Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “TANKS”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 901 records · Page 50
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Opportunities and data requirements for data-driven prognostics and health management in liquid hydrogen storage systems

During the past decade, Prognostics and Health Management (PHM) has become an important set of tools in various areas of industry and academic reliability engineering. PHM consists of a variety of mathematical and computational methods used to support data-driven decision-making to increase the safety, availability, and reliability of complex engineering systems. In particular, PHM can provide crucial insight into reliability and safety design improvements for developing technologies where historical performance and failure data are limited. This is the case of hydrogen fueling and storage technologies. This work presents a high-level approach for designing data-driven PHM applications for bulk liquid hydrogen (LH 2 ) storage systems for hydrogen fueling stations. This paper addresses core aspects of the design, development, and implementation of data-driven PHM applications that can improve the reliability assessment of hydrogen components. The analysis focuses on the relationship between data availability and diagnostic/prognostic capabilities; potential challenges; and integration schemes for current risk mitigation measures. We identify potential condition-monitoring data sources for key components in an LH 2 storage system, including storage tanks, piping, and pumps. Further, we determine that the short-term goals for the implementation of data-driven models in PHM frameworks in hydrogen systems should focus on developing adequate data collection and analysis strategies, as well as exploring the effect on reliability, safety, and regulations for hydrogen systems.

08 HYDROGEN↗
DOE OSTI2022

Capacity Assessment and Cost Analysis of Geologic Storage of Hydrogen: A Case Study in Intermountain-West Region USA

Hydrogen is an integral component of the current energy transition roadmap to decarbonize the economy and create an environmentally-sustainable future. However, surface storage options (e.g., tanks) do not provide the required capacity or durability to deploy a regional or nationwide hydrogen economy. In this study, we have analyzed the techno-economic feasibility of the geologic storage of hydrogen in depleted gas reservoirs, salt caverns, and saline aquifers in the Intermountain-West (I-WEST) region. We have identified the most favorable candidate sites for hydrogen storage and estimated the volumetric storage capacity. Our results show that the geologic storage of hydrogen can provide at least 72% of total energy consumption of the I-WEST region in 2020. We also calculated the capital and levelized costs of each storage option. We found that a depleted gas reservoir is the most cost-effective candidate among the three geologic storage options. Interestingly, the cushion gas type plays a significant role in the storage cost when we consider hydrogen storage in saline aquifers. The levelized costs of hydrogen storage in depleted gas reservoirs, salt caverns, and saline aquifers with large-scale storage capacity are approximately $\$$1.15, $\$$2.50, and $\$$3.27 per kg of H 2 , respectively. Here, this work provides essential guidance for the geologic hydrogen storage in the I-WEST region.

08 HYDROGEN↗
DOE OSTI2022

An arbitrary Lagrange-Eulerian investigation of HRAM shallow jet pre-spurt formation and time sensitivities to impact plate dynamics

With dry bay fires persisting as a significant contributor to aircraft vulnerability despite chronicled developments in survivability technologies, an accurate fire prediction capability remains paramount for credible vulnerability assessments. Physics based modeling of the hydrodynamic ram (HRAM) fluid deposition process is a key component of such capability, wherein capturing the first instance of fluid spurt, referred to herein as shallow jet spurts, is a core focus. Such pre-spurts as they have been formerly identified have only been witnessed sporadically in HRAM spurt experiments. In this work, ALE3D, a first-principles multi-physics code was employed to model the shallow jet spurt phenomenon with spherical projectiles impacting water-filled tanks faced with aluminum panels, such that the underlying physics and sensitivities could be explored. Development and verification of the 2D axisymmetric model is described relative to trends observed in a prior experimental campaign. Results from the verified model suggest shallow jet spurts have at least a quadratic sensitivity to the fundamental vibrational mode of the impact plate across impact velocities 610–1829 m/s (2000–6000 ft/s). It is further explained how shallow jet spurts are arrested for impacts at the two extremes of plate rigidity. This research constitutes the first fluid-structure modeling of shallow jet spurts which future three-dimensional analyses will expound upon.

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

Estimating biofuel contaminant concentration from 4D ERT with mixing models

Here, we present the results of a lab-scaled feasibility study to assess the performance of electrical resistivity tomography for detection, characterization, and monitoring of fuel grade ethanol releases to the subsurface. Further, we attempt to determine the concentration distribution of the ethanol from the electrical resistivity tomography data using mixing-models. Ethanol is a renewable fuel source as well as an oxygenate fuel additive currently used to replace the known carcinogen methyl tert-butyl ether; however, ethanol is preferentially biodegraded and a cosolvent. When introduced to areas previously impacted by nonethanol-based fuels, it will facilitate the persistence of carcinogenic fuel compounds like benzene and ethylbenzene, as well as remobilize them to the ground water. These compounds would otherwise be retained in the soil column undergoing active or passive remediation processes such as soil vapor extraction or natural attenuation. Here, we introduce ethanol to a saturated Ottawa sand in a tank instrumented for four-dimensional geoelectrical measurements. Forward model results suggest pure phase ethanol released into a water saturated silica sand should present a detectable target for electrical resistivity tomography relative to a saturated silica sand only. We observe the introduction of ethanol to the closed hydraulic system and subsequent migration over the duration of the experiment. One-dimensional and three–dimensional temporal data are assessed for the detection, characterization, and monitoring of the ethanol release. Results suggest one-dimensional geoelectrical measurements may be useful for monitoring a release, while three-dimensional geoelectrical field imaging would be useful to characterize, monitor, and design effective remediation approaches for an ethanol release, assuming field conditions do not preclude the application of geoelectrical methods. We then attempt to use predictive mixing models to calculate the distribution of ethanol concentration within the measurement domain. For this study we examine four different models: a nested parallel mixing model, a nested cubic mixing model, the complex refractive index model (CRIM), and the Lichtenecker-Rother (L-R) model. The L-R model, modified to include an electrical formation factor geometry term, provided the best agreement with expected EtOH concentrations.

09 BIOMASS FUELS↗
DOE OSTI2024

Polynomial chaos expansions on principal geodesic Grassmannian submanifolds for surrogate modeling and uncertainty quantification

In this work we introduce a manifold learning-based surrogate modeling framework for uncertainty quantification in high-dimensional stochastic systems. Our first goal is to perform data mining on the available simulation data to identify a set of low-dimensional (latent) descriptors that efficiently parameterize the response of the high-dimensional computational model. To this end, we employ Principal Geodesic Analysis on the Grassmann manifold of the response to identify a set of disjoint principal geodesic submanifolds, of possibly different dimension, that captures the variation in the data. Since operations on the Grassmann require the data to be concentrated, we propose an adaptive algorithm based on Riemannian K-means and the minimization of the sample Fréchet variance on the Grassmann manifold to identify “local” principal geodesic submanifolds that represent different system behavior across the parameter space. Polynomial chaos expansion is then used to construct a mapping between the random input parameters and the projection of the response on these local principal geodesic submanifolds. Here, the method is demonstrated on four test cases, a toy-example that involves points on a hypersphere, a Lotka-Volterra dynamical system, a continuous-flow stirred-tank chemical reactor system, and a two-dimensional Rayleigh-Bénard convection problem.

42 ENGINEERING↗
DOE OSTI2020

Impact of zero valent iron aging on reductive removal of technetium-99

Zero valent iron (ZVI) is a promising material for reductive removal of technetium from industrial waste streams. An example application of this method could be to treatment of low activity aqueous waste that is currently stored in tanks at the Hanford site. However, there is still a lack of understanding of the useful lifetime of ZVI for treatment and the changes in reductive removal of Tc over time. In this research, we studied the reductive removal of Tc from aqueous solutions by ZVI aged with up to 30 days by contact with 0.08 M NaCl solutions. These results show that ZVI could be used to remove Tc(VII) from aqueous solutions by its reduction to the less soluble and relatively immobile Tc(IV) with greater than 99% removal in three hours. Still, greater than 90% of Tc is removed with ZVI aging up to one week. However, after 10 days of aging of zero valent iron, a significant decrease in removal of Tc occurs (55% removal at three hours) followed by negligible removal after aging for two weeks or more which is consistent with formation of iron oxides on the surface. Further, these results correlate with XRD and FTIR analysis showing an increase in magnetite followed by maghemite and goethite with aging time.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Unveiling the parasitic-reaction-driven surface reconstruction in Ni-rich cathode and the electrochemical role of Li 2 CO 3

Nickel-rich transition-metal oxides are widely regarded as promising cathode materials for high-energy-density lithium-ion batteries for emerging electric vehicles. However, achieving high energy density in Ni-rich cathodes is accompanied by substantial safety and cycle-life obstacles. The major issues of Ni-rich cathodes at high working potentials are originated from the unstable cathode-electrolyte interface, while the underlying mechanism of parasitic reactions towards surface reconstructions of cathode materials is not well understood. In this work, we controlled the Li 2 CO 3 impurity content on LiNi 0.83 Mn 0.1 Co 0.07 O 2 cathodes using air, tank-air, and O 2 synthesis environments. Home-built high-precision leakage current and on-line electrochemical mass spectroscopy experiments verify that Li 2 CO 3 impurity is a significant promoter of parasitic reactions on Ni-rich cathodes. The rate of parasitic reactions is strongly correlated to Li 2 CO 3 content and severe performance deterioration of Ni83 cathodes. The post-mortem characterizations via high-resolution transition electron microscope and X-ray photoelectron spectroscopy depth profiles reveal that parasitic reactions promote more Ni reduction and O deficiency and even rock-salt phase transformation at the surface of cathode materials. Here, our observation suggests that surface reconstructions have a strong affiliation to parasitic reactions that create chemically acidic environment to etch away the lattice oxygen and offer the electrical charge to reduce the valence state of transition metal. Thus, this study advances our understanding on surface reconstructions of Ni-rich cathodes and prepares us for searching for rational strategies.

36 MATERIALS SCIENCE↗
DOE OSTI2023

The influence of water, diet, and temperature on 87 Sr/ 86 Sr in fin spines of juvenile Atlantic Sturgeon Acipenser oxyrinchus oxyrinchus

Analysis of microchemistry in fish fin spines offers a non-lethal approach to address key questions relating to spatial patterns and habitat use of fish. Reconstruction of life history is based on chemical changes within calcified structures with an underlying assumption of elemental incorporation relative to environmental concentration. However, information is limited on the relative influence of water and diet concentrations of elements to corresponding concentrations within fin spines. Strontium (Sr) is commonly used in trace element studies because of its predictable changes within watersheds, with recent applications showing utility of 87 Sr/ 86 Sr for greater spatial resolution. Therefore, this study evaluated the influence of water and diet 87 Sr/ 86 Sr on pectoral fin spines of Atlantic Sturgeon A. oxyrinchus oxyrinchus in controlled laboratory experiments. In the first experiment, fish were exposed to a control, water spiked with 0.10 mg/L of 87 Sr or diet spiked with 0.25 µg/g or 0.50 µg/g of 87 Sr in replicated tanks for 12 weeks. In a second experiment, to determine the time duration required to occupy a different environment for fin spine chemistry to change, fish were maintained in water- or diet-spiked treatments for 1, 2, 3, or 6 weeks. Additionally, to determine if temperature has an influence on 87 Sr/ 86 Sr in fin spines, fish were held at 15 and 25°C for 12 weeks. Fin spines were analyzed using laser ablation multi-collector inductively coupled plasma mass spectrometry (LA-MC-ICP-MS), and water and diet samples were analyzed using solution based ICP-MS. Results from Experiment 1 indicate water is the primary contributor and diet a secondary contributor of 87 Sr/ 86 Sr in pectoral fin spines of Atlantic Sturgeon. Results from Experiment 2 indicate fin spine 87 Sr/ 86 Sr can be influenced by water after 1 week and diet after 12 weeks. Additionally, although sample size was limited (n=3), water temperature did not have an effect on 87 Sr/ 86 Sr fin spine chemistry. In conclusion, these results provide guidance for interpretation of 87 Sr/ 86 Sr in pectoral fin spines of sturgeon and indicate usefulness of the technique for retrospectively estimating movement and habitat use.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Background Concentrations of Argon-39 in Shallow Soil Gas

While radioisotopes of noble gases are known to be indicators of underground nuclear explosions (UNE), McIntyre et al. (2017) was the first to report the presence of 39Ar in shallow soil gas in association with a decades old UNE. While this finding hinted at the potential application of 39Ar to be used as an indicator of an UNE, doing so would also require an understanding of the natural concentrations of 39Ar present in soil gas. Without knowing the expected range and variability of naturally occurring concentrations of 39Ar, it is difficult to determine what measured concentrations would be indicative of an elevated concentration. This paper presents results from 16 soil gas samples and three atmospheric air samples collected from various locations across the western United States. Shallow soil gas samples were collected into self-contained underwater breathing apparatus (SCUBA) tanks using a custom-built soil gas sampling system and then processed and analyzed for 39Ar. The measured concentrations of 39Ar varied from atmospheric air concentrations to about 3.5 times atmospheric air concentrations. The variation in concentration was primarily attributed to the latitude the sample was collected at, which was consistent with previous work (Johnson et al. 2015). The results presented here represent the first measurements of natural background 39Ar concentrations in shallow soil gas. This data will be necessary if 39Ar is to be used as an indicator of UNE.

Fritz, Brad G.↗
DOE OSTI2023

Prevalence of Listeria monocytogenes , Salmonella spp., Shiga toxin-producing Escherichia coli , and Campylobacter spp. in raw milk in the United States between 2000 and 2019: A systematic review and meta-analysis

Raw (unpasteurized) milk is available for sale and direct human consumption within some states in the United States (US); it cannot be sold or distributed in interstate commerce. Raw milk may contain pathogenic microorganisms that, when consumed, may cause illness and sometimes may result in death. No comprehensive review for prevalence and levels of the major bacterial pathogens in raw milk in the US exists. The objective of the present research was to systematically review the scientific literature published from 2000 to 2019 to estimate the prevalence and levels of Listeria monocytogenes, Salmonella spp., Shiga toxin-producing Escherichia coli (STEC), and Campylobacter spp. in raw milk in the US. Peer-reviewed studies were retrieved systematically from PubMed®, Embase®, and Web of ScienceTM. The unique complete nonduplicate references were uploaded into the Health Assessment Work Collaborative (HAWC). Based on the selection criteria, twenty studies were included in the systematic review and meta-analysis. Comprehensive Meta-Analysis (CMA) was used for statistical analyses, specifically, random effects meta-analyses were used to synthesize raw bulk tank milk (BTM) and milk filters (MF) data. Data from studies using culture and non–culture-based detection methods were included. Forest plots generated in CMA (Biostat, Englewood, NJ) were used to visualize the results. The average prevalence (event rate) of L. monocytogenes, Salmonella spp., STEC, and Campylobacter spp. in raw BTM in the US was estimated at 4.3% (95% confidence intervals [CIs], 2.8–6.5%), 3.6% (95% CIs, 2.0–6.2%), 4.3% (95% CIs, 2.4–7.4%), and 6.0% (95% CIs, 3.2–10.9%), respectively. Estimated prevalence was generally larger in MF than in BTM. There was not enough data to perform a meta-analysis for the prevalence or levels of pathogens in raw milk from retail establishments or other milk categories.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

n-Butanol or isobutanol as a value-added fuel additive to inhibit microbial degradation of stored gasoline

Biofouling of gasoline can occur during fuel storage caused by bacteria and fungi that form a biofilm at a fuel/water interface and that produce organic acids and sulfides. Fuel additives are applied to gasoline to prevent biofouling but are relatively expensive, are not always effective against biofilms, and do not contribute to the combustibility of gasoline. Bio-isobutanol is an approved, certified advanced biofuel and is added up to 16% ( v/v ) in gasoline blends “iBut16”; n-butanol blends are currently under review. Microorganisms are inhibited by n-butanol or isobutanol when the aqueous concentration reaches >2-3% (w/ v ). We determined that n-butanol partitions into the aqueous phase of a model gasoline/water system reaching concentrations of 42 g/L and up to 48 g/L from gasoline blends at 10% and 24% ( v/v ), respectively. Likewise, isobutanol blended in gasoline at 10% and 24% ( v/v ) partitioned into an aqueous phase at 45 g/L and 53 g/L, respectively. Several bacterial and fungal strains that originate from fuel storage tanks, or are known to be solvent tolerant, were evaluated for their potential growth in a range of n- and isobutanol concentrations. Growth rates for all strains tested were reduced by 40–100% relative to untreated controls in n- and isobutanol concentrations of 1.5 and 2.0% ( v/v ). No observable growth occurred for any of the microorganisms in solvent concentrations at 3.0% ( v/v ). T amphiphilic and chaotropic properties of n- or isobutanol help them inhibit microbial growth and could serve as effective biocides during fuel storage as well as being valuable fuel additives.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Glass Design Using Machine Learning Property Models with Prediction Uncertainties: Nuclear Waste Glass Formulation

The United States Department of Energy is responsible for managing the legacy nuclear waste stored in underground tanks at the Hanford Site. The waste will be separately vitrified as low-activity waste and high-level waste fractions. Waste glass formulation algorithms have been traditionally developed using partial quadratic mixture property-composition models. Recently, machine learning (ML) techniques have been used to predict glass properties and discover new glass materials for nuclear waste vitrification, and these advancements can be utilized to improve waste glass composition design. In this proof-of-principle study, ML algorithms such as Gaussian process regression (GPR) were used to interpolate glass properties (e.g., viscosity, electrical conductivity, chemical durability). After selecting appropriate sets of GPR hyper-parameters for each property, an optimization program was developed to formulate glass compositions to maximize waste loading while simultaneously satisfying property within constraints. The results of the ML-based waste loadings and glass compositions were compared to those obtained using the traditional methods. Comparing to the previous glass design framework, the ML-based optimization methods offer improved glass designs and a streamlined approach to generation of optimally designed data and near real-time updates.

glass formulation, machine learning, constraints, ↗
DOE OSTI2026

Low Activity Waste Glass Optimization with Property Models from Machine Learning, Part 2: Experimental Validation and Active Learning

The United States Department of Energy is responsible for managing legacy nuclear waste stored in underground tanks at the Hanford Site. To treat the waste, it is planned as the current baseline to separately vitrify low-activity waste (LAW) and high-level waste fractions. Previously, machine learning (ML) based glass property models (e.g., chemical durability, viscosity, electrical conductivity and SO3 solubility) were developed with prediction uncertainties. A waste glass optimization approach was then established to enable the capability of using these ML models in LAW glass formulation. In this study, the previous ML models were first experimentally validated, and the results were incorporated back into the database to update the ML models. The updated models and formulations showed increased waste loading while reducing the failure rate, demonstrating improved predictive accuracy, reduced uncertainties, and the effectiveness of active learning in guiding high-dimensional, nonlinear LAW glass design. This represents the first experimental validation of ML based LAW glass formulation, with practical benefits such as higher waste loading, shorter mission duration, and lower operational risk.

Lu, Xiaonan (ORCID:0000000179708148)↗
DOE OSTI2020

LiNi x Fe y Al z O 2 , a new cobalt-free layered cathode material for advanced Li-ion batteries

Recently, rapid fluctuations in cobalt prices have created a worsening supply chain constraint that has become a serious cause of concern amidst global battery manufacturers. To address this challenge, we report herein a new class of cobalt-free, nickel-rich layered cathode material termed the NFA class with general formula LiNi x Fe y Al z O 2 (x + y + z = 1). Using co-precipitation reaction in a continuous stirred tank reactor, we synthesized NFA(OH) 2 precursors with the constituent Ni, Fe and Al elements successfully incorporated. The obtained LiNFAO 2 cathode was characterized using X-Ray diffraction, Mössbauer spectroscopy and scanning electron microscopy. Electrochemical behavior was assessed using cyclic voltammetry, galvanostatic charge/discharge, electrochemical impedance spectroscopy and galvanostatic intermittent titration technique at various states of lithiation/delithiation. Electrochemical performance evaluations revealed that our cobalt-free material delivers high capacity of 190 mAh/g at 0.1C. Rate and cycling performance evaluations also indicated good rate capability and cycling stability with 88% capacity retention after 100 cycles at C/3. Using NFA cathodes, we also fabricated a 0.5Ah (C/3) cobalt-free Li-ion battery which demonstrated reasonable cycling stability with ~72% capacity retained after 200 cycles. Overall, our work demonstrates the immense potential of the cobalt-free NFA class cathodes as viable candidates towards development of next generation cost effective lithium ion batteries.

25 ENERGY STORAGE↗
DOE OSTI2025

On optimal control of hybrid dynamical systems using complementarity constraints

Optimal control for switch-based dynamical systems is a challenging problem in the process control literature. In this study, we model these systems as hybrid dynamical systems with finite number of unknown switching points and reformulate them using non-smooth and non-convex complementarity constraints as a mathematical program with complementarity constraints (MPCC). We utilize a moving finite element based strategy to discretize the differential equation system to accurately locate the unknown switching points at the finite element boundary and achieve high-order accuracy at intermediate non-collocation points. We propose a globalization approach to solve the discretized MPCC problem using a mixed NLP/MILP-based strategy to converge to a non-spurious first-order optimal solution. The method is tested on three dynamic optimization examples, including a gas–liquid tank model and an optimal control problem with a sliding mode solution.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Critical roles of pores and moisture in sustainable nanocellulose-based super-thermal insulators

In a recent report in Matter, Bergström and co-workers describe a novel thermal transport behavior that subverts this assumption of porous materials. In their work, the authors describe a nanocellulose-based foam that features ultrahigh porosity (> 99.6%) and aligned µm-scale pores (10–100 µm) whose radial thermal conductivity (i.e., perpendicular to the pore alignment) is close to that of free air in the dry state. Furthermore, the radial thermal conductivity of the cellulose-based foam can be reduced to ~14 mW/(m·K) when the relative humidity is ~35%. Super-thermal insulators, which demonstrate a thermal conductivity below that of stationary air (~ 25 mW/(m·K), 20 ºC, 1.0 atm), are needed to minimize heat loss in various applications (e.g., buildings, thermal energy storage tanks, cold chain packaging, etc.) to mitigate the energy crisis and reduce carbon emissions. Introducing pores into a material is a facile and effective way to achieve low thermal conductivity as pores can suppress thermal transport through solids by reducing the cross-sectional area and increasing the tortuosity of the heat transfer pathway. In porous structures there are two kinds of pores: open and closed. While increased porosity can reduce heat conduction through solids with an open porous structure, the improved gas conduction creates a competing effect that simultaneously elevates the heat transfer. Therefore, the thermal conductivity of a material with µm-scale open pores is usually larger than that of stationary air. Reducing the pore size to less than the mean free path of air (~ 70 nm, 20 ºC, 1.0 atm) can effectively reduce gas conduction, enabling the material to achieve a thermal conductivity below that of stationary air. However, high cost of the nanosized raw materials and time-consuming fabrication processes limit the large-scale applications of nanoporous thermal insulators. Meanwhile, closed pores can block heat transport only through the continuous gas phase. As a result, the thermal conductivity of a closed porous structure can theoretically be much smaller than that of stationary air if the solid conduction can also be suppressed by (1) lowering the solid content of the material, (2) reducing the thermal conductivity of the building blocks of the material, and/or (3) increasing interfacial thermal resistance between neighboring building blocks. Most processes used to generate porous structures (e.g., supercritical drying, freeze drying) involve a solvent that escapes the material. Therefore, it is difficult to create pores and isolate them simultaneously, preventing the fabrication of super-thermal insulators with closed pores.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Air-stable, earth-abundant molten chlorides and corrosion-resistant containment for chemically-robust, high-temperature thermal energy storage for concentrated solar power

A dramatic reduction in man-made CO 2 emissions could be achieved if the cost of electricity generated from concentrated solar power (CSP) plants could become competitive with fossil-fuel-derived electricity. The solar heat-to-electricity conversion efficiency of CSP plants may be significantly increased (and the associated electricity cost decreased) by operating CSP turbines with inlet temperatures ≥750 °C instead of ≤550 °C, and by using thermal energy storage (TES) at ≥750 °C to allow for rapidly dispatchable and/or continuous electricity production. Unfortunately, earth-abundant MgCl 2 -KCl-based liquids currently being considered as low-cost media for large-scale, high-temperature TES are susceptible to oxidation in ambient air, with associated undesired changes in liquid composition and enhanced corrosion of metal alloys in pipes and tanks containing such liquids. In this paper, alternative high-temperature, earth-abundant molten chlorides that are resistant to oxidation in ambient air are identified via thermodynamic calculations. Here, the oxidation resistance, and corrosion-resistant containment, of such molten chlorides at 750 °C are then demonstrated. Such an air-tolerant strategy, involving chemically-robust, low-cost TES media paired with effective containment materials, provides a critical advance towards the higher-temperature operation of, and lower-cost electricity generation from, CSP plants.

14 SOLAR ENERGY↗
DOE OSTI2022

An implantable biomechanical energy harvester for animal monitoring devices

Insufficient service life and the resulting need for battery replacements have been a great challenge for implantable electronic devices. This is particularly true for animal tracking applications, because recapturing animals is often unlikely once they are released to the wild. To tackle this problem, we developed a biomechanical energy harvester that uses a Macro Fiber Composite™ (MFC) piezoelectric beam to harvest the mechanical energy from animals’ body bending movements as the power source for implantable and wearable devices. Prototypes of an underwater acoustic transmitter using this technology were subdermally implanted into juvenile white sturgeon and their energy harvesting performance was evaluated through the device’s transmissions. Additionally, the fish successfully recovered from the implantation surgery and freely swam inside a tank. The transmitter prototypes in the fish continually transmitted signals for a period up to 5 weeks. A benchtop test setup was also created to emulate the fish’s body bending, estimate the device’s energy harvesting performance in the live fish, and perform accelerated fatigue testing of the energy harvester by applying test parameters learned from a video study of the fish’s body movement and behavior characteristics. The gradual depolarization of the piezoelectric ceramic material in the MFC under cyclic mechanical loading was the main limiting factor for the life span of the energy harvester. Pathways for improvement are proposed to achieve long-term efficacy of powering implantable and wearable electronic devices.

42 ENGINEERING↗