A general ultrathin‐nanosheet‐induced strategy for producing a 3D mesoporous network of Co3O4 is reported. The fabrication process introduces a 3D N‐doped carbon network to adsorb metal cobalt ions ...via dipping process. Then, this carbon matrix serves as the sacrificed template, whose N‐doping effect and ultrathin nanosheet features play critical roles for controlling the formation of Co3O4 networks. The obtained material exhibits a 3D interconnected architecture with large specific surface area and abundant mesopores, which is constructed by nanoparticles. Merited by the optimized structure in three length scales of nanoparticles–mesopores–networks, this Co3O4 nanostructure possesses superior performance as a LIB anode: high capacity (1033 mAh g−1 at 0.1 A g−1) and long‐life stability (700 cycles at 5 A g−1). Moreover, this strategy is verified to be effective for producing other transition metal oxides, including Fe2O3, ZnO, Mn3O4, NiCo2O4, and CoFe2O4.
A general ultrathin‐nanosheet‐induced strategy is introduced for producing 3D mesoporous network of transition metal oxides (TMOs). An N‐doped carbon network serves as the sacrificed template, which can be applied to many kinds of TMOs. The obtained material exhibits an interconnected mesopore architecture and possesses superior performance as a lithium ion anode.
Full text
Available for:
BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
The honeycomb-like porous Co3O4 grown on three dimensional graphene networks/nickel foam (3DGN/NF) has been successfully prepared by a facile solution growth process with subsequent annealing ...treatment, in which the Co-based metal organic framework (ZIF-67) act as the precursor of the metal oxide. The Co3O4/three-dimensional graphene networks/Ni foam (Co3O4/3DGN/NF) hybrid as the electrode for supercapacitor can deliver high specific capacitance (321 F g−1 at 1 A g−1) and excellent long-cycling stability (88% of the maximum capacitance after 2000 charge-discharge cycles). Furthermore, the Co3O4/3DGN/NF hybrid exhibits the maximum energy density of 7.5 W h kg−1 with the power density of 794 W kg−1 and remain 4.1 W h kg−1 with the power density of 15 kW kg−1 in the two-electrode system. The enhanced electrochemical properties can be attributed to the unique nanostructure of Co3O4 with admirable pseudocapacitance performance and the intimate integration of graphene with the Co3O4 and the Ni foam matrix, which not only enhances the electron conductivity for fast electron and ion transport but also provides high specific surface area and excellent structural stability.
Honeycomb-like porous Co3O4 derived from MOF grown on 3D graphene networks/nickel foam is applied as the binder-free electrode of supercapacitors with excellent electrochemical performances. Display omitted
•Honeycomb-like Co3O4/3DGN/NF hybrid was prepared by using the Co-based metal–organic frameworks as the precursor.•The as-fabricated hybrid was applied as a binder-free electrode for supercapacitors.•The electrode shows an excellent electrochemical performance.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
There is a lot of evidence that suggests that microRNAs (miRs) play an imperative role in the pathogenesis of polycystic ovary syndrome (PCOS). This study was designed to decipher the role of ...miR-125b in PCOS pathogenesis.
Expression analysis of miR-125b was determined by real-time quantitative polymerase chain reaction and the KGN ovarian granulosa cell viability was examined by CCK-8 assay. DAPI assay and flow cytometry were carried out for the detection of apoptosis and cell cycle distribution respectively. Protein levels were checked by immunoblotting.
The miR-125b transcript levels were considerably high in polycystic ovaries and ovarian granulosa KGN cells. The inhibition of miR-125b expression decreased the viability of the KGN cells by arresting the cells at the G2/M check point. Target Scan analysis revealed cyclin B1 as the target of miR-125b and suppression of miR-125b caused considerable up-regulation of cyclin B1 expression. Like miR-125b inhibition, cyclin B1 silencing also inhibited the KGN cell viability via G2/M arrest. Ectopic expression of miR-125b was unable to nullify the effects of cyclin-B silencing on KGN cell viability but the overexpression of cyclin B1 nullified the effects of the miR-125b suppression on KGN cell proliferation.
Since miR-125b controls the proliferation rate of granulosa cells in polycystic ovaries, it might be addressed as a potential therapeutic target for PCOS patients.
The traditional cumulant method (CM) for probabilistic optimal power flow (P-OPF) needs to perform linearization on the Karush–Kuhn–Tucker (KKT) first-order conditions, therefore requiring input ...variables (wind power or loads) varying within small ranges. To handle large fluctuations resulting from large-scale wind power and loads, a novel P-OPF method is proposed, where the correlations among input variables are also taken into account. Firstly, the inverse Nataf transformation and Cholesky decomposition are used to obtain samples of wind speeds and loads with a given correlation matrix. Then, the K-means algorithm is introduced to group the samples of wind power outputs and loads into a number of clusters, so that in each cluster samples of stochastic variables have small variances. In each cluster, the CM for P-OPF is conducted to obtain the cumulants of system variables. According to these cumulants, the moments of system variables corresponding to each cluster are computed. The moments of system variables for the total samples are obtained by combining the moments for all grouped clusters through the total probability formula. Then, the moments for the total samples are used to calculate the corresponding cumulants. Finally, Cornish–Fisher expansion is introduced to obtain the probability density functions (PDFs) of system variables. IEEE 9-bus and 118-bus test systems are modified to examine the proposed method. Study results show that the proposed method can produce more accurate results than traditional CM for P-OPF and is more efficient than Monte Carlo simulation (MCS).
Full text
Available for:
IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Quantum machine learning stands out as one of the most promising applications of quantum computing, widely believed to possess potential quantum advantages. In the era of noisy intermediate-scale ...quantum, the scale and quality of quantum computers are limited, and quantum algorithms based on fault-tolerant quantum computing paradigms cannot be experimentally verified in the short term. The variational quantum algorithm design paradigm can better adapt to the practical characteristics of noisy quantum hardware and is currently one of the most promising solutions. However, variational quantum algorithms, due to their highly entangled nature, encounter the phenomenon known as the “barren plateau” during the optimization and training processes, making effective optimization challenging. This paper addresses this challenging issue by researching a variational quantum neural network optimization method based on collective intelligence algorithms. The aim is to overcome optimization difficulties encountered by traditional methods such as gradient descent. We study two typical applications of using quantum neural networks: random 2D Hamiltonian ground state solving and quantum phase recognition. We find that the collective intelligence algorithm shows a better optimization compared to gradient descent. The solution accuracy of ground energy and phase classification is enhanced, and the optimization iterations are also reduced. We highlight that the collective intelligence algorithm has great potential in tackling the optimization of variational quantum algorithms.
The increasing penetration of wind power brings great uncertainties into power systems, which poses challenges to system planning and operation. This paper proposes a novel probabilistic load flow ...(PLF) method based on clustering technique to handle large fluctuations from large-scale wind power integration. The traditional cumulant method (CM) for PLF is based on the linearization of load flow equations around the operating point, therefore resulting in significant errors when input random variables have large fluctuations. In the proposed method, the samples of wind power and loads are first generated by the inverse Nataf transformation and then clustered using an improved
K
-means algorithm to obtain input variable samples with small variances in each cluster. With such pre-processing, the cumulant method can be applied within each cluster to calculate cumulants of output random variables with improved accuracy. The results obtained in each cluster are combined according to the law of total probability to calculate the final cumulants of output random variables for the whole samples. The proposed method is validated on modified IEEE 9-bus and 118-bus test systems with additional wind farms. Compared with the traditional CM, 2
m
+1 point estimate method (PEM), Monte Carlo simulation (MCS) and Latin hypercube sampling (LHS) based MCS, the proposed method can achieve a better performance with consideration of both computational efficiency and accuracy.
Modular multilevel converters (MMCs) are widely utilized in dc applications. With the development of MMCs, many applications require the MMCs to have additional functions and characteristics, such as ...dc fault clearing capability and low submodule capacitance. A unidirectional current H-bridge submodule (UCH-SM) has been proposed, which uses low submodule capacitance and possesses dc fault clearing capability. However, the reactive power capability is limited during low active power because of the inadequate dc bias in arm currents caused by the low dc current. Although retaining a rated dc current even at zero active power has been proposed, it results in increasing the power losses and large capacitance. This study proposes a new operating mode based on variable dc voltage and variable dc current (VVVCM) for point-to-point dc systems. The basic idea is that both the dc voltage and current vary on the basis of active power and a lower limit is set for the dc current to provide adequate dc bias in the arm currents during reactive power exchange. Analysis shows that the UCH-MMC in VVVCM has an enlarged P-Q capability range and still retains low capacitor usage. Simulation results verify the effectiveness of the proposed mode.
Epithelial ovarian carcinoma (EOC) is one of the most common gynecologic malignancies with a high mortality rate. Serum biomarkers and imaging approaches are insufficient in identifying EOC patients ...at an early stage. This study is to set up a combination of proteins from serum small extracellular vesicles (sEVs) for the diagnosis of early-stage EOC and to determine its performance. A biomarker for early-stage ovarian cancer (BESOC) cohort was used as a Chinese multi-center population-based biomarker study and registered as a Chinese Clinical Trial ChiCTR2000040136. The sEV protein levels of CA125, HE4, and C5a were measured in 299 subjects. Logistic regression was exploited to calculate the odds ratio and to create the sEV protein model for the predicted probability and subsequently receiver-operating characteristic (ROC) analysis. The combined sEV marker panel of CA125, HE4, and C5a as a sEV model obtained an area under curve (AUC) of 0.912, which was greater than the serum model (0.809), by ROC analysis to identify EOC patients from the whole cohort. With the cutoff of 0.370, the sensitivity and specificity of the sEV model were 0.80 and 0.89, which were much better performance than the serum markers (sensitivity: 0.55~0.66; specificity: 0.59~0.68) and the risk of ovarian malignancy algorithm (ROMA) index approved by the U.S. Food and Drug Administration (sensitivity: 0.65; specificity: 0.61), to identify EOC patients from patients with benign ovarian diseases or other controls. The sEV levels of CA125 significantly differed among early-stage and late-stage EOC (
p
< 0.001). Moreover, the AUC of ROC to identify early-stage EOC patients was 0.888. Further investigation revealed that the sEV levels of these 3 proteins significantly decreased after cytoreductive surgery (CA125,
p
= 0.008; HE4,
p
= 0.025; C5a,
p
= 0.044). In summary, our study showed that CA125, HE4, and C5a levels in serum sEVs can identify EOC patients at the early stage, elucidating the possibility of using a sEV model for the diagnosis of early-stage EOC.
Zn-ion hybrid supercapacitors (ZHSs) are an advanced energy storage system with high energy/power density. However, the development of cathodes with high-performance is still a challenge. Herein, N, ...O co-doped hierarchical porous carbon (HPC) integrated with carbon cloth (CC) was fabricated as a promising cathode for aqueous ZHSs, which delivered a high specific capacity of 138.5 mA h g
−1
with excellent rate performance ( 75 mA h g
−1
at 20 A g
−1
) and superb cycling stability without decay after 10 000 cycles. As a result, an exceptionally high energy density of 110 W h kg
−1
and attractive power density of 20 kW kg
−1
can be obtained. More importantly, the dual cation (H
+
and Zn
2+
) chemical absorption process for additional capacity is firstly proposed and verified by
ex situ
experiments, while the precipitation/dissolution process of zinc hydroxide sulphate hydrate is explained. Furthermore, a quasi-solid-state HPC/CC-based ZHS device based on gel electrolyte also showed promising potential for practical applications. This work provides a new pathway to develop carbon-based cathode materials for sustainable ZHSs.
A novel carbon cathode was fabricated for high-performance Zn-ion supercapacitors with enhanced pseudocapacitance.
PDF
