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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Quantum channel capacities

A brief general review is presented of the theory of information transmission capacities of quantum communication channels, which is a development of the classical Shannon theory. Unlike a classical communication channel, a quantum channel is characterised by a whole set of different capacities, which depend on the type of transmitted information (classical or quantum) and on additional resources used during transmission. The main characteristics of a quantum channel are considered: classical capacity, capacity assisted by entanglement between the channel input and output, quantum capacity and secret classical capacity. The unique role of the quantum entanglement property, which manifests itself, in particular, in a nonclassical phenomenon of capacity superadditivity, is emphasised. (paper)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Revealing the Mechanism Behind Sudden Capacity Loss in Lithium Metal Batteries

Rechargeable Li-metal batteries (LMBs) are attractive energy storage candidates for electric vehicles (EVs) because they offer higher energy density than batteries built with intercalation electrodes. However, one of the main barriers to the commercial deployment of LMBs has been their relatively short cycle life. Re-designing the electrolyte system shows promise in achieving acceptable cycle life, but even so, the resulting cells display a challenging end-of-life (EOL) behavior: a sudden capacity loss. Herein, we report a new method for analyzing voltage profiles during cycling to distinguish between the capacity loss originating from the loss of cathode capacity vs growth in cell resistance. Further, this analysis reveals that sudden capacity loss was preceded by acceleration in the rate of growth of cell resistance, and cycling of multiple cells showed that this phenomenon is sensitive to the initial quantity of electrolyte in the cells. In contrast, the cathode capacity degraded at a constant rate independent of the electrolyte quantity. Combining this evidence with post-analysis of harvested electrolyte and electrodes, we conclude that neither the loss of active lithium nor the loss of active cathode material was the primary source of sudden capacity loss; instead, consumption and decomposition of electrolyte causes the drastic capacity loss at EOL.

25 ENERGY STORAGE↗
DOE OSTI2025

Stable Cycling of Sodium All‐Solid‐State Batteries with High‐Capacity Cathode Presodiation

Sodium all-solid-state batteries (NaSSBs) with an alloy-type anode (e.g., Sn and Sb) offer superior capacity and energy density compared to hard carbon anode. However, the irreversible loss of Na + at the alloy anode during the initial cycle results in diminished capacity and stability, impairing full-cell performance. Here, this study presents an easy-to-implement cathode presodiation strategy by employing a Na-rich material to address these challenges. Leveraging the high theoretical capacity and suitable voltage window, Na 2 S is chosen as the Na donor, which is activated by creating a mixed electron-ion conducting network, delivering a high capacity of 511.7 mAh g −1 . By adding a small amount (i.e., 3 wt.%) of Na 2 S to the cathode composite, a NaCrO 2 || Sn full cell demonstrated capacity improvement from 90.8 to 118.2 mAh g −1 (based on cathode mass). The capacity-balanced full cell can thus cycle to more than 300 times with >90% capacity retention. This work provides a practical solution to enhance the full-cell performance and advance the transformation from half-cell to full-cell applications of NaSSBs.

25 - ENERGY STORAGE↗
DOE OSTI2020

Probing Sources of Capacity Fade in LiNi 0.6 Mn 0.2 Co 0.2 O 2 (NMC622): An Operando XRD Study of Li/NMC622 Batteries during Extended Cycling

LiNi 0.6 Mn 0.2 Co 0.2 O 2 (NMC622) is one of the most promising Li-ion battery cathodes as it delivers high capacity at high potentials. However high potentials also lead to decreases in capacity retention where the disintegration of the secondary particles has been implicated as a major driving force of this capacity fade. This has been attributed to anisotropic lattice changes and increased microstrain during cycling. To probe how these factors affect capacity fade, Li/NMC622 batteries were cycled from 3-4.3 or 4.7 V and probed with operando X-ray diffraction over the 1st, 2nd, and 101st cycles. Further characterization with scanning electron microscopy, and inductively coupled plasmaoptical emission spectroscopy was also performed. The use of operando XRD over many cycles allowed for the collection of detailed structural information in real time over a time frame in which fading can be observed. During the first two cycles, the cells charged to 4.7 V exhibit increased anisotropic lattice changes as compared to the cells charged to 4.3 V. Upon the 101st cycle, when significant fade has been observed, the cells charged to 4.3 and 4.7 V show identical lattice changes to one another, while the 4.7 V charge limit induces more microstrain. This shows that elevated microstrain at high charge limits is a major driver for particle disintegration in NMC622 cathodes. This study provides important insights into the mechanisms of particle disintegration and capacity fade in NMC/Li-ion batteries, which will enable the design of NMC electrodes that deliver both higher capacities and exhibit better capacity retention.

25 ENERGY STORAGE↗
DOE OSTI2025

Porous and Amorphous Mn x Mo 3 S 13 Chalcogel Electrode for High-Capacity Conversion-Based Lithium-Ion Batteries

While Li-ion batteries (LIBs) are a leading energy storage technology, their energy densities are limited by the low capacity of conventional intercalation cathodes, driving interest in high energy-density Li–S batteries that make use of conversion chemistry. Achieving high capacity, reversibility, and cycle stability, and controlling volume changes in conversion batteries during the charge–discharge process, however, remains challenging. Here, in this study, we present a porous, amorphous, sulfide-based Mn x Mo 3 S 13 chalcogel, which concurrently offers high capacity and cycle stability. The solution-processable room temperature synthesized Mn x Mo 3 S 13 (x = 0.25) chalcogel exhibits a local structure that resembles the Mo 3 S 13 cluster with Mn 2+ distributed across the Mo 3 S 13 matrix, as determined by synchrotron X-ray pair distribution function (PDF) and extended X-ray absorption fine structure (EXAFS). Ab initio molecular dynamics (AIMD) simulations reveal that Mn 2+ incorporation shortens the polysulfide chain in the gel matrix compared to the Mo 3 S 13 chalcogel, while forming a coordination environment with disulfide groups, analogous to the experimental findings. A Li/Mn 0.25 Mo 3 S 13 half-cell delivers 897 mAh g –1 capacity during the first discharge and retains 571 mAh g –1 capacity after 100 cycles at a C/3 rate. Distribution of relaxation time (DRT) unveils a stable solid–electrolyte interphase (SEI) formation upon cycling that enables charge–discharge reversibility. Here, the enhanced capacity retention and cycle stability compared to those of the Li/Mo 3 S 13 cell are attributed to the reduced dissolution of active mass into the electrolyte, facilitated by the formation of shorter polysulfide chains within the Mn 0.25 Mo 3 S 13 structure and the strong affinity of Lewis-acidic Mn 2+ for polysulfide anions generated during the charge–discharge process of the Li/Mn 0.25 Mo 3 S 13 cell. Thus, this work illustrates a design principle of material for high-capacity and cycle-stable Li-metal sulfide batteries.

25 ENERGY STORAGE↗
DOE OSTI2022

Global stocks and capacity of mineral-associated soil organic carbon

Abstract Soil is the largest terrestrial reservoir of organic carbon and is central for climate change mitigation and carbon-climate feedbacks. Chemical and physical associations of soil carbon with minerals play a critical role in carbon storage, but the amount and global capacity for storage in this form remain unquantified. Here, we produce spatially-resolved global estimates of mineral-associated organic carbon stocks and carbon-storage capacity by analyzing 1144 globally-distributed soil profiles. We show that current stocks total 899 Pg C to a depth of 1 m in non-permafrost mineral soils. Although this constitutes 66% and 70% of soil carbon in surface and deeper layers, respectively, it is only 42% and 21% of the mineralogical capacity. Regions under agricultural management and deeper soil layers show the largest undersaturation of mineral-associated carbon. Critically, the degree of undersaturation indicates sequestration efficiency over years to decades. We show that, across 103 carbon-accrual measurements spanning management interventions globally, soils furthest from their mineralogical capacity are more effective at accruing carbon; sequestration rates average 3-times higher in soils at one tenth of their capacity compared to soils at one half of their capacity. Our findings provide insights into the world’s soils, their capacity to store carbon, and priority regions and actions for soil carbon management.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Heat capacity of microgram oxide samples by fast scanning calorimetry

Quantitative scanning calorimetry on microgram-sized samples opens a broad, new range of opportunities for studying the thermodynamic properties of quantity-limited materials, including those produced under extreme conditions or found as rare accessory minerals in nature. We calibrated the Mettler Toledo Flash DSC 2+ calorimeter to obtain quantitative heat capacities in the range 200–350 °C, using samples weighing between 2 and 11.5 μg. Our technique is applied to a new set of oxide materials to which it has never been used before, without the need for melting, glass transitions, or phase transformations. Heat capacity data were obtained for silica in the high pressure stishovite (rutile) structure, dense post-stishovite glass, standard fused quartz, and for TiO2 rutile. These heat capacities agree within 5%–15% with the literature values reported for rutile, stishovite, and fused SiO2 glass. The heat capacity of post-stishovite glass, made by heating stishovite to 1000 °C, is a newly reported value. After accurate calibrations, measured heat capacities were then used to calculate masses for samples in the microgram range, a substantial improvement over measurement in conventional microbalances, which have uncertainties approaching 50%–100% for such small samples. Since the typical uncertainty of heat capacities measured on 10–100 mg samples in conventional differential scanning calorimetry is typically 7% (1%–5% with careful work), flash differential scanning calorimetry, using samples a factor of 1000 smaller, increases the uncertainty of heat capacity measurements by a factor of <3, opening the door for meaningful measurements on ultra-small, high-pressure samples and other quantity-limited materials.

Instruments & Instrumentation↗
DOE OSTI2026

Capacities of Entanglement Distribution From a Central Source

Distribution of entanglement is an essential task in quantum information processing and the realization of quantum networks. In our work, we theoretically investigate the scenario where a central source prepares an N -partite entangled state and transmits each entangled subsystem to one of N receivers through noisy quantum channels. The receivers are then able to perform local operations assisted by unlimited classical communication to distill target entangled states from the noisy channel output. In this operational context, we define the EPR distribution capacity and the GHZ distribution capacity of a quantum channel as the largest rates at which Einstein-Podolsky-Rosen (EPR) states and Greenberger-Horne-Zeilinger (GHZ) states can be faithfully distributed through the channel, respectively. We establish lower and upper bounds on the EPR distribution capacity by connecting it with the task of assisted entanglement distillation. We also construct an explicit protocol consisting of a combination of a quantum communication code and a classical-post-processing-assisted entanglement generation code, which yields a simple achievable lower bound for generic channels. As applications of these results, we give an exact expression for the EPR distribution capacity over two erasure channels and bounds on the EPR distribution capacity over two generalized amplitude damping channels. We also bound the GHZ distribution capacity, which results in an exact characterization of the GHZ distribution capacity when the most noisy channel is a dephasing channel.

42 ENGINEERING↗
DOE OSTI2024

Capacity Fade of Graphite/NMC811: Influence of Particle Morphology, Electrolyte, and Charge Voltage

LiNi 0.8 Mn 0.1 Co 0.1 O 2 (NMC811) is an important Li-ion battery cathode material; however, there is a tradeoff between delivered capacity and capacity retention. As the charge potential increases the capacity rises but at the expense of capacity retention. The decrease in capacity retention has been ascribed to several factors including particle cracking, surface reconstruction, transition metal dissolution, and electrolyte reactivity. The present study compares 4.1 and 4.3 V charging limits in commercially relevant graphite/NMC811 pouch cells for single crystal (SC) and polycrystalline (PC) NMC811 with ethylene carbonate (EC)-containing or EC-free electrolytes. The electrochemistry is rationalized through analysis of electrochemical impedance spectroscopy, positive electrode X-ray photoelectron spectroscopy, soft X-ray absorption spectroscopy, X-ray diffraction, and negative electrode mapping by X-ray fluorescence. Graphite/SC-NMC811 cells show high-capacity retention at 4.1 V but exhibit degradation at 4.3 V charging potentials. The EC-free electrolyte cells led to higher capacity fade, especially when charged to 4.3 V. Cathode dissolution and deposition on the negative electrode from PC-NMC811 cells was higher than for samples from SC-NMC811 cells. This study reveals the impact of material type, charge voltage, and electrolyte composition on the reactions at the positive electrode, their influence on the negative electrode, and evolution with cycle number.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Grid Capacity – What is it, what determines it, does one number work, and how does it relate to electric vehicles?

Grid capacity is effectively how much power the system can reliably deliver, whether that is to serve loads (load service capacity) or accept generation (hosting capacity). Grid capacity can also mean different things at different scales. On the whole power system, grid capacity may be the maximum amount of power generation available. For a specific region, grid capacity may be limited by how much power the transmission and distribution lines can safely carry to that region. At the feeder level, it may be how much photovoltaic generation can be included before reliability or operations are impacted. At the end-use or residential level, grid capacity may be the size of the service breaker for that house.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

IDAES Enterprise: Generation Expansion Planning with Enhanced Requirements for Capacity Adequacy Under Renewable Intermittency

Achieving net zero carbon emissions likely requires future power systems to integrate new, flexible energy technologies to accommodate higher levels of capacity from variable renewable energy sources. To determine the optimal deployment of new electricity capacity and to study the likelihood of deployments of new energy technologies, an expansion planning model has been developed as part of the IDAES-Enterprise suite of grid models. The Generation Expansion Planning (GEP) model is a multi-period model in which investment decisions occur yearly, and a Unit Commitment (UC) problem is examined on an hourly timescale. To reduce computational complexity of the GEP model, the UC problem is solved for average “representative days” which leaves out extreme, but relatively common, scenarios in which low renewable generation occurs, leaving the system with inadequacy in capacity. The IDAES-Enterprise GEP model has been modified to include these extreme scenarios while keeping the model reasonably tractable. Specifically, a lazy constraint technique was implemented to check for capacity adequacy on an hourly basis over a large data set of aligned load-wind-solar profiles. As a vast majority of the capacity constraints will not be violated, the technique lowers computational expense by searching for violated capacity constraints over an “iterative manner,” adding those infeasible constraints back into the model. Results on a test case of the Southwest Power Pool shows that the lazy constraint technique significantly reduces retirements and increases installments of natural gas combined cycles and flexible natural gas units. It also reduces some retirements of coal units. These modifications provide a more reasonable estimation of required dispatchable power generation capacity to ensure feasibility during peak net load.

Liu, Peng↗
DOE OSTI2024

Novel One-Step Production of Carbon-Coated Sn Nanoparticles for High-Capacity Anodes in Lithium-Ion Batteries

Lithium-ion batteries offer the highest energy density of any currently available portable energy storage technology. By using different anode materials, these batteries could have an even greater energy density. One material, tin, has a theoretical lithium capacity (994 mAh/g) over three-times higher than commercial carbon anode materials. Unfortunately, to achieve this high capacity, bulk tin undergoes a large volume expansion, and the material pulverizes during cycling, giving a rapid capacity fade. To mitigate this issue, tin must be scaled down to the nano-level to take advantage of unique micromechanics at the nanoscale. Synthesis techniques for Sn nanoparticle anodes are costly and overly complicated for commercial production. A novel one-step process for producing carbon-coated Sn nanoparticles via spark plasma erosion (SPE) shows great promise as a simple, inexpensive production method. The SPE method, characterization of the resulting particles, and their high-capacity reversible electrochemical performance as anodes are described. With only a 10% addition of these novel SPE carbon-coated Sn particles, one anode composition demonstrated a reversible capacity of ~460 mAh/g, achieving the theoretical capacity of that particular electrode formulation. These SPE carbon-coated Sn nanoparticles are drop-in ready for present commercial lithium-ion anode processing and would provide a ~10% increase in the total capacity of current commercial lithium-ion cells.

25 ENERGY STORAGE↗
NASA NTRS2003

Mapping Soil pH Buffering Capacity of Selected Fields

Soil pH buffering capacity, since it varies spatially within crop production fields, may be used to define sampling zones to assess lime requirement, or for modeling changes in soil pH when acid forming fertilizers or manures are added to a field. Our objective was to develop a procedure to map this soil property. One hundred thirty six soil samples (0 to 15 cm depth) from three Georgia Coastal Plain fields were titrated with calcium hydroxide to characterize differences in pH buffering capacity of the soils. Since the relationship between soil pH and added calcium hydroxide was approximately linear for all samples up to pH 6.5, the slope values of these linear relationships for all soils were regressed on the organic C and clay contents of the 136 soil samples using multiple linear regression. The equation that fit the data best was b (slope of pH vs. lime added) = 0.00029 - 0.00003 * % clay + 0.00135 * % O/C, r(exp 2) = 0.68. This equation was applied within geographic information system (GIS) software to create maps of soil pH buffering capacity for the three fields. When the mapped values of the pH buffering capacity were compared with measured values for a total of 18 locations in the three fields, there was good general agreement. A regression of directly measured pH buffering capacities on mapped pH buffering capacities at the field locations for these samples gave an r(exp 2) of 0.88 with a slope of 1.04 for a group of soils that varied approximately tenfold in their pH buffering capacities.

Weaver, A. R.↗
NASA NTRS2016

Prediction of Weather Impacts on Airport Arrival Meter Fix Capacity

This paper introduces a data driven model for predicting airport arrival capacity with a look-ahead time 2-8 hour forecast. The model is suitable for air traffic flow management by explicitly investigating the impact of convective weather on airport arrival meter fix throughput. Estimation of the arrival airport capacity under arrival meter fix flow constraints due to severe weather is an important part of Air Traffic Management (ATM). Airport arrival capacity can be reduced if one or more airport arrival meter fixes are partially or completely blocked by convective weather. When the predicted airport arrival demands exceed the predicted available airport's arrival capacity for a sustained period, Ground Delay Program (GDP) operations will be triggered by ATM system. Serious imbalances between demand and capacity occur most frequently when the airport capacity is severely degraded due to either bad airport terminal surface weather or inclement convective weather around airport arrival fixes. A model that predicts the weather-impacted airport arrival meter fix throughput may help ATM personnel to plan GDP operations more efficiently. This paper identifies the characteristics of air traffic flow across arrival meter fixes at Newark Liberty International Airport (EWR). The proposed approach, based on machine-learning methods, is developed to predict the weather impacted EWR arrival Meter Fix (MF) throughput. Sector forecast coverage is used to envision the weather impact on airport arrival MF flow, and the validation is accomplished by using Convective Weather Avoidance Model (CWAM) 0.5 to 2-hour and Collaborative Convective Forecast Product (CCFP) 4 to 8-hour look-ahead forecast data for the period of April-September in 2014. Furthermore, the regression tree ensemble learning of random forests approach for translating a sector forecast coverage model to an EWR arrival meter fix throughput model is examined. The results suggest that ATM decision makers in charge of MF flow control and GDP planning may benefit from adopting the airport arrival meter capacity prediction models to estimate the inclement weather impacts.

Wang, Yao X.↗
NASA NTRS2018

Recommendations Emerging from an Analysis of NASA's Deep Space Communications Capacity

During 2016-2017, NASA’s Space Communications and Navigation (SCaN) Office chartered a study of Deep Space Network (DSN) communications capacity relative to projected future-mission demand over the next 30 years. In this paper, we briefly describe the methodology used to analyze capacity vs. demand over such a broad timeframe, summarize key findings emerging from the analysis, and discuss the associated recommendations. Performing the analysis entailed: identifying key factors shaping the anticipated future mission set, identifying several alternative future mission set scenarios consistent with these factors, and then analyzing each mission set scenario in terms of required antenna capacity, downlink and uplink capabilities, and spectrum as a function of time. On the basis of these aggregate requirements, DSN loading simulations were then conducted that examined how well each of the postulated mission sets could load up onto the the DSN’s “in-plan” architecture. To the extent that capacity shortfalls emerged during these baseline simulations, architectural solutions to the shortfalls were then postulated and tested via additional simulations. In general, the trend analyses and baseline loading simulations indicated a significant progression in challenges over the next three decades. In the current decade, the DSN appeared to be operating very close to capacity. The first human exploration mission and its secondary payload launch opportunities for cubesats traveling beyond GEO contributed to this loading. As a consequence, the main challenge appeared to be managing peak assetcontention periods. In the next decade, the DSN continued to operate close to capacity but also began transitioning to more frequent human mission support. Upgrading for, and operating, a human-rated system while continuing to meet robotic mission customer requirements emerged as the key challenge. In the 2030’s and beyond, simulations suggested a need for fundamentally new capability and capacity. The high data rates and long link distances characteristic of human Mars exploration drove requirements far beyond what is currently “in plan.” The key challenge then became determining the most cost-effective combination of RF and optical assets for communicating with the postulated human Mars assets while still providing for the needs of all the other missions across the solar system. Various link budget, visibility, and loading analyses ultimately suggested that the human Mars exploration demands of the 2030’s could best be addressed with two cross-linked RF-optical areostationary relays (or an areostationary relay and deep space habitat) providing a dual “trunk link” to an array of 2-to-3 additional 34m beam waveguide antennas and an ~8.5m optical antenna at each DSN Complex. The dual “trunk link” would enable the same amount of total data return to Earth as a single trunk link at twice the data rate, but with only half the required array size on the ground, assuming use of Multiple Spacecraft Per Antenna (MSPA) techniques. MSPA techniques, including a Multiple Uplink Per Antenna (MUPA) technique currently under investigation, also showed promise for reducing asset contention in the decades prior to human Mars exploration.

Lee, Carlyn-Ann↗
DOE OSTI2023

Information Processing Capacity of Spintronic Oscillator

Physical reservoir computing is a framework that enables energy‐efficient information processing by using physical systems. Nonlinear dynamics in physical systems provide a computational capability that is unique to reservoirs. It is, however, difficult to find an appropriate task for a reservoir because of the complexity of nonlinear information processing. The information processing capacity has recently been used to clarify systematically the tasks that are solved by reservoirs; it quantifies the memory capacity of reservoirs in accordance with the order of nonlinearity. Herein, an experimental evaluation of the information processing capacity of a spintronic oscillator consisting of nanostructured ferromagnets is reported. The spintronic reservoir state is electrically manipulated by adding a delayed‐feedback circuit. The total capacity reaches a maximum of 5.6 at the edge of the echo state property. A trade‐off between the linear and nonlinear components of the capacity is also found. The result can be used to better understand the nonlinear information processing in reservoirs and to find good matches between reservoirs and tasks. As an example, a function‐approximation task is performed and it is found that it can be efficiently solved when the reservoir state is appropriately tuned so that its information processing capacity matches that of the task.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Revisiting the initial irreversible capacity loss of LiNi 0.6 Co 0.2 Mn 0.2 O 2 cathode material batteries

Layered LiNi 0.6 Co 0.2 Mn 0.2 O 2 (NCM622) attracts widespread attention primarily due to its potential for high energy density and moderate thermal stability. However, the low initial coulombic efficiency (ICE) of the material limits the maximum utilization of their capacity. The capacity loss in the first cycle occurs under 4.0V and keep almost constant are considered as common characteristics for NCM-based materials. A clear cognition on the initial capacity loss may light the way to improve the practical reversible capacity of NCM622 at 4.0V. Conducting operando X-ray diffraction during galvanostatic charge/discharge cycling at different temperature (25 degrees C, 45 degrees C and 60 degrees C) and different current (0.1C, 0.01C, 1C=120 mA g -1 ) in the voltage range of 2.7-4.0V, we find that only 8% of the measured initial irreversible capacity loss is associated with parasitic reactions that form cathode/electrolyte interface, and that the dominant contributors include the slow Li + diffusion kinetics (similar to 46% contribution) and irreversible O3/H1-3 phase transition (similar to 46% contribution). Finally, this semi-quantitative study provides new insight on initial capacity loss, guiding further targeted modification and fully utilization of NCM622.

25 ENERGY STORAGE↗
DOE OSTI2022

Forecasting battery capacity and power degradation with multi-task learning

Lithium-ion batteries degrade due to usage and exposure to environmental conditions, which affects their capability to store energy and supply power. Accurately predicting the capacity and power fade of lithium-ion battery cells is challenging due to intrinsic manufacturing variances and coupled nonlinear ageing mechanisms. In this paper, we propose a data-driven prognostics framework to predict both capacity and power fade simultaneously with multi-task learning. The model is able to predict the degradation trajectory of both capacity and internal resistance together with knee-points and end-of-life points accurately at early-life stage. The validation shows an average percentage error of 2.37% and 1.24% for the prediction of capacity fade and resistance rise, respectively. The model's ability to accurately predict the degradation, facing capacity and resistance estimation errors, further demonstrates the model's robustness and generalizability. Compared with single-task learning models for forecasting capacity and power degradation, the model shows a significant prediction accuracy improvement and computational cost reduction. This work presents the highlights of multi-task learning in the degradation prognostics for lithium-ion batteries.

25 ENERGY STORAGE↗