Research Development on K‑Ion Batteries Hosaka, Tomooki; Kubota, Kei; Hameed, A. Shahul ...
Chemical reviews,
07/2020, Letnik:
120, Številka:
14
Journal Article
Recenzirano
Li-ion batteries (LIBs), commercialized in 1991, have the highest energy density among practical secondary batteries and are widely utilized in electronics, electric vehicles, and even stationary ...energy storage systems. Along with the expansion of their demand and application, concern about the resources of Li and Co is growing. Therefore, secondary batteries composed of earth-abundant elements are desired to complement LIBs. In recent years, K-ion batteries (KIBs) have attracted significant attention as potential alternatives to LIBs. Previous studies have developed positive and negative electrode materials for KIBs and demonstrated several unique advantages of KIBs over LIBs and Na-ion batteries (NIBs). Thus, besides being free from any scarce/toxic elements, the low standard electrode potentials of K/K+ electrodes lead to high operation voltages competitive to those observed in LIBs. Moreover, K+ ions exhibit faster ionic diffusion in electrolytes due to weaker interaction with solvents and anions than that of Li+ ions; this is essential to realize high-power KIBs. This review comprehensively covers the studies on electrochemical materials for KIBs, including electrode and electrolyte materials and a discussion on recent achievements and remaining/emerging issues. The review also includes insights into electrode reactions and solid-state ionics and nonaqueous solution chemistry as well as perspectives on the research-based development of KIBs compared to those of LIBs and NIBs.
K-ion batteries (KIBs) are promising for large-scale electrical energy storage owing to the abundant resources and the electrochemical specificity of potassium. Among the positive electrode materials ...for KIBs, vanadium-based polyanionic materials are interesting because of their high working voltage and good structural stability which dictates the cycle life. In this study, a potassium vanadium oxide phosphate, K
6
(VO)
2
(V
2
O
3
)
2
(PO
4
)
4
(P
2
O
7
), has been investigated as a 4 V class positive electrode material for non-aqueous KIBs. The material is synthesized through pyrolysis of a single metal-organic molecular precursor, K
2
(VOHPO
4
)
2
(C
2
O
4
) at 500 °C in air. The material demonstrates a reversible extraction/insertion of 2.7 mol of potassium from/into the structure at a discharge voltage of ∼4.03 V
vs.
K.
Operando
and
ex situ
powder X-ray diffraction analyses reveal that the material undergoes reversible K extraction/insertion during charge/discharge
via
a two-phase reaction mechanism. Despite the extraction/insertion of large potassium ions, the material demonstrates an insignificant volume change of ∼1.2% during charge/discharge resulting in excellent cycling stability without capacity degradation over 100 cycles in a highly concentrated electrolyte cell. Robustness of the polyanionic framework is proved from identical XRD patterns of the pristine and cycled electrodes (after 100 cycles).
Highly pure K
6
(VO)
2
(V
2
O
3
)
2
(PO
4
)
4
(P
2
O
7
), synthesized from the oxalatophosphate precursor, demonstrates a reversible potassium extraction/insertion capacity of 59 mA h g
−1
with a single discharge voltage plateau at 4.0 V at room temperature.
Na-ion batteries (SIBs), perceived as the most promising alternative energy storage technology, are attractive for large-scale stationary applications due to the cost effectiveness and global ...abundance of sodium. One of the formidable challenges in the way of their extensive commercialization is the development of suitable low-cost positive electrode materials with high energy density and long cycle life. In this study, a phosphite-based layered polyanionic material with the formula, Na
2
(VOHPO
3
)
2
(C
2
O
4
)·2H
2
O, has been investigated as a novel positive electrode for SIBs. The material was synthesized through a room temperature precipitation method and undergoes reversible Na
+
-ion insertion at an average discharge voltage of 3.65 V which is higher than that of the same V
4+
/V
5+
redox couple of NaVOPO
4
(3.4 V) in a non-aqueous Na cell. The material exhibits a high discharge capacity of ∼101 mA h g
−1
at 0.1C rate in Na half-cells. Capacity fading encountered by the pristine material was overcome with the help of ball-milling with carbon. The layered material facilitates the migration of large Na
+
ions, resulting in a superior rate performance (∼80 mA h g
−1
at 10C rate). In addition, a long-term cycling stability over 1000 cycles was demonstrated at 2C rate with 62% capacity retention.
Operando
XRD studies reveal that the reversible Na
+
-ion insertion in the framework happens
via
a bi-phasic mechanism. The feasibility of full cells was demonstrated using NaTi
2
(PO
4
)
3
as the negative electrode and the full cell exhibited a reversible capacity of 71 mA h g
−1
at 0.1C rate and 65 mA h g
−1
at 1C rate with good capacity retention.
A phosphite-based layered polyanionic material, Na
2
(VOHPO
3
)
2
(C
2
O
4
)·2H
2
O, exhibits a superior rate performance (∼80 mA h g
−1
at 10C rate) and a long-term cycling stability for 1000 cycles at 2C rate in Na cells.
Nature-inspired metaheuristic algorithms remain a strong trend in optimization. Human-inspired optimization algorithms should be more intuitive and relatable. This paper proposes a novel optimization ...algorithm inspired by a human search party. We hypothesize the behavioral model of a search party searching for a treasure. Motivated by the search party’s behavior, we abstract the “Divide, Conquer, Assemble” (DCA) approach. The DCA approach allows us to parallelize the traditional gradient descent algorithm in a strikingly simple manner. Essentially, multiple gradient descent instances with different learning rates are run parallelly, periodically sharing information. We call it the search party gradient descent (SPGD) algorithm. Experiments performed on a diverse set of classical benchmark functions show that our algorithm is good at optimizing. We believe our algorithm’s apparent lack of complexity will equip researchers to solve problems efficiently. We compare the proposed algorithm with SciPy’s optimize library and it is found to be competent with it.
Gadilam river basin has gained its importance due to the presence of Neyveli Lignite open cast mines and other industrial complexes. It is also due to extensive depressurization of Cuddalore aquifer, ...and bore wells for New Veeranam Scheme are constructed downstream of the basin. Geochemical indicators of groundwater were used to identify the chemical processes that control hydrogeochemistry. Chemical parameters of groundwater such as pH, electrical conductivity, total dissolved solids, sodium (Na ⁺ ), potassium (K ⁺ ), calcium (Ca ⁺ ), magnesium (Mg ⁺ ), bicarbonate graphic removed , sulfate graphic removed , phosphate graphic removed , and silica (H₄SiO₄) were determined. Interpretation of hydrogeochemical data suggests that leaching of ions followed by weathering and anthropogenic impact controls the chemistry of the groundwater. Isotopic study reveals that recharge from meteoric source in sedimentary terrain and rock-water interaction with significant evaporation prevails in hard rock region.
Gradient descent (GD) is an elementary optimization (OP) algorithm quite well-known in machine learning. It is the preferred choice of the OP algorithm for highly smooth and convex functions. In its ...native form, GD has one primary hyperparameter: Learning rate/Step size. Despite the availability of various methods, tuning this learning rate remains a considerable challenge. In this paper, we propose “MABSearch,” a GD algorithm using a multi-armed bandit (MAB) strategy to ‘learn’ and choose the optimal learning rate suitable for the objective function under consideration. The proposed algorithm remains true to its predecessors by preserving their innate simplicity. Python code of MABSearch is available at GitHub (
https://github.com/Shahul-Rahman/MABSearch-Learning-the-learning-rate
).
ZnFe2O4 and Mg x Cu0.2Zn0.82–x Fe1.98O4 (where x = 0.20, 0.25, 0.30, 0.35, and 0.40) nanoparticles were synthesized by sol–gel assisted combustion method. X-ray diffraction (XRD), FTIR spectroscopy, ...Raman spectroscopy, scanning electron microscopy (SEM), transmission electron microscopy (TEM), and Brunauer–Emmett–Teller (BET) surface area studies were used to characterize the synthesized compounds. ZnFe2O4 and the doped compounds crystallize in Fd3m space group. The lattice parameter of ZnFe2O4 is calculated to be a = 8.448(3) Å, while the doped compounds show a slight decrease in the lattice parameter with an increase in the Mg content. The particle size of all the compositions are in the range of ∼50–80 nm, and the surface area of the compounds are in the range of 11–12 m2 g–1. Cyclic voltammetry (CV), galvanostatic cycling, and electrochemical impedance spectroscopy (EIS) studies were used to investigate the electrochemical properties of the different compositions. The as-synthesized samples at 600 °C show large-capacity fading, while the samples reheated at 800 °C show better cycling stability. ZnFe2O4 exhibits a high reversible capacity of 575 mAh g–1 after 60 cycles at a current density of 100 mA g–1. Mg0.2Cu0.2Zn0.62Fe1.98O4 shows a similar capacity of 576 mAh g–1 after 60 cycles with better capacity retention.
This paper describes an automatic image analysis technique for p53 immunostained tissue sections of oral cancer. The tissue images are segmented using the entropy thresholding and clustered cells are ...resolved by selectively applying watershed transform. Each cell nuclei of tissue images is classified as positive or negative according to the staining intensity using support vector machine, and then, tissue score is determined as per J-scoring protocol. The performance of the feature and also scoring technique has been evaluated separately by an individual dataset. According to the experimental result, the feature extracted from the blue component has attained the highest classification accuracy of 98.01% with sensitivity and specificity of 98.86% & 94.74% respectively. The outcome of automatic technique based on the blue component has a strong agreement with the manual score. Therefore, automatic tissue scoring has high potential in the field of modern cancer diagnosis and specific therapy design for the patients.
•An automatic tissue image analysis technique has been presented.•Nuclei segmentation is performed by entropy thresholding and watershed transform.•Maximal separation feature is extracted from nuclei for classification.•Automatic J-score is determined and compared with manual score.•The outcome based on the blue component has a strong agreement with the manual score.
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