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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Optimize the Autonomous Sensor Fish Device for Understanding Interactions of Aquatic Animals with Marine and Hydrokinetic and Hydro Systems (CRADA 476) Final Report

This project at the Pacific Northwest National Laboratory (PNNL) enhances our understanding of how aquatic life interacts with marine renewable energy (MRE) and hydropower systems through the development and testing of advanced sensor technology. The Marine Sensor Fish (MSF) and its smaller variants, the Sensor Fish Mini (SF Mini) and Flexible Sensor Fish (FSF), measure critical environmental stressors, such as shear forces, pressure changes, and strike impacts, that are essential for assessing the risks posed by energy devices, including tidal turbines, hydropower installations, and other MRE infrastructure. Rigorous field testing has shown that these tools are effective in capturing detailed data on turbulence, pressure variations, strike impacts, and other stressors near these devices, providing valuable insights into the conditions faced by aquatic species. Economically, these tools offer renewable energy developers a practical solution for streamlining environmental assessments and ensuring regulatory compliance, ultimately reducing costs associated with evaluating and mitigating ecological impacts. This research also benefits the public by promoting the growth of renewable energy sources that protect aquatic ecosystems, advancing both sustainable energy production and environmental stewardship.

13 HYDRO ENERGY↗
DOE OSTI2025

First experimental determination of the ⁴⁰Ar(𝑛, 2𝑛)³⁹Ar reaction cross section and ³⁹Ar production in Earth’s atmosphere

The cosmogenic ³⁹Ar(t1∕2 = 268 years) isotope of argon is used for geophysical dating and tracing of underground and ocean water, as well as ice owing to its appropriate half-life and chemical inertness as a noble gas; ³⁹Ar serves also in nuclear weapon test monitoring. We measured for the first time the total cross section of the main ³⁹Ar cosmogenic production reaction in the atmosphere, namely ⁴⁰Ar(𝑛, 2𝑛)39 Ar, using 14.8 ± 0.3 MeV neutrons. The neutrons, produced by a deuterium-tritium generator, impinged on a stainless steel sphere filled with Ar gas highly enriched in the ⁴⁰Ar isotope and were monitored by a stack of fast-neutron activation foils. The reaction yield was measured by atom counting of long-lived ³⁹Ar with noble gas accelerator mass spectrometry and, independently, by decay counting relative to atmospheric argon (³⁹Ar/Ar= 8.12 × 10−16 ). A total ⁴⁰Ar(𝑛, 2𝑛)39 Ar cross section of 610 ± 100 mb was determined at 14.8 ± 0.3 MeV incident neutron energy. This result serves as a benchmark for recent theoretical calculations and evaluations, found to reproduce well the experimental total cross section. We use these energy-dependent theoretical cross sections together with experimental spectra of cosmogenic neutrons at different altitudes to calculate the global average rate of neutron-induced ³⁹Ar atmospheric production, resulting in 770 ± 240 39 Ar atoms/cm²/day. The secular equilibrium between the ³⁹Ar calculated production rate and radioactive decay rate leads to a partial isotopic abundance ³⁹Ar/Ar = (5.9 ± 1.8) × 10−16 , showing that ≈73% of atmospheric ³⁹Ar is produced by cosmogenic neutrons, the remaining part believed to be induced by muons and high-energy 𝛾 rays. The ⁴⁰Ar(𝑛, 2𝑛)³⁹Ar cross section at 14 MeV is also a key parameter for quantifying the anthropogenic contribution to atmospheric 39 Ar produced during the thermonuclear tests of the 1960s. We estimate that anthropogenic ³⁹Ar accounts for roughly 20% of the present atmospheric inventory.

39 Ar atmospheric production↗
DOE OSTI2020

Performance Prediction of Big Data Transfer Through Experimental Analysis and Machine Learning

Big data transfer in next-generation scientific applications is now commonly carried out over connections with guaranteed bandwidth provisioned in High-performance Networks (HPNs) through advance bandwidth reservation. To use HPN resources efficiently, provisioning agents need to carefully schedule data transfer requests and allocate appropriate bandwidths. Such reserved bandwidths, if not fully utilized by the requesting user, could be simply wasted or cause extra overhead and complexity in management due to exclusive access. This calls for the capability of performance prediction to reserve bandwidth resources that match actual needs. Towards this goal, we employ machine learning algorithms to predict big data transfer performance based on extensive performance measurements, which are collected over a span of several years from a large number of data transfer tests using different protocols and toolkits between various end sites on several real-life physical or emulated HPN testbeds. We first identify a comprehensive list of attributes involved in a typical big data transfer process, including end host system configurations, network connection properties, and control parameters of data transfer methods. We then conduct an in-depth exploratory analysis of their impacts on application-level throughput, which provides insights into big data transfer performance and motivates the use of machine learning. We also investigate the applicability of machine learning algorithms and derive their general performance bounds for performance prediction of big data transfer in HPNs. Experimental results show that, with appropriate data preprocessing, the proposed machine learning-based approach achieves 95% or higher prediction accuracy in up to 90% of the cases with very noisy real-life performance measurements.

Yun, Daqing↗
DOE OSTI2020

Performance Prediction of Big Data Transfer Through Experimental Analysis and Machine Learning

Big data transfer in next-generation scientific ap- plications is now commonly carried out over connections with guaranteed bandwidth provisioned in High-performance Net- works (HPNs) through advance bandwidth reservation. To use HPN resources efficiently, provisioning agents need to carefully schedule data transfer requests and allocate appropriate band- widths. Such reserved bandwidths, if not fully utilized by the requesting user, could be simply wasted or cause extra overhead and complexity in management due to exclusive access. This calls for the capability of performance prediction to reserve bandwidth resources that match actual needs. Towards this goal, we employ machine learning algorithms to predict big data transfer perfor- mance based on extensive performance measurements, which are collected over a span of several years from a large number of data transfer tests using different protocols and toolkits between various end sites on several real-life physical or emulated HPN testbeds. We first identify a comprehensive list of attributes involved in a typical big data transfer process, including end host system configurations, network connection properties, and control parameters of data transfer methods. We then conduct an in-depth exploratory analysis of their impacts on application- level throughput, which provides insights into big data transfer performance and motivates the use of machine learning. We also investigate the applicability of machine learning algorithms and derive their general performance bounds for performance prediction of big data transfer in HPNs. Experimental results show that, with appropriate data preprocessing, the proposed machine learning-based approach achieves 95% or higher pre- diction accuracy in up to 90% of the cases with very noisy real-life performance measurements.

Yun, Daqing↗
DOE OSTI2017

Absolute Dosimetry Model of the University of Washington Clinical Neutron Therapy System (CNTS)

The University of Washington (UW) Clinical Neutron Therapy System (CNTS) generates a fast neutron beam using 50.5 MeV protons incident on a beryllium target. The CNTS is mainly used for fast neutron therapy in the treatment of cancer but is also used for radiation effects testing and the production of rare isotopes, or isotopes with a short half-life, for medical imaging and therapy. The accelerator and treatment head is modeled using the MCNP6 Monte Carlo code to enable beam characterization (neutron and photon fluence, linear energy transfer, secondary particle production), study the behavior of neutron dosimeters and ionization chamber (IC) responses, and to conduct first principle studies of the relative biological effectiveness (RBE) of fast neutrons compared to {sup 60}Co γ-rays. Measurements of neutron dose in selected CNTS fields were made using a model-17 ion chamber (IC-17) flowing methane-based, tissue-equivalent (TE) gas. As a first approximation, we compared IC-17 measurements to the MCNP calculated dose in a thin layer of water at selected locations along the central axis of the beam. To examine the impact of the composition of the chamber fill-gas and the chamber design characteristics, we also developed a high-resolution (∼ 50 μm) MCNP model of the IC-17 from a computerized tomography (CT) scan. Initial results indicate that the dose response of the IC-17 ion chamber is up to 30% larger (smaller?) compared to the dose to water for neutrons with energies >20 MeV. Differences in chamber and water response as large as 800% occur for neutrons with kinetic energies below 1 keV. The simulations of IC-17 response (and dose to water) for CNTS fast neutron spectra match measured doses within 4.6% for all field sizes and irradiation geometries considered. This reported studies provide additional evidence establishing use of the IC-17 ion chamber model or a thin layer of water as a reasonable surrogate for CNTS fast neutron dose calculations.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2021

Overview/Recap of the 2020 Accelerated Irradiation of Reactor Structural Materials Workshop

The workshop provided a snapshot look at current international, in-reactor testing and irradiation capabilities. Gaps were identified where possible, and discussions focused on potential mitigation strategies and recommended paths forward. As new material innovations are being developed for in-reactor applications for reactor life extension long-term operation, and advanced reactor technologies, there is an increased need for materials qualification and assessment programs. In-reactor testing capabilities are vital to the on-going success of these DOE-NE programs and initiatives. In recent years, multiple international research reactors have been placed in a permanent shut-down state and have begun full decommissioning. These activities have created new risks in the delivery of on-going and/or expected research programs. Beyond performing simple irradiations in test reactors, few facilities exist internationally which can perform instrumented, in-situ irradiations on structural materials, and with the recent shut down of facilities hosted at Halden and NRU (example: instrumented fatigue loop, and in-situ creep), there are further gaps in the industry left un-filled. A new focus is being placed on the use of accelerator- based technologies to fill in some of these gaps, but these must be viewed as supplemental, and not surrogates to in-reactor capabilities

36 - MATERIALS SCIENCE↗
DOE OSTI2024

In-service Oxidation and IASCC in High Fluence Baffle-Former Bolts Retrieved from a Westinghouse PWR

Baffle-former bolts (BFBs) are subjected to significant mechanical stress and neutron irradiation from the reactor core during the plant operation. Over the long operation period, these conditions lead to potential degradation and reduced load-carrying capacity of the bolts, and life extension of existing pressurized water reactors (PWRs) would only cause more damage to the bolt material. To this end, the Light Water Reactor Sustainability (LWRS) Program Materials Research Pathway (MRP) successfully harvested two high fluence BFBs from a Westinghouse two-loop downflow type PWR in 2016. In the same year, the two BFBs were received at the Westinghouse Churchill facility for inspection and specimen fabrication. The fabrication was completed in 2017 with specimens shipped to Oak Ridge National Laboratory (ORNL) for further testing. The objective of this project is to provide information that is integral to evaluating end of life microstructure and properties as a benchmark of international models developed for predicting radiation-induced swelling, segregation, precipitation, mechanical property degradation, and with the latest findings, susceptibility to irradiation-assisted stress corrosion cracking (IASCC).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

Experimental Study on Surrogate Nuclear Fuel Rods under Reversed Cyclic Bending

The mechanical behavior of spent nuclear fuel (SNF) rods under reversed cyclic bending or bending fatigue must be understood to evaluate their vibration integrity in a transportation environment. This is especially important for high-burnup fuels (>45 GWd/MTU), which have the potential for increased structural damage. It has been demonstrated that the bending fatigue of SNF rods can be effectively studied using surrogate rods. In this investigation, surrogate rods made of stainless steel (SS) 304 cladding and aluminum oxide pellets were tested under load or moment control at a variety of amplitude levels at 5 Hz using the Cyclic Integrated Reversible-Bending Fatigue Tester developed at Oak Ridge National Laboratory. The behavior of the rods was further characterized using flexural rigidity and hysteresis data, and fractography was performed on the failed rods. The proposed surrogate rods captured many of the characteristics of deformation and failure mode observed in SNF, including the linear-to-nonlinear deformation transition and large residual curvature in static tests, PPI and PCMI failure mechanisms, and large variation in the initial structural condition. Rod degradation was measured and characterized by measuring the flexural rigidity; the degradation of the rigidity depended on both the moment amplitude applied and the initial structural condition of the rods. It was also shown that a cracking initiation site can be located on the internal surface or the external surface of cladding. Finally, fatigue damage to the bending rods can be described in terms of flexural rigidity, and the fatigue life of rods can be predicted once damage model parameters are properly evaluated. The developed experimental approach, test protocol, and analysis method can be used to study the vibration integrity of SNF rods in the future.

cladding failure↗
DOE OSTI2022

srlife: A Fast Tool for High Temperature Receiver Design and Analysis

This report describes a tool for estimating the structural service life of tubular, panel solar receivers operating at high temperatures. A complete version of the tool is available as open source software at https://github.com/Argonne-National-Laboratory/srlife and can be installed through the PyPi (https://pypi.org) package manager. Given the basic receiver geometry and the thermal loads on the receiver, the tool provides 1D, 2D, or 3D thermal and structural (single tube and simplified system) analysis and creep-fatigue service life prediction for six metallic alloys – 316H, 800H, Alloy 617, Alloy 740H, and Alloy 230. With the exception of Alloy 230 where the material data is preliminary, the software included a detailed set of models for the materials, well-supported by high temperature experimental test data. The tool is designed for easy integration with a software stack, including solar field and thermohydraulic simulations, for optimizing receiver designs to meet service life and economic targets. The report describes several heuristics that can be applied in srlife to reduce the analysis time by several orders of magnitude but with fairly accurate life estimation when compared with full analysis. The report provides several examples demonstrating the utility of srlife in receiver design. Finally, the report discusses high temperature tests on Alloy 282, collected as part of this project, used to develop and support the material model for that alloy.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Multivariable degradation modeling and life prediction using multivariate fractional Brownian motion

In system prognostics and health management, multivariable degradation models have been widely developed to predict the life of complex systems using degradation data of multiple Performance Characteristics (PCs). Recent studies have detected a Long-Term Memory (LTM) effect among the degradation process of various PCs, implying a strong coupling phenomenon between the future degradation behavior and historical degradation trajectory. Although the LTM has been widely integrated into single-PC-based degradation modeling, it has not been considered in multi-PC-based scenarios. To capture LTM among multiple PCs, this article proposes a novel LTM-integrated Multivariate Degradation Model (MDM) for system life prediction based on multivariate fractional Brownian motion, which simultaneously incorporates the cross-correlation among different PCs. To estimate parameters of the LTM-integrated MDM, a maximum likelihood method is developed. Here, two likelihood-ratio hypothesis tests are developed to test the existence of the overall and individual LTM effect among multiple PCs. Both simulation studies and physical experiments on the performance degradation of solar energy conversion and storage devices are conducted to validate the proposed model. Results reveal that the proposed LTM-integrated MDM significantly outperforms existing MDMs in life prediction, while the lifetime uncertainty is heavily underestimated by those traditional approaches that neglect the LTM.

42 ENGINEERING↗
DOE OSTI2020

Long Term Assessment of Radiocesium in Deer, Fish, Soil, and Vegetation at the Savannah River Site

Throughout the Savannah River Site's (SRS) operational history, many radionuclides have been released into the environment. However, due to fallout from weapons testing, the amount released from SRS, its persistence in the environment, and the seclusion of the Site, radiocesium (Cs-137) is one of the most critical radionuclides in the SRS environment. The Effective half-life (Te) is the time it takes for a radionuclide in the environment to decrease by 50% of its initial amount. There are three means of radionuclide removal: Physical: Radioactive decay, sedimentation, and washout; Chemical: Changes in pH, oxidation state or adsorption; Biological: Changes in the food web or translocation. Effective half-life (T{sub e}) = log{sub e}2/λ{sub e} Where λ{sub e} is estimated from the slopes of loge-transformed Cs-137 activity concentrations regressed on year. The objective of this work was to calculate the effective half-life of Cs-137 in various biota at SRS and to perform an assessment of the changes in the effective half life over time. Compared to 2013 data, there is a slight increase in the effective half-lives for fish at most sampling locations. This effective half-life increase is an indication that the rate of Cs-137 loss is starting to plateau. The effective half-life of Cs-137 in SRS fish ranges from 4-11 years. The effective half-life of Cs-137 in soil at the Creek plantation is about 15 years. The effective half-life of Cs-137 in grassy vegetation at the Creek Plantation is about 14 years. The effective half-life of deer hunted on the SRS is about 15.5 years. After termination of all reactor activity by 1980, the Cs-137 activity began to drop drastically.

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

Is the testing effect ready to be put to work? Evidence from the laboratory to the classroom.

The testing effect refers to the benefits to retention that result from structuring learning activities in the form of a test. As educators consider implementing test-enhanced learning paradigms in real classroom environments, we think it is critical to consider how an array of factors affecting test-enhanced learning in laboratory studies bear on test-enhanced learning in real-world classroom environments. As such, this review discusses the degree to which test feedback, test format (of formative tests), number of tests, level of the test questions, timing of tests (relative to initial learning), and retention duration have import for testing effects in ecologically valid contexts (e.g., classroom studies). Attention is also devoted to characteristics of much laboratory testing-effect research that may limit translation to classroom environments, such as the complexity of the material being learned, the value of the testing effect relative to other generative learning activities in classrooms, an educational orientation that favors criterial tests focused on transfer of learning, and online instructional modalities. We consider how student-centric variables present in the classroom (e.g., cognitive abilities, motivation) may have bearing on the effects of testing-effect techniques implemented in the classroom. We conclude that the testing effect is a robust phenomenon that benefits a wide variety of learners in a broad array of learning domains. Still, studies are needed to compare the benefit of testing to other learning strategies, to further characterize how individual differences relate to testing benefits, and to examine whether testing benefits learners at advanced levels.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Experimental Aging and Lifetime Prediction in Grid Applications for Large-Format Commercial Li-Ion Batteries

Due to the growth of electric vehicle and stationary energy storage markets, the production and use of lithium-ion batteries has grown exponentially in recent years. For many of these applications, large-format lithium-ion batteries are being utilized, as large cells have less inactive material relative to their energy capacity and require fewer electrical connections to assemble into packs. And especially for stationary energy storage systems, where energy delivered is the only revenue source, the economics of these battery systems is highly dependent on cell lifetime. However, testing of large-format lithium-ion batteries is time consuming and requires high current channels and large testing chambers, making information on the performance of commercial, large-format lithium-ion batteries hard to come by. Here, accelerated aging test data from four commercial large-format lithium-ion batteries is reported. These batteries span both NMC-Gr and LFP-Gr cell chemistries, pouch and prismatic formats, and a range of cell designs with varying power capabilities. Accelerated aging test results are analyzed to examine both cell performance, in terms of efficiency and thermal response under load, as well as cell lifetime. Cell thermal response is characterized by measuring temperature during cycle aging, which is used to calculated a normalized thermal resistance value that may help estimate both cell cooling needs or to help extrapolate aging test results to different thermal environments. Cell lifetime is evaluated qualitatively, considering simply the average calendar and cycle life across a range of conditions, as well as quantitatively, using statistical modeling and machine-learning methods to identify predictive aging models from the accelerated aging data. These predictive aging models are then used to investigate cell sensitivities to stressors, such as cycling temperature, voltage window, and C-rate, as well as to predict cell lifetime in various stationary storage applications. Results from this work show that cell lifetime and sensitivity to aging conditions varies substantially across commercial cells, necessitating testing for specific cell formats to make quantitative lifetime predictions. That being said, all commercial cells tested here are predicted to reach at least 10-year lifetimes for stationary storage applications. Based on the aging test results and modeling, some cells are expected to be relatively insensitive to temperature and use-case, making them suited for simple use cases with little or no thermal management and simple controls, while the lifetime of other cells could be extended to 20+ years if operated with thermal management and degradation-aware controls.

battery↗
DOE OSTI2023

The Effect of Prostate-Specific Antigen (PSA) Test on Radiation Risk Estimate for Prostate Cancer Incidence among Atomic-Bomb Survivors

Following our previous report on the radiation doseresponse for prostate cancer incidence rates in the Life Span Study (LSS) cohort of atomic bomb survivors, we reevaluated the radiation-related risk adjusting for differences in baseline cancer incidence rates among three subsets of the LSS cohort defined by the timing of their first participation in biennial health examinations offered to the Adult Health Study (AHS) sub-cohort members and prostate-specificantigen (PSA) testing status for AHS participants: 1. nonAHS participants, 2. AHS participants before receiving PSA test, and 3. AHS participants after receiving PSA test. We found a 2.9-fold increase in the baseline incidence rates among AHS participants after receiving PSA test. After adjusting for the PSA-testing-status effects on the baseline rates the estimated excess relative risk (ERR) per Gy was 0.54 (95% CI: 0.15, 1.05), which was almost identical to the previously reported unadjusted ERR estimate (0.57, 95% CI: 0.21, 1.00). The current results confirmed that, while the PSA testing among AHS participants increased the baseline incidence rates, it did not impact the radiation risk estimate, strengthening the previously reported dose-response relationship for prostate cancer incidence in the LSS. As the use of PSA tests continue in screening and medical settings, analyses of possible effects of PSA testing should be an important aspect of future epidemiological studies of the association between radiation exposure and prostate cancer.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2020

Influence of copper content on the high temperature tensile and low cycle fatigue behavior of cast Al-Cu-Mn-Zr alloys

The relationship between low cycle fatigue (LCF) and monotonic tensile fracture strain was investigated for cast Al-Cu-Mn-Zr alloys containing 6 and 9 wt% Cu at 250 °C. The 9% Cu alloy consisted of larger size and volume fraction of brittle intermetallic grain boundary particles that fractured during tensile tests to reduce the fracture strain by 50% compared to the 6% Cu alloy. We found that LCF life was similar between the two alloys and weakly influenced by the particles. LCF life and fracture strain were poorly correlated due to the dominant influence of particles on monotonic tensile crack but not on fatigue crack.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Life Prediction of Large Lithium-Ion Battery Packs with Active and Passive Balancing

Lithium-ion battery packs take a major part of large-scale stationary energy storage systems. One challenge in reducing battery pack cost is to reduce pack size without compromising pack service performance and lifespan. Prognostic life model can be a powerful tool to handle the state of health (SOH) estimate and enable active life balancing strategy to reduce cell imbalance and extend pack life. This work proposed a life model using both empirical and physical-based approaches. The life model described the compounding effect of different degradations on the entire cell with an empirical model. Then its lower-level submodels considered the complex physical links between testing statistics (state of charge level, C-rate level, duty cycles, etc.) and the degradation reaction rates with respect to specific aging mechanisms. The hybrid approach made the life model generic, robust and stable regardless of battery chemistry and application usage. The model was validated with a custom pack with both passive and active balancing systems implemented, which created four different aging paths in the pack. The life model successfully captured the aging trajectories of all four paths. The life model prediction errors on capacity fade and resistance growth were within +/-3% and +/-5% of the experiment measurements.

25 ENERGY STORAGE↗
DOE OSTI2023

Interplay between Shelf Life and Printability of Silica-Filled Suspensions

Although fumed silica/siloxane suspensions are commonly employed in additive manufacturing technology, the interplay between shelf life, storage conditions, and printability has yet to be explored. In this work, direct ink writing (DIW) was used to print unique three-dimensional structures that required suspensions to retain shape and form while being printed onto a substrate. Suspensions containing varying concentrations of hydrophobic and hydrophilic silica were formulated and evaluated over a time span of thirty days. Storage conditions included low (8%) and high (50%) relative humidity and temperatures ranging from 4 °C to 25 °C. The shelf life of the suspensions was examined by comparing the print quality of pristine and aged samples via rheology, optical microscopy, and mechanical testing. Results showed a significant decrease in printability over time for suspensions containing hydrophilic fumed silica, whereas the printability of suspensions containing hydrophobic fumed silica remained largely unchanged after storage. The findings in this work established the following recommendations for extending the shelf life and printability of suspensions commonly used in DIW technology: (1) higher fumed silica concentrations, (2) low humidity and low temperature storage environments, and (3) the use of hydrophobic fumed silica instead of hydrophilic fumed silica.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Cobalt-Free Cathodes for Next Generation Li-Ion Batteries

In this U.S. Department of Energy sponsored project Nexceris, in collaboration with project partners; The Ohio State University and Navitas Advanced Systems have advanced the technical maturity of a non-cobalt containing cathode for next-generation Li-ion batteries. The cathode is based on the lithium manganese nickel-titanium oxide, LiNi 0.5 Mn 1.5 TiO 4 (LNMTO) high voltage spinel. To address limitations with poor cycle and calendar life an microstucturally hierarchical LNMO/LNMTO core-shell cathode powder has been developed that enables the formation of a solid-electrolyte interface that effectively passivates the cathode surface. The microstructural enhancements of the cathode material focus on preferentially enriching the surface with titanium. In parallel, new, optimized binder and electrolyte chemistries have been incorporated to address degradation mechanisms associated with high-voltage systems. Single-layer pouch cell and large-format 2-Ah cell testing have shown that an optimized LNMO/LNMTO core-shell powder significantly improves initial cell capacity and cycle life compared to homogeneous LNMO powder. To support development and the fabrication of 2-Ah cells a novel Hybrid Alternative Wet-Chemical Synthesis (HAWCS) process have been developed. This low-cost, synthesis approach enables the excellent compositional and particle morphology control achieved with co-precipitation without the strict process controls and associated expensive process equipment.

25 ENERGY STORAGE↗