Collider bias correction for multiple covariates in GWAS using robust multivariable Mendelian randomization.

Genome-wide association studies (GWAS) have identified many genetic loci associated with complex traits and diseases in the past 20 years. Multiple heritable covariates may be added into GWAS regression models to estimate direct effects of genetic variants on a focal trait, or to improve the power by accounting for environmental effects and other sources of trait variations. When one or more covariates are causally affected by both genetic variants and hidden confounders, adjusting for them in GWAS will produce biased estimation of SNP effects, known as collider bias. Several approaches have been developed to correct collider bias through estimating the bias by Mendelian randomization (MR). However, these methods work for only one covariate, some of which utilize MR methods with relatively strong assumptions, both of which may not hold in practice. In this paper, we extend the bias-correction approaches in two aspects: first we derive an analytical expression for the collider bias in the presence of multiple covariates, then we propose estimating the bias using a robust multivariable MR (MVMR) method based on constrained maximum likelihood (called MVMR-cML), allowing the presence of invalid instrumental variables (IVs) and correlated pleiotropy. We also established the estimation consistency and asymptotic normality of the new bias-corrected estimator. We conducted simulations to show that all methods mitigated collider bias under various scenarios. In real data analyses, we applied the methods to two GWAS examples, the first a GWAS of waist-hip ratio with adjustment for only one covariate, body-mass index (BMI), and the second a GWAS of BMI adjusting metabolomic principle components as multiple covariates, illustrating the effectiveness of bias correction.

Recent progress in critical electrode and electrolyte materials for flexible zinc-ion batteries.

With the increasing popularity of flexible and wearable electronic devices, the demand for power supplies that can be easily bent or worn is also rapidly growing. However, traditional lithium ion batteries are difficult to adapt to complex wearable devices because of their unsatisfactory flexibility and thickness as well as safety issues. Zinc-ion batteries have several advantages, including low redox potential, high theoretical capacity, high safety, and abundant reserves. These features make flexible zinc-ion batteries (FZIBs) an ideal wearable energy storage device candidate. The electrochemical performance and mechanical deformability of FZIBs were pivotally determined based on the properties of their electrode and electrolyte. Herein, we summarize some recent advances from 2015 to 2023 in the design and preparation of various electrode and electrolyte materials for FZIBs with controllable morphology and structure, excellent mechanical property, and enhanced electrochemical performance. Moreover, efforts to explore the potential practical applications of FZIBs have also been considered. Finally, we present and discuss current challenges and opportunities for the development of high-performance FZIBs.

Surface Modification Driven Initial Coulombic Efficiency and Rate Performance Enhancement of Li1.2 Mn0.54 Ni0.13 Co0.13 O2 Cathode.

Due to its high energy density and low cost, Li-rich Mn-based layered oxides are considered potential cathode materials for next generation Li-ion batteries. However, they still suffer from the serious obstacle of low initial Coulombic efficiency, which is detrimental to their practical application. Here, an efficient surface modification method via NH4 H2 PO4 assisted pyrolysis is performed to improve the Coulombic efficiency of Li1.2 Mn0.54 Ni0.13 Co0.13 O2 , where appropriate oxygen vacancies, Li3 PO4 and spinel phase are synchronously generated in the surface layer of LMR microspheres. Under the synergistic effect of the oxygen vacancies and spinel phase, the unavoidable oxygen release in the cycling process was effectively suppressed. Moreover, the induced Li3 PO4 nanolayer could boost the lithium-ion diffusion and mitigate the dissolution of transition metal ions, especially manganese ions, in the material. The optimally modified sample yielded an impressive initial Coulombic efficiency and outstanding rate performance.

1,25(OH)2 D3 inhibits Lewis lung cancer cell migration via NHE1-sensitive metabolic reprograming.

High prevalence and metastasis rates are characteristics of lung cancer. Glycolysis provides energy for the development and metastasis of cancer cells. The 1,25-dihydroxy vitamin D3 (1,25(OH)2 D3 ) has been linked to reducing cancer risk and regulates various physiological functions. We hypothesized that 1,25(OH)2 D3 could be associated with the expression and activity of Na+ /H+ exchanger isoform 1 (NHE1) of Lewis lung cancer cells, thus regulating glycolysis as well as migration by actin reorganization. Followed by online public data analysis, Vitamin D3 receptor, the receptor of 1,25(OH)2 D3 has been proved to be abundant in lung cancers. We demonstrated that 1,25(OH)2 D3 treatment suppressed transcript levels, protein levels, and activity of NHE1 in LLC cells. Furthermore, 1,25(OH)2 D3 treatment resets the metabolic balance between glycolysis and OXPHOS, mainly including reducing glycolytic enzymes expression and lactate production. In vivo experiments showed the inhibition effects on tumor growth as well. Therefore, we concluded that 1,25(OH)2 D3 could amend the NHE1 function, which leads to metabolic reprogramming and cytoskeleton reconstruction, finally inhibits the cell migration.

Two Birds with One Stone: V4 C3 MXene Synergistically Promoted VS2 Cathode and Zinc Anode for High-Performance Aqueous Zinc-Ion Batteries.

Aqueous zinc-ion batteries (AZIBs) are considered to be a rising star in the large-scale energy storage area because of their low cost and environmental friendliness properties. However, the limited electrochemical performance of the cathode and severe zinc dendrite of the anode severely hinder the practical application of AZIBs. Herein, a novel 3D interconnected VS2 ⊥V4 C3 Tx heterostructure material is prepared via one-step solvothermal method. Morphological and structural characterizations show that VS2 nanosheets are uniformly and dispersedly distributed on the surface of the V4 C3 MXene substrate, which can effectively suppress volume change of the VS2 . Owing to the open heterostructure along with the high conductivity of V4 C3 MXene, the VS2 ⊥V4 C3 Tx cathode shows a high specific capacity of 273.9 mAh g-1 at 1 A g-1 and an excellent rate capability of 143.2 mAh g-1 at 20 A g-1 . The V4 C3 MXene can also effectively suppress zinc dendrite growth when used as protective layer for the Zn anode, making the V4 C3 Tx @Zn symmetric cell with a stable voltage profile for ≈1700 h. Benefitting from the synergistic modification effect of V4 C3 MXene on both the cathode and anode, the VS2 ⊥V4 C3 Tx ||V4 C3 Tx @Zn battery exhibits a long cycling lifespan of 5000 cycles with a capacity of 157.1 mAh g-1 at 5A g-1 .

Nonparametric prediction distribution from resolution-wise regression with heterogeneous data.

Modeling and inference for heterogeneous data have gained great interest recently due to rapid developments in personalized marketing. Most existing regression approaches are based on the conditional mean and may require additional cluster information to accommodate data heterogeneity. In this paper, we propose a novel nonparametric resolution-wise regression procedure to provide an estimated distribution of the response instead of one single value. We achieve this by decomposing the information of the response and the predictors into resolutions and patterns respectively based on marginal binary expansions. The relationships between resolutions and patterns are modeled by penalized logistic regressions. Combining the resolution-wise prediction, we deliver a histogram of the conditional response to approximate the distribution. Moreover, we show a sure independence screening property and the consistency of the proposed method for growing dimensions. Simulations and a real estate valuation dataset further illustrate the effectiveness of the proposed method.

Identification of IRF1 as a Novel Pyroptosis-Related Prognostic Biomarker of Atopic Dermatitis.

Purpose: The aim of this study was to characterize key biomarkers associated with pyroptosis in atopic dermatitis (AD). Materials and methods: To identify the differentially expressed pyroptosis-related genes (DEPRGs), the gene expression profiles GSE16161 and GSE32924 from the Gene Expression Omnibus (GEO) database were utilized. Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were conducted to determine the potential biological functions and involved pathways. Furthermore, protein-protein interaction network analyses were performed to identify hub genes. The types and proportions of infiltrating immune cells were detected by immune filtration analysis using CIBERSORT. A 12-axis competing endogenous RNA (ceRNA) network was constructed utilizing the miRNet database. Immunohistochemistry (IHC) further validated the differential expression of a key gene IRF1 in the skin tissues collected from AD patients. The collection of skin tissue from human subjects in this study were reviewed and approved by the IRB of Yueyang Integrated Chinese and Western Medicine Hospital (KYSKSB2020-125). Results: The study identified a total of 76 DEPRGs, which were enriched in genes associated with the inflammatory response and immune regulation. There was a higher percentage of activated dendritic cells and a lower percentage of resting mast cells in AD samples. PVT1 expression was associated with upregulation of hub genes including CXCL8, IRF1, MKI67, and TP53 in the ceRNA network and was correlated with activated dendritic cells in AD. As a transcription factor, IRF1 could regulate the production of downstream inflammatory factors. The IHC study revealed that IRF1 was overexpressed in the skin tissues of AD patients, which were consistent with the results of the bioinformatic study. Conclusions: IRF1 and its related genes were identified as key pyroptosis-related biomarkers in AD, which is a crucial pathway in the pathogenesis of AD.

Formaldehyde promotes tumor-associated macrophage polarizations and functions through induction of HIF-1α-mediated glycolysis.

Formaldehyde (FA) exposure has been positively correlated with many diseases including various types of cancers. However, the mechanisms of FA-related carcinogenesis are still unclear. Tumor-associated macrophages (TAMs) are the most abundant immune cells in tumor microenvironment, which is a heterogeneous population consist of both pro-inflammatory (M1) and immunosuppressive (M2) cells. TAMs are deeply involved in tumor development and progression. Our previous studies demonstrated that FA enhanced M1 polarization of macrophages through induction of HIF-1α-mediated glycolysis. To examine if TAM polarizations are also potentiated by FA, BALB/c nude mice were inoculated with A549 cells to develop subcutaneous tumors and exposed to 2.0 mg/m3 FA for 14 days. Significant increases of both M1 and M2 polarizations of TAMs were observed in tumor tissues of FA-exposed mice. After confirmation of the potentiation effects in RAW264.7 and THP-1-derived in vitro TAM models, FA at 25 and 50 µM was found to enhance TAM immunosuppressive functions and glycolytic metabolism. In addition, FA-induced glycolysis in TAMs was reversed by a specific HIF-1α inhibitor PX-478 at 5 µM, and suppression of glycolytic metabolism with a glucose analog 2-DG at 1 mM also alleviated FA-potentiated TAM functions, which indicated that FA induced TAM polarizations through the upregulation of HIF-1α-mediated glycolysis. These results illustrated a potential carcinogenic mechanism of FA through metabolic disturbance of tumor immunity, which could be utilized to develop preventative or therapeutic agents for FA-induced carcinogenesis and immune disorders.

Cannabis smoke suppresses antiviral immune responses to influenza A in mice.

Rationale: Despite its increasingly widespread use, little is known about the impact of cannabis smoking on the response to viral infections like influenza A virus (IAV). Many assume that cannabis smoking will disrupt antiviral responses in a manner similar to cigarette smoking; however, since cannabinoids exhibit anti-inflammatory effects, cannabis smoke exposure may impact viral infection in distinct ways. Methods: Male and female BALB/c mice were exposed daily to cannabis smoke and concurrently intranasally instilled with IAV. Viral burden, inflammatory mediator levels (multiplex ELISA), lung immune cells populations (flow cytometry) and gene expression patterns (RNA sequencing) were assessed in the lungs. Plasma IAV-specific antibodies were measured via ELISA. Results: We found that cannabis smoke exposure increased pulmonary viral burden while decreasing total leukocytes, including macrophages, monocytes and dendritic cell populations in the lungs. Furthermore, infection-induced upregulation of certain inflammatory mediators (interferon-γ and C-C motif chemokine ligand 5) was blunted by cannabis smoke exposure, which in females was linked to the transcriptional downregulation of pathways involved in innate and adaptive immune responses. Finally, plasma levels of IAV-specific IgM and IgG1 were significantly decreased in cannabis smoke-exposed, infected mice compared to infected controls, only in female mice. Conclusions: Overall, cannabis smoke exposure disrupted host-defence processes, leading to increased viral burden and dampened inflammatory signalling. These results suggest that cannabis smoking is detrimental to the maintenance of pulmonary homeostasis during viral infection and highlight the need for data regarding the impact on immune competency in humans.

HIGH-DIMENSIONAL FACTOR REGRESSION FOR HETEROGENEOUS SUBPOPULATIONS.

In modern scientific research, data heterogeneity is commonly observed owing to the abundance of complex data. We propose a factor regression model for data with heterogeneous subpopulations. The proposed model can be represented as a decomposition of heterogeneous and homogeneous terms. The heterogeneous term is driven by latent factors in different subpopulations. The homogeneous term captures common variation in the covariates and shares common regression coefficients across subpopulations. Our proposed model attains a good balance between a global model and a group-specific model. The global model ignores the data heterogeneity, while the group-specific model fits each subgroup separately. We prove the estimation and prediction consistency for our proposed estimators, and show that it has better convergence rates than those of the group-specific and global models. We show that the extra cost of estimating latent factors is asymptotically negligible and the minimax rate is still attainable. We further demonstrate the robustness of our proposed method by studying its prediction error under a mis-specified group-specific model. Finally, we conduct simulation studies and analyze a data set from the Alzheimer's Disease Neuroimaging Initiative and an aggregated microarray data set to further demonstrate the competitiveness and interpretability of our proposed factor regression model.

A new ratiometric fluorescence nanosensor based on NaYF4:3%Er@NaYF4 upconversion nanoparticles for sensitive determination of Rose Bengal in water.

Rose Bengal (RB) is used as a sensitizer in ambient water due to its property of catalyzing the production of singlet oxygen (1O2). However, this property also brings phototoxicity and carcinogenicity. The NaYF4:3%Er@NaYF4 core-shell upconversion nanoparticles (UCNPs) with higher upconversion efficiency was synthesized to detect RB in ambient water. Due to fluorescence resonance energy transfer (FRET) between RB and UCNPs, the upconversion fluorescence at 538 nm emitted by UCNPs was quenched by the RB, while the emission at 566 nm of RB raised. In the best conditions, the ratiometric emission intensity F566/F538 was positively proportional to RB concentration and the linear range was 0.04-15.0 µg·mL-1 (R2 = 0.996). The detection limit (S/N = 3) of RB was 2.46 ng·mL-1. The recoveries ranged from 99.0% to 105.6% (relative standard deviation 0.97-3.24%, n = 3) in tap water and 100.3%-104.9% (relative standard deviation 0.66-1.94%, n = 3) in lake water. This proposed method exhibits lower detection limit and larger linear, which possesses practical application value to the detection of RB in water.

New insights into the biology and development of lung cancer in never smokers-implications for early detection and treatment.

Lung cancer is the leading cause of cancer deaths worldwide. Despite never smokers comprising between 10 and 25% of all cases, lung cancer in never smokers (LCNS) is relatively under characterized from an etiological and biological perspective. The application of multi-omics techniques on large patient cohorts has significantly advanced the current understanding of LCNS tumor biology. By synthesizing the findings of multi-omics studies on LCNS from a clinical perspective, we can directly translate knowledge regarding tumor biology into implications for patient care. Primarily focused on never smokers with lung adenocarcinoma, this review details the predominance of driver mutations, particularly in East Asian patients, as well as the frequency and importance of germline variants in LCNS. The mutational patterns present in LCNS tumors are thoroughly explored, highlighting the high abundance of the APOBEC signature. Moreover, this review recognizes the spectrum of immune profiles present in LCNS tumors and posits how it can be translated to treatment selection. The recurring and novel insights from multi-omics studies on LCNS tumor biology have a wide range of clinical implications. Risk factors such as exposure to outdoor air pollution, second hand smoke, and potentially diet have a genomic imprint in LCNS at varying degrees, and although they do not encompass all LCNS cases, they can be leveraged to stratify risk. Germline variants similarly contribute to a notable proportion of LCNS, which warrants detailed documentation of family history of lung cancer among never smokers and demonstrates value in developing testing for pathogenic variants in never smokers for early detection in the future. Molecular driver subtypes and specific co-mutations and mutational signatures have prognostic value in LCNS and can guide treatment selection. LCNS tumors with no known driver alterations tend to be stem-like and genes contributing to this state may serve as potential therapeutic targets. Overall, the comprehensive findings of multi-omics studies exert a wide influence on clinical management and future research directions in the realm of LCNS.

Dehydration-enhanced ion-pore interactions dominate anion transport and selectivity in nanochannels.

State-of-the-art ion-selective membranes with ultrahigh precision are of significance for water desalination and energy conservation, but their development is limited by the lack of understanding of the mechanisms of ion transport at the subnanometer scale. Herein, we investigate transport of three typical anions (F-, Cl-, and Br-) under confinement using in situ liquid time-of-flight secondary ion mass spectrometry in combination with transition-state theory. The operando analysis reveals that dehydration and related ion-pore interactions govern anion-selective transport. For strongly hydrated ions [(H2O)nF- and (H2O)nCl-], dehydration enhances ion effective charge and thus the electrostatic interactions with membrane, observed as an increase in decomposed energy from electrostatics, leading to more hindered transport. Contrarily, weakly hydrated ions [(H2O)nBr-] have greater permeability as they allow an intact hydration structure during transport due to their smaller size and the most right-skewed hydration distribution. Our work demonstrates that precisely regulating ion dehydration to maximize the difference in ion-pore interactions could enable the development of ideal ion-selective membranes.

Ion-Specific Nanoconfinement Effect in Multilayered Graphene Membranes: A Combined Nuclear Magnetic Resonance and Computational Study.

Ion adsorption within nanopores is involved in numerous applications. However, a comprehensive understanding of the fundamental relationship between in-pore ion concentration and pore size, particularly in the sub-2 nm range, is scarce. This study investigates the ion-species-dependent concentration in multilayered graphene membranes (MGMs) with tunable nanoslit sizes (0.5-1.6 nm) using nuclear magnetic resonance and computational simulations. For Na+-based electrolytes in MGMs, the concentration of anions in graphene nanoslits increases in correlation with their chaotropic properties. As the nanoslit size decreases, the concentration of chaotropic ion (BF4-) increases, whereas the concentration of kosmotropic ions (Cit3-, PO43-) and other ions (Ac-, F-) decreases or changes slightly. Notably, anions remain more concentrated than counter Na+ ions, leading to electroneutrality breakdown and unipolar anion packing in MGMs. A continuum modeling approach, integrating molecular dynamic simulation with the Poisson-Boltzmann model, elucidates these observations by considering water-mediated ion-graphene non-electrostatic interactions and charge screening from graphene walls.

"Blue-free" orange ZnO-related light-emitting diode based on a natural interface layer of Ga2O3 and ZnGa2O4.

To fabricate a ZnO-related light-emitting diode (LED) with zero emission at blue wavelengths ("blue-free"), an ingenious strategy is employed. Specifically, for the first time to the best of our knowledge, a natural oxide interface layer, possessing remarkable visible emission potential, is introduced into the Au/i-ZnO/n-GaN metal-insulator-semiconductor (MIS) structure. The unique Au/i-ZnO/interface layer/n-GaN structure successfully eliminated the harmful blue emissions (400-500 nm) from the ZnO film, and the remarkable orange electroluminescence is mainly attributed to the impact ionization process of the natural interface layer at high electric field. It is worth mentioning that the device achieved ultra-low color temperature (2101 K) and excellent color rendering index (92.8) under electrical injection, indicating that the device could fulfill the requirements of electronic display systems and general illumination, and might even play unexpected roles in special lighting domains. The results obtained provide a novel and effective strategy for the design and preparation of ZnO-related LEDs.

Magneto-electrochemistry driven ultralong-life Zn-VS2 aqueous zinc-ion batteries.

The development of high energy density and long cycle lifespan aqueous zinc ion batteries is hindered by the limited cathode materials and serious zinc dendrite growth. In this work, a defect-rich VS2 cathode material is manufactured by in situ electrochemical defect engineering under high charge cut-off voltage. Owing to the rich abundant vacancies and lattice distortion in the ab plane, the tailored VS2 can unlock the transport path of Zn2+ along the c-axis, enabling 3D Zn2+ transport along both the ab plane and c-axis, and reduce the electrostatic interaction between VS2 and zinc ions, thus achieving excellent rate capability (332 mA h g-1 and 227.8 mA h g-1 at 1 A g-1 and 20 A g-1, respectively). The thermally favorable intercalation and 3D rapid transport of Zn2+ in the defect-rich VS2 are verified by multiple ex situ characterizations and density functional theory (DFT) calculations. However, the long cycling stability of the Zn-VS2 battery is still unsatisfactory due to the Zn dendrite issue. It can be found that the introduction of an external magnetic field enables changing the movement of Zn2+, suppressing the growth of zinc dendrites, and resulting in enhanced cycling stability from about 90 to 600 h in the Zn||Zn symmetric cell. As a result, a high-performance Zn-VS2 full cell is realized by operating under a weak magnetic field, which shows an ultralong cycle lifespan with a capacity of 126 mA h g-1 after 7400 cycles at 5 A g-1, and delivers the highest energy density of 304.7 W h kg-1 and maximum power density of 17.8 kW kg-1.

Formaldehyde exacerbates asthma in mice through the potentiation of HIF-1α-mediated pro-inflammatory responses in pulmonary macrophages.

Exposure to formaldehyde (FA) has been indicated to be positively correlated with increased incidence of allergic asthma in many epidemiological and experimental studies. However, few studies have ever addressed the molecular basis of the correlation. In the present study, it was found that inhaling 2.0 mg/m3 FA for 2 weeks could exacerbate the pulmonary inflammation and mucus over-accumulation in OVA-induced murine asthmatic model. The pro-inflammatory cytokines, such as IL-1ß, TNF-α, IL-6 and IL-8, were increased in lung and serum of FA-exposed asthmatic mice. The contribution of HIF-1α signaling in FA-exacerbated allergic asthma was confirmed by bioinformatic analysis. HIF-1α and its downstream proteins, which are known as mediators of glycolysis, were found to be upregulated by 50 µM FA, and the FA-enhanced of glycolysis was reversed by inhibition of HIF-1α with PX-478 in vitro and YC-1 in vivo. Furthermore, it was confirmed that inhibition of HIF-1α signaling could restrain the macrophagic inflammatory responses and asthma exacerbation induced by FA. Collectively, these results revealed that FA could exacerbate asthma through the potentiation of HIF-1α-mediated inflammatory responses in macrophages, which also indicated the universal roles of FA-triggered macrophage metabolic and functional alterations in inflammatory or allergic diseases.

Carbon Foam-Supported VS2 Cathode for High-Performance Flexible Self-Healing Quasi-Solid-State Zinc-Ion Batteries.

As the new generation of energy storage systems, the flexible battery can effectively broaden the application area and scope of energy storage devices. Flexibility and energy density are the two core evaluation parameters for the flexible battery. In this work, a flexible VS2 material (VS2 @CF) is fabricated by growing the VS2 nanosheet arrays on carbon foam (CF) using a simple hydrothermal method. Benefiting from the high electric conductivity and 3D foam structure, VS2 @CF shows an excellent rate capability (172.8 mAh g-1 at 5 A g-1 ) and cycling performance (130.2 mAh g-1 at 1 A g-1 after 1000 cycles) when it served as cathode material for aqueous zinc-ion batteries. More importantly, the quasi-solid-state battery VS2 @CF//Zn@CF assembled by the VS2 @CF cathode, CF-supported Zn anode, and a self-healing gel electrolyte also exhibits excellent rate capability (261.5 and 149.8 mAh g-1 at 0.2 and 5 A g-1 , respectively) and cycle performance with a capacity of 126.6 mAh g-1 after 100 cycles at 1 A g-1 . Moreover, the VS2 @CF//Zn@CF full cell also shows good flexible and self-healing properties, which can be charged and discharged normally under different bending angles and after being destroyed and then self-healing.

Molecular-level uniform graphene/polyaniline composite film for flexible supercapacitors with high-areal capacitance.

To increase the specific capacitance of supercapacitors, polyaniline (PANI) has been chosen as additive electrode material for the pseudocapacitive performance. Here, we synthesize a molecular-level uniform reduced graphene oxide/PANI (rGO/PANI) composite film with high flexibility and conductivity via self-assembly and specific thermal reduction, which performs great potential in flexible supercapacitors with high areal capacitance. Particularly, the electrode of rGO/PANI-42.9% exhibits a high specific areal capacitance (1826 mF cm-2at 0.2 mA cm-2), and it also presents a good cycling stability (it remains 76% of its initial capacitance after 10 500 cycles). Moreover, the specific gravimetric capacitance of rGO/PANI-33.3% reaches up to 256.4 F g-1at 0.2 A g-1, showing greatly enhanced performance compared with the pure rGO electrode (183 F g-1). The results of various characteristic analysis demonstrate that electrochemical performance of the as-prepared rGO/PANI film is closely associated with the uniform distribution of PANI in rGO/PANI composite. Overall, our reported method is convenient and environmental-friendly, and could be beneficial for the development of high-performance capacitive energy storage materials.

Crystallinity Tuning of Na3 V2 (PO4 )3 : Unlocking Sodium Storage Capacity and Inducing Pseudocapacitance Behavior.

As a promising cathode material of sodium-ion batteries, Na3 V2 (PO4 )3 (NVP) has attracted extensive attention in recent years due to its high stability and fast Na+ ion diffusion. However, the reversible capacity based on the two-electron reaction mechanism is not satisfactory limited by the inactive M1 lattice sites during the insertion/extraction process. Herein, self-supporting 3D porous NVP materials with different crystallinity are fabricated on carbon foam substrates by a facile electrostatic spray deposition method. The V5+ /V4+ redox couple is effectively activated and the three-electron reactions are realized in NVP for sodium storage by a proper crystallinity tuning. In a disordered NVP sample, an ultra-high specific capacity of 179.6 mAh g-1 at 0.2 C is achieved due to the coexistence of redox reactions of the V4+ /V3+ and V5+ /V4+ couples. Moreover, a pseudocapacitive charge storage mechanism induced by the disordered structure is first observed in the NVP electrode. An innovative model is given to understand the disorder-induced-pseudocapacitance phenomenon in this polyanion cathode material.