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At least 217 records · Page 12

Vermont's Clean Energy Jobs Potential Through 2030

According to the U.S. Census Bureau, Vermont had 406,641 people in its working population (15 to 64 years of age) in 2019. The graphs below show solar photovoltaic (PV), land-based wind, battery energy storage (BES), and energy efficiency job estimates in 2020, 2025, and 2030. These job estimates do not represent net job creation. Rather, they represent the size of the workforce required to achieve projected national deployment levels of each technology for 2025 and 2030 if the state captures the same proportion of jobs in the sector as it did in 2020.

clean energy↗

Virginia's Clean Energy Jobs Potential Through 2030

According to the U.S. Census Bureau, Virginia had 5,629,718 people in its working population (15 to 64 years of age) in 2019. The graphs below show solar photovoltaic (PV), land-based wind, battery energy storage (BES), and energy efficiency job estimates in 2020, 2025, and 2030. These job estimates do not represent net job creation. Rather, they represent the size of the workforce required to achieve projected national deployment levels of each technology for 2025 and 2030 if the state captures the same proportion of jobs in the sector as it did in 2020.

clean energy↗

West Virginia's Clean Energy Jobs Potential Through 2030

According to the U.S. Census Bureau, West Virginia had 1,129,785 people in its working population (15 to 64 years of age) in 2019. The graphs below show solar photovoltaic (PV), land-based wind, battery energy storage (BES), and energy efficiency job estimates in 2020, 2025, and 2030. These job estimates do not represent net job creation. Rather, they represent the size of the workforce required to achieve projected national deployment levels of each technology for 2025 and 2030 if the state captures the same proportion of jobs in the sector as it did in 2020.

clean energy↗

Washington's Clean Energy Jobs Potential Through 2030

According to the U.S. Census Bureau, Washington had 5,017,738 people in its working population (15 to 64 years of age) in 2019. The graphs below show solar photovoltaic (PV), land-based wind, battery energy storage (BES), and energy efficiency job estimates in 2020, 2025, and 2030. These job estimates do not represent net job creation. Rather, they represent the size of the workforce required to achieve projected national deployment levels of each technology for 2025 and 2030 if the state captures the same proportion of jobs in the sector as it did in 2020.

clean energy↗

Wisconsin's Clean Energy Jobs Potential Through 2030

According to the U.S. Census Bureau, Wisconsin had 3,762,091 people in its working population (15 to 64 years of age) in 2019. The graphs below show solar photovoltaic (PV), land-based wind, battery energy storage (BES), and energy efficiency job estimates in 2020, 2025, and 2030. These job estimates do not represent net job creation. Rather, they represent the size of the workforce required to achieve projected national deployment levels of each technology for 2025 and 2030 if the state captures the same proportion of jobs in the sector as it did in 2020.

clean energy↗

Wyoming's Clean Energy Jobs Potential Through 2030

According to the U.S. Census Bureau, Wyoming had 367,435 people in its working population (15 to 64 years of age) in 2019. The graphs below show solar photovoltaic (PV), land-based wind, battery energy storage (BES), and energy efficiency job estimates in 2020, 2025, and 2030. These job estimates do not represent net job creation. Rather, they represent the size of the workforce required to achieve projected national deployment levels of each technology for 2025 and 2030 if the state captures the same proportion of jobs in the sector as it did in 2020.

clean energy↗

Washington DC's Clean Energy Jobs Potential Through 2030

According to the U.S. Census Bureau, Washington DC had 416,300 people in its working population (15 to 64 years of age) in 2019. The graphs below show solar photovoltaic (PV), land-based wind, battery energy storage (BES), and energy efficiency job estimates in 2020, 2025, and 2030. These job estimates do not represent net job creation. Rather, they represent the size of the workforce required to achieve projected national deployment levels of each technology for 2025 and 2030 if the state captures the same proportion of jobs in the sector as it did in 2020.

clean energy↗

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

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

25 ENERGY STORAGE↗

PyBLM (Python-based Battery Life Model) [SWR-21-50]

PyBLM is a battery life model to predict the capacity fade of two home battery energy storage systems, manufactured by LG and Tesla. The battery life model is built from experimental test data, and accounts for calendar and cycling aging mechanisms as functions of cell environmental conditions and use. PyBLM is developed in Python and formatted to work in conjunction with another NREL software named TEMPEST (Thermo-Electric Model for Powering Energy Storage Technologies).

Mishra, Partha↗

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↗

Anodic Interfacial Evolution in Extremely Fast Charged Lithium-Ion Batteries

Interfacial reaction mechanisms at the anode/separator interface play a central role in the performance and safety of lithium-ion batteries during fast charging. We report a mechanistic study on the evolution and interactions of the aging mechanisms at the anode/separator interface in lithium cobalt oxide/graphite pouch cells charged with variable charging rates (1–6C) over 10 cycles. In situ electrochemical measurements, including voltage relaxation, Coulombic efficiency, and direct current internal resistance, indicated an incremental lithium loss until the C rates were ≤5C. A substantial capacity fade is observed in the first few cycles of fast charging, but the magnitude of capacity fade progressively diminishes with the number of cycles, indicating a suppression in the lithium deposition mechanism. Post-mortem film thickness, X-ray photoelectron spectroscopy (XPS), and scanning electron microscopy (SEM) analyses were performed to elucidate the evolution of electrolyte decomposition, the solid–electrolyte interface (SEI), lithium plating, and film fracture mechanisms with C rate. XPS measurements confirmed an increasing lithium concentration in an SEI film with an increase in the C rate. SEM images showed a growth of dendritic lithium on the anode surface from 1C to 3C. Precrack formation leading to an interfacial film fracture was observed at higher C rates. Furthermore, a differential analysis of the discharge capacity indicated a possible two-phase delithiation from the anode and reduced cathodic lithiation due to lithium loss at high C rates.

36 MATERIALS SCIENCE↗

Complementary Electrolyte Design for Li Metal Batteries in Electric Vehicle Applications

In this report a complementary electrolyte system with 0.8 M lithium bis(fluorosulfonylimide) (LiFSI) salt and 2 wt % lithium perchlorate (LiCLO4) additive in fluoroethylene carbonate (FEC)/ethyl methyl carbonate (EMC) solution enables not only stable cycling of lithium metal batteries (LMBs) with practical loading (<30 μm lithium anode, cathode loading > 4 mAh/cm 2 ) but also outstanding degradation stability toward the end of cycle life when compared to the conventional electrolyte. Although the use of LiFSI salt can increase the electrolyte conductivity and lengthen the cycle life of LMBs, the aged lithium anode morphology formed by the sacrificial decomposition of LiFSI is highly porous, leading to an abrupt cell capacity drop toward the end of cycling. Moreover, the inability to stop aluminum corrosion by the LiFSI-based electrolyte also causes cracking of the cathode tab during prolonged cycling. It is observed that a highly porous aged lithium consumed electrolyte at a higher rate, leading to the dry-out of electrolyte solvents. On the contrary, dense aged lithium anode morphology increased the localized current applied on the lithium, causing the formation of lithium dendrite. Thus, porosity control is the key to enhance battery performance. In this complementary system, LiClO 4 was introduced as an advanced additive to not only improve the capacity retention rate but also mitigate the abrupt capacity drop toward the end of cycle life because LiClO 4 acted as a pore astringent reducing the porosity of the aged lithium metal anode to the desired level. Moreover, the addition of LiClO 4 can also suppress the AI corrosion, allowing stable high-voltage cycling of LMBs. The synergistic effect of combining LiFSI salt and a LiClO 4 additive leads to an electrolyte system that can facilitate the application of high-energy LMBs with practical electrode loading.

25 ENERGY STORAGE↗

Lithium-Ion Batteries with Lithium Manganese Iron Phosphate Cathodes and Lithium Titanate Anodes: Linking Electrode Dynamics to Cell Performance

This study examines the electrochemical performance, impedance behavior, and aging mechanisms of lithium-ion cells pairing lithium manganese iron phosphate (LiMn 0.6 Fe 0.4 PO 4 , LMFP64) cathodes with lithium titanate (Li 4 Ti 5 O 12 , LTO) anodes. LMFP64 half-cells display distinct Fe and Mn redox plateaus at ∼3.5 and ∼4.1 V, respectively, and deliver excellent rate capability. Three-electrode measurements show that LMFP64 dominates cell impedance, which changes sharply across the Fe–Mn redox transition and decreases with increasing temperature (30 °C–50 °C). Voltage hysteresis arises mainly from the cathode, with higher C-rates shortening redox plateaus and broadening the transition region. Elevated temperature lowers impedance, especially near the Mn-redox and transition regions, but accelerates capacity fade. Post-cycling analyses of electrodes confirm structural stability of LMFP64 and indicate loss of lithium inventory (LLI) as the source of capacity fade. This LLI causes potential slippage between the LMFP64 and LTO electrodes, which decreases the Fe-redox plateau width. Long-term cycling highlights the critical role of electrode overhang: cathode overhang mitigates capacity fade by buffering lithium loss, whereas anode overhang cells experience faster capacity decline due to uncompensated lithium depletion. These results clarify LMFP64/LTO battery impedance evolution, thermal effects, and degradation pathways and provide insights for their applications in electric vehicles.

Area Specific Impedance↗

Extreme fast charge aging: Effect of electrode loading and NMC composition on inhomogeneous degradation in graphite bulk and electrode/electrolyte interface

Empowering extreme fast charging (XFC) requires a comprehensive understanding of its application with advanced anode and cathode materials in lithium-ion batteries. No report exists for the full extent of limitations for the anode with crosstalk effect from paired cathode as well as Li plating due to electrode loading under XFC. In this study, a combination of cell testing and multiple length characterization is used to investigate XFC aging mechanism in cells with a low loading of 1.5 mAh cm -2 and high loading of 2.5 mAh cm -2 for graphite (Gr)/Ni-rich LiNi x Mn y Co 1-x-y O 2 (NMCs). Operando XRD mappings show 1.5 mAh cm -2 loadings result in higher strain in graphite for all three cathode types. Among the three NMC cathodes, the graphite from NMC532 and NMC811 cells show comparable strain. Scanning electron microscopy (SEM) images show distinct differences between 6-C-charged anodes in two loadings. Significantly increased electrode thickness can be seen due to more damage in the graphite bulk and accumulation of the electrolyte decomposition products in electrode pores. X-ray photoelectron spectroscopy (XPS) reveals both cathode chemistry and Li plating influence the non-uniform SEI composition on graphite surface. We report higher Ni content in NMC811 promotes the higher levels of salt decomposition on the SEI and formation of higher mass of electrolyte aging products.

25 ENERGY STORAGE↗

Improving Electronic Conductivity of Layered Oxides through the Formation of Two-Dimensional Heterointerface for Intercalation Batteries

Synthetic strategies for the improvement in electronic conductivities and electrochemical stabilities of transition metal oxide cathodes, which are limiting factors in the performance of commercial intercalation batteries, are required for next-generation, high-performance battery systems. Furthermore, the chemical preintercalation approach, consisting of a combined sequence of a sol–gel process, extended aging, and a hydrothermal treatment, is a versatile, wet synthesis technique that allows for the incorporation of a polar species between the layers of transition metal oxides. Here, formation of a layered 2D δ-C x V 2 O 5 · n H 2 O heterostructure occurs via chemical preintercalation of dopamine molecules between bilayers of vanadium oxide followed by the hydrothermal treatment of the precipitate, leading to carbonization of the organic molecules. The presence of carbon layers within the structure has been confirmed via a combined analysis of scanning electron microscopy, X-ray diffraction, thermogravimetric analysis, Raman spectroscopy, X-ray photoelectron spectroscopy, electrochemical impedance spectroscopy, four-probe conductivity measurements, and scanning transmission electron microscopy characterization. 2D δ-C x V 2 O 5 · n H 2 O heterostructure electrodes demonstrated significantly improved electrochemical performance, particularly at higher current densities, in Li-ion cells. The heterostructure electrodes exhibited 75% of the capacity retention when the current was changed from 20 mA g –1 (206 mAh g –1 ) to 300 mA g –1 (155 mAh g –1 ), while the reference δ-V 2 O 5 · n H 2 O electrodes exhibited only 10% capacity retention in the same experiment. Remarkably, 2D δ-C x V 2 O 5 · n H 2 O heterostructure electrodes demonstrated significantly improved capacity retention (94% after 30 cycles) for bilayered vanadium oxide electrodes in Li-ion cells during galvanostatic cycling at 20 mA g –1 . The improved electrochemical performance, in both extended cycling and rate capability studies, of the 2D δ-C x V 2 O 5 · n H 2 O heterostructure electrodes in the Li-ion system is ascribed to the intermittent formation of carbon layers within the bilayered structure, which leads to increased electronic conductivity and improved structural stability of the heterostructure compared to the reference δ-V 2 O 5 · n H 2 O electrodes.

25 ENERGY STORAGE↗

Structure and dynamics of small polyimide oligomers with silicon as a function of aging

The effect of UV curing and shearing on the structure and behavior of a polyimide (PI) binder as it disperses silicon particles in a battery electrode slurry was investigated. PI dispersant effectiveness increases with UV curing time, which controls the overall binder molecular weight. Here, the shear force during electrode casting causes higher molecular weight PI to agglomerate, resulting in battery anodes with poorly dispersed Si particles that do not cycle well. It is hypothesized that when PI binder is added above a critical amount, it conformally coats the silicon particles and greatly impedes Li ion transport. There is an “interzonal region” for binder loading where it disperses silicon well and provides a coverage that facilitates Li transport through the anode material and into the silicon particles. These results have implications in ensuring reproducible electrode manufacturing and increasing cell performance by optimizing the PI structure and coordination with the silicon precursor.

36 MATERIALS SCIENCE↗

Performance and lifetime of intercalative water deionization cells for mono- and divalent ion removal

We report intercalative deionization (IDI) uses two cation intercalation electrodes separated by an anion exchange membrane in a symmetric cell design that has the potential to deliver electrochemically desalinated water in an energy- and water-efficient way. Here, we define and measure metrics to describe the performance and lifetime of IDI cells and compare them for NaCl and CaCl 2 feed solutions. With 20 mM NaCl, NiHCF/AEM/NiHCF flow cells achieve 10 mM average concentration change at a productivity of 20 l/h/m 2 and 5 mM average concentration change at 130 l/h/m 2 . In both cases the cells are operated at a 3C current rate and consume ~30 Wh/m 3 of energy. With 10 mM CaCl 2 , the specific capacity and salt removal of IDI flow cells is ~4 times lower. NiHCF/NiHCF beaker cells with CaCl 2 electrolyte suffer from strong capacity fade, while the same cells with NaCl electrolyte achieve 500 cycles without any capacity fade. Our post-mortem analysis using X-ray diffraction, secondary electron microscopy, energy dispersive X-ray spectroscopy, synchrotron-based X-ray absorption spectroscopy and micro X-ray fluorescence mapping reveals that NiHCF dissolves upon repeated intercalation with Ca 2+ , releasing residual K + , Ni 2+ and Fe(CN) 6 3 , which precipitates as a crystalline decomposition product on the electrodes. This side reaction deprives the active material NiHCF of charge compensating Fe, and thus accounts for the observed capacity fade.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Approximate Dynamic Programming With Enhanced Off-Policy Learning for Coordinating Distributed Energy Resources

Herein this paper proposes an innovative approximate dynamic programming (ADP) method for distributed energy resource coordination with the loss of life of battery energy storage system (BESS) explicitly modeled. The dispatch policy is designed to account for both calendrical and cyclical aging effects on BESS, explicitly modeling the impacts of ambient temperature on BESS lifespan. The proposed ADP employs an adaptive critic method and enhanced off-policy deterministic policy gradient (DPG) strategy, addressing the limitations of the on-policy gradient-based ADP approaches, including inadequate exploration, low data usage, and computational complexity. In particular, a customized policy is proposed to guide the algorithm to explore some promising decisions and thereby improve exploration capability and learning efficiency compared to conventional DPG-based learning approaches, which may struggle to find a global optimum due to random noisy action-based exploration or require expert demonstration with extra effort. The proposed method is illustrated using the IEEE 123-node system and compared with the existing ADP methods to prove solution accuracy and demonstrate the effects of incorporating degradation models into control design. Case studies showed that the proposed ADP effectively coordinates DERs with a 10 times smaller optimization gap compared to existing methods, and the incorporation of the BESS life loss model ensures the expected lifespan and results in significant cost savings.

24 POWER TRANSMISSION AND DISTRIBUTION↗