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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 OSTI2023

Tunable phase structure in NaNbO 3 ceramics by grain-size effect, electric field and heat treatment

Large polarization and strain change during antiferroelectric - ferroelectric phase transition under electric field is the foundation for realizing excellent electrical properties in antiferroelectric ceramics, therefore, the adjustment of antiferroelectricity and clarification of the corresponding mechanism is the foundation for controlling electrical properties. NaNbO3 is the most complex perovskite system showing multiple antiferroelectric phases in a wide temperature range, in which the antiferroelectricity shows obvious instability with changing external and internal conditions, namely the antiferroelectric phase can be adjusted by grain-size effect, electric field and heat treatment. According to the systematical study in terms of the Rietveld refinement of synchrotron XRD and Raman, NaNbO3 exhibits a ferrielectric P21ma structure at room temperature, the ferroelectric component of which increases with decreasing grain size. Two antiferroelectric tetragonal phases exist around Curie temperature TC before the entrance of antiferroelectric R phase zone, while an antiferroelectric monoclinic phase, which can be maintained to room temperature by annealing treatment, acts as the bridge for the depolarization of the poled NaNbO3 with ferroelectric Q phase. A detailed phase diagram mainly focused on the antiferroelectric phase zones of NaNbO3 is plotted, which gives a clear understanding about the polymorphic phase transitions under different conditions. Finally, the results concluded in this work would give a clear guidance for designing high-performance NaNbO3-based lead-free ceramics from the point of structure.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A dynamic volumetric heat source model for laser additive manufacturing

Melt pool scale models of laser powder bed fusion (LPBF) offer insights into the process-structure-property relationships in additive manufacturing (AM). These models often neglect physical phenomena such as vapor cavity formation and fluid mechanics to reduce computational demands. Instead, volumetric heat source models are used to represent the effects that these phenomena have on the predicted melt pool dimensions. Generally, the dimensions and effective absorption of the volumetric heat source are calibrated to reproduce melt pool dimensions observed in metallographic cross sections taken from single-track experiments on bare plate. However, the transient nature of LPBF often deviates the melt pool dimensions from the assumed steady-state conditions of single-track experiments, motivating the need for a volumetric heat source model that more generally considers the dynamic relationship between melt pool shape and laser-material interactions. Here, we introduce a two-parameter volumetric heat source model that integrates several existing models into a generalized mathematical expression, providing independent control over the radial heat distribution via the parameter k and the volumetric shape of the heat source via the parameter m. This parameterization enables the calibration of melt pool shape predictions through simultaneous adjustment of these parameters, while keeping the radial heat source dimensions consistent with the experimental spot size (D4σ) and constraining the heat source depth and absorption to physically derived expressions for cavities. Consequently, the proposed volumetric heat source model adapts to changes in the local melt pool conditions due to scanning strategy and part geometry by dynamically adjusting the heat source depth and absorption. We demonstrate the capabilities of the proposed model through comparisons with a collection of experiments from the Additive Manufacturing Benchmark (AMBench).

36 MATERIALS SCIENCE↗
DOE OSTI2025

Optimized Illuminance Operation-A Light-Driven Dilution Strategy to Improve Microalgae Biomass Productivity

Periodic dilution is a necessary operation to avoid light limitation due to self-shading as the culture grows dense. However, environmental conditions are constantly changing in outdoor cultivation systems, making it difficult to determine the optimal dilution rate. To address this challenge, this study evaluated a dilution approach based on light penetration to optimize illuminance (OptiLum) in the culture. Biomass concentration was controlled via sensor-feedback directed dilution to ensure that light reaching the bottom of the culture was maintained above the compensation intensity. Under replicated outdoor pond conditions, by keeping the entire culture within a net-positive photosynthetic zone, the OptiLum operation improved the biomass productivities of two top-performing strains, Picochlorum celeri and Tetraselmis striata, by 95 % and 86 %, respectively, compared to conventional semi-continuous batch cultivation. The dilution rate varied daily and was dynamically adjusted based on the light status within the culture, which is concurrently influenced by weather, culture density, and growth rate. The techno-economic analysis showed that the OptiLum operation could reduce biomass production cost by as much as 24 % and 33 % for P. celeri and T. striata, respectively, assuming a low-cost dewatering approach with initial gravity settling of biomass can be realized for both strains. However, a more costly two-stage dewatering strategy, comprising only membranes and centrifuges, may be necessary for non-settling strains, such as P. celeri, which would alternatively increase production costs by 23 % for the OptiLum case. The results demonstrated that the proposed OptiLum operation is a promising approach to improve biomass productivity and lower production cost via weather-responsive and self-adjusting dilution.

09 BIOMASS FUELS↗
DOE OSTI2023

Preliminary verification of the MCNP perturbation and fixed-source tally sensitivity tools

Integral benchmark experiments are vital in the adjustment and validation of the nuclear data that govern predictive simulations across the nuclear community. The nuclear data sensitivity capabilities of the Monte Carlo N-Particle (MCNP ®) transport code are currently limited; however, expanding sensitivity capabilities will allow benchmark experiments to be designed to resolve compensating errors and adjust nuclear data where previously prohibitively difficult. This paper provides details of a preliminary verification for the use of (i.) the recently revised perturbation and (ii.) developmental fixed-source sensitivity tools within MCNP to calculate sensitivities of tallied responses (such as current integrated over a surface, F1, and flux averaged over a cell, F4) to nuclear data in fixed-source simulations. Energy-binned and energy-integrated sensitivities calculated with these tools are compared against sensitivities calculated using a central-difference approximation. Here, the verification is completed for four configurations of a benchmarked system using a 4.5-kg plutonium sphere surrounded by varying amounts of copper and/or polyethylene. The results show that sensitivities calculated with the perturbation and fixed-source sensitivity tools agree with the central-difference-based approach.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Managing the techno-economic impacts of partial string failure in multistring energy storage systems

The role of energy storage systems (ESSs) is becoming increasingly important for today’s electric power systems. Unavailability of an ESS assigned to critical grid services may cause unwanted disruption of those services and hence, may have a significant techno-economic impact. Like any physical equipment, an ESS is vulnerable to various types of faults. Failure of one or more strings in a multistring ESS does not have to be the cause of shutting down the entire ESS. It can still operate with a partial number of strings and continue providing critical services to the grid, if there are no reliability or safety issues and is acceptable under applicable standards. However, it is important to make sure that the control strategies are adaptable to the changes in ESS capacity caused by failed strings. Also, depending on the previous operation and type of failure, the reallocation of duty cycle burden among available strings could be non-uniform. These complexities suggest that mitigation of the impact of partial failure in multistring ESSs is not trivial and needs careful consideration. This is the topic of this paper. The proposed work investigates the impact of partial failure of a large multistring ESS on the assigned service and develops strategies to adjust the ESS control duty cycles for reducing such impacts. In doing so, the paper proposes a novel two-stage framework that plans for the multistring failure using robust optimization theory and then adjusts in real-time using a rule-based algorithm, based on the real-time information on the power availability of the string. Illustrations provided in this work are based on frequency regulation use-case, which is a common application for many utility-scale ESSs. A 750 kilowatt (kW)/1500 kilowatt-hour (kWh) 3-string ESS is used for the demonstration in this work and the efficacy of the proposed method is demonstrated and compared against methods that do not incorporate string failure in their strategy. In particular, here we show that revenue loss of 93% can be incurred when partial string failure is not included in operation and planning. These losses in revenue are reduced by 60% with the proposed method.

25 ENERGY STORAGE↗
DOE OSTI2023

Variable renewable energy deployment in low-emission scenarios: The role of technology cost and value

While rapid deployment of variable renewable energy (VRE) technologies, namely wind and solar PV, is often projected in 2C pathways generated by integrated assessment models, there is a wide range in projected VRE deployment by mid-century. Such differences could be the result of differences in assumptions about future technology costs and/or differences in model approaches for capturing other aspects of technology competitiveness. Here we introduce a consistent competitiveness metric, profitability-adjusted levelized cost of electricity (or PLCOE), to an integrated assessment model (EPPA) to evaluate the representation of technology competition, including VRE, in low-emission scenarios. We show that representing the value of technology (alongside cost) may significantly impact VRE deployment relative to scenarios without such an adjustment. In addition, we show that varying VRE costs by about 35% in 2050 results in differences in VRE deployment that span much of the range in outcomes (over the same period) observed in likely 2C scenarios assessed by the IPCC, suggesting that both cost and value are key drivers of VRE deployment in such scenarios. Given the central role that VRE technologies play in the electricity mix across most scenarios, we also find that alternative cost assumptions for VRE technologies can lead to changes in electricity prices, the associated demand for electricity, and total final and primary energy consumption. However, the demand for fuels other than electricity is relatively insensitive to VRE assumptions in the 2C scenarios considered here.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Electromagnetic wave absorption of multifunctional cementitious composites incorporating polyvinyl alcohol (PVA) fibers and fly ash: Effects of microstructure and hydration

Highlights: • The cementitious composite shows excellent wide-band electromagnetic wave absorption in a frequency range of 2–18 GHz. • The PVA fibers and the fly ash change the dielectric properties of the cementitious composite by Debye polarization. • The iron oxide of the cementitious binders contributes to the magnetic properties of the composites. • The impacts of the microstructure and the hydration of the cementitious composite on its microwave absorption are analyzed. This paper devises a novel method for the adjustment of the pore structure and the hydration of cement to improve the electromagnetic wave absorption of the cementitious composites incorporating polyvinyl alcohol (PVA) fibers and fly ash in a frequency range of 2–18 GHz. The underlying mechanism of the absorption is investigated to explore the possibility of the structural and functional integration of these composites. The electromagnetic parameters of the prepared cementitious composites and those of the raw materials are analyzed in a frequency range of 0.5–18 GHz. Moreover, the pore structure and the chemical environment of the cementitious composites are examined by mercury intrusion porosimetry (MIP), back-scattered electron detector (BSE), and X-ray photoelectron spectroscopy (XPS). The results indicate that the PVA fibers and the high-volume fly ash have a positive effect on electromagnetic wave absorption of the cementitious composites through the adjustment of their pore structure and hydration.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Major element composition controls rare earth element solubility during leaching of coal fly ash and coal by-products

Coal combustion ash and pre-combustion coal refuse are currently under consideration as potential sources of rare earth elements. One of the early steps in recovering REEs from coal by-products is often acid leaching, which can result in low pH leachates with complex aqueous chemistry. The aim of this work was to understand the connection between REE solubility, pH, and major elemental components of leachates for coal by-products. To accomplish this, we investigated the effects of solids concentration (i.e., pulp density) and pH adjustment on REE solubility in acid leachates of coal fly ashes from the Powder River Basin (PRB) and Appalachian Basin in the United States, and a coal processing refuse from the Southwestern U.S. For PRB ashes, the concentrations of soluble REEs generally increased with increasing pulp density; however, at pulp density values above 80–100 g/L, the soluble REE concentrations in the leachates were markedly lower. Similarly, the soluble concentrations of other major solutes (Fe, Al, Si) that leached from PRB fly ashes were also non-linear with pulp density. These major elements tended to reach maximum concentration values at 60–70 g/L pulp density. In contrast, for the Appalachian fly ashes and the coal by-product, soluble concentrations of REE and major elements in leachates increased linearly with pulp density. Chemical equilibria calculations of mineral saturation indices indicated that trends in soluble REE concentrations could be explained by saturation conditions for Fe and Al-(hydr)oxides and possibly sulfate minerals, but not lanthanide hydroxides. Furthermore, pH adjustment of the acid leachates showed that REEs and many major solutes were removed from solution at pH values above 4.5, also consistent with Fe- and Al-(hydr)oxide precipitation. These results highlight the importance of understanding the chemical composition of leachates when designing REE recovery processes for low-grade geologic feedstocks and that precipitation of hydr(oxide) or sulfate minerals of major elements rather than discreet formation of REE mineral phases could be used for process optimization.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2021

Burning velocities of R-32/O 2 /N 2 mixtures: Experimental measurements and development of a validated detailed chemical kinetic model

This work entails characterizing the flammability of the refrigerant R-32 (CH 2 F 2 ) by both experimental measurements and modeling. Burning velocities S u were measured using a constant-volume spherical-flame method for R-32/O2/N 2 mixtures with O 2 /N 2 ratios ranging from 21% (synthetic air) to 40%, pressures of (1 to 3) bar, and equivalence ratios $\phi$ of (0.8 to 1.3). Based on a critical assessment of available data, and extended by our own calculations, a detailed chemical kinetic model was developed and key reactions determined using reaction path and sensitivity analyses. Initiation and combustion were identified as distinct kinetic regimes and burning velocities were found to be controlled by two primary reactions: unimolecular decomposition of CH 2 F 2 → CHF + HF and the subsequent reaction, CHF + O 2 → CHFO + O, the latter reaction initiating the radical chain propagating and branching by producing O atoms. Sensitive rate constants in the kinetic model were critically adjusted within their uncertainties and current knowledge bounds to best fit the experimental burning velocities. We found that rate constants in the model could be adjusted to match a given experimental S u for specific conditions (O 2 loading, P, T, $\phi$). This, however, then fixes predicted burning velocities for other all conditions within (3 to 4)% if physically realistic rate parameters are maintained. Thus, the entire set of experimental data is fit, not just to particular conditions. Relative random uncertainties in the experimental Su measurements were (4 to 6)%, but assumptions made for thermal radiation lost by the burned gas in the spherical-flame experiments add an additional systematic uncertainty. Systematic differences between the limiting cases of adiabatic (no thermal radiation lost) and optically-thin (all thermal radiation lost) varied significantly with conditions and ranged from (4 to 30)% at high to low velocities, respectively, translating into uncertainties of (2 to 15)% considering the average of two limiting cases. Comparison of experimental and kinetically modeled Su values suggests that the burned gas tends towards the optically-thin limit at the lowest pressures and fuel loadings and toward the adiabatic limit at the highest pressures and loadings. We tested and found support for this conclusion with a detailed analysis as a function of all the conditions (T, P, % O 2 , $\phi$). This behavior appears to transition from optically-thin to adiabatic as the density of the initial fuel increases, which results in increased CO 2 in the burned gas and thus increased absorption of the thermal radiation (consistent with the Beer-Lambert Law). The validated detailed model based on evaluated kinetics is shown to accurately predict burning velocities for R-32 O 2 /N 2 mixtures over a wide range of conditions and provides a reliable basis for extrapolation to other conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Frhodo: A program for simulating chemical kinetic measurements and optimizing kinetic mechanisms

Chemical kinetic simulations are frequently used to extract kinetic and mechanistic information from experimental data by fitting simulations to the data. For simple systems of consecutive single channel reactions this is a relatively straightforward task. However, as the complexity of the system increases and particularly for systems involving competitive multi-channel reactions manually optimizing a mechanism to obtain the best fits to a range of experimental data quickly becomes a time-intensive and challenging process, especially when rate coefficients have pressure and temperature dependencies. There is considerable potential for exploiting automated optimization methods to rapidly screen reaction mechanisms and optimize the fit by adjusting rate coefficients within well-defined constraints. A new chemical kinetics simulation program, Frhodo, has been developed for this purpose. The program allows either manual simulation of individual experiments or fully automated optimization against a range of experimental data by adjusting user selected reactions within user defined constraints. Frhodo incorporates machine learning-based optimization routines that work by either minimizing standardized residuals or through Bayesian parameter estimation. Frhodo's optimization capabilities are demonstrated by reexamining two previously studied systems of relevance to combustion. Dissociation of diacetyl followed by recombination of methyl radicals is an example of a sequence of single channel, consecutive reactions. Pyrolysis of 2-methyl furan exemplifies multi-channel, unimolecular reactions that are often encountered and have temperature and pressure dependencies in the rate coefficients of the channels and branching ratios between them. For both systems the optimization routines resulted in solutions similar to the original studies. Finally, comments are made on the strengths and limitations of the approach.

0D simulation↗
DOE OSTI2025

Chemical timescale effects on detonation convergence

Numerical simulations of detonation-containing flows have emerged as crucial tools for designing next- generation power and propulsion devices. As these tools mature, it is important for the combustion community to properly understand and isolate grid resolution effects when simulating detonations. To this end, the objective of this work is to provide a comprehensive analysis of the numerical convergence of unsteady detonation simulations, with focus on isolating the impacts of chemical timescale modifications on convergence characteristics in the context of operator splitting. With the aid of an AMReX-based adaptive mesh refinement flow solver-which enables resolutions up to ($\mathcal{O}$ (1000) cells-per-induction length-the convergence analysis is conducted using two kinetics configurations: (1) the simplified three-step Arrhenius-based model mechanism of Short and Quirk (1997), where chemical timescales in the detonation are modified by adjusting activation energies in the initiation and branching reactions, and (2) a detailed hydrogen- air mechanism, where the chemical timescales are adjusted by varying the ambient pressure. The convergence of unsteady self-sustained detonations in one-dimensional channels is then analyzed with reference to steady-state theoretical baseline solutions using these mechanisms. The goal of the analysis is to provide a detailed comparison of the effects of grid resolution on both macroscopic (peak pressures and wave speeds) and microscopic (wave structure) quantities of interest, drawing connections between the deviations from steady-state baselines and minimum chemical timescales. In particular, chemical timescale reductions were found to have minimal impact on the convergence of macroscopic properties. Furthermore, analyses of microscopic convergence trends, particularly in the reaction front location, revealed a key insight: maintaining the induction time while eliminating prohibitive chemical timescales through mechanism simplifications and combustion modeling can significantly enhance detonation convergence properties. Ultimately, this work uncovers resolution-dependent unsteady detonation convergence regimes and highlights the important role played by not only the chemical timescales, but also the ratio between the chemical timescale and induction time on the numerical convergence of the detonation wave structure.

Adaptive mesh refinement↗
DOE OSTI2025

An open control sequence specification to scale building demand flexibility via analytics software

For over two decades, researchers and practitioners have showcased the ability of large commercial buildings to provide grid services by shedding or shifting load. Various utility demand response (DR) and virtual power plant (VPP) programs throughout the United States are presently utilizing these demand-side resources. However, growth of these programs have been limited, in part due to the high cost necessary to integrate the DR control strategies into the building automation system (BAS). Implementing these strategies involves adjusting control sequences, necessitating dozens of hours of customized programming per building, limiting their adoption to large organizations and progressive owners. Recent efforts by researchers and industry have demonstrated the capability of energy management and information systems (EMIS), originally designed for fault detection and diagnostics, to interface with existing BAS and perform supervisory control to optimize building operations. While these approaches are quickly being adopted by industry, demand flexibility (DF) control strategies remain limited in product offerings. One of the challenges is the lack of documented best-practice DF sequences, despite the rich literature on field implementations. This paper develops a new open-specification for a zone-based temperature adjustment shed strategy for commercial building HVAC systems, describing the specification’s implementation in two EMIS tools in both experimental and field settings. Both implementations successfully reduced electric load by at least 40% on average during the called event, while maintaining temperature limits. This study’s detailed process from specification to deployment shows the potential for scalability as well as highlights challenges related to integration with heterogeneous BAS products.

Granderson, Jessica↗
DOE OSTI2020

Two trillion gallons: Fuel savings from fuel economy improvements to US light-duty vehicles, 1975–2018

Since 1975, the fuel economy of new light-duty vehicles sold in the U.S. has almost doubled. Fuel economy improvements on laboratory tests gradually became real improvements on the road as newer, more efficient vehicles replaced older less efficient ones. Fleet-wide fuel economy gains produced large fuel savings. In this paper, we show that fuel economy gains measured on laboratory test cycles, adjusted for on-road conditions and weighted by the distribution of vehicles by age and their relative use, closely match estimates by the Federal Highway Administration based primarily on traffic counts and motor fuel tax records. Furthermore, adjusting for the rebound effect of fuel economy on vehicle miles traveled, we estimate the fuel savings, CO 2 emissions reductions and dollars saved on fuel due to fuel economy improvements over the past 43 years. Through the end of 2018, estimated cumulative fuel savings amount to approximately 2 trillion gallons of gasoline. We estimate that roughly one-fifth of the savings can be attributed to gasoline price increases over the period and four-fifths to fuel economy and greenhouse gas (ghg) standards.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Incidence of chronic respiratory conditions among oil spill responders: Five years of follow-up in the Deepwater Horizon Oil Spill Coast Guard Cohort study

Background: Over ten years after the Deepwater Horizon (DWH) oil spill, our understanding of long term respiratory health risks associated with oil spill response exposures is limited. Here we conducted a prospective analysis in a cohort of U.S. Coast Guard personnel with universal military healthcare. Methods: For all active duty cohort members (N = 45,193) in the DWH Oil Spill Coast Guard Cohort Study we obtained medical encounter data from October 01, 2007 to September 30, 2015 (i.e., ~2.5 years pre-spill; ~5.5 years post-spill). We used Cox Proportional Hazards regressions to calculate adjusted hazard ratios (aHR), comparing risks for incident respiratory conditions/symptoms (2010–2015) for: responders vs. non-responders; responders reporting crude oil exposure, any inhalation of crude oil vapors, and being in the vicinity of burning crude oil versus responders without those exposures. We also evaluated self-reported crude oil and oil dispersant exposures, combined. Within-responder comparisons were adjusted for age, sex, and smoking. Results: While elevated aHRs for responder/non-responder comparisons were generally weak, within-responder comparisons showed stronger risks with exposure to crude oil. Notably, for responders reporting exposure to crude oil via inhalation, there were elevated risks for all sinusitis (aHR = 1.48; 95%CI, 1.06–2.06), unspecified chronic sinusitis (aHR = 1.55; 95%CI, 1.08–2.22), chronic obstructive pulmonary disease (COPD) and other allied conditions (aHR = 1.43; 95%CI, 1.00–2.06), and dyspnea and respiratory abnormalities (aHR = 1.29; 95%CI, 1.00–1.67); there was a suggestion of elevated risk for diseases classified as asthma and reactive airway diseases (aHR = 1.18; 95%CI, 0.98–1.41), including the specific condition, asthma (aHR = 1.35; 95%CI, 0.80–2.27), the symptom, shortness of breath (aHR = 1.50; 95%CI, 0.89–2.54), and the overall classification of chronic respiratory conditions (aHR = 1.18; 95%CI, 0.98–1.43). Exposure to both crude oil and dispersant was positively associated with elevated risk for shortness of breath (HR = 2.24; 95%CI, 1.09–4.64). Conclusions: Among active duty Coast Guard personnel, oil spill clean-up exposures were associated with moderately increased risk for longer term respiratory conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

A reforecasting-based dynamic reserve estimation for variable renewable generation and demand uncertainty

The installed capacity of renewables-based energy sources has been increasing in traditional power systems. In order to accommodate the increased variability and uncertainty associated with the deeper penetration of renewable sources like solar and wind, adjusted amounts of dynamic reserve are needed. Although probabilistic dynamic reserve estimation methods have been previously developed, most of them consider the uncertainty to be represented by parametric density functions that tend to perform poorly under extreme events and, moreover, neglect uncertainty introduced by the forecasting model itself. Toward addressing these limitations, this work presents, for the first time, a dynamic reserve estimation method for flexibility that incorporates nonparametric density estimation and a machine learning based reforecasting to provide a day-ahead prediction of the mean and spread of uncertainty around the base forecast. The prediction is, in turn, used to estimate the up and down reserve relative to the base forecast. Here, the present method takes various endogenous and exogenous features, including the calendar variables, as input to estimate the day-ahead reserve. Using a combination of reforecasting and dynamic reserve estimation techniques, the method is shown to adjust better to the dynamic nature of reserve requirements providing only what is needed to accommodate the expected deviations. Considering California Independent System Operator (CAISO) solar, wind and load data over an 18 month period, up to 67% reduction in the amount of reserve capacity needed for a one day reserve and reserve penalty for solar uncertainty is demonstrated. Additionally, the risk of reserve insufficiency in meeting the net demand is reduced by 20% with the proposed method.

14 SOLAR ENERGY↗
DOE OSTI2023

Environmental exposure to industrial air pollution is associated with decreased male fertility

Objective: To understand how chronic exposure to industrial air pollution is associated with male fertility through semen parameters. Design: Retrospective cohort study. Subjects: Men in the Subfertility, Health and Assisted Reproduction cohort who underwent a semen analysis 2005-2017 with ≥1 measured semen parameter (N=21,563). Intervention(s): Residential histories for each man were constructed using locations from administrative records linked through the Utah Population Database. Industrial facilities with air emissions of nine endocrine disrupting compound chemical classes were identified from the Environmental Protection Agency Risk-Screening Environmental Indicators microdata. Chemical levels were linked with residential histories for the 5 years prior to each semen analysis. Main Outcome Measures: Semen analyses were classified as azoospermic or oligozoospermic (< 15 M/mL) using World Health Organization cutoffs for concentration. Bulk semen parameters such as concentration, total count, ejaculate volume, total motility, total motile count, and total progressive motile count were also measured. Multivariable regression models with robust standard errors were used to associate exposure quartiles for each of the nine chemical classes with each semen parameter, adjusting for age, race, and ethnicity, as well as neighborhood socioeconomic disadvantage. Results: After adjustment for demographic covariates, several chemical classes were associated with azoospermia and decreased total motility and volume. For exposure in the 4th relative to 1st quartile, significant associations were observed for acrylonitrile (β total motility = -0.87 pp), aromatic hydrocarbons (odds ratio [OR]azoospermia = 1.53; β volume = -0.14 mL), dioxins (OR azoospermia = 1.31; β volume = -0.09 mL; β total motility = -2.65 pp), heavy metals (β total motility = -2.78pp), organic solvents (OR azoospermia = 1.75; β volume = -0.10 mL), organochlorines (OR azoospermia = 2.09; β volume = -0.12 mL), phthalates (OR azoospermia = 1.44; β volume = -0.09 mL; β total motility = -1.21 pp), and silver particles (OR azoospermia = 1.64; β volume = -0.11 mL). All semen parameters significantly decreased with increasing socioeconomic disadvantage. Men who lived in the most disadvantaged areas had concentration, volume, and total motility of 6.70 M/mL, 0.13 mL, and 1.79 pp lower, respectively. Count, motile count, and total progressive motile count all decreased by 30–34 M.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2022

Implications of rootless geothermal models: Missing processes, parameter compensation, and imposter convection

Numerical models of geothermal systems commonly capture only the top of a reservoir. Deeper areas of the reservoir are simplified to a boundary at the base of the model domain. Commonly, the basal boundary is given either a heat source or a source of mass and enthalpy. Here we developed and present simple numerical experiments which demonstrate that these approaches do not produce the correct model behavior in comparison to a model that captures the entire convecting domain with a heat flux only. We describe a variety of incorrect types of model behavior that arise directly from the choice of boundary condition, independent of the specific parameterization of the model. Heat sources are sensitive to the thickness of the domain and parameters take unphysical values to compensate for the reduced height. The combined mass/heat boundary can produce temperatures that show similarities to circulating geothermal systems, but with incorrect fluid flow and a strong boundary layer focused at the base of the simulated clay cap. These errors likely cause parameters to adjust their values to compensate for the incorrect physics. We highlight these issues and show an example from a developed reservoir model. Initial calibrations to natural state temperature were unsuitable for history matching. The 3D model required parameter adjustments to achieve a more realistic production model. Appropriate mitigation measures should be considered to reduce parameter compensation and improve decision-support models.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Removal of impurity Metals as Phosphates from Lithium-ion Battery leachates

Recovery of critical materials from end-of life (EOL) lithium-ion batteries (LIB) is gaining interest as demands for materials grows. Hydrometallurgical processes start with an intermediate product known as black mass which contains critical materials of interest (Co, Ni, Li, and graphite) as well as impurities such as Cu, Al, and Fe. These impurities are deleterious to downstream separation processes, as well as impact functionality of the final products. Here, these impurities effectively compete with most solvent extraction (SX) and metal recovery processes to diminish the overall yields of the desired materials. In this work, a process flowsheet is presented where a previously reported electrochemical leaching (ECL) process is followed by selective precipitation using diammonium hydrogen phosphate (DAP) to remove Cu, Al, and Fe from LIB leachate solutions. The electrochemical leach process removes Cu and produces a pH-adjusted leachate, ca. pH 2, without requiring an extra Cu extraction step. The addition of the precipitant DAP to leachate by slightly adjusting the pH to 3–4 at 45 °C, precipitates 95–99% of Al and Fe as their phosphates and the leachate retains >95% of Co, Ni and Li. After the filtration of phosphate impurities, the solution is ready for further processing, such as SX. As an unexpected result from the leachate processing, 20–30% of the Ni and Co co-crystalize as the double salt after cooling to room temperature, which could provide a shorter route to their recovery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗