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DOE OSTI2025

A thermodynamically consistent discretization of 1D thermal-fluid models using their metriplectic 4-bracket structure

Thermodynamically consistent models in continuum physics, i.e. models which satisfy the first and second laws of thermodynamics, may be expressed using the metriplectic formalism. In this work, we leverage the structures underlying this modeling formalism to preserve thermodynamic consistency in discretizations of a fluid model. The procedure relies (1) on ensuring that the spatial semi-discretization retains certain symmetries and degeneracies of the Poisson and metriplectic 4-brackets, and (2) on the use of an appropriate energy conserving time-stepping method. Here, the minimally simple yet nontrivial example of a one-dimensional thermal-fluid model is treated. It is found that preservation of the requisite symmetries and degeneracies of the 4-bracket is relatively simple to ensure in Galerkin spatial discretizations, suggesting a path forward for thermodynamically consistent discretizations of more complex fluid models using more specialized Galerkin methods.

Hamiltonian structure↗

DOE OSTI2022

Hydration of alumina (Al 2 O 3 ) toward advancing aluminum particles for energy generation applications

Transforming metal particle combustion may require alteration of the metal oxide passivation shell surrounding the metal core. One approach for aluminum (Al) relies on the hydrated form of the metal oxide to incite surface reactions. Here, this study explores the conditions required for hydrating alumina (Al 2 O 3 ) particles and then extends those conditions toward hydration of the Al 2 O 3 passivation layer surrounding an Al core particle. By raising the pH of the water slurry to 11 and controlling temperature and time in slurry (i.e., aging), aluminum hydroxide Al(OH) 3 formation from Al 2 O 3 particles was optimized. The procedure was then extended to Al nanoparticles (nAl). Even though heating and extended aging time in slurry proved advantageous for Al 2 O 3 particles, these conditions were discarded for nAl particles because they favored formation of AlOOH, a less desirable hydrate. Through microscopy, spectroscopy, X-ray diffraction, and thermal analyses, results indicate that for a pH range of 11.26–11.56, the original Al 2 O 3 shell on Al particles transformed into Al(OH) 3 . Results indicate a feasible path forward towards producing new shell chemistries that may result in more directed energy from metal particle combustion.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Nanoparticles caged with DNA nanostructures

Nanoparticles (NPs) offer many benefits in biotechnology because of their small size and unique properties. Furthermore, many applications require precise positioning of the NPs or biological targeting molecules on their surfaces. DNA cages constructed from DNA tile, origami, or wireframe nanostructures offer a promising path forward because of their simplicity and programmability that can be used to generate complex, dynamic 2D and 3D geometries. Such materials can be used to pattern DNA on NP surfaces and organize NPs into specific supramolecular structures. DNA-caged NPs can be implemented in biosensing and drug delivery applications with cavities precisely designed to encapsulate-specific biomolecules. Ultimately, such approaches provide a springboard for future DNA robot designs that will enable controlled interactions with biological systems.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2015

Degradation science: Mesoscopic evolution and temporal analytics of photovoltaic energy materials

Based on recent advances in nanoscience, data science and the availability of massive real-world datastreams, the mesoscopic evolution of mesoscopic energy materials can now be more fully studied. The temporal evolution is vastly complex in time and length scales and is fundamentally challenging to scientific understanding of degradation mechanisms and pathways responsible for energy materials evolution over lifetime. We propose a paradigm shift towards mesoscopic evolution modeling, based on physical and statistical models, that would integrate laboratory studies and real-world massive datastreams into a stress/mechanism/response framework with predictive capabilities. These epidemiological studies encompass the variability in properties that affect performance of material ensembles. Mesoscopic evolution modeling is shown to encompass the heterogeneity of these materials and systems, and enables the discrimination of the fast dynamics of their functional use and the slow and/or rare events of their degradation. As a result, we delineate paths forward for degradation science.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

A review of black carbon in snow and ice and its impact on the cryosphere

Black carbon (BC) has emerged as an important short-lived climate forcer. Due to its light absorption properties, BC can darken the snow/ice surface, affect the energy balance, and further lead to acceleration of the cryospheric melting. By reviewing the recent published literatures, we present an overview of the historical changes, spatial distribution of BC in snow/ice, and how these changes are related to the melting of the cryosphere (e.g., glaciers, snow cover, and sea ice). Ice core records show an abrupt increase of BC concentrations that began in the 1850s and continued throughout the 20th century, which is consistent with an increase in BC emissions owing to industrialization. A decrease in the amount of BC since 1970s in Arctic and European ice cores has been partially attributed to the Clean Air Act. However, in the Himalayas, BC records show a continuous increase during this period. BC concentrations in snow and ice in the mid-latitude regions are one to two orders of magnitude higher than those in the polar regions. In particular, BC concentrations in aged snow and granular ice in ablation areas of mountain glaciers are one to three orders of magnitude higher than those in fresh snow or snowpits in the glacier accumulation areas due to BC accumulation during melting season. BC in the surface snow/ice is responsible for about 20% of the albedo reduction in the Tibetan Plateau during glacier melt season. Globally, observations and modeling results indicate that radiative forcing (RF) induced by BC in snow and ice is highest in the mid-latitudes, ranging from several W m–2 in fresh snow to hundreds of W m–2 in aged snow and granular ice in glacier ablation areas. The large BC-in-snow RF and associated snow albedo feedback lead to an acceleration in the total glacier melt (approximately 20%) and/or a reduction in the duration of the snow cover by several days, resulting in an increase of glacier discharge. Given our limited understanding of the role of BC in cryospheric melting, it is important to synthesize the existing research on the multi-scale processes related to BC in snow and ice to identify the gaps in our understanding of these processes and to propose a path forward to improve the quality of our observations of the aforementioned phenomena to fill these gaps.

Kang, Shichang↗

DOE OSTI2023

Implementation and test of an automated control hunting fault correction algorithm in a fault detection and diagnostics tool

Control hunting due to improper proportional–integral–derivative (PID) parameters in the building automation system (BAS) is one of the most common faults identified in commercial buildings. It can cause suboptimal performance and early failure of heating, ventilation, and air conditioning (HVAC) equipment. Commercial fault detection and diagnostics (FDD) software represents one of the fastest growing market segments in smart building technologies in the United States. Implementation of PID retuning procedures as an auto-correction algorithm and integration into FDD software has the potential to mitigate control hunting across a heterogeneous portfolio of buildings with different BAS in a scalable way. This paper presents the development, implementation, and field testing of an automated control hunting fault correction algorithm based on lambda tuning open-loop rules. The algorithm was developed in a commercial FDD software and successfully tested among nine variable air volume boxes in an office building in the United States. The paper shows the feasibility of using FDD tools to automatically correct control hunting faults, discusses scalability considerations, and proposes a path forward for the HVAC industry and academia to further improve this technology.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

Liquid electrolytes for low-temperature lithium batteries: main limitations, current advances, and future perspectives

Lithium-ion batteries (LIBs) can now be used in almost all modern electronic devices and electric vehicles. However, as the range of applications increases, the challenges increase as well, especially at very low temperatures. Many individual processes could result in capacity loss of LIBs at low temperatures; however, most of them are associated with the liquid electrolyte inside the battery. In this review, we first discuss the main limitations in developing liquid electrolytes used in low-temperature LIBs, and then we summarize the current advances in low-temperature electrolytes, including lithium salts, solvents, additives, and new strategies. Finally, we present some perspectives on the current state of low-temperature electrolytes for LIBs, outlining the most promising research areas in this field. In conclusion, this review will provide useful insights into the design of cryogenic electrolytes and the path forward to the widespread use of LIBs in cryogenic environments.

25 ENERGY STORAGE↗

DOE OSTI2023

Hydrothermal catalytic conversion of oleic acid to heptadecane over Ni/ZrO 2

There is growing interest in the substitution of expensive noble metal catalysts with low-cost earth-abundant metals in applications targeting biofuels production from waste organic feedstocks. Here, nickel (Ni) catalysts supported on zirconium dioxide (ZrO 2 ), both with and without copper (Cu) as a co-metal, were tested in hydrothermal reactions of unsaturated and saturated C18 fatty acids as models for waste oil feedstocks. In contrast to recent reports, this study showed no enhancement of nickel's activity for fatty acid conversion to alkane products when Cu was present. Ni/ZrO 2 prepared by metal coprecipitation methods converted 100% of oleic acid with 25% selectivity to heptadecane after 5h of reaction at 350 °C using methanol as a hydrogen donor source, increasing to 41% heptadecane after 20 h. Lower yields were observed with catalysts prepared by wet impregnation and using alternative hydrogen donor sources (glycerol, formic acid). Greater selectivity to heptadecane was also observed at higher temperatures (370 °C) and when the initial fatty acid had greater saturation. Longer term exposure to hydrothermal media led to metal sintering and catalyst deactivation. Findings support a path forward to the development of earth-abundant metal catalysts for the upgrading of waste organic feedstocks.

09 BIOMASS FUELS↗

DOE OSTI2018

Hard X-ray fluorescence spectroscopy of high pressure cavitating fluids in aluminum nozzles

X-rays are frequently used to study the internal geometry of dense objects, and to measure the density of multiphase flows. However, quantitatively measuring fluid density inside a metallic object such as a high pressure spray nozzle is difficult. X-rays of sufficiently high energy to penetrate a metal object are not appreciably absorbed by the fluid inside. This requires the use of plastic or beryllium test sections, which are not suited to high pressure conditions. We present a high-energy X-ray fluorescence technique which can overcome this problem. The experiments were conducted at the 7-BM beamline of the Advanced Photon Source at Argonne National Laboratory. A hydrocarbon fluid was seeded with cerium nanoparticles. The fluid was pumped at high pressure through aluminum nozzles with inner diameters of 0.36-0.90 mm and wall thicknesses of 2-3 mm. A collimated, monochromatic 42.5 keV X-ray beam excited K-edge fluorescence from the cerium. The K-alpha emission lines at 34-35 keV were recorded by a cryogenic germanium detector. Changes in fluid density due to cavitation of the liquid inside the nozzle were measured by raster scanning the nozzle across the beam. A spatial resolution of 20 x 20 mu m(2) was achieved with a slitted beam, which was improved to 5 x 10 mu m(2) with X-ray focusing mirrors. The uncertainty in the path-integrated vapor fraction was 30-40 mu m at 95% confidence. A limitation of this approach is that for low vapor pressure fluids, the nanoparticles increase the vapor pressure of the fluid and act as additional nucleation sites. These experiments demonstrate a path forward for measurements of multiphase flows inside metal components under conditions that are not feasible in optically accessible materials.

47 OTHER INSTRUMENTATION↗

DOE OSTI2015

Preoperative Single-Fraction Partial Breast Radiation Therapy: A Novel Phase 1, Dose-Escalation Protocol With Radiation Response Biomarkers

Purpose: Women with biologically favorable early-stage breast cancer are increasingly treated with accelerated partial breast radiation (PBI). However, treatment-related morbidities have been linked to the large postoperative treatment volumes required for external beam PBI. Relative to external beam delivery, alternative PBI techniques require equipment that is not universally available. To address these issues, we designed a phase 1 trial utilizing widely available technology to 1) evaluate the safety of a single radiation treatment delivered preoperatively to the small-volume, intact breast tumor and 2) identify imaging and genomic markers of radiation response. Methods and Materials: Women aged ≥55 years with clinically node-negative, estrogen receptor–positive, and/or progesterone receptor–positive HER2−, T1 invasive carcinomas, or low- to intermediate-grade in situ disease ≤2 cm were enrolled (n=32). Intensity modulated radiation therapy was used to deliver 15 Gy (n=8), 18 Gy (n=8), or 21 Gy (n=16) to the tumor with a 1.5-cm margin. Lumpectomy was performed within 10 days. Paired pre- and postradiation magnetic resonance images and patient tumor samples were analyzed. Results: No dose-limiting toxicity was observed. At a median follow-up of 23 months, there have been no recurrences. Physician-rated cosmetic outcomes were good/excellent, and chronic toxicities were grade 1 to 2 (fibrosis, hyperpigmentation) in patients receiving preoperative radiation only. Evidence of dose-dependent changes in vascular permeability, cell density, and expression of genes regulating immunity and cell death were seen in response to radiation. Conclusions: Preoperative single-dose radiation therapy to intact breast tumors is well tolerated. Radiation response is marked by early indicators of cell death in this biologically favorable patient cohort. This study represents a first step toward a novel partial breast radiation approach. Preoperative radiation should be tested in future clinical trials because it has the potential to challenge the current treatment paradigm and provide a path forward to identify radiation response biomarkers.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2023

Application of community data to surface complexation modeling framework development: Iron oxide protolysis

This study presents a comprehensive community data-driven surface complexation modeling framework for simulating potentiometric titration of mineral surfaces. Compiled community data for ferrihydrite, goethite, hematite, and magnetite are fit to produce representative protolysis constants that can reproduce potentiometric titration data collected from multiple literature sources. Using this framework, the impact of surface complexation model type and surface site density (SSD) on the fit quality and protolysis constants can be readily evaluated. For example, the non-electrostatic model yielded a poor data fit compared to diffuse double layer model and constant capacitance models due to the absence of known surface charge effects. Regardless of the choice of iron oxide mineral, pK a1 decreased with increasing SSD while the opposite tendency was observed for pK a2 . This newly developed framework demonstrates a method to reconcile community data-wide potentiometric titration data using Findable, Accessible, Interoperable, Reusable data principles to produce mineral protolysis constants that improve robustness of surface complexation models for applications in metal sorption and reactive transport modeling. The framework is readily expandable (as community data increase) and extensible (as the number of minerals increase). The framework provides a path forward for developing self-consistent, comprehensive, and updateable surface complexation databases for surface complexation and reactive transport modeling.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2021

Direct aromatization of CO 2 via combined CO 2 hydrogenation and zeolite-based acid catalysis

Aromatics, including benzene, toluene, and xylenes (BTX), are essential chemical building blocks and are widely used as solvents, fuel additives, and polymers. With the recent development in CO 2 capture technologies and the progress made in producing H 2 using renewable energy, direct hydrogenation of CO 2 to aromatics via heterogeneous catalysis has emerged as a promising pathway to accomplish the production of aromatics with simultaneous utilization of waste CO 2 . In this review, we focus on recent advances in the nascent field of direct CO 2 aromatization, whereby tandem catalysts composed of CO 2 hydrogenation and aromatization functionalities are designed and deployed. We review two categories of tandem catalysts: catalysts integrating Fe-based/H-ZSM-5 components following RWGS (reverse water-gas shift of CO 2 to CO)-FT (Fischer-Tropsch synthesis of lower olefins)-aromatization pathways, and catalysts combining metal oxide/H-ZSM-5 domains following CO 2 to methanolaromatization pathways. The key parameters that determine the catalytic performance, such as the composition and structure of the Fe-based or metal oxide-based CO 2 conversion catalysts, the properties of H-ZSM-5, and the synergy between the two components, are analyzed to provide insights for the design of efficient tandem catalysts for CO 2 aromatization. In parallel, thermodynamic analyses, mechanistic studies, and density functional theory (DFT) computations for the relevant reaction routes and pathways are discussed to offer improved understanding of CO 2 activation, reaction intermediates, and product formation. In closing, the challenges and prospects for these tandem reactions are addressed to provide suggested paths forward for future research.

10 SYNTHETIC FUELS↗

DOE OSTI2022

Explicitly antisymmetrized neural network layers for variational Monte Carlo simulation

The combination of neural networks and quantum Monte Carlo methods has arisen as a promising path forward for highly accurate electronic structure calculations. Previous proposals have combined equivariant neural network layers with a final antisymmetric layer in order to satisfy the antisymmetry requirements of the electronic wavefunction. However, to date it is unclear if one can represent antisymmetric functions of physical interest, and it is difficult to precisely measure the expressiveness of the antisymmetric layer. Here, this work attempts to address this problem by introducing explicitly antisymmetrized universal neural network layers. This approach has a computational cost which increases factorially with respect to the system size, but we are nonetheless able to apply it to small systems to better understand how the structure of the antisymmetric layer affects its performance. We first introduce a generic antisymmetric (GA) neural network layer, which we use to replace the entire antisymmetric layer of the highly accurate ansatz known as the FermiNet. We demonstrate that the resulting FermiNet-GA architecture can yield effectively the exact ground state energy for small atoms and molecules. We then consider a factorized antisymmetric (FA) layer which more directly generalizes the FermiNet by replacing the products of determinants with products of antisymmetrized neural networks. We find, interestingly, that the resulting FermiNet-FA architecture does not significantly outperform the FermiNet. This strongly suggests that the sum of products of antisymmetries is a key limiting aspect of the FermiNet architecture. To explore this further, we investigate a slight modification of the FermiNet, called the full determinant mode, which replaces each product of determinants with a single combined determinant. We find that the full single-determinant FermiNet closes a large part of the gap between the standard single-determinant FermiNet and FermiNet-GA on small atomic and molecular problems. Surprisingly, on the nitrogen molecule at a dissociating bond length of 4.0 Bohr, the full single-determinant FermiNet can outperform the largest standard FermiNet calculation with 64 determinants.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Computational modeling and neutron imaging to understand interface shape and solute segregation during the vertical gradient freeze growth of BaBrCl:Eu

In this work we apply continuum models to analyze phase change, heat transfer, fluid flow, solute transport, and segregation in order to understand prior neutron imaging observations of the vertical gradient freeze growth of Eu-doped BaBrCl. The models provide a rigorous framework in which to understand the mechanisms that are responsible for the complicated evolution of interface shape and dopant distribution in the growth experiment. We explain how a transition in the solid/liquid interface shape from concave to convex is driven by changes in radial heat transfer caused by furnace design. We also provide a mechanistic explanation of how dynamic growth conditions and changes of the flow structure in the melt result in complicated segregation patterns in this system. A growth pause caused by controller lock-up is shown to result in a band of solute depletion in accordance with classical theory. However, changing flow patterns during growth result in a non-monotonic axial distribution of solute that cannot be explained by simple application of classical segregation models. We assert that the approach presented here, namely the use of rigorous models in conjunction advanced diagnostics, such as neutron imaging, provides an exciting path forward for process optimization and control, accelerating the incremental advances that have, in the past, typically relied on empiricism, experience, and intuition.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Role of chemical disorder on radiation-induced defect production and damage evolution in NiFeCoCr

Understanding chemical disorder in many concentrated solid solution alloys (CSAs) at the levels of electrons and atoms has attracted increasing attention as a path forward to reveal and identify underlying mechanisms for extraordinary mechanical properties and improved radiation tolerance. Single-phase NiFeCoCr CSA is a common base for many high-entropy alloys (HEAs) that have shown improved mechanical strength and radiation tolerance. In this study, defect production and damage evolution in NiFeCoCr under ion irradiation at room temperature to dose over 20 dpa are determined using ion channeling technique along both <100> and <110> directions utilizing multiple probing beam energies. The results obtained from the multi-axial and multi-energy channeling analysis are compared with those previously obtained for Ni crystals irradiated under similar conditions. The influence of chemical complexity on defect production and clustering at early-stage under room temperature irradiation up to dose of 1 dpa is discussed based on positron annihilation spectroscopy results. Defect structure evaluation in Ni and NiFeCoCr is also discussed based on transmission electron microscopy results over a prolonged irradiation at both room and elevated temperatures. Compared with chemically complex NiFeCoCr, larger dislocation loops thus less lattice strain are expected to form in pure Ni. Moreover, the role of chemical disorder in this CSA is also investigated based on ab initio calculations using large supercells. Finally, to understand the impact of chemical complexity effect on defect structure evolution, this integrated research effort attempts to link the relatively large charge redistribution due to difference in valence electron counts resulting from alloying different 3d transition metal elements, moderate lattice distortion arising from similar adaptable atomic size, and notable suppressed or delayed damage evolution in NiFeCoCr.

36 MATERIALS SCIENCE↗

DOE OSTI2024

An approach to combine neutron and ion irradiation data to accelerate material qualification for nuclear reactors

Next-generation nuclear power plants are generally characterized by higher operating temperatures, increased neutron fluences and energies, and distinct corrosive coolant environments versus the existing light water reactor fleet. Whether using existing materials in new environments, newly developed materials tailored for these environments, or new manufacturing methods, the traditional decades-long approach for materials qualification does not facilitate rapid deployment. Ion irradiation has demonstrated success in reproducing material microstructure and select property evolution resulting from neutron irradiation with three to four orders of magnitude reduction in time and cost, making it an ideal candidate for accelerated irradiation testing. Because microstructure has a large impact on bulk material properties, limited neutron irradiation data at lower damage levels can in principle be combined with accelerated ion testing results and modeling and simulation to form an accurate prediction of microstructure evolution and select properties under different neutron irradiation conditions and at higher damage levels. The objective of this work is to present a conceptual framework of specific steps to fulfill several technical challenges associated with qualifying materials for performance in radiation environments on an accelerated time frame. A brief review of the regulatory landscape for materials in nuclear environments is presented, followed by additional overviews to understand the current state of the art for correlation of materials properties across radiation environments using experimental and computational methodologies. Finally, the roles of academia, national laboratories, and industry in the advancement of this accelerated materials qualification framework are discussed as a path forward, with possible case studies presented.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2021

Autonomous experimentation systems for materials development: A community perspective

Solutions to many of the world's problems depend upon materials research and development. However, advanced materials can take decades to discover and decades more to fully deploy. Humans and robots have begun to partner to advance science and technology orders of magnitude faster than humans do today through the development and exploitation of closed-loop, autonomous experimentation systems. This review discusses the specific challenges and opportunities related to materials discovery and development that will emerge from this new paradigm. Our perspective incorporates input from stakeholders in academia, industry, government laboratories, and funding agencies. We outline the current status, barriers, and needed investments, culminating with a vision for the path forward. We intend the article to spark interest in this emerging research area and to motivate potential practitioners by illustrating early successes. We also aspire to encourage a creative reimagining of the next generation of materials science infrastructure. To this end, we frame future investments in materials science and technology, hardware and software infrastructure, artificial intelligence and autonomy methods, and critical workforce development for autonomous research.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Towards the design of nature-inspired materials: Impact of complex pore morphologies via higher-order homogenization

Even though the development of novel materials that mimic nature is widely used in a variety of engineering and scientific fields, the relationship between effective material properties and underlying, often complex pore morphology is still not fully understood. To address this knowledge gap and accelerate the development of novel nature-inspired materials, this paper adopts a higher-order asymptotic homogenization method to numerically investigate the effect of complex micropore morphology on the effective mechanical properties of a porous system. Specifically, we create unique pore morphologies with varying levels of complexity that serve as a more realistic representation of natural materials. Here, we then use the second-order homogenization method to capture the role of pore size, shape, orientation, and distribution on effective properties. By creating different pore morphologies, we systematically studied the relationship between morphology and effective mechanical properties. The results highlight the necessity of higher-order parameters to fully capture the role of realistic pore morphologies on effective mechanical properties and provide a path forward in the design of nature-inspired materials.

36 MATERIALS SCIENCE↗