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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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At least 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Tracking Flows of End-of-Life Battery Materials and Manufacturing Scrap

This paper defines terms such as “recycling rate” that enable the characterization of flows of battery materials and expands the terminology to accommodate the description of complex product recycling. It also estimates the maximum percentage of U.S. demand for critical elements that could be satisfied by recycling as demand continues to grow, and it defines and estimates the recycling rate for lithium-ion batteries. Finally, it clarifies the role of manufacturing scrap as the domestic U.S. supply chain is built up. It concludes that recycling will be important in the long term, but growth still requires that new material be extracted to supply additional material.

25 ENERGY STORAGE↗
DOE OSTI2020

Mass Balance Accounting for CO 2 Storage with Enhanced Oil Recovery in Northern Michigan

The Midwest Regional Carbon Sequestration Partnership (MRCSP) was founded in 2003 as part of the U.S. Department of Energy’s (DOE’s) Regional Carbon Sequestration Partnership initiative. Since its founding, MRCSP has made significant strides toward making CCUS a viable option for states in the region. The public/private consortium, funded through the DOE Regional Carbon Sequestration Initiative, brings together nearly 40 industry partners and 10 states. Battelle, as the project lead, oversees research, development and operations and coordinates activities among the partners. The incremental, phased approach has built a valuable knowledge base for the industry and paved the way for commercial-scale adoption of CCUS technologies. From 2008 to 2020, MRCSP Phase III focused on the development of large-scale injection projects. This report is part of a series of reports prepared under the Midwestern Regional Carbon Sequestration Partnership (MRCSP) Phase III (Development Phase). These reports summarize and detail the findings of the work conducted under the Phase III project. MRCSP monitoring efforts began in February 2013, with an overarching goal of monitoring at least 1 million metric tons (MT) of net CO 2 stored at a CO 2 -EOR complex in northern Michigan. This report highlights the mass balance accounting of injection, production and recycling activities at ten CO 2 -EOR reefs. The reefs that were monitored for CO 2 -EOR operations include a late-stage depleted reef, eight active CO 2 -EOR reefs and two new reefs added to the CO 2 -EOR complex where a CO 2 flood was initiated.

, production↗
DOE OSTI2022

GEN3D Experimental and Numerical Development of GEN3 Durability Models

Understanding of the high temperature durability of particles and the materials that contain them is critical to next generation of concentrating solar power (CSP) technology. Here we studied the durability of particles and their containment materials under extreme UV cycling, thermal cycling, and in low-speed high temperature mechanical wear situations. The optical stability of seven candidate particles has been determined following exposure to the high temperature conditions present in a generation 3 particle-based CSP technology. Particle solar weighted absorptance and emittance measured periodically during 10,000 high solar irradiance exposure cycles and up to 400 hours of isothermal aging has been documented. The particle aging due to repeated exposure to concentrated solar flux represented the 30-year lifetime of a power plant. Models were fit to the absorptivity and emissivity data following the isothermal aging provides the projected optical degradation of the particles as a function of temperature. Mechanical wear was studied through the use of custom developed wear testing facilities for measuring high temperature impact wear, abrasion wear, and particle attrition. Additionally, a novel technique for measuring the high temperature mechanical properties of single particles was developed. Through these tests it was observed that high nickel alloys generally showed lower wear than comparable iron based steels, particularly at elevated temperatures of 800°C. Mechanical wear at these temperatures is a highly complex phenomenon combining both mechanical wear and oxidation. Additionally, the containment materials wear rates are influenced by the particles (both hardness and roundness), making the wear mechanisms complex. The initial wear test conducted in the abrasion test rig revealed a substantial amount of oxide materials in the particle bed after testing (in relative to later tests), and substantially more wear, likely indicating a need for concern in startup operation of particle facilities to not incur high wear from the presence of oxides. Particle attrition experiments have only been conducted for a single material but increase size distribution, reduction in circularity, and particle diameter is observed. Efforts to develop predictive models was limited due to a testing campaign that prioritized testing materials for particle pathway developers over building a comprehensive design of experiments. The results discussed in this report inform future CSP developers and researchers further de risking the technology and assisting in its future development. ParticleBased CSP development provides a path to dispatchable solar power generation with storage at a price competitive in the current energy market. Lowering the cost of CSP technology provides a carbon free power generation solution that can assist in the transition from fossil fuels to renewable sources of electricity.

14 SOLAR ENERGY↗
DOE OSTI2020

Transuranic Waste Volume Reduction Methods for Los Alamos National Laboratory

Los Alamos National Laboratory (LANL, or the Lab) is one of the United States’ (U.S.) weapons complex nuclear security laboratories; it is owned by the Department of Energy (DOE) and operated by Triad National Security, LLC. LANL’s mission is to solve national security challenges through scientific excellence, which includes nuclear deterrence and stockpile stewardship. Such activities generate a variety of radioactive waste types, including transuranic (TRU) waste. The National Nuclear Security Administration (NNSA) is under a congressional mandate to produce no fewer than 80 plutonium pits per year by 2030 to meet Department of Defense requirements and support the nuclear deterrent. LANL is responsible for producing at least 30 pits per year by 2026, while the Savannah River Site will produce 50 pits per year by 2030. As of August 2018, the NNSA TRU waste inventory at LANL was at 53% capacity. In order to ensure the nuclear material missions are able to continue uninterrupted, the storage of TRU waste needs to remain below 60% of total capacity. As LANL increases production and prepares to meet the 30 pits per year goal, waste generation will increase substantially. Thus, there is a need to rejuvenate current infrastructure and implement TRU waste reduction methods in the coming years.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Investigating User Experiences with Data Abstractions on High Performance Computing Systems

Scientific exploration generates expanding volumes of data that commonly require High Performance Computing (HPC) systems to facilitate research. HPC systems are complex ecosystems of hardware and software that frequently are not user friendly. The Usable Data Abstractions (UDA) project set out to build usable software for scientific workflows in HPC environments by undertaking multiple rounds of qualitative user research. Qualitative research investigates how individuals accomplish their work and our interview-based study surfaced a variety of insights about the experiences of working in and with HPC ecosystems. This report examines multiple facets to the experiences of scientists and developers using and supporting HPC systems. We discuss how stakeholders grasp the design and configuration of these systems, the impacts of abstraction layers on their ability to successfully do work, and the varied perceptions of time that shape this work. Examining the adoption of the Cori HPC at NERSC we explore the anticipations and lived experiences of users interacting with this system’s novel storage feature, the Burst Buffer. We present lessons learned from across these insights to illustrate just some of the challenges HPC facilities and their stakeholders need to account for when procuring and supporting these essential scientific resources to ensure their usability and utility to a variety of scientific practices.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Impacts of vacancy-induced polarization and distortion on diffusion in Solid Electrolyte Li 3 OCl

We report that Lithium-rich oxychloride antiperovskites are promising solid electrolytes for enabling next-generation batteries. Here, we report a comprehensive study varying Li + concentrations in Li 3 OCl using ab initio molecular dynamics simulations. The simulations accurately capture the complex interactions between Li + vacancies (V$^'_{Li}$), the dominant mobile species in Li 3 OCl. The V$^'_{Li}$ polarize and distort the host lattice, inducing additional non-vacancy-mediated diffusion mechanisms and correlated diffusion events that reduce the activation energy barrier at concentrations as low as 1.5% V$^'_{Li}$. Our analyses of discretized diffusion events in both space and time illustrate the critical interplay between correlated dynamics, polarization and local distortion in promoting ionic conductivity in Li 3 OCl.

25 ENERGY STORAGE↗
DOE OSTI2026

KBKit: A Python Toolkit for Kirkwood–Buff Theory from Molecular Dynamics

Thermodynamic properties of liquid mixtures govern processes that range from drug delivery to energy storage, yet extracting these properties from molecular simulations remains challenging. Kirkwood–Buff (KB) theory offers a rigorous route by linking microscopic pair distribution functions to macroscopic free energies, but practical use of the theory has been hindered by two obstacles: (i) the long simulations needed to obtain well-converged Kirkwood-Buff integrals (KBIs) and (ii) the specialized corrections required to translate finite-size data to the thermodynamic limit. $\texttt{KBKit}$ is an open-source Python package that removes these barriers. It automatically computes KBIs and derived thermodynamic quantities from GROMACS input files, applies state-of-the-art finite-size corrections, and provides built-in diagnostic tools to quantify statistical uncertainty. Written with modern software-engineering practices—continuous integration, extensive unit testing, and thorough documentation—$\texttt{KBKit}$ is both reliable and easy to extend. By condensing complex KBI analysis into a few intuitive commands, $\texttt{KBKit}$ enables researchers to incorporate KB theory into routine simulation workflows and accelerate the discovery of solution-phase thermodynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Binary Cation Matrix Electrolyte and Its Effect on Solid Electrolyte Interphase Suppression and Evolution of Si Anode

An unstable solid electrolyte interphase (SEI) has been recognized as one of the biggest challenges to commercializing silicon (Si) anodes for high-energy-density batteries. This work thoroughly investigates a binary cation matrix of Mg 2+ +Li + electrolyte and its role in SEI development, suppression, and evolution of a Si anode. Findings demonstrate that introducing Mg ions dramatically reduces the SEI growth before lithiation occurs, primarily due to the suppression of solvent reduction, particularly ethylene carbonate (EC) reduction. The Mg 2+ alters the Li + cation solvation environment as EC preferably participates in the oxophyllic Mg 2+ solvation sheath, thereby altering the solvent reduction process, resulting in a distinct SEI formation mechanism. The initial SEI formation before lithiation is reduced by 70% in the electrolyte with the presence of Mg 2+ cations. While the SEI continues to develop in the postlithiation, the inclusion of Mg ions results in an approximately 80% reduction in the postlithiation SEI growth. Continuous electrochemical cycling reveals that Mg 2+ plays a crucial role in stabilizing the deep-lithiated Si phases, which effectively mitigates side reactions, resulting in controlled SEI growth and stable interphase while eliminating complex Li x Si y formation. Mg ions promote the development of a notably more rigid and homogeneous SEI, characterized by a reduced dissipation (ΔD) in the Mg 2+ +Li + ion matrix compared to the solely Li + system. In conclusion, this report reveals how the Mg 2+ +Li + ion matrix affects the SEI evolution, viscoelastic properties, and electrochemical behavior at the Si interface in real time, laying the groundwork for devising strategies to enhance the performance and longevity of Si-based next-generation battery systems.

25 ENERGY STORAGE↗
DOE OSTI2022

Real-Time Interactive 4D-STEM Phase-Contrast Imaging From Electron Event Representation Data: Less computation with the right representation

The arrival of direct electron detectors (DED) with high frame-rates in the field of scanning transmission electron microscopy has enabled many experimental techniques that require collection of a full diffraction pattern at each scan position, a field which is subsumed under the name four dimensional-scanning transmission electron microscopy (4D-STEM). DED frame rates approaching 100 kHz require data transmission rates and data storage capabilities that exceed commonly available computing infrastructure. Current commercial DEDs allow the user to make compromises in pixel bit depth, detector binning or windowing to reduce the per-frame file size and allow higher frame rates. This change in detector specifications requires decisions to be made before data acquisition that may reduce or lose information that could have been advantageous during data analysis. The 4D Camera, a DED with 87 kHz frame-rate developed at Lawrence Berkeley National Laboratory, reduces the raw data to a linear-index encoded electron event representation (EER). Here we show with experimental data from the 4D Camera that linear-index encoded EER and its direct use in 4D-STEM phase contrast imaging methods enables real-time, interactive phase-contrast from large-area 4D-STEM datasets. Furthermore, we detail the computational complexity advantages of the EER and the necessary computational steps to achieve real-time interactive ptychography and center-of-mass differential phase contrast using commonly available hardware accelerators.

4D-STEM↗
DOE OSTI2021

Early Battery Performance Prediction for Mixed Use Charging Profiles Using Hierarchal Machine Learning

A key step limiting how fast batteries can be deployed is the time necessary to provide evaluation and validation of performance. Using data analysis approaches, such as machine learning, the validation process can be accelerated. However, questions on the validity of projecting models trained on limited data or simple cycling profiles, such as constant current cycling, to real-world scenarios with complex loads remains. Here, we present the ability to predict performance with less than 1.2% mean absolute percent error when trained on cells aged using complex electric vehicle discharge profiles, and either AC Level 2 charge or DC Fast charge profiles, using only the first 45 cycles, namely 5% of the total testing time. While error is low across the projections, this study also highlights that battery lifetime analysis using only cycling data may not extrapolate safely to certain real-world conditions due to the impact of calendar degradation.

25 ENERGY STORAGE↗
DOE OSTI2023

Uptake of Pb and the Formation of Mixed (Ba,Pb)SO 4 Monolayers on Barite During Cyclic Exposure to Lead-Containing Sulfuric Acid

Barite (BaSO 4 ) is a common additive in lead-acid batteries, where it acts as a nucleating agent to promote the reversible formation and dissolution of PbSO 4 during battery cycling. However, little is known about the molecular-scale mechanisms the nucleation and cyclic evolution of PbSO 4 over a battery’s lifetime. In this study, we explore the responses of a barite (001) surface to cycles of high and low lead concentrations in the presence of 100 mM sulfuric acid using in-situ atomic force microscopy and high-resolution X-ray reflectivity. Here we find that PbSO 4 epitaxial films readily nucleate on the barite surface, even from solutions that are undersaturated relative to bulk PbSO 4 . Despite this, barite (001) proves to be an ineffective nucleator of bulk PbSO 4 , as multilayer growth is suppressed even in highly supersaturated solutions. Instead, we find evidence that Pb 2+ ions can directly exchange with Ba 2+ to create mixed (Ba,Pb)SO 4 surfaces. These chemically mixed surfaces do not host PbSO4 monolayers as readily as pristine barite, and the original reactivity is not regained until a fresh surface is reestablished by aggressive etching. Our results can be partly explained by traditional models of Stranski-Krastanov (S-K) growth, in which monolayer films are stabilized by a reduction in surface energy, but multilayer growth is inhibited by epitaxial strain. Complementary density functional theory calculations confirmed the basic energetic-terms of traditional S-K models, but also showed evidence form more complex, thickness-dependent, energetics than would be predicted from the S-K models. The experimental results can be better understood by extending the S-K model to consider the formation of mixed surfaces and films, which can have reduced strain and interfacial energies relative to pure films, while also being stabilized by entropy of mixing. These insights into non-stoichiometric heteroepitaxy will enable better predictions of how barite affects PbSO 4 nucleation in battery environments.

25 ENERGY STORAGE↗
DOE OSTI2022

Synthesis and Characterization of Magnesium Vanadates as Potential Magnesium‐Ion Cathode Materials through an Ab Initio Guided Carbothermal Reduction Approach**

Abstract Many technologically relevant materials for advanced energy storage and catalysis feature reduced transition‐metal (TM) oxides that are often nontrivial to prepare because of the need to control the reducing nature of the atmosphere in which they are synthesized. Herein, we show that an ab initio predictive synthesis strategy can be used to produce multi‐gram‐scale products of various MgV x O y ‐type phases (δ‐MgV 2 O 5 , spinel MgV 2 O 4 , and MgVO 3 ) containing V 3+ or V 4+ relevant for Mg‐ion battery cathodes. Characterization of these phases using 25 Mg solid‐state NMR spectroscopy illustrates the potential of 25 Mg NMR for studying reversible magnesiation and local charge distributions. Rotor‐assisted population transfer (RAPT) is used as a much‐needed signal‐to‐noise enhancement technique. The ab initio guided synthesis method is seen as a step forward towards a predictive synthesis strategy for targeting specific complex TM oxides with variable oxidation states of technological importance.

Lee, Jeongjae↗
DOE OSTI2026

Exploring the potential of using L-Band InSAR for the mapping of flooded vegetation in tropical wetlands

Wetlands play a critical role in global water and carbon cycles, yet monitoring their water extent remains difficult, particularly beneath dense vegetation. SAR-based techniques such as backscatter thresholding are limited by complex scattering mechanisms, while fully polarimetric SAR (PolSAR) data capable of detecting doublebounce scattering remain scarce. To address these challenges, this study evaluates the potential of Interferometric SAR (InSAR) for mapping water surfaces beneath vegetation, termed flooded vegetation, using the Atrato floodplain in Colombia as a case study. We develop an automated workflow combining InSAR fringe detection with local phase homogeneity analysis and random sampling of processing parameters to generate probabilistic flooded vegetation maps. Applied to ALOS PALSAR-1 L-band image pairs from 2007–2011, the workflow captures seasonal fluctuations in flooded extent ranging from 500 to 1,500 km2. Compared to other L-band SAR inundation products, the InSAR-based maps identify broader flooded areas, with ~70% agreement in pairwise comparisons. Around 84% of detections align with existing wetland inventories and seasonal changes correspond with regional hydrological indicators, including terrestrial water storage anomalies and water gauge measurements. PolSAR analysis shows that InSAR complements backscatter-based methods by detecting inundation in areas with weak double-bounce signals. These findings suggest that combining InSAR with backscatter-based methods can improve detection of flooded vegetation, which is especially relevant for the upcoming NISAR mission that will offer frequent global L-band observations.

Coastal inundation↗
DOE OSTI2022

Hollow-core optical fibre sensors for operando Raman spectroscopy investigation of Li-ion battery liquid electrolytes

Improved analytical tools are urgently required to identify degradation and failure mechanisms in Li-ion batteries. However, understanding and ultimately avoiding these detrimental mechanisms requires continuous tracking of complex electrochemical processes in different battery components. Here, we report an operando spectroscopy method that enables monitoring the chemistry of a carbonate-based liquid electrolyte during electrochemical cycling in Li-ion batteries with a graphite anode and a LiNi 0.8 Mn 0.1 Co 0.1 O 2 cathode. By embedding a hollow-core optical fibre probe inside a lab-scale pouch cell, we demonstrate the effective evolution of the liquid electrolyte species by background-free Raman spectroscopy. The analysis of the spectroscopy measurements reveals changes in the ratio of carbonate solvents and electrolyte additives as a function of the cell voltage and show the potential to track the lithium-ion solvation dynamics. The proposed operando methodology contributes to understanding better the current Li-ion battery limitations and paves the way for studies of the degradation mechanisms in different electrochemical energy storage systems.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

The Emergence and Promise of Functional Chemogeography of Organic Matter

Organisms in ecosystems continuously release a myriad of organic matter molecules that undergo microbial and abiotic transformation, processes that critically influence carbon storage and climate feedbacks. Yet, a systematic understanding of what determines the transformation and persistence of organic matter across spatiotemporal scales remains elusive. We propose an emerging framework, termed “functional chemogeography,” to understand transformation and persistence of organic matter based on the chemical traits of molecules. This framework extends beyond a sole focus on intrinsic traits, which remain relatively constant across spatiotemporal scales, to emphasize extrinsic traits such as biochemical transformations and environmental responses, which vary spatiotemporally and are shaped by both intrinsic traits and the environment. When upscaled to the assemblage level using functional diversity indices, these extrinsic traits reveal a significant, and in some cases superior, capacity than intrinsic traits to explain biogeochemical processes, as demonstrated through a case study of dissolved organic matter in China's lakes. In conclusion, by integrating trait-based perspectives into predictive models, this framework helps bridge chemical complexity with ecosystem biogeochemistry, thereby advancing our ability to predict the fate of global organic carbon under environmental change.

chemical traits↗
DOE OSTI2021

Perspective—Mass Conservation in Models for Electrodeposition/Stripping in Lithium Metal Batteries

Electrochemical models at different scales and varying levels of complexity have been used in the literature to study the evolution of the anode surface in lithium metal batteries. This includes continuum, mesoscale (phase-field approaches), and multiscale models. In this paper, using a motivating example of a moving boundary model in one dimension, we show how battery models need proper formulation for mass conservation, especially when simulated over multiple charge and discharge cycles. The article concludes with some thoughts on mass conservation and proper formulation for multiscale models.

25 ENERGY STORAGE↗
DOE OSTI2023

LOCOMOTIVES - Comprehensive Impact and Cost Assessment Framework of Carbon Lowering Approaches for the US Rail Freight System

The goal of this project is to develop a tool to aid railroads and other stakeholders assess and approach the decarbonization of freight rail operations by identifying new, viable low-carbon energy storage and conversion systems for future locomotive systems and how they should be deployed on the existing US freight rail network. In the first quarter, the project focused on collecting data, establishing a simulation workflow, and engaging industry through the creation of the Industry Advisory Board (IAB). In the second quarter, the project focused on selecting fuel pathways and powertrain technologies, setting performance targets, conducting a techno-economic analyses, and developing the simulation framework that would serve as the backbone of the future toolhead. The third quarter involved developing an industry-oriented interactive dashboard powered by a five-step sequential framework, as well as holding industry advisory board meetings as per the initial technology-to-market plan. In the remaining project quarters, the NUFRIEND dashboard were fine-tuned with the help of IAB member feedback and in-depth scenario analyses were conducted to support the techno-economic analysis of energy sources. Additionally, dashboard documentation, project insights, and open-source code on GitHub were prepared and released. Throughout the project, the team completed testing and analysis of all model components, integrated all initial test scenarios, and conducted stakeholder engagement. Lower-carbon drop-in fuels can be deployed as admixtures and are considered uniform across the network at a desired penetration rate, while hydrogen and battery-electric technology deployment poses a more complex problem as they require significant investments to be made in the siting of refueling/charging facilities and the replacement of locomotive fleets. Thus, strategies for locating and sizing refueling/charging facilities on a railroad’s network to meet their energy demands were developed to inform deployment decisions. To address this challenge, the Northwestern University Freight Rail Infrastructure & Energy Network Decarbonization (NUFRIEND) framework presents a five-step sequential framework to select O-D paths, locate facilities, reroute flows, size facilities, and evaluate the deployment for alternative energy sources that require locomotive powertrains to be converted and new refueling infrastructure to be deployed. The NUFRIEND Framework is an industry-oriented tool for simulating the deployment of new energy technologies across the US freight rail network. The framework provides a comprehensive network-level optimization and scenario simulation tool for decarbonizing the freight rail sector, addressing the uncertainties surrounding technological developments by supporting sensitivity analyses for different operational and technological parameters through a transparent and flexible input module. It offers practical alternatives to diesel locomotives and can be applied for any railroad considering the specific network structure and freight demand, outputting evaluation metrics for the associated emissions and costs relative to diesel operations. A number of relevant simulation scenarios were run and analyzed for key insights on the value of different alternative technologies for freight rail decarbonization. The project developments and findings have been presented at numerous conferences and events.

08 HYDROGEN↗
DOE OSTI2020

Analysis of Planar-Cavity Receiver Reactor for Solar Thermochemical Dry-Reforming

Concentrating solar thermal (CST) systems can be leveraged to provide not only heat for power generation, but also for energy storage and thermochemical fuel production. Such solar thermochemical processes have been studied conceptually, from solar thermochemical hydrogen production (STCH) and thermochemical energy storage (TCES), to gasification, reforming, and fuel upgrading by various means. The solar receiver and reactor are critical components in the conversion of solar energy into chemical energy in the form of 'solar fuels'. For effective conversion of solar energy within a coupled solar receiver-reactor, extremely high temperatures are required, thereby demanding a high solar concentration ratio (CR) for efficient operation. This creates a design challenge for the receiver-reactor, as many thermochemical processes involve gas or gas-solid systems that are limited by low heat transfer coefficients. A unique receiver design is proposed that has the potential to incorporate various high-temperature thermochemical processes such as TCES-assisted power generation, methane reforming, or STCH processes. Modeling this receiver and its potential applications requires a full three-dimensional model that accurately captures the interconnected effects of receiver geometry, spatial solar irradiance, complex radiation, reaction kinetics, fluid dynamics, and heat transfer. In this paper we analyze a CST system integrated with this unique planar-cavity receiver-reactor design using the developed model. The model presented in this paper showed where improved thermal management was needed to achieve suitable receiver performance when a dry-methane reforming process is implemented.

14 SOLAR ENERGY↗