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At least 37 records · Page 2

Machine Learning Based Metamodel for Faster Life Cycle Assessment of Large Portfolio of Buildings

Managing a large portfolio of buildings involves decisions on reuse, retrofit, renovation, rehabilitation, and new construction, influenced by trade-offs between performance metrics such as cost, time, and operational flexibility over the building's life cycle. Traditional life cycle assessment tools for evaluating these metrics can be labor- and compute-intensive, requiring extensive data and modeling for each building. Metamodels (or surrogate models) using machine learning have been explored as faster alternatives, but training these models has been hindered by the limited availability of comprehensive data on key life cycle metrics. Recent advancements in machine learning, particularly deep learning techniques like zero-shot and few-shot learning, allow models to learn from sparse or limited data. We propose a machine learning-based metamodel that leverages these techniques for rapid estimation of key building life cycle metrics. This presentation will cover the model architecture, data collection, training, and validation processes, along with an ongoing case study applied to a large portfolio of buildings. We will discuss the model's performance in terms of accuracy, compute time, limitations, and its potential for expanding to additional life cycle metrics. This data-driven approach offers a promising direction for the rapid evaluation of large building portfolios.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Nuclear Weapon Life Cycle [Slides]

This presentation provides an overview of the processes of the nuclear weapon life cycle, joint nuclear weapon life cycle responsibilities, key players in the life cycle process, joint nuclear weapon life cycle phases, the Phase 6.X process, and refurbishment activities.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Greenhouse Gas Life Cycle Emissions Assessment Model (GLEAM) Model Documentation

The Greenhouse gas Life cycle Emissions Assessment Model (GLEAM) estimates life cycle greenhouse gas emissions from future scenarios of electricity generation considering a wide range of generation technologies. Building on the National Laboratory of the Rockies longstanding effort to quantify life cycle emissions by electricity generation technology under the LCA Harmonization Project, GLEAM streamlines the process of estimating cumulative greenhouse gas emissions on a life cycle basis. Given a set of inputs regarding annual installed and decommissioned generation capacity, as well as generation, GLEAM estimates the carbon dioxide equivalent emissions by year. The model also offers optional modules to decompose carbon dioxide equivalent emissions into constituent greenhouse gases (e.g., carbon dioxide, methane, and nitrous oxide) as well as estimate hydrogen leakage from relevant technologies. The results from GLEAM can be used to inform future electricity planning scenarios as well as investment or regulatory decisions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Seasonal controls on isolated convective storm drafts, precipitation intensity, and life cycle as observed during GoAmazon2014/5

Abstract. Isolated deep convective cloud life cycle and seasonal changes in storm properties are observed for daytime events during the US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Green Ocean Amazon Experiment (GoAmazon2014/5) campaign to understand controls on storm behavior. Storm life cycles are documented using surveillance radar from initiation through maturity and dissipation. Vertical air velocity estimates are obtained from radar wind profiler overpasses, with the storm environment informed by radiosondes. Dry-season storm conditions favored reduced morning shallow cloud coverage and larger low-level convective available potential energy (CAPE) than wet-season counterparts. The typical dry-season storm reached its peak intensity and size earlier in its life cycle compared with wet-season cells. These cells exhibited updrafts in core precipitation regions (Z>35 dBZ) to above the melting level as well as persistent downdrafts aloft within precipitation adjacent to their cores. Moreover, dry-season cells recorded more intense updrafts to earlier life cycle stages as well as a higher incidence of strong updrafts (i.e., >5 m s−1) at low levels. In contrast, wet-season storms were longer-lived and featured a higher incidence of moderate (i.e., 2–5 m s−1) updrafts aloft. These storms also favored a shift in their most intense properties to later life cycle stages. Strong downdrafts were less frequent within wet-season cells aloft, indicating a potential systematic difference in draft behaviors, as linked to graupel loading and other factors between the seasons. Results from a stochastic parcel model suggest that dry-season cells may expect stronger updrafts at low levels because of larger low-level CAPE in the dry season. Wet-season cells anticipate strong updrafts aloft because of larger free-tropospheric relative humidity and reduced entrainment-driven dilution. Enhanced dry-season downdrafts are partially attributed to increased evaporation, dry-air entrainment mixing, and negative buoyancy in regions adjacent to sampled dry-season cores.

54 ENVIRONMENTAL SCIENCES↗

California's harvested wood products: A time-dependent assessment of life cycle greenhouse gas emissions

Following life-cycle assessment (LCA) methodology, this study presents a state-level estimation of embodied carbon of wood products harvested in 2019 from California and subsequently processed, manufactured, transported, used, and disposed at the end-of-life (EoL). In a conventional static approach to LCA, all GHG emissions were aggregated and considered to occur at year 0 of the given time horizon (500 years in this study) and used a static characterization factor (CF). In dynamic LCA, GHG emissions occurring in different years were considered, and their global warming impact (GWI) was determined using a time-dependent CF over the selected time horizon of 500 years. Four scenarios were developed to examine the impact of EoL choices on GWI. It was found that dynamic GWI for all scenarios ranged from 0.27 to 0.93 million tonne CO₂e, which were 45–73 % lower than those estimated with static LCA approach, indicating that the static LCA approach could lead to an underestimation of the benefits of substituting wood for non-wood products, compared to those based on dynamic LCA approach. This analysis also demonstrated that the choice of EoL treatment option is a key factor affecting the estimated GWI as it directly determines the annual emission of GHGs released into atmosphere and subsequently their warming effect depending on the time harvested wood products (HWPs) spend in the horizon of assessment. Altogether, the dynamic LCA performed in this study enabled more robust interpretations of embodied carbon by including temporal boundaries associated with the HWPs life cycle.

54 ENVIRONMENTAL SCIENCES↗

Recycling and Life Cycle Issues for Lightweight Vehicles

This chapter addresses recycling and life cycle considerations related to the growing use of lightweight materials in vehicles. This chapter first addresses the benefit of a life cycle perspective in materials choice, and the role that recycling plays in reducing energy inputs and environmental impacts in a vehicle’s life cycle. Some limitations of life cycle analysis and results of several vehicle- and fleet-level assessments are drawn from published studies. With emphasis on lightweight materials such as aluminum, magnesium, and polymer composites, the status of the existing recycling infrastructure and technological challenges being faced by the industry also are discussed.

Das, Sujit↗

A Simplified Method to Evaluate Energy Life Cycle Cost Effectiveness for Electron Ion Collider Infrastructure Design

The new DOE Order 436.1A approved on April 25 th provides instructions to incorporate principles of sustainability early in the project planning and design process. Integral to the principles of sustainability is life cycle cost effectiveness Life Cycle Cost (LCC) Analysis is vital to the sustainable energy efficient design and construction of the Electron Ion Collider (EIC). Reducing energy consumption has a direct impact on reducing life cycle operating costs with benefits to the environment. The early stages of the project are the most influential where design decisions and so life-cycle considerations during this stage can result in significant impacts to the energy footprint of the design. For example, when comparing between various options, it is necessary to compare the energy savings in $\frac{US$}{kWh}$ to the capital cost in US$. And although uncertain by nature, it is important to factor in the expected inflation and discount of future spendings to compare with the cost of immediate capital investment. This tech note presents a tool that engineers can readily use to analyze energy operating costs using an incremental life cycle cost method when comparing different design alternative.

43 PARTICLE ACCELERATORS↗

Methodology Guidelines on Life Cycle Assessment of Photovoltaic 2020, 4th Edition

Life Cycle Assessment (LCA) is a structured, comprehensive method of quantifying material- and energy-flows and their associated emissions caused in the life cycle 1 of goods and services. The ISO 14040 and 14044 standards provide the framework for LCA. However, this framework leaves the individual practitioner with a range of choices that can affect the results and thus the conclusions of an LCA study. The present version of the IEA LCA guidelines is the result of the third update. They were developed and are updated to provide guidance on assuring consistency, balance, and quality to enhance the credibility and reliability of the results from LCAs on photovoltaic (PV) electricity generation systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Life Cycle Greenhouse Gas Emissions of Coal-Biomass Co-Firing Power Plants with Carbon Capture and Storage

The United States has set a target to achieve the net-zero economy by 2050. Bioenergy with Carbon Capture and Sequestration (BECCS) is one of the promising negative-emission routes in the mitigation portfolio to help meet this goal. Coal-biomass co-firing with carbon capture and storage (CCS) is a key BECCS technology to realize the carbon mitigation at fossil-fuel power plants. The mitigation potential of co-firing option is affected by numerous critical factors, such as biomass properties, co-firing level, and carbon capture rate. The objectives of the study are to characterize and estimate the life cycle greenhouse gas (GHG) emissions and performance of coal-biomass co-firing power plants with CCS, determine the breakeven co-firing level at power plants necessary to achieve net-zero life cycle emissions, and quantify the variabilities and uncertainties in life cycle emissions. The scope of the life cycle assessment includes the fuel supply, combustion-based power generation, and CO2 transport and storage. A fuel-based life cycle module is developed and embedded in the Integrated Environmental Control Model (IECM), a fossil-fuel power plant modeling tool. This study then applies the enhanced IECM to conduct the process-based life cycle assessment for an array of biomass co-firing scenarios. Deterministic analysis indicates that reaching net-zero life cycle emissions in a biomass co-firing plant without CCS deployment is challenging. Combining biomass co-firing and CCS deployment can significantly lower the overall life cycle emissions of power plants. Net-zero life cycle emissions can be achieved with a 20 wt.% co-firing level and 90% CCS when the Powder River Basin coal is co-fired with energy crops or forestry residues. However, the breakeven co-firing level for net-zero emissions depend on the selected fuel properties. Fuel supply and plant operation are the critical stages influencing the life cycle emissions of power plants with 90% CCS. Deployment of deep CCS beyond 90% CO2 capture can remarkably reduce operational emissions and the breakeven co-firing level. With 99% CCS, the breakeven co-firing rate can be reduced to 12% on average. These findings highlight the trade-offs between technical performance and environmental impact of biomass co-firing at coal-fired power plants and emphasize the role of deep CCS in achieving a net-zero emissions future.

Wu, Wanying↗

Life-Cycle Baseline Customization for the Formerly Utilized Sites Remedial Action Program - 20304

One of the responsibilities of the federal government is to estimate sound and defensible life-cycle baseline costs for use in federal budget estimates and to meet federal financial reporting requirements. To accomplish this, the US Department of Energy (DOE) Office of Legacy Management (LM) and the US Army Corps of Engineers (USACE) have partnered together to ensure that the liabilities documented in each Formerly Utilized Sites Remedial Action Program (FUSRAP) site's life-cycle baseline are specifically tailored. FUSRAP was created in the mid-1970's to clean up radiological contamination resulting from the early development of nuclear weapons. DOE was responsible for FUSRAP until October 1997, when Congress transferred the administration and execution of FUSRAP site cleanups to USACE. By 1997, DOE had completed the cleanup of 25 of the 46 sites that were active within the program and had begun cleanup at 13 additional sites. USACE was assigned responsibility for the cleanup of the 21 remaining FUSRAP sites, and at 8 additional sites that had since been referred for cleanup. The LM mission for the FUSRAP sites is to perform long-term surveillance and maintenance (LTS and M). Currently, LM provides long-term stewardship for 34 completed FUSRAP sites. Another 20 sites are under active remediation by USACE. Within the last 5 years, USACE has completed the cleanup at five FUSRAP sites and the LTS and M responsibility has been transferred to LM. By 2029, USACE will compete remediation at eight additional sites and LTS and M for those sites will transfer to LM. Because responsibilities for the FUSRAP sites transfer between USACE and LM upon completion of remedial actions, both agencies maintain life-cycle baselines for different stages of the project and both must have a strong understanding of the needs and requirements for each site. This understanding ensures that the life-cycle baselines form a complete and accurate picture of what is required for the site and for the FUSRAP program. LM focuses on several things when customizing the life-cycle baseline estimates for the FUSRAP sites, including (1) Understanding the unique requirements for each site. By reviewing site-specific documents prepared by USACE, such as Feasibility Studies and Records of Decision, and partnering with USACE to gain additional insight about site conditions and requirements for stewardship, as well as potential risks, LM can better develop the life-cycle baselines. (2) Developing site-specific labor breakdowns. This ensures the required labor mix is baselined for specific activities by comparing the labor mix required to perform activities at (a) other LM-managed FUSRAP sites and (b) non-FUSRAP LM sites and (c) by USACE at active FUSRAP sites. (3) Taking a tiered approach to life-cycle baseline planning. Estimates for sites transferring to LM in the near term (5 years) are more definitive than for sites transferring in the out-year period. Remedial actions at the near-term sites are at or near completion, providing LM a strong understanding of the LTS and M requirements and remaining liabilities. This in turn allows for site-specific customization of the baseline. (4) Using a robust risk management approach to ensure that liabilities specific to each site are identified, evaluated by probability and severity, and documented in relation to the impact to cost or schedule. To ensure the most accuracy within all the baselines, the FUSRAP life-cycle baselines are updated as needed to support program, project, and contract management needs. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Using Life Cycle Assessment to Inform CBI Research Priorities

Life cycle assessment (LCA) is used within the Center for Bioenergy Innovation (CBI) to provide information about how feedstock agricultural practices, supply chain logistics, biorefinery operating parameters, and the slate of biofuels and products contribute to environmental impacts, and how CBI's research priorities can result in less impactful biofuel supply chains. This poster provides an overview of the LCA methodology used within CBI and focuses on data needs in general and from other CBI teams. Assumptions and simplifications within biofuel LCA studies are reviewed, including options for modeling multi-functional processes. Calculation details for life cycle environmental impacts used within CBI - global warming potential, cumulative energy demand, and the Available Water Remaining indicator - are presented, along with a discussion of carbon intensity as an alternative metric for evaluating sustainable aviation fuel and other biofuels. The process of interpreting impact results to guide research priorities is discussed, with examples drawn from CBI's upcoming manuscript on switchgrass yield and cell wall composition.

bioenergy↗

Life Cycle Analysis of Thermoelectric Power Generation in the United States

In this article, the basics of performing a life cycle analysis of thermoelectric power generation are discussed, with three examples of life cycle greenhouse gas (GHG) balances for thermoelectric power generation forms: coal, natural gas, and nuclear. The final section compares multiple electricity generation methods in the United States. Results are presented on the basis of 1 megawatt-hour (MWh) of electricity delivered to the end user. Environmental life cycle results for greenhouse gas (GHG) emissions are presented as carbon dioxide equivalents, based on 100-year global warming potentials (GWPs) established by the 6th Assessment Report from the Intergovernmental Panel on Climate Change in 2021, commonly referred to as AR6 GWP values (IPCC, 2021). Additional details on other environmental life cycle impacts from non-GHG emissions to air, emissions to water, solid waste generation, and land use are available on the Department of Energy, National Energy Technology Laboratory’s Life Cycle Analysis website: www.netl.doe.gov/LCA.

Cutshaw, Ashley↗

2016 US Petroleum fuels Life Cycle Baseline Data Package

This data package accompanies the report "2016 U.S. Petroleum Fuels Life Cycle Baseline." It contains the openLCA life cycle model that generated the results and an Excel spreadsheet that contains well-to-tank life cycle inventory for all products.

Life Cycle Analysis Options - Fuels↗

Life-Cycle Cost Analysis Framework for Water Efficiency Measures

Life-Cycle Cost Analysis Framework for Water Efficiency Measures: Guidance Designed for Federal Agencies (hereafter referred to as “this report”) provides a technical framework for federal agencies to conduct a life-cycle cost analysis (LCCA) for water efficiency projects in accordance with 42 U.S.C. § 8253. This report leverages insights from the 2023 report, PNNL-34006, Water and Wastewater Annual Price Escalation Rates for Selected Cities Across the United States: 2023 Edition (Unger et al. 2023). The primary objective of this report is to provide a framework to assist federal agencies with evaluating the full economic impact of water efficiency projects by assessing both initial investments and long-term operational benefits. An LCCA can provide a comprehensive view of all costs associated with a water efficiency project, including initial investment, ongoing operations and maintenance (O&M), and eventual disposal or replacement, ensuring the most cost-effective solution is selected. The LCCA methodology outlined in this report enables users to compare base case scenarios with potential alternatives using a standardized present value approach. It incorporates key cost components such as energy, water and wastewater, installation, O&M, and equipment replacement. Additionally, the framework introduces relevant evaluation metrics, such as the net savings and the savings-to-investment ratio, to ensure that water efficiency measures are economically justified over the lifespan of the project. To support practical application, this report also describes various water efficiency strategies that may be analyzed using an LCCA, including plumbing retrofits, irrigation upgrades, alternative water use, and cooling system improvements. By applying this framework, federal agencies can ensure compliance with regulatory mandates while maximizing the return on investment and contributing to resilient water management practices. The information provided in this report is aligned with the Federal Energy Management Program (FEMP) life-cycle cost (LCC) methodology, as conveyed in National Institute of Standards and Technology (NIST) Handbook 135 (Kneifel and Webb 2022). This report is intended to provide relatively high-level guidance, acting as a complement to, rather than a substitute for, that resource.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

CRADA Final Report: Ultralong Cycle Life and Ultrafast Charging Batteries to Electrify High Duty-Cycle, Mobile Platforms

As part of the Cyclotron Road program, Tyfast Energy Corp. aimed to investigate the Li 3 V 2 O 5 (LVO) anode material for next generation lithium batteries. State of the art and fast charging lithium-ion batteries are based on the lithium titanate or Li 4 Ti 5 O 12 (LTO) anode chemistry. LTO cells demonstrate fast charging times (<6 mins), long cycle life (>20,000 cycles), but at the expense of very low energy density (<200Wh/L, <80Wh/kg). Silicon anodes have the promise of achieving fast charging times, however, issues with cycling stability in combination with fast charging is unknown. LVO has unique properties that enable new performance window for lithium batteries. First, LVO operates at an average potential of 0.6V vs. Li/Li + , well above the Li-metal plating region allowing ultrafast charge capability without sacrificing safety. Second, the LVO has a high specific capacity of 250 mAh/g making battery pack energy density equivalent with current high-energy Li-ion chemistries.

25 ENERGY STORAGE↗

Projecting Life-Cycle Environmental Impacts of Corn Production in the U.S. Midwest under Future Climate Scenarios using machine learning approach

Emission factors and process-based mechanism models are popular approaches used to estimate life-cycle environmental impacts. However, emission factors are often incapable of describing spatial and temporal heterogeneity of agricultural emissions, whereas process-based mechanism models, capable of capturing the heterogeneity, tend to be very complicated, and time-consuming. Efficient predictions of life-cycle environmental impacts from agricultural production are lacking. This study develops a rapid predictive model to quantify life-cycle global warming (GW), eutrophication (EU) and acidification (AD) impacts of corn production using a novel machine learning approach. We used the boosted regression tree (BRT) model to estimate current and future life-cycle environmental impacts of corn production in 12 U.S. Midwest at county scale under four Intergovernmental Panel on Climate Change (IPCC)’s climate scenarios (RCP2.6. 4.5, 6.0, and 8.5) for years 2009-2100. Results show that future life-cycle GW, EU and AD impacts of corn production will increase under all four scenarios, with the worst environmental impacts shown under the RCP 8.5 scenario. Significant spatial variation were estimated to be 3.6, 29.9 and 1.8-folds under the RCP4.5 scenario, and 6.6, 152.9 and 1.6-folds under the RCP8.5 scenario, respectively. Findings from this study demonstrate the importance of considering county-level life-cycle environmental impacts and the influences of climate change in future years to aid in developing potential adaptation and mitigation programs and policies.

Machine learning, climate change, projections, env↗

Comparative Life Cycle Analysis of Scalable Single-Junction and Tandem Perovskite Solar Cell (PSC) Systems

Efficient, low-cost solar cells based upon perovskites have the potential to transform the US and global energy portfolio and improve energy security if they can be manufactured in an environmentally sustainable manner. However, previous life cycle analyses (LCA) of perovskite solar cells (PSC) used lab recipes to project the environmental impact of industrial PSC production – using materials and processes that may not be representative of industrial productions due to high material waste and complex synthesis – and such studies were limited to a few single-junction technologies. Thus, the goal of this project was threefold: a) to review the most promising for industrial production single-junction and tandem PSC technologies, b) to build life-cycle materials inventories that reflect scalable production of these technologies, and c) to conduct comprehensive life-cycle analysis of these technologies and compare their environmental impact with those of established commercial technologies. In response, this project identified challenges for fabrication transitioning from laboratory to sustainable industrial production, developed life-cycle inventory (LCI) data for scaling to industrial production four promising single-junction and three tandem PSC systems and produced life-cycle-investigations using, as metrics, a complete spectrum of energy, environmental and ecological impact indicators. Special focus was given to the use of lead, silver and indium in PSC. The project used the Life Cycle Assessment (LCA) methodology as standardized by the Society of Environmental Toxicology and Chemistry (SETAC), ISO standards 14040 and 14044, and the International Energy Agency PVPS Task 12 LCA guidelines. LCA allows the calculation of a number of energy and environmental and impact categories, including energy cumulative energy demand (CED), global warming potential (GWP), human toxicity potential (HTP), eco-toxicity potential (ETP), abiotic resource depletion potential (ADP), acidification potential (AP), ozone depletion potential (ODP), photochemical oxidation potential (POP), eutrophication potential (EP). In addition to those, we calculated the Energy Pay-Back Time (EPBT) and the Energy Return On Investment (EROI). We provide LCA impacts for complete perovskite PV systems – including balance of system components – installed at three irradiation levels and considering reference and future potential module efficiencies. Finally, a sensitivity analysis on perovskite lifetime has been performed, considering 10, 20 and 30 years. Contribution analysis of the impacts of each material and layer of PSC shows, that the use of Pb in metalorganic PSC does not result in significant environmental impacts as the major contributions to environmental indicators arise from the use of Ag and encapsulation materials. Solution-based PSC manufacturing was found to be less impactful to the environment than vapor-based fabrication, and roll-to-roll (RtR) printing uses less energy and generates the lowest emissions. PSC produced with RtR manufacturing could reach the same Energy Return on Energy Investment (EROI) as that of crystalline-Si PV within 12 years of life, whereas the most energy demanding spray coating on rigid substrates, would require a 20-yr life to match the EROI of 30-yr lasting silicon PV. This work lays the foundation for sustainability investigations in a comparative context of large-scale production and deployment of PSC. The results of this project have the potential to have a significant impact on the future of PV manufacturing, by providing industry, policy-makers, and academia with insights necessary to choose which, if any, lead-based solar cell life cycles are environmentally sustainable.

14 SOLAR ENERGY↗

Electrolyte and Cutoff Potential Effects on Cycle Life of Li4Ti5O12/LiNi0.9Mn0.1O2 Batteries for Behind-the-Meter Storage Applications

Behind-the-Meter Storage (BTMS) is a stationary battery energy storage system that is connected to the electrical distribution system on the customer's side of the utility's service meter. BTMS systems are used to store electrical energy from the grid as well as inconstant, renewable energy, such as local solar and wind generation. A successful BTMS system will allow the customer to pair their energy generation and storage to optimize electrical consumption from the grid, improving reliability and minimizing cost. For BTMS applications, batteries must be designed and optimized with different set of criteria from other leading segments of the Li-ion battery market, like transportation, due the system being stationary and proximal to the residential or commercial building it's benefitting. BTMS applications prioritize safety, cost (low/no-critical materials), reliability (20-year calendar life), and durability (10,000 cycle life), while having the ability to (minimally) compromise energy density and rate capability. Lithium titanate (Li4Ti5O12-, LTO) is a promising anode candidate for BTMS applications due to its high safety and capacity retention, while maintaining a reasonable 160 mAhg-1 reversable capacity and composition of relatively abundant materials. (1) Specifically, LTO has a high working voltage which helps to prevent Li dendrite formation, improving safety. Furthermore, LTO also has negligible lithiation-based volume change, leading to less mechanical pulverization, or loss of active material, upon cycling. For the cathode, materials with little or no Co are of high interest due to the high cost and low abundance of Co. LiMn2O4 (LMO) has been paired with LTO for BTMS applications in the past due to its safety, low cost (abundancy), and reasonably high operating voltage. (2-4) However, the low capacity of LMO limits energy density and specific energy. While not the highest priority for BTMS applications, increasing energy density will enable deployment in space constrained BTMS applications and decrease total cost. LiNi0.9Mn0.1O2 (LN-MO) is a recently developed material with promise due to its high operating voltage and relatively low price. (5) However, Ni-rich layered oxides, including LNMO, tend to struggle with capacity retention during high-voltage cycling due to mechanical pulverization, irreversible phase transitions, and unstable solid-electrolyte interphase. The study presented here focuses on building an understanding of how electrolyte solvent and varied cutoff potentials will impact the cycle life of LTO/LN-MO cells. Specifically, a comparison is provided between ethylene carbonate (EC), ethyl methyl carbonate (EMC), fluoroethylene carbonate (FEC), and Gen2 electrolyte solvents with 1M Lithium hexafluorophosphate (LiPF6) salt, cycling to two upper termination potentials, 2.6V and 2.7V. Electrochemical testing and diagnostics (e.g., differential capacity analysis, area specific impedance, constant voltage hold, and rate capability) and post-mortem characterization will be used to understand the aging behavior and failure mechanisms of the 8 cell combinations (four electrolytes and two voltage cutoffs). Cells with FEC electrolyte showed a lower initial capacity compared to cells with Gen2, EMC, and EC cycling at both voltages; however, the cells with FEC showed consistent trends in capacity retention with 2.6V and 2.7V termination potentials, while the cells with the other electrolytes showed much higher rates of capacity loss when cycling to the higher voltage. These results indicate that FEC may play a role in improving durability of high-voltage, Ni-rich electrode systems for use in high-cycle applications, such as BTMS.

electrolyte↗