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At least 199 records · Page 11

An assessment of the harvesting and fuel performance of a single-pass cut-and-chip harvester in commercial-scale short-rotation poplar crops as influenced by crop and weather conditions

There is a need for data on commercial-scale harvesting operations in hybrid poplar short rotation crops to better understand costs and logistics, especially for modeling large scale biorefineries. An investigation was conducted on the in-field performance of a single-pass cut-and-chip harvester operating in commercial fields for over 370 individual wagon loads representing a range of crop and field conditions. Mean material capacity peaked at 70 Mg h -1 in dry conditions in lower biomass (<60 Mg ha -1 ), but was only 28 Mg h -1 during wet conditions and often higher standing biomass. Wet ground conditions require the harvester to divert additional power to maintaining forward movement, which results in decreased material capacity and increased fuel consumption. Crops with higher standing biomass had taller trees that do not always feed as smoothly into the harvester, slowing forward progress and lowering material capacity. Mean crop specific fuel consumption, L of fuel per Mg of biomass processed, generally decreased as standing biomass increased. When standing biomass was above 40 Mg ha -1 mean crop specific fuel consumption (FCC) was 1.69 L Mg -1 in dry conditions and 3.98 L Mg -1 in wet conditions, but when standing biomass was below 40 Mg ha-1 FCC increased drastically (as high as 5 L Mg -1 ) because the harvester is putting more effort into forward speed instead of material processing. Developing relationships between material capacity and fuel consumption based on standing biomass and ground conditions at representative scales are essential for conducting environmental and economic analyses of these systems.

09 BIOMASS FUELS↗

Reactivity of net-zero carbon alcohol fuels and their corresponding aldehyde intermediates on PGM-based commercial oxidation catalysts for lean-burn emissions control

Alcohol net-zero carbon fuels will play a significant role in decarbonization of the hard-to-electrify transportation sectors. However, the combustion process in alcohol-fueled engines generate toxic aldehydes. For commercialization of net-zero carbon fuels on engines, compliance with the stringent U.S. EPA regulations is necessary. Here, this contribution focuses on reactivity of alcohols and aldehydes on commercial diesel oxidation catalysts (DOC) to inform selection of future net-zero carbon fuels. Alcohol (and aldehyde) light-off temperatures were measured on aged DOCs under full synthetic engine-exhaust conditions. Methanol was the most reactive, while ethanol completely oxidized at higher temperatures. Alcohols typically formed less reactive aldehyde intermediates. DRIFTS revealed strongly adsorbing surface formates and acetates during methanol and ethanol oxidation, respectively, resulting in inhibition effects. Preliminary alcohol oxidation mechanisms combining flow reactor and DRIFTS observations are presented. Aldehydes inhibited CO oxidation. Minimal N 2 O formation was observed for the alcohols investigated.

Alcohol oxidation↗

Functionalized benzylamines from commercial kraft lignin

Benzylamines are key intermediates in pharmaceuticals, agrochemicals, and polymers, but their conventional production relies on benzyl chloride - a petroleum-derived compound with high toxicity and energy demands. Lignin, accounting for up to 30% of plant biomass, is the largest renewable source of aromatic carbon on Earth. However, its highly complex and recalcitrant structure poses a major barrier to efficient conversion into high-value chemicals. Here, in this study, we developed a catalytic approach to convert commercial kraft lignin into phenolic benzylamines through selective depolymerization and subsequent functionalization. We systematically evaluated the effects of three alcohol solvents, formic acid (FA), and a ruthenium-on‑carbon (Ru/C) catalyst on monophenol yield and selectivity. Up to 6.5 wt% monophenol yield was achieved using methanol (MeOH), FA, and Ru/C at 300 °C for 2 h. Quantum thermodynamic simulations based on the COSMO-RS model confirmed the superior solvation and reactivity of the MeOH + FA system, rationalizing observed product yield. The purified monophenolic products, primarily guaiacol and alkyl guaiacols, were then converted into functionalized benzylamines with >90% yield via a multicomponent Mannich reaction under mild conditions. Techno economic analysis (TEA) and life cycle assessment (LCA) underscore the importance of improving lignin depolymerization yields and expanding biorefinery scale. Solvent-only configurations outperform other options in both cost and emissions, with the methanol-only case performing the best ($\$$105 /kg and 26 kg CO 2e /kg) at a large-scale facility. This study establishes a scalable, bio-based pathway for producing benzylamines from commercial kraft lignin, advancing lignin valorization and offering a sustainable alternative to produce petrochemical-based benzylamines.

Catalytic reduction↗

Large-scale simulation-based parametric analysis of an optimal precooling strategy for demand flexibility in a commercial office building

Achieving success with grid-interactive efficient buildings (GEBs) is closely tied to the utilization of flexible loads. A valuable strategy involves the implementation of precooling techniques before high-demand events, such as peak hours, by adjusting zone air temperature setpoints. This leads to a reduction in thermal loads and peak electricity demand during these times, as the building’s thermal mass stores and subsequently releases thermal energy. However, the effectiveness of the pre-cooling optimization is highly contingent on specific conditions such as building thermal properties, weather conditions, utility rate structure, HVAC equipment sizing, etc. Therefore, investigating the impacts of these condition-specific factors is crucial, especially when considering precooling strategies that utilize thermal mass in commercial buildings. In this paper, we first devised a novel heuristic control approach that incorporates parameterized optimal precooling thermostat schedules to enhance demand flexibility in a commercial office building. Subsequently, we conducted a thorough performance evaluation of this control strategy. Here, the optimal thermostat schedule was parameterized using three optimization variables: the precooling start time, the precooling end time, and the precooling temperature setpoint. Utilizing the DOE medium-sized office building as the virtual testbed, we showed that the parameterized schedule effectively approximates model predictive control and requires drastically reduced computational overhead. In addition, we investigated the impact of different influencing factors on the optimal precooling strategy. These factors include building thermal mass, outdoor air conditions, and energy price profiles. Using high-performance computing, we simulated a total of 225 scenarios, consisting of three levels of thermal mass, five typical outdoor air temperature profiles, and fifteen time-of-use price plans. The results demonstrate that optimal thermostat scheduling could save substantial energy cost in medium-sized office buildings with heavy thermal mass but with some energy penalty. Although the potential for cost savings is lower in buildings with low and medium thermal mass, the energy penalty remains consistent in all three thermal mass scenarios. The study also highlights the need to account for zone diversity and recognize that a one-size-fits-all-zone setpoint schedule may not be suitable for all zones and can lead to unnecessary energy wastage. Furthermore, the results highlight that while outdoor air conditions play a role in cost and energy performance, the cooling load exerts a more immediate and substantial influence on cost savings in precooling strategies. Although cost savings are comparable under certain conditions with the same cooling load, observed deviations in energy penalty indicate potential disparities in the efficiency of the HVAC system during the load-shifting process. In addition, the duration of peak pricing and the ratio between peak and off-peak times exhibit clear correlations with cost savings and energy consumption, aligning with intuitive expectations. These findings offer valuable insights for optimizing precooling strategies in office buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Commercial building HVAC demand flexibility with model predictive control: Field demonstration and literature insights

Model Predictive Control (MPC) for building Heating Ventilation and Air Conditioning (HVAC) systems is beginning to gain traction in the market, with a few controls companies incorporating it into their product offerings. However, it remains difficult to assess whether the energy cost savings are enough to justify the cost of MPC implementation for a particular building, given the limited number of reported demonstrations. For small commercial and residential buildings with relatively uniform systems, standardized approaches can help lower implementation costs. In contrast, for large buildings or district systems, the potential magnitude of cost savings could justify more customized solutions. Estimating the cost-effectiveness of MPC becomes more challenging for medium and large commercial buildings, where a one-size-fits-all solution may not be suitable, and the potential energy cost savings may be insufficient to justify a customized solution. To make MPC technology more appealing, incorporating additional value streams beyond energy efficiency alone can significantly increase its attractiveness. One such revenue stream is demand flexibility, in response to dynamic electricity prices, where MPC can leverage the thermal mass of the building to shift the load and support the grid. Building on an extensive literature review of MPC field studies focused on cost savings and demand flexibility, this paper presents the results of implementing MPC control in a large office building HVAC system in Berkeley, CA. Four different dynamic electricity price profiles were integrated into the MPC objective function to shift building demand while maintaining comfort, and field testing was performed with each price profile across four seasons. The results show potential for 40–65 % demand decrease percentage and up to 61 % annual cost savings compared to the existing rule-based control strategy, under the tested dynamic price scenarios. This paper also presents a sensitivity analysis on the cost savings with respect to the price profile variability, discusses the implementation effort for the price-responsive MPC, and compares the cost savings found in this study to those found in literature on the basis of dynamic price variability, or so-called Electricity Price Relative Standard Deviation.

Zanetti, Ettore↗

Machine learning-enhanced MPC for demand flexibility in small commercial buildings: An experimental study

Small- and medium-sized commercial buildings (SMCBs) represent the majority of U.S. commercial building stock and a significant share of peak electricity demand, yet they often lack centralized building automation systems, representing a significant untapped resource for urban energy management. This infrastructure gap makes advanced control implementation challenging, limiting the potential for widespread demand flexibility. Model Predictive Control (MPC) has shown strong potential for load shifting, peak demand reduction, and cost savings, but its effectiveness is hindered by unmeasured disturbances such as internal heat gains. This paper presents a Hybrid MPC framework that integrates a physics-based gray-box building thermal model, identified using a lumped disturbance (LD) approach, with a machine learning (ML) model for forecasting unmeasured disturbances. The hybrid approach is designed for buildings with multiple individually controlled heat pump and thermostat pairs, common in SMCBs, and aims to optimize coordinated scheduling of multiple heat pumps under dynamic electricity pricing while respecting comfort constraints. The methodology is validated through both simulations of case study buildings and experimental studies at a highly-instrumented test facility. Simulation results show that the Hybrid MPC achieves substantial load shifting and peak demand reduction, approaching the performance of an ideal MPC with perfect disturbance knowledge, and outperforming a conventional MPC without disturbance forecasting. In experiments, the Hybrid MPC reduced daily HVAC energy costs by 8.7%, peak-price time load (load shifting) by 41.7%, and peak demand by 29.2% compared to baseline control, demonstrating comparable benefits to the 11.6% cost savings, 42.9% load shifting, and 23.2% peak reduction of the ideal MPC. These results demonstrate that the proposed hybrid modeling approach can significantly improve MPC performance in real-world SMCB applications without requiring additional disturbance measurements.

Demand Flexibility↗

Near isothermal compressed air energy storage system in residential and commercial buildings: Techno-economic analysis

Electrical energy storage systems offer a wide range of options to efficiently manage our power supply infrastructure. Energy and environmental security via renewable resources and energy storage devices will also play a critical role in addressing the supply-demand challenges. A novel energy efficient storage system based on near isothermal compressed air energy storage concept, named as Ground-Level Integrated Diverse Energy Storage (GLIDES) is analyzed for integration with residential and commercial buildings. Additionally, the influence of different configurational aspects on key performance and cost attributes is presented in this study. GLIDES modules in the range of 0.5 kWh–15 kWh configurations were considered for residential buildings whereas 25 kW h–500 kW h modules were considered for commercial buildings. Detailed cost and performance analysis of the GLIDES module proved them to be an effective resource in lowering the peak energy demand and corresponding utility bills.

25 ENERGY STORAGE↗

Degradation and Modeling of Large-Format Commercial Lithium-Ion Cells as a Function of Chemistry, Design, and Aging Conditions

Demand for large-format (>10 Ah) lithium-ion batteries has increased substantially in recent years, due to the growth of both electric vehicle and stationary energy storage markets. The economics of these applications is sensitive to the lifetime of the batteries, and end-of-life can either be due to energy or power limitations. Despite this, there is little information from cell manufacturers on the sensitivity of cell degradation to environmental conditions or battery use. This work reports accelerated aging test data from four commercial large-format lithium-ion batteries from three manufacturers, with varying design (thickness, casings, ...), chemistry (lithium-iron-phosphate (LFP) or lithium-nickel-manganese-cobalt-oxide positive electrodes (NMC), with graphite (Gr) negative electrodes), and capacity (50 to 250 Amp hours). The tested LFP|Gr cell is found to be relatively insensitive to cycling conditions like temperature or voltage window, while NMC|Gr cells have varying sensitivity. Degradation trends are further investigated by training predictive models: simple polynomial trend lines, a semi-empirical reduced-order model, and an empirical reduced-order model identified using machine-learning based on symbolic regression. Calendar and cycle life are simulated over a variety of conditions to directly compare the various batteries. Cell size and thickness are found to substantially impact sensitivity to temperature during cycle aging, while electrode chemistry impacts depth-of-discharge sensitivity. Real-world battery lifetime is evaluated by simulating residential energy storage and commercial frequency containment reserve systems in several U.S. climate regions. Predicted lifetime across cell types varies from 7 years to 20+ years, though all cells are predicted to have at least 10 year life in certain conditions.

battery lifetime↗

Comprehensive evaluation of commercially scalable atomic-layer-deposited alumina coating impact on full cell battery performance across varied test conditions

Atomic Layer Deposition (ALD) has emerged as a strategic enhancement method for lithium-ion battery (LIB) materials offering potential benefits and durability benefits for industrial battery production. However, the translation from laboratory achievements to commercial-scale applications has been limited. Here, this study aims to bridge this gap by comprehensively evaluating the effects of commercially scalable Al 2 O 3 ALD coatings using full pouch cell performance as a means to assess the ALD impact. We utilized large-scale slot-die coating techniques to ensure consistent electrode quality and tested four configurations of pouch cells to analyze the individual effects of ALD coating on anode and cathode electroactive materials. Our extensive testing matrix included long-term cycling, fast discharge, fast charge, leakage current, and high voltage tests. While at lower C-rates (<~1C), the influence of Al 2 O 3 coatings on cell performance is not significant. Fast charging conditions reveal that the anode ALD coating significantly enhances performance via a passivating effect, while on the cathode, it is detrimental, potentially due to increased resistance of the thin interfacial layer formed during the ALD processing. Leakage current and high-voltage tests show that the application of ALD coatings on either anode or cathode effectively minimizes side reactions at the electrode-electrolyte interface. Additionally, ALD coatings significantly mitigate concentrated and localized lithium plating on the anodes. These insights provide a valuable understanding of the potential of ALD technologies in LIB manufacturing to tailor cell performance, paving the way for safer, more efficient, and cost-effective battery solutions.

25 ENERGY STORAGE↗

Post-irradiation examination of commercial tantalum alloys following neutron irradiation

Post irradiation examination of two commercial tantalum alloys (based on Ta-8 %W) revealed significant irradiation hardening following neutron irradiation in the High Flux Isotope Reactor at Oak Ridge National Laboratory. Tensile samples of commercial Ta alloys T-111 and ASTAR-811C were irradiated to a total neutron fluence (E > 0.1 MeV) in the range (2–4)x10 21 n/cm 2 (0.39–0.75 dpa) at an irradiation temperature near 900 °C. Tensile testing conducted at room temperature and at 800 °C revealed significant irradiation hardening under all test conditions. Samples that were tensile tested at room temperature exhibited brittle failure, whereas ductility was maintained for elevated temperature testing. The irradiation hardening and embrittlement noted for both alloys was attributed to irradiation-induced dislocation loop formation as confirmed through scanning transmission electron microscopy analysis. Corresponding energy dispersive x-ray spectroscopy revealed radiation-induced segregation of Hf in these loop populations. This Hf enrichment is shown to result in eventual co-precipitation of elongated (Hf,O)-rich precipitates along the dislocation loops. Further, these results show that irradiation hardening is enhanced via irradiation-enhanced precipitation at elevated irradiation temperatures. Consequently, the minimum recommended operating temperature window for Ta alloys should be increased to account for observed hardening/embrittlement at irradiation temperatures as high as 900 °C (1,173 K).

36 MATERIALS SCIENCE↗

The comparative strength and fracture toughness properties of commercial 95W-3.5Ni1.5Fe and 95W-3.5Ni1.5Cu tungsten heavy alloys

Due to the sharp surface cracks resulting from high and cyclic thermal loads, fracture toughness is a crucial property for fusion divertor materials. Tungsten heavy alloys (WHA) have emerged as a leading candidate for plasma facing component applications. Both the WNiFe and WNiCu WHAs have been considered. However, there is no fracture toughness data in the literature on the WNiCu WHA. Therefore, maximum load elastic–plastic fracture toughness (K Jm ) of a commercial 95W-3.5Ni1.5Cu (NiCu) WHA plate is reported here for the first time. The NiCu WHA K Jm is compared to a corresponding K Jm for commercial 95W-3.5Ni1.5Fe (NiFe) WHA, along with comparisons of their respective microstructures, microhardness, and tensile properties. Although their room temperature yield strengths are similar (≈ 600 MPa), the NiFe WHA has higher ultimate stress (818 MPa vs. 642 MPa) and total elongation (8% vs. 1.2%) compared to the NiCu WHA. Most notably, the room temperature elastic–plastic K Jm for the NiFe WHA of ≈ 80 ± 8 MPa$\sqrt{m}$, is nearly twice that of the NiCu WHA at ≈ 47 ± 4 MPa$\sqrt{m}$. Further, while the NiFe WHA experienced stable ductile tearing, the crack propagated unstably (approximately elastically) after reaching the maximum load in the NiCu WHA. The higher K Jm of the NiFe WHA is attributed to its higher flow stress and ductility, along with the energy dissipation and microcrack dilatational stress shielding, provided by a wide distribution of arrested process-zone microcracks, which are largely absent in the NiCu WHA. Since, the 95W-NiFe WHA has distinctly better mechanical properties than 95W-NiCu WHA, it is a more suitable candidate for the fusion reactor application.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Commercial aluminum powders, Part I: Particle size characterization and slow heating rate thermal analysis.

We characterized nine commercial aluminum (Al) powders using several methods to measure particle characteristics and thermal analysis, with the goal to understand how these parameters influence energy release. Although it is well-known that lot-to-lot variations in commercial nanoparticles are common, the Al powders were more heterogeneous than anticipated – both with regards to particle size distributions and impurities. Manufacturer specifications – often quoted in the literature without confirmation – were not always accurate for the specific sample lots we investigated. In several cases, different conclusions could be drawn from individual particle size techniques; a combination of multiple techniques provides a clearer picture of the powder properties. Thorough characterization of Al powders is required prior to interpretation of experimental results from a variety of applications. In particular, previous studies have shown contradictory results on the influence of Al on detonation performance, perhaps partially due to insufficient characterization of the Al powders themselves.

36 MATERIALS SCIENCE↗

A novel probabilistic regression model for electrical peak demand estimate of commercial and manufacturing buildings

Due to the high cost of electricity in commercial and industrial sectors, demand forecast models have gained increasing attention. However, there are two unresolved issues: (1) Models are not adaptable when exposed to previously unknown data (2) The value of regression methods vs. state-of-the-art machine learning models has not been made apparent before. This study’s goal is to develop probabilistic demand estimation models. Herein, we propose a probabilistic Bayesian regression framework that can not only estimate future demands with high accuracy but also be updated once new information is available. By applying the proposed algorithm to two real-world case studies (commercial and manufacturing), we show a 40.3% and 30.8% improvement in terms of mean absolute error for the two cases. Moreover, the proposed technique outperforms powerful machine learning approaches, including support vector machine by 10.39%, random forest by 6.17%, and multilayer perceptron by 9.14% in terms of mean absolute percentage error.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Lighting and visual comfort performance of commercially available tubular daylight devices

Tubular daylight devices (TDDs) require a much smaller roof opening than conventional skylights and, because of their highly reflective tube, they can deliver daylight farther away from the building envelope. This can provide lighting energy savings, increasing resilience in new and existing buildings. Different types and configurations are available amongst commercially available TDDs, including domes/diffusers with varying optical properties and the diameter of the TDD. This paper presents a comprehensive experimental evaluation of the lighting and visual comfort performance of multiple configurations of commercially available TDDs, varying dome type (prismatic and clear), diffuser type (Fresnel and prismatic), and diameter (53 and 35 cm), under a range of environmental conditions (different times of day/year, sky cover). Based on illuminance measurements, estimated lighting energy use is also presented. Results indicate that, for clear sky, light levels increase and energy use decreases with solar altitude (e.g., 16 Wh/m 2 daily energy use intensity on a high maximum daily solar altitude (MDSA) day and 34 Wh/m 2 on a low MDSA day) and TDD diameter (e.g., 34 Wh/m 2 and 69 Wh/m 2 for 53 cm and 35 cm TDDs, respectively, for low MDSA). The daily illuminance profile is more rounded for prismatic domes and has higher peaks for clear domes; this translates into a somewhat higher average daily useful daylight illuminance (DUDI) for prismatic domes (86 %) when compared to clear domes (80 %). No clear impact of diffuser type was apparent. In conclusion, measurements indicated no discomfort glare for any of the conditions tested.

14 SOLAR ENERGY↗

Modeling receiver flux of commercial power tower concentrating solar power plants using ray tracing: a round-robin comparison of SolTrace, Solstice, and TieSOL

This study presents a multi-stage, cross-validation comparison of three software packages for Monte Carlo ray tracing (MCRT) applied to central tower concentrating solar power (CSP) systems. The three packages evaluated are: (1) SolTrace, an open-source tool developed by the National Renewable Energy Laboratory (NREL); (2) Solstice, an open-source program created by CNRS-PROMES and Meso-Star, with enhancements for CSP applications (called solsticepy) from the Australian National University; and (3) TieSOL, a commercial software developed by Tietronix. This investigation extends previous ray tracing comparisons by incorporating models of multi-facet heliostats within a commercial-scale solar field, taking into account zoned focal lengths and canting configurations. Receiver flux distributions were compared across the tools using a series of case studies, including single-heliostat scenarios, isolated blocking situations, and comprehensive full-field simulations. The case studies were designed to diagnose differences across the models at varying levels of complexity, and to identify and resolve discrepancies as additional parameters were introduced. Key factors examined in the analysis include sun positions, heliostat location, facet and canting focus, and aimpoint strategies. The comparison aims to improve the accuracy and reliability of these tools while providing benchmark cases for validating future optical modeling tools.

14 SOLAR ENERGY↗

Corrosion of novel reactive silver ink and commercial silver-based metallizations in diluted acetic acid

Silver-based metallizations in photovoltaic modules are susceptible to corrosion by acetic acid generated in ethylene vinyl acetate encapsulated modules, resulting in power losses over time. Here, three silver-based metallizations are exposed to diluted acetic acid, in concentrations representative of that found in field-exposed modules. Compositional, morphological, and structural changes of the metallizations are studied over 3000 h of exposure to diluted acetic acid using Raman spectroscopy mapping, X-ray diffraction, and scanning electron microscopy. The three metallizations studied are: 1) a commercial high-temperature fire-through Ag paste, commonly used for Si diffused junction solar cells; 2) a commercial low-temperature paste normally used for silicon heterojunction cells; and 3) a novel low-temperature reactive silver ink shown to be suitable for photovoltaic applications. We find distinct corrosion rates for the high-temperature silver paste and reactive silver ink in the presence of diluted acetic acid. However, the low-temperature silver paste appears to be more corrosion resistant, likely due to a polymer layer that protects the silver particles.

36 MATERIALS SCIENCE↗

Characterization of Shallow, Undoped Ge/SiGe Quantum Wells Commercially Grown on 8-in. (100) Si Wafers

Hole spins in Ge quantum wells have shown success in both spintronic and quantum applications, thereby increasing the demand for high-quality material. We performed material analysis and device characterization of commercially grown shallow and undoped Ge/SiGe quantum well heterostructures on 8-in. (100) Si wafers. Material analysis reveals the high crystalline quality, sharp interfaces, and uniformity of the material. We demonstrate a high mobility (1.7 × 10 5 cm 2 V –1 s –1 ) 2D hole gas in a device with a conduction threshold density of 9.2 × 10 10 cm –2 . We study the use of surface preparation as a tool to control barrier thickness, density, mobility, and interface trap density. We report interface trap densities of 6 × 10 12 eV –1 . Our results validate the material’s high quality and show that further investigation into improving device performance is needed. We conclude that surface preparations which include weak Ge etchants, such as dilute H 2 O 2 , can be used for postgrowth control of quantum well depth in Ge-rich SiGe while still providing a relatively smooth oxide–semiconductor interface. Our results show that interface state density is mostly independent of our surface preparations, thereby implying that a Si cap layer is not necessary for device performance. Transport in our devices is instead limited by the quantum well depth. Commercially sourced Ge/SiGe, such as studied here, will provide accessibility for future investigations.

36 MATERIALS SCIENCE↗

Engineering Surface Oxygenated Functionalities on Commercial Carbon toward Ultrafast Sodium Storage in Ether-Based Electrolytes

The pursuit of a high-capacity anode material has been urgently required for commercializing sodium-ion batteries with a high energy density and an improved working safety. In the absence of thermodynamically stable sodium intercalated compounds with graphite, constructing nanostructures with expanded interlayer distances is still the mainstream option for developing high-performance carbonaceous anodes. In this regard, a surface-functionalized and pore-forming strategy through a facile CO 2 thermal etching route was rationally adopted to engineer negligible oxygenated functionalities on commercial carbon for boosting the sodium storage process. Benefitted from the abundant ionic/electronic pathways and more active reaction sites in the microporous structure with noticeable pseudocapacitive behaviors, the functionalized porous carbon could achieve a highly reversible capacity of 505 mA h g -1 at 50 mA g -1 , an excellent rate performance of 181 mA h g -1 at 16,000 mA g -1 , and an exceptional rate cycle stability of 176 mA h g -1 at 3200 mA g -1 over 1000 cycles. These outstanding electrochemical properties should be ascribed to a synergistic mechanism, fully utilizing the graphitic and amorphous structures for synchronous intercalations of sodium ions and solvated sodium ion compounds, respectively. Finally, the controllable generation and evolution of a robust but thin solid electrolyte interphase film with the emergence of obvious capacitive reactions on the defective surface, favoring the rapid migration of sodium ions and solvated species, also contribute to a remarkable electrochemical performance of this porous carbon black.

25 ENERGY STORAGE↗