show a yield strength over 2.0 GPa and a quasi-linear elastic strain as larger as similar to 6.5% with adjustable apparent elastic modulus from 30 to 50 GPa.

42 ENGINEERING↗

DOE OSTI2024

Computing the QRPA level density with the finite amplitude method

Here, we describe a new algorithm to calculate the vibrational nuclear level density of an atomic nucleus. Fictitious perturbation operators that probe the response of the system are generated by drawing their matrix elements from some probability distribution function. We use the Finite Amplitude Method to explicitly compute the response for each such sample. With the help of the Kernel Polynomial Method, we build an estimator of the vibrational level density and provide the upper bound of the relative error in the limit of infinitely many random samples. The new algorithm can give accurate estimates of the vibrational level density. Since it is based on drawing multiple samples of perturbation operators, its computational implementation is naturally parallel and scales like the number of available processing units.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2018

Meeting the imperative to accelerate environmental bioelectromagnetics research

Highlights: • Concerns mount about adverse health effects of low-level radiofrequency (RF) radiation. • Bioelectronics and environmental RF effects research both need an omics platform. • Standard bioelectromagnetic data models would advance dosimetry and omics work. • Steps toward developing standards and a shared research platform are proposed. In this article, the author draws on his experience in the world of geospatial information technology standards to suggest a path toward acceleration of bioelectromagnetics science. Many studies show biological effects of extremely low frequency (ELF) and radiofrequency (RF) radiation despite that fact that the radiation is too weak to cause temperature changes in biological features. Considered together in worst case scenarios, such effects, many of which appear to have long latencies, could have potentially disastrous consequences for the health and safety of humans and wildlife. Other studies show no such effects, and in both cases, often there are significant research quality deficits that make it difficult to draw firm conclusions from the data. The progress of bioelectromagnetics science is retarded by a lack of standard data models and experimental protocols that could improve the overall quality of research and make it easier for researchers to benefit from omics-related bioinformatics resources. {sup C}ertainty of safety{sup }of wireless devices used in digital communications and remote sensing (radar) is impossible without dosimetry standards that reflect the effects of non-thermal exposures. Electrical signaling in biological systems, a poorly funded research domain, is as biologically important as chemical signaling, a richly funded research domain, and these two types of signaling are inextricably connected. Entreprenuerial scientists pursuing bioelectronic innovations have begun to attract new funding. With appropriate institutional coordination, this new funding could equally benefit those investigating environmental effects of ELF and RF radiation. The author proposes a concerted effort among both bioelectronics technology stakeholders and environmental bioelectromagnetics science researchers to collaborate in developing institutional arrangements and standard data models that would give the science a stronger bioinformatics platform and give researchers better access to omics data. What is proposed here is essentially a bioelectromagnetics omics initiative.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Can developing countries leapfrog the centralized electrification paradigm?

Due to the rapidly decreasing costs of small renewable electricity generation 'systems, centralized power systems are no longer a necessary condition of universal access to modern energy services. Developing countries, where centralized electricity infrastructures are less developed, may be able to adopt these new technologies more quickly. We first review the costs of grid extension and distributed solar home systems (SHSs) as reported by a number of different studies. We then present a general analytic framework for analyzing the choice between extending the grid and implementing distributed solar home systems. Drawing upon reported grid expansion cost data for three specific regions, we demonstrate this framework by determining the electricity consumption levels at which the costs of provision through centralized and decentralized approaches are equivalent in these regions. We then calculate SHS capital costs that are necessary for these technologies provide each of five tiers of energy access, as defined by the United Nations Sustainable Energy for All initiative. Our results suggest that solar home systems can play an important role in achieving universal access to basic energy services. The extent of this role depends on three primary factors: SHS costs, grid expansion costs, and centralized generation costs. Given current technology costs, centralized systems will still be required to enable higher levels of consumption; however, cost reduction trends have the potential to disrupt this paradigm. By looking ahead rather than replicating older infrastructure styles, developing countries can leapfrog to a more distributed electricity service model. (C) 2016 International Energy Initiative. Published by Elsevier Inc. All rights reserved.

distributed electrification↗

DOE OSTI2013

Monte Carlo Simulations of the Corrosion of Aluminoborosilicate Glasses

Aluminum is one of the most common components included in nuclear waste glasses. Therefore, Monte Carlo (MC) simulations were carried out to investigate the influence of aluminum on the rate and mechanism of dissolution of sodium borosilicate glasses in static conditions. The glasses studied were in the compositional range (70-2x)% SiO2 x% Al2O3 15% B2O3 (15+x)% Na2O, where 0 ≤ x ≤ 15%. The simulation results show that increasing amounts of aluminum in the pristine glasses slow down the initial rate of dissolution as determined from the rate of boron release. However, the extent of corrosion - as measured by the total amount of boron release - initially increases with addition of Al2O3, up to 5 Al2O3 mol%, but subsequently decreases with further Al2O3 addition. The MC simulations reveal that this behavior is due to the interplay between two opposing mechanisms: (1) aluminum slows down the kinetics of hydrolysis/condensation reactions that drive the reorganization of the glass surface and eventual formation of a blocking layer; and (2) aluminum strengthens the glass thereby increasing the lifetime of the upper part of its surface and allowing for more rapid formation of a blocking layer. Additional MC simulations were performed whereby a process representing the formation of a secondary aluminosilicate phase was included. Secondary phase formation draws dissolved glass components out of the aqueous solution, thereby diminishing the rate of condensation and delaying the formation of a blocking layer. As a result, the extent of corrosion is found to increase continuously with increasing Al2O3 content, as observed experimentally. For Al2O3 < 10 mol%, the MC simulations also indicate that, because the secondary phase solubility eventually controls the aluminum content in the part of the altered layer in contact with the bulk aqueous solution, the dissolved aluminum and silicon concentrations at steady state are not dependent on the Al2O3 content of the pristine aluminoborosilicate glass.

Environmental Molecular Sciences Laboratory↗

DOE OSTI2013

Microstructure and texture evolution of Cu–Nb composite wires

The evolution of microstructure and texture in Cu–Nb composite wires fabricated by an accumulative drawing and bundling process was investigated by backscattered electron (BSE), electron backscatter diffraction (EBSD) and transmission electron microscopy (TEM). Results indicate the onset of severe curling and shape changing occurred at the size of Nb ∼ 400 nm with a surface increase of about 6.91 μm{sup 2}/μm{sup 3} (the area per unit volume). Two kinds of grain boundaries in Nb are suggested: one is 20°–50° boundary with a rotate/tilt axis around <110> parallel to drawing direction (DD), and another is > 50° boundary with the axis perpendicular to DD. The curling phenomenon occurred at the Cu–Nb interface and is related not only to the deformation mechanism of Nb but also to the presence of interface. This result is distinct from reported works showing that curling takes place when BCC metals are heavily drawn (Area reduction > 73%). The variation in microstructure and texture evolution between Cu and Nb filaments was discussed based on the differences in deformation mechanisms of these two metals. - Highlights: • Microstructure and texture evolution were studied systematically by EBSD. • In Nb, grain boundaries of 20°–50° have a rotate/tile axis around <110>//DD. • The rotation axes of above 50° boundaries are concentrated around <111> ⊥ DD in Nb. • Curling is related to not only deformation mode of BCC but also Cu–Nb interface.

36 MATERIALS SCIENCE↗

DOE OSTI2013

Optimization of chemical compositions in low-carbon Al-killed enamel steel produced by ultra-fast continuous annealing

The influence of Mn,S and B contents on microstructural characteristics, mechanical properties and hydrogen trapping ability of low-carbon Al-killed enamel steel was investigated. The materials were produced and processed in a laboratory and the ultra-fast continuous annealing processing was performed using a continuous annealing simulator. It was found that increasing Mn,S contents in steel can improve its hydrogen trapping ability which is attributed by refined ferrite grains, more dispersed cementite and added MnS inclusions. Nevertheless, it deteriorates mechanical properties of steel sheet. Addition of trace boron results in both good mechanical properties and significantly improved hydrogen trapping ability. The boron combined with nitrogen segregating at grain boundaries, cementite and MnS inclusions, provides higher amount of attractive hydrogen trapping sites and raises the activation energy for hydrogen desorption from them. - Highlights: • We study microstructures and properties in low-carbon Al-killed enamel steel. • Hydrogen diffusion coefficients are measured to reflect fish-scale resistance. • Manganese improves hydrogen trapping ability but decrease deep-drawing ability. • Boron improves both hydrogen trapping ability and deep-drawing ability. • Both excellent mechanical properties and fish-scale resistance can be matched.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Polyamide-crosslinked graphene oxide membrane for forward osmosis

We report a novel polyamide-graphene oxide (PA-GO) membrane was synthesized on a polyethersulfone support by first intra-crosslinking GO aggregates via m-xylylenediamine (MXDA) and then inter-crosslinking GO aggregates via trimethyle chloride (TMC). This method allows for the use of hydrophilic, more porous supports in forward osmosis (FO) membranes, thereby lending much flexibility to membrane synthesis and also potentially reducing internal concentration polarization in FO. The elemental composition, morphology, and hydrophilicity of the synthesized PA-GO membrane were characterized to confirm intra- and inter-crosslinking reactions and understand membrane properties. It was found that the mixing temperature of MXDA and GO should be controlled below 20 °C to avoid the formation of large GO aggregates and hence reduce membrane heterogeneity and defects. The performance of the PA-GO membrane was compared with that of a commercial FO membrane using trisodium citrate (TSC), Na 2 SO 4 , and MgCl 2 , respectively, as draw solutes. Under the same osmotic pressure, the water flux of the PA-GO membrane was the highest with TSC as draw solute, moderate with Na 2 SO 4 , and almost zero with MgCl 2 , while the ranking of solute fluxes followed a reverse order, revealing that an effective solute barrier plays an important role in making FO membranes with high water flux and low solute flux.

42 ENGINEERING↗

DOE OSTI2017

Grain engineering: How nanoscale inhomogeneities can control charge collection in solar cells

Statistical and correlative analysis are increasingly important in the design and study of new materials, from semiconductors to metals. Non-destructive measurement techniques, with high spatial resolution, capable of correlating composition and/or structure with device properties, are few and far between. For the case of polycrystalline and inhomogeneous materials, the added challenge is that nanoscale resolution is in general not compatible with the large sampling areas necessary to have a statistical representation of the specimen under study. For the study of grain cores and grain boundaries in polycrystalline solar absorbers this is of particular importance since their dissimilar behavior and variability throughout the samples makes it difficult to draw conclusions and ultimately optimize the material. In this study, we present a nanoscale in-operando approach based on the multimodal utilization of synchrotron nano x-ray fluorescence and x-ray beam induced current collected for grain core and grain boundary areas and correlated pixel-by-pixel in fully operational Cu(In(1-x)Gax)Se2Cu(In(1-x)Gax)Se2 solar cells. We observe that low gallium cells have grain boundaries that over perform compared to the grain cores and high gallium cells have boundaries that under perform. These results demonstrate how nanoscale correlative X-ray microscopy can guide research pathways towards grain engineering low cost, high efficiency solar cells.

14 SOLAR ENERGY↗

DOE OSTI2022

Radiocarbon analysis as a method for verifying atmospheric CO 2 uptake during carbon mineralization

Sequestration of atmospheric CO 2 is required to constrain the warming of Earth’s climate. Carbon mineralization refers to the precipitation of carbonate minerals by reaction of CO 2 and Mg- and Ca-rich rocks; if the source of the CO 2 is atmospheric and the precipitated carbonate is protected from subsequent dissolution, this process at sufficient scale may be able to reliably draw down atmospheric greenhouse gas levels. Such reactions occur passively in ultramafic settings and previous work has demonstrated that they actively draw down local CO 2 (g) concentrations. However, a method for unambiguously attributing the sequestered carbon solid product to atmospheric sources is still lacking. Here, we test if radiocarbon can be used to verify that the carbon being incorporated into carbonate minerals during carbon mineralization is atmospheric in origin. Additionally, samples from recently exposed ultramafic sites are analyzed and the results demonstrate the utility of this technique for verifying true atmospheric carbon reduction.

58 GEOSCIENCES↗

DOE OSTI2020

Developing a common approach for classifying building stock energy models

Buildings contribute 40% of global greenhouse gas emissions; therefore, strategies that can substantially reduce emissions from the building stock are key components of broader efforts to mitigate climate change and achieve sustainable development goals. Models that represent the energy use of the building stock at scale under various scenarios of technology deployment have become essential tools for the development and assessment of such strategies. Within the past decade, the capabilities of building stock energy models have improved considerably, while model transferability and sharing has increased. Given these advancements, a new scheme for classifying building stock energy models is needed to facilitate communication of modeling approaches and the handling of important model dimensions. In this article, we present a new building stock energy model classification framework that leverages international modeling expertise from the participants of the International Energy Agency's Annex 70 on Building Energy Epidemiology. Drawing from existing classification studies, here we propose a multi-layer quadrant scheme that classifies modeling techniques by their design (top-down or bottom-up) and degree of transparency (black-box or white-box); hybrid techniques are also addressed. The quadrant scheme is unique from previous classification approaches in its non-hierarchical organization, coverage of and ability to incorporate emerging modeling techniques, and treatment of additional modeling dimensions. The new classification framework will be complemented by a reporting protocol and online registry of existing models as part of ongoing work in Annex 70 to increase the interpretability and utility of building stock energy models for energy policy making.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2021

An Open-Source Virtual Testbed for a Real Net-Zero Energy Community

Net zero energy communities (NZECs) are critical to ensure sustainability and resilience of modernized power systems. System modeling helps overcome technical challenges in designing and operating NZECs. In this paper, we present the modeling work based on a real NZEC. Two sets of models are developed: higher-fidelity physics-based models considering the interaction between subsystems of the studied NZEC and capturing fast-dynamics; and lower-fidelity data-driven models requiring less resource to establish and/or run. All models are validated against measurements from this real NZEC. In addition, we create a simulation framework which streamlines the processes for simulation and thus allows using developed models to form a virtual testbed. To demonstrate the usage of the virtual testbed, a case study is conducted where a building-to-grid integration control is evaluated via simulation. The evaluation results suggest that the tested control significantly smooths the power draw of the studied community and doesn’t sacrifice the thermal comfort to a great extent.

Huang, Sen↗

DOE OSTI2022

Semi-Automated, Object-Based Tomography of Dislocation Structures

The characterization of the three-dimensional arrangement of dislocations is important for many analyses in materials science. Dislocation tomography in transmission electron microscopy is conventionally accomplished through intensity-based reconstruction algorithms. Although such methods work successfully, a disadvantage is that they require many images to be collected over a large tilt range. Here, we present an alternative, semi-automated object-based approach that reduces the data collection requirements by drawing on the prior knowledge that dislocations are line objects. Our approach consists of three steps: (1) initial extraction of dislocation line objects from the individual frames, (2) alignment and matching of these objects across the frames in the tilt series, and (3) tomographic reconstruction to determine the full three-dimensional configuration of the dislocations. Drawing on innovations in graph theory, we employ a node-line segment representation for the dislocation lines and a novel arc-length mapping scheme to relate the dislocations to each other across the images in the tilt series. We demonstrate the method for a dataset collected from a dislocation network imaged by diffraction-contrast scanning transmission electron microscopy. Based on these results and a detailed uncertainty analysis for the algorithm, we discuss opportunities for optimizing data collection and further automating the method.

47 OTHER INSTRUMENTATION↗

DOE OSTI2016

Influence of Surface Oxidation on Ion Dynamics and Capacitance in Porous and Nonporous Carbon Electrodes

We investigate the influence of surface chemistry and ion confinement on capacitance and electrosorption dynamics of room-temperature ionic liquids (RTILs) in supercapacitors. Using air oxidation and vacuum annealing, we produced defunctionalized and oxygen-rich surfaces of carbide-derived carbons (CDCs) and graphene nanoplatelets (GNPs). While oxidized surfaces of porous CDCs improve capacitance and rate handling abilities of ions, defunctionalized nonporous GNPs improve charge storage densities on planar electrodes. Quasi-elastic neutron scattering (QENS) and inelastic neutron scattering (INS) probed the structure, dynamics, and orientation of RTIL ions confined in divergently functionalized pores. Oxidized, ionophilic surfaces draw ions closer to pore surfaces and enhance potential-driven ion transport during electrosorption. Molecular dynamics (MD) simulations corroborated experimental data and demonstrated the significance of surface functional groups on ion orientations, accumulation densities, and capacitance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

INBOUND APPOINTEE PUBLICATION Importance of Substrate-Particle Repulsion for Protein-Templated Assembly of Metal Nanoparticles

We study the protein-directed assembly of colloidal gold nanoparticles on de novo designed protein nanofiber templates. Using sequential assembly on glass substrates, we attach of positively-charged gold nanoparticles to protein nanofibers engineered to have a high density of negatively-charged surface residues. Using a combination of electron and optical microscopy, we measure the density of particle attachment and characterize binding specificity. By varying nanoparticle size and pH of the solution, we explore the importance of charge-dependent particle-fiber and particle-substrate interactions. We find an inverse correlation between particle size and attachment density to the protein nanofibers, attributed to the balance between size-dependent electrostatic particle-fiber attraction and particle-substrate repulsion. We show pH-dependent particle attachment density and binding specificity in relation to the protonation fraction of each assembly layer. Finally, we employ hyperspectral scattering microscopy to draw conclusions about particle density and interparticle spacings of optically-observable particle assemblies.

Guye, Kathryn N.↗