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At least 181 records · Page 10

C@SnS 2 core-shell 0D/2D nanocomposite with excellent electrochemical performance as lithium-ion battery anode

C@SnS 2 core-shell 0D/2D nanocomposite was successfully prepared by a one-step hydrothermal method. The SnS 2 nanosheets were heterogeneously nucleated and grown on the surface of carbon spheres. As an anode for lithium-ion batteries, the electrochemical performance of the C@SnS 2 composite outperforms that of SnS 2 nanoflowers. After 100 cycles, the reversible discharge specific capacity reaches an impressive value of 802 mAh g -1 at a current density of 100 mA g -1 . Even after 600 cycles, the discharge specific capacity remains a value of 442 mAh g -1 , under a high current density of 1 A g -1 . Further, this remarkable lithium-ion storage performance can be attributed to the unique core-shell nanostructure and the synergy between SnS 2 nanosheets and carbon spheres. This study advances our understanding of the vital role of carbon in fabricating nano-heterojunction or composite electrodes and provides a feasible route to significantly improve the electrochemical properties of SnS 2 and other metal sulfides.

25 ENERGY STORAGE↗

Effect of crystallite size on lithium storage performance of high entropy oxide (Cr 0.2 Mn 0.2 Co 0.2 Ni 0.2 Zn 0.2 ) 3 O 4 nanoparticles

High-entropy oxides (HEOs), known for their high theoretical capacity and structural stability, are considered promising anode materials for next-generation lithium-ion batteries (LIBs). In this research, we synthesized a novel spinel-type HEO, (Cr 0.2 Mn 0.2 Co 0.2 Ni 0.2 Zn 0.2 ) 3 O 4 , using a solution combustion method. By adjusting the quantity of the combustion agent, we produced samples with varying crystallite sizes. The crystallite size of the HEOs initially enlarges with an increased combustion agent, then diminishes. The enhancement of crystallite size correlates with improved electrochemical performance for lithium storage. Notably, the (Cr 0.2 Mn 0.2 Co 0.2 Ni 0.2 Zn 0.2 ) 3 O 4 nanoparticles, with the largest crystallite size of 36.3 nm, demonstrated a reversible capacity of 343 mA h g -1 after 100 cycles at 100 mA g -1 , a capacity retention to 319 mA h g -1 after 1000 cycles at 1 A g -1 , and a commendable rate capability of 260 mA h g -1 at 2 A g -1 . Furthermore, this study underscores the pivotal role of crystallite size in LIB performance and presents a viable strategy to enhance the lithium storage capabilities of HEOs and other metal oxides.

25 ENERGY STORAGE↗

(CrMnCoNiTi) 3 O 4 high-entropy spinel oxide as a high-performance electrode for supercapacitors

In this study, spinel-structured (CrMnCoNiTi)₃O₄ high-entropy oxides (HEOs) have been successfully synthesized using the solution combustion method, and their performance as supercapacitor electrode materials was investigated. These HEOs exhibit excellent performance, stemming from the unique high-entropy effect and lattice distortion. This structure effectively buffers volumetric strain during cycling, conferring the material with extremely high structural stability and specific capacity. The material demonstrates a high specific capacity of 491.5 C∙g⁻¹ at a current density of 0.5 A∙g⁻¹. Furthermore, it shows extraordinary cycling stability: after 10,000 charge/discharge cycles at 5 A∙g⁻¹, the capacity retention rate is 99%, and the Coulombic efficiency consistently remains close to 100%. Ex-situ structural characterizations further reveal that this excellent cycling durability originates from a cooperative multination valence reconstruction mechanism within an entropy-stabilized spinel framework. Additionally, a symmetric supercapacitor assembled using this material and 1 M KOH electrolyte successfully extended the working voltage to 1.2 V. This research highlights the great potential of high-entropy oxides in synergizing high energy density and ultra-long cycling life, laying a solid foundation for the development of next-generation high-performance supercapacitor electrode materials.

High entropy oxides↗

China's plug-in hybrid electric vehicle transition: An operational carbon perspective

Assessing the emissions of plug-in hybrid electric vehicle (PHEV) operations is crucial for accelerating the carbon–neutral transition in the passenger car sector. This study is the first to adopt a bottom-up model to measure the real-world energy use and carbon dioxide emissions of China’s top twenty selling PHEV models across different regions from 2020 to 2022. The results indicate that (1) the actual electricity intensity of the best-selling PHEV models (20.2–38.2 kWh/100 km) was 30–40 % higher than the New European Driving Cycle values, and the actual gasoline intensity (4.7–23.5 L/100 km) was 3–6 times greater than the New European Driving Cycle values. (2) The overall energy use of the best-selling models varied among different regions, and the energy use from 2020 to 2022 in Southern China was double that Northern China and the Yangtze River Middle Reach. (3) The top-selling models emitted 4.7 megatons of carbon dioxide nationwide from 2020 to 2022, with 1.9 megatons released by electricity consumption and 2.8 megatons released by gasoline combustion. Furthermore, targeted policy implications for expediting the carbon–neutral transition within the passenger car sector are proposed. In essence, this study explores and compares benchmark data at both the national and regional levels, along with performance metrics associated with PHEV operations. The main objective is to aid nationwide decarbonization efforts, focusing on carbon reduction and promoting the rapid transition of road transportation toward a net-zero carbon future.

33 ADVANCED PROPULSION SYSTEMS↗

Co-benefits of subnationally differentiated carbon pricing policies in China: Alleviation of heavy PM 2.5 pollution and improvement in environmental equity

Carbon policies differentiated according to regional disparities have been recognized and recommended. However, the air quality co-benefits of differentiated policies remain unclear. Here we combine a multi-regional dynamic computable general equilibrium (CGE) model and an extend response surface model (ERSM) to investigate the impact of nationally uniform and subnationally differentiated carbon pricing policies on fine particulate matter (PM 2.5 ) concentrations in China. All policies examined lead to the same accumulated national CO 2 emissions (2020–2050), with the 2030 emissions attaining China's national abatement target. We find that, when subnational policies differentiated according to provincial PM 2.5 concentrations are implemented, the higher-than-average carbon price over more polluted provinces results in twice as much reduction in CO 2 and air pollutant emissions in 2050 as the national policy. As a result, the subnational policies cause larger PM 2.5 concentration reductions in these provinces (9%–18%) than the national policy (7%–11%). Also, the subnational policies eliminate high PM 2.5 exposure of over 45 μg/m 3 which 12% people suffer from under the national policy. Overall, the subnational policies substantially reduce regional disparity in PM 2.5 pollution and hence improve environmental equity. The results suggest that subnationally differentiated carbon policies are a promising instrument to mitigate severe pollution and promote environmental equity.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

The importance of capturing power system operational details in resource adequacy assessments

Traditional methods for assessing the resource adequacy (RA) of a power system are becoming obsolete due to emerging trends such as the increasing deployment of variable renewable energy and storage. Consequently, analysts are recommending that RA be assessed using a Monte Carlo simulation approach that models chronological power system operations over many instances of possible operating conditions. However, this approach is necessarily more complex and computationally demanding, which is an obstacle to real-world implementation. Here, in this study, we investigate which operational details of power systems are important to capture in order to accurately evaluate a system's RA, versus details that add complexity but do not meaningfully affect RA results. To do so, we develop a probabilistic RA assessment framework by adapting an existing production cost model and apply it to a case study based on the IEEE Reliability Test System. Our results indicate that multi-year data, storage dispatch, and transmission limits are key details to incorporate. Accurate RA results can be obtained using non-economic dispatch strategies as long as they are coordinated with detailed operational strategies. We also demonstrate how popular expectation-based RA metrics can mask important differences in the characteristics of loss of load events.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Low concentration electrolyte: A new approach for achieving high performance lithium batteries

The conventional perspective suggests that low-concentration electrolytes (LCEs) face challenges in achieving stable charge/discharge properties due to the decreased ionic conductivity resulting from lower Li + concentrations. However, the successful utilization of LCEs in lithium/sodium-ion batteries has brought them into the forefront of consideration for high performance battery systems. It is possible to achieve improved interface stability and ion transport performance for LCEs through adjusting electrolyte components, such as salts, solvents, and additives. This review provides timely update of the recent research progress, design strategies and remaining challenges of LCEs to answer several questions: i) What is the key factor for designing LCEs? ii) How to balance the low salt concentration and good ionic conductivity? iii) What is the interphasial mechanism of anode/cathode in LCEs? Firstly, the development of LCEs is discussed with typical examples. Subsequently, effectiveness of solvents on overall performances of LCEs is comprehensively summarized in detail. Finally, the challenges and possible research direction of LCEs are discussed. This review provides critical guidance for designing novel electrolytes for secondary batteries.

25 ENERGY STORAGE↗

Multi-site evaluation of stratified and balanced sampling of soil organic carbon stocks in agricultural fields

Estimating soil organic carbon (SOC) stocks in agricultural fields is essential for environmental and agronomic research, management, and policy. Stratified sampling is a classic strategy for estimating mean soil properties, and has recently been codified in SOC monitoring protocols. However, for the specific task of estimating the SOC stock of an agricultural field, concrete guidance is needed for which covariates to stratify on and how much stratification can improve estimation efficiency. It is also unknown how stratified sampling of SOC stocks compares to modern alternatives, notably doubly balanced sampling. To address these gaps, we collected high-density (average of 7 samples ha -1 ) and deep (average of 75 cm) measurements of SOC stocks at eight commercial fields under maize-soybean production in two US Midwestern states. We combined these measurements with a Bayesian geostatistical model to evaluate stratified and balanced sampling strategies that use a set of readily-available geographic, topographic, spectroscopic, and soil survey data. We examined the number of samples needed to achieve a given level of SOC stock estimation accuracy. While stratified sampling using these variables enables an average sample size reduction of 17% (95% CI, 11% to 23%) compared to simple random sampling, doubly balanced sampling is consistently more efficient, reducing sample sizes by 32% (95% CI, 25% to 37%). The data most important to these efficiency gains are a remotely-sensed SOC index, SSURGO estimates of SOC stocks, and the topographic wetness index. We conclude that in order to meet the urgent challenge of climate change, SOC stocks in agricultural fields could be more efficiently estimated by taking advantage of this readily-available data, especially with doubly balanced sampling.

54 ENVIRONMENTAL SCIENCES↗

Spectroscopy and dynamics of the v = 1 levels derived from the OH(D) stretching modes in the I‾∙HDO complex using CW and time-resolved, resonant two-photon infrared excitation of the cryogenically cooled ions

The vibrational energy levels of the two isotopomers adopted by the I‾∙HDO ion-molecule complex occur such that the OH(D) stretching fundamentals span its dissociation energy, thus enabling a spectroscopic investigation of the dynamics displayed by a system prepared in the vicinity of the dissociation threshold. This regime is explored using infrared photoexcitation of the mass-selected complexes cooled in a cryogenic radiofrequency (Paul) ion trap. Survey spectra are obtained at modest resolution using two-color, IR-IR photodissociation with nanosecond lasers to establish the level structure and unimolecular decay dynamics of the v = 1 and 2 levels of the bound OH(D) oscillator. The v = 1 levels are prepared by fixed frequency excitation in the trap and the absorption spectra arising from this excited state are probed by photofragmentation of the complex with a second pulsed IR laser after a variable delay time (0 to 20 ms). The transitions to levels above the dissociation threshold for I‾ + HDO formation are observed to be sharp (~5 cm -1 FWHM). At low pressure, the bound OD (v = 1) population relaxes very slowly (~3 ms), consistent with resonant fluorescence in the IR. The collisional quenching rate constants of this level by the He buffer gas were estimated to be on the order 3 x 10 -12 cm 3 /s based on a crude Stern-Volmer analysis. Here, the rotational fine structure and linewidths (≲0.01 cm -1 FWHM) arising from transitions of the non-bonded OH stretch fundamental of the OD-bound isotopomer that lies just above the dissociation energy are determined using single photon photodissociation by excitation of the 10 K ions with a single-frequency, CW IR laser in the ion trap.

Cryogenic ion infrared spectroscopy↗

Attribution of heterogeneous stress distributions in low-grain polycrystals under conditions leading to damage

In high-purity polycrystalline metallic materials, voids tend to favor grain boundaries as nucleation sites due to the elevated stress states produced by granular interactions and the weakened grain boundary from the relative atomic disorder. To quantify the key factors of this elevated stress state, simple compression of a small multi-grain cylinder of body-centered cubic tantalum was simulated using a single crystal plasticity model that incorporates non-Schmid effects. Four increasingly complex synthetic microstructures were created to tractably incorporate grain boundary interactions, and a statistically significant number of combinations were performed by varying the initial crystallographic orientations of the microstructure. Most of these simulations produce the maximum von Mises stress on a grain boundary and less frequently at the multi-grain junctions. To build a statistical model for the maximum von Mises stress at the grain boundary, physically based features that could contribute to the elevated stress state were selected. Then, a learning algorithm based on information theory was used to identify which of these features contributed the most information to the data set. The identified features include a grain’s propensity to accommodate both elastic and plastic deformations and their directional components. The misalignment of the direction of each grain’s mechanical response was found to be strongly correlated to the magnitude of the stress near the grain boundary. For all of the synthetic microstructures, the statistical models produce a residual distribution that is nearly Gaussian with a variance of, at most, 10% of the prior distribution. The successful performance of the statistical model implies the correct identification of the physical features that cause severe stress localization in polycrystalline materials. The statistical models constructed here can be used to formulate a physically motivated void nucleation model which is sensitive to a microstructure’s propensity to produce elevated stress states. As a result, these statistical models also enable the design of material microstructures, in which the crystallographic orientation is chosen to resist void nucleation.

36 MATERIALS SCIENCE↗