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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Overcoming the conversion reaction limitation at three-phase interfaces using mixed conductors towards energy-dense solid-state Li–S batteries

Lithium–sulfur (Li–S) all-solid-state batteries (ASSBs) hold great promise for next-generation safe, durable and energy-dense battery technology. However, solid-state sulfur conversion reactions are kinetically sluggish and primarily constrained to the restricted three-phase boundary area of sulfur, carbon and solid electrolytes, making it challenging to achieve high sulfur utilization. Here, in this study, we develop and implement mixed ionic–electronic conductors (MIECs) in sulfur cathodes to replace conventional solid electrolytes and invoke conversion reactions at sulfur–MIEC interfaces in addition to traditional three-phase boundaries. Microscopic and tomographic analyses reveal the emergence of mixed-conducting domains embedded in sulfur at sulfur–MIEC boundaries, helping promote the thorough conversion of active sulfur into Li 2 S. Consequently, substantially improved active sulfur ratios (up to 87.3%) and conversion degrees (>94%) are achieved in Li–S ASSBs with high discharge capacity (>1,450 mAh g –1 ) and long cycle life (>1,000 cycles). The strategy is also applied to enhance the active material utilization of other conversion cathodes.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Intelligence-assisted predesign for the sustainable recycling of lithium-ion batteries and beyond

The unprecedented consumption of lithium-ion batteries (LIBs) is occurring to meet the needs of modern transportation electrification. Recycling-friendly designs intrinsically facilitate the long-term sustainable utilization of natural resources, reducing the detrimental impacts of spent LIBs on the environment, and improving the economic viability of recycling. For this, we propose the incorporation of an intelligence-assisted predesign strategy into the battery-management system and battery chemistry, including ameliorating the traceability of battery structure and operation status, promoting cost-effective material sorting and separation, and adopting sustainable battery materials. The purposeful predesign of intelligent “Reuse–Refurbish–Recover” (3R) LIBs could be realized in an economically and environmentally sustainable (EES) manner. We report the intelligence-assisted predesign strategy will promote multi-disciplinary cooperation in a systematic and synergetic way; in addition, it will empower governments to establish and implement a series of regulations and standards for addressing the environmental pollution issues from spent batteries, thus avoiding the ever-increasing consumption of natural resources.

25 ENERGY STORAGE↗
DOE OSTI2024

Manganese-rich high entropy oxides for lithium-ion batteries:materials design approaches to address voltage fade

Lithium- and manganese-rich oxides are of interest as lithium-ion battery cathode materials as Mn is earth abundant, low cost, and can deliver high capacity. Herein, a high entropy strategy was used to prepare Mn rich high entropy oxide (HEO) materials by including four additional metals (Ni, Co, Fe and Al) in the compositions using a mild co-precipitation method. Two HEOs (Li x Ni 0.1 Mn 0.6 Co 0.1 Al 0.1 Fe 0.1 O y , where x = 1.5 for HEO-L and x = 0.5 for HEO-H) with layered and spinel-layered hybrid structures were investigated where the morphology, elemental composition, structure, atomic level phase distribution, and electrochemistry were determined. The HEO-L samples involve a Li 2 TMO 3 layered structure with ~39% stacking faults. HEO-H is a hybrid structure comprised of 80 wt% spinel and 20 wt% LiMO 2 layered structure. The high entropy manganese-rich HEO-L showed higher capacity and 93% retention of the average voltage after 100 cycles while HEO-H showed higher capacity retention and near 100% average voltage retention. Finally, operando X-ray absorption spectroscopy revealed that the Ni, Co, and Mn are redox active in both materials while the Fe center remains at the Fe 3+ oxidation state throughout cycling, where the changes in the oxidation states for both materials during discharge were consistent with the delivered electrochemical capacity rationalizing the observed electrochemistry.

25 ENERGY STORAGE↗
DOE OSTI2020

Real-time Nonlinear Model Predictive Control (NMPC) Strategies using Physics-Based Models for Advanced Lithium-ion Battery Management System (BMS)

Optimal operation of lithium-ion batteries requires robust battery models for advanced battery management systems (ABMS). A nonlinear model predictive control strategy is proposed that directly employs the pseudo-two-dimensional (P2D) model for making predictions. Using robust and efficient model simulation algorithms developed previously, the computational time of the nonlinear model predictive control algorithm is quantified, and the ability to use such models for nonlinear model predictive control for ABMS is established.

25 ENERGY STORAGE↗
DOE OSTI2020

Solvation Rule for Solid‐Electrolyte Interphase Enabler in Lithium‐Metal Batteries

Abstract Despite the exceptionally high energy density of lithium metal anodes, the practical application of lithium‐metal batteries (LMBs) is still impeded by the instability of the interphase between the lithium metal and the electrolyte. To formulate a functional electrolyte system that can stabilize the lithium‐metal anode, the solvation behavior of the solvent molecules must be understood because the electrochemical properties of a solvent can be heavily influenced by its solvation status. We unambiguously demonstrated the solvation rule for the solid‐electrolyte interphase (SEI) enabler in an electrolyte system. In this study, fluoroethylene carbonate was used as the SEI enabler due to its ability to form a robust SEI on the lithium metal surface, allowing relatively stable LMB cycling. The results revealed that the solvation number of fluoroethylene carbonate must be ≥1 to ensure the formation of a stable SEI in which the sacrificial reduction of the SEI enabler subsequently leads to the stable cycling of LMBs.

Su, Chi‐Cheung↗
DOE OSTI2023

Electric Vehicle Lithium-Ion Battery Life Cycle Management

There is no question that electric vehicles (EVs), which are key for addressing climate change impacts from the transportation sector, are quickly gaining popularity and availability. With limits and other challenges related to the supply of critical battery minerals, maximizing the use of EV batteries and ensuring recovery of battery minerals is imperative. Therefore, proper end-of-life-cycle management (reuse and recycling) of these batteries must be part of the EV ecosystem from the perspective of both the supply chain and environmental footprint. Second use of batteries for energy storage systems extends the initial life of these resources and provides a buffer until economical material recovery facilities are in place. Although there are multiple pathways to recycling and recovery of materials, new recovery technologies are moving toward commercially available hydrometallurgy and promising direct recycling, which analysis has shown has the lowest overall carbon footprint. Strategically locating these plants close to battery collection further reduces transportation and thus recycling and recovering costs. Proper life cycle management could alleviate future lithium-ion battery materials supply chains for EVs. Governments and other stakeholders around the world have started initiatives and proposed regulations to address the challenges associated with life cycle management of EV lithium batteries. Finally, as manufacturers are increasingly faced with the likelihood of such extensive regulatory requirements, attention should be given to new designs, sales, and service models that can reduce life cycle management costs.

25 ENERGY STORAGE↗
DOE OSTI2025

The Origin of Improved Performance in Boron‐Alloyed Silicon Nanoparticle‐Based Anodes for Lithium‐Ion Batteries

Stabilizing the solid electrolyte interphase (SEI) remains a key challenge for silicon‐based lithium‐ion battery anodes. Alloying silicon with secondary elements like boron has emerged as a promising strategy to improve the cycle life of silicon anodes, yet the underlying mechanism remains unclear. To address this knowledge gap, how boron concentration influences battery performance is systematically investigated. These results show a near‐monotonic increase in cycle lifetime with higher boron content, with boron‐rich electrodes significantly outperforming pure silicon. Additionally, silicon‐boron alloy anodes exhibit nearly three times longer calendar life than pure silicon. Through detailed mechanistic analysis, alternative contributing factors are systematically ruled out, and it is proposed that improved passivation arises from a strong permanent dipole at the nanoparticle surface. This dipole, formed by undercoordinated and highly Lewis acidic boron, creates a static, ion‐dense layer that stabilizes the electrochemical interface, reducing parasitic electrolyte decomposition and enhancing long‐term stability. These findings suggest that, within the SEI framework, the electric double layer is an important consideration in surface passivation. This insight provides an underexplored parameter space for optimizing silicon anodes in next‐generation lithium‐ion batteries.

25 ENERGY STORAGE↗
DOE OSTI2021

Layered Heterostructure Ionogel Electrolytes for High‐Performance Solid‐State Lithium‐Ion Batteries

Abstract Ionogel electrolytes based on ionic liquids and gelling matrices offer several advantages for solid‐state lithium‐ion batteries, including nonflammability, wide processing compatibility, and favorable electrochemical and thermal properties. However, the absence of ionic liquids that are concurrently stable at low and high potentials constrains the electrochemical windows of ionogel electrolytes and thus their high‐energy‐density applications. Here, ionogel electrolytes with a layered heterostructure are introduced, combining high‐potential (anodic stability: >5 V vs Li/Li + ) and low‐potential (cathodic stability: <0 V vs Li/Li + ) imidazolium ionic liquids in a hexagonal boron nitride nanoplatelet matrix. These layered heterostructure ionogel electrolytes lead to extended electrochemical windows, while preserving high ionic conductivity (>1 mS cm −1 at room temperature). Using the layered heterostructure ionogel electrolytes, full‐cell solid‐state lithium‐ion batteries with a nickel manganese cobalt oxide cathode and a graphite anode are demonstrated, exhibiting voltages that are unachievable with either the high‐potential or low‐potential ionic liquid alone. Compared to ionogel electrolytes based on mixed ionic liquids, the layered heterostructure ionogel electrolytes enable higher stability operation of full‐cell lithium‐ion batteries, resulting in significantly enhanced cycling performance.

Hyun, Woo Jin↗
DOE OSTI2020

An Efficient Electrochemical Tanks-in-Series Model for Lithium Sulfur Batteries

This article applies and efficiently implements the Tanks-in-Series methodology ( J. Electrochem. Soc. , 167 , 013534 (2020)) to generate a computationally efficient electrochemical model for Lithium-Sulfur batteries. The original Tank model approach for Lithium-ion batteries is modified to account for porosity changes with time. In addition, an exponential scaling method is introduced that enables efficient simulation of the model equations to address the wide range of time constants present for different reactions in the Lithium-Sulfur system. The Tank Model achieves acceptable voltage error even for transport-limited discharged conditions. Predictions of internal electrochemical variables are examined, and electrochemical implications of the approximations discussed. This suggests significant potential for real-time applications such as optimal charging, cell-balancing, and estimation, and represents a step forward in efforts to incorporate detailed electrochemical models in advanced Battery Management Systems for Lithium-Sulfur batteries.

Parke, Caitlin D. (ORCID:0000000177324044)↗
DOE OSTI2022

Insight into the Fast-Rechargeability of a Novel Mo 1.5 W 1.5 Nb 14 O 44 Anode Material for High-Performance Lithium-Ion Batteries

Wadsley–Roth phased niobates are promising anode materials for lithium-ion batteries, while their inherently low electrical conductivity still limits their rate-capability. Herein, a novel doped Mo 1.5 W 1.5 Nb 14 O 44 (MWNO) material is facilely prepared via an ionothermal-synthesis-assisted doping strategy. The detailed crystal structure of MWNO is characterized by neutron powder diffraction and aberration corrected scanning transmission electron microscope, unveiling the full occupation of Mo 6+ -dopant at the t1 tetrahedral site. In half-cells, MWNO exhibits enhanced fast-rechargeability. In this work, the origin of the improved performance is investigated by ultraviolet–visible diffuse reflectance spectroscopy, density functional theory (DFT) computation, and electrochemical impedance spectroscopy, revealing that bandgap narrowing improves the electrical conductivity of MWNO. Furthermore, operando X-ray diffraction elucidates that MWNO exhibits a typical solid-solution phase conversion-based lithium-ion insertion/extraction mechanism with reversible structural evolution during the electrochemical reaction. The boosted lithium-ion diffusivity of MWNO, due to the Mo 6+ /W 6+ doping effect, is confirmed by a galvanostatic intermittent titration technique and DFT. With the simultaneously enhanced electrical conductivity and lithium-ion diffusivity, MWNO successfully demonstrates its fast-rechargeability and practicality in the LiNi 0.5 Mn 1.5 O 4 -coupled full-cells. Therefore, this work illustrates the potential of ionothermal synthesis in energy storage materials and provides a mechanistic understanding of the doping effect on improving material's electrochemical performance.

25 ENERGY STORAGE↗
DOE OSTI2025

Customizable Technical Specifications for Lithium-Ion Battery Storage Projects

Learn how to navigate the FEMP Lithium-ion Battery Storage Technical Specifications, a key resource for federal agencies developing onsite energy storage projects. This webinar, led by technical experts, will provide a step-by-step walkthrough of the specifications, supplemented with a real-world case study. Gain practical insights to support successful battery storage project development and implementation.

25 ENERGY STORAGE↗
DOE OSTI2025

Systematic feature design for cycle life prediction of lithium-ion batteries during formation

Optimization of the formation step in lithium-ion battery manufacturing is challenging due to limited physical understanding of solid-electrolyte interphase formation and the long testing time (∼100 days) for cells to reach the end of life. We propose a systematic feature-design framework that requires minimal domain knowledge for accurate cycle life prediction during formation. By only using two simple Q (V) features designed from our framework, extracted from formation data without any additional diagnostic cycles, we achieved an average of 9.87% error for cycle life prediction. Here, the physics-based investigation guided by the two designed features shows that the voltage ranges identified by our framework capture the effects of formation temperature and microscopic-particle resistance heterogeneity. By designing highly predictive, robust, and interpretable features, our approach can accelerate industrial battery formation research, leveraging the interplay between data-driven feature design and mechanistic understanding.

25 ENERGY STORAGE↗
DOE OSTI2023

Rational Design of Fluorinated Electrolytes for Low Temperature Lithium‐Ion Batteries

Abstract Nonaqueous carbonate electrolytes are commonly used in commercial lithium‐ion battery (LIB). However, the sluggish Li + diffusivity and high interfacial charge transfer resistance at low temperature (LT) limit their wide adoption among geographical areas with high latitudes and altitudes. Herein, a rational design of new electrolytes is demonstrated, which can significantly improve the low temperature performance below −20 °C. This electrolyte is achieved by tailoring the chemical structure, i.e., altering the fluorination position and the degree of fluorination, of ethyl acetate solvent. It is found that fluorination adjacent to the carbonyl group or high degree of fluorination leads to a stronger electron‐withdrawing effect, resulting in low atomic charge on the carbonyl oxygen solvating sites, and thus low binding energies with Li + ions at LT. The optimal electrolyte 2,2,2‐trifluoroethyl acetate (EA‐f) shows significantly improved cycle life and C‐rate of a NMC622/graphite cell when cycled at −20 °C and −40 °C, respectively. In addition to superior LT performance, the electrolyte is nonflammable and tolerant for high voltage charging all owing to its fluorine content. This work provides guidance in designing next‐generation electrolytes to address the critical challenge at subzero temperatures.

25 ENERGY STORAGE↗
DOE OSTI2025

Concavity-based local erosion and sphere-size-based local dilation applied to lithium-ion battery electrode microstructures for particle identification

Performance metrics of lithium-ion batteries can be extracted from the analysis of electrode microstructures nanoscale imaging. The characterization workflow can involve a challenging particle identification, or instance segmentation, step. In this work, we propose a new identification method based on an original transformation: a sphere-size-based local dilation followed by a concavity-based local erosion, that is local morphology closing. The new transformation is much more efficient than the global morphology closing, with correct identification achieved with only 1.7 % dilation volume and 2.6 % erosion volume on a test geometry, compared to 39.2 % and more than 50 %, respectively, with its global counterpart. The new method has been then benchmarked versus other identification algorithms (watershed and pseudo coulomb repulsive field) on a real electrode microstructure with equal or better segmentation achieved.

25 ENERGY STORAGE↗
DOE OSTI2022

Coal-derived graphene foam and micron-sized silicon composite anodes for lithium-ion batteries

Silicon-based materials demonstrate significant potential as lithium-ion batteries (LIBs) anode, but their expansion and degradation present engineering design challenges for commercial application. In this study, a porous three-dimensional (3D) graphene and micron-sized silicon composite anode (Si@G foam) was synthesized using humic acid (HA) derived from coal as a graphene precursor. In-situ formation of graphene structure through reducing HA was confirmed by Raman spectra. The reduced HA (rHA) shows similar electrical conductivity compared to the commercial conductive carbon. SEM images depict a 3D skeleton of coal-derived graphene, with silicon particles distributed on the 3D graphene foam's internal surface. The Si@G composite-anode displays a good reversible capacity of ~656 mAh/g at a current density of 50 mA/g, as well as a high-rate capability of ~433 mAh/g at a current density of 800 mA/g, and outstanding cycling stability –89.8% capacity retention after 300 cycles, which is significantly higher than that of other foam structures. During lithiation and de-lithiation, the graphene foam serves as a matrix of electrical conductors and a volume expansion support for silicon. This 3D graphene network will be beneficial for developing advanced silicon-based anodes for high-performance LIBs.

25 ENERGY STORAGE↗
DOE OSTI2022

Multifunctional transitional metal-based phosphide nanoparticles towards improved polysulfide confinement and redox kinetics for highly stable lithium-sulfur batteries

The shuttle effect and the sluggish redox kinetics of lithium polysulfides (LiPSs) are the major issues impeding the practical applications of lithium-sulfur batteries (LSBs). Herein, a highly-efficient Ni 2 P electrocatalyst supported on N, P co-doped graphene (Ni 2 P@NPG) is developed via a simple “recrystallization-self-assembly” method to address the above issues. Here, the ultrafine Ni 2 P nanoparticles ensure abundant adsorption-diffusion-conversion interfaces for accelerating LiPSs transformation and Li 2 S deposition, which extremely decreases the accumulation of LiPSs in the electrolyte and therefore prevents the migration of LiPSs. Their superior catalytic performance is demonstrated by reduced Gibbs free energy changes of rate-limiting step based on the systematic theoretical calculations and the reduced shuttle effect is tested by the three-dimensional reconstructions of Raman depth profiles. Benefiting from these synergistic effects, the LSBs with Ni 2 P@NPG modified separators present a superior cycling performance with an average capacity decay rate of 0.048 % per cycle at 1C around the 400 cycles and a high-rate capacity of 731 mAh/g at 2C. Even with a high-sulfur loading of 3.53 mg cm –2 , the cell can still contain a reversible capacity of 809 mAh/g at 0.2C with a remarkable columbic efficiency of 98.4 %.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Polyethylene Glycol Surface Modification and Polythiophene Side-Chain Chemistry: A Combined Strategy toward High-Capacity Lithium-Ion Battery Anodes

In the development of high-capacity lithium-ion batteries (LIBs), the combined optimization of active material interfaces and polymer binder chemistry plays a critical role in improving electrode performance and longevity. This work explores a dual design strategy incorporating polyethylene glycol (PEG) surface modification and carboxylated polythiophene side-chain tailoring to enhance the electrochemical behavior of magnetite (Fe 3 O 4 )-based anodes. PEG is employed to improve interfacial stability, while carboxylated polythiophene binders with varying alkyl side-chain lengths─poly[3-(potassium-4-butanoate)thiophene-2,5-diyl] (P3KBT), poly[3-(potassium-5-pentanoate)thiophene-2,5-diyl] (P3KPT), and poly[3-(potassium-6-hexanoate)thiophene-2,5-diyl] (P3KHT)─are used to modulate molecular interactions and ion transport. Among these three analogs, the PEG–Fe 3 O 4 –P3KHT electrode exhibits superior ion-transfer kinetics, the highest capacity retention, and the lowest charge-transfer resistance after extended cycling. Compared to their non-PEG analogs, PEG-coated electrodes demonstrate enhanced structural integrity and electrochemical behavior, emphasizing the synergistic effects of surface modification and side-chain chemistry. These findings highlight the importance of interfacial interactions and molecular design in achieving robust and high-performance composite anodes for next-generation LIBs.

Fe3O4↗
DOE OSTI2023

Modeling the 4D discharge of lithium-ion batteries with a multiscale time-dependent deep learning framework

The lithium-ion battery (LIB) field is moving towards the direction of investigating spatially resolved physical phenomena in the 3D porous microstructure of electrodes. These pore-scale simulations give new insights into the local dynamics of lithiation/de-lithiation and charge transport, Nevertheless, the computational time of these simulations limits the integration of these models in optimization workflows of cycling conditions or electrode manufacturing processes. Machine learning models present a way of assessing in real-time the performance of materials. While several successful techniques for replicating simulations with machine learning have been proposed, this case study presents a more demanding problem, due to the necessity of understanding the behavior of heterogeneous 3D local data, as it evolves in time: this poses both a scientific and a technical challenge. To this end, we propose an autoregressive multiscale convolutional neural network model to predict relevant quantities at the pore-scale in the solid phase: the lithium concentration (in the active material) and potential (in the active material and carbon binder). Here, these are ultimately used to reconstruct the battery discharge curve. 3D images of the electrode microstructures are the input to the network, trained with a dataset of finite element method simulations to predict the discharge behavior of the cathode side in lithium ion batteries. We propose this machine learning model as a proof-of-concept of the applicability of multiscale networks for time-dependent physics problems. The trained model exhibits very high accuracy (with errors lower than 2 %) in forecasting the discharge behavior of new unseen cathodes.

25 ENERGY STORAGE↗