One-step hydrothermal synthesis of vanadium dioxide/carbon core-shell composite with improved ammonium ion storage for aqueous ammonium-ion battery.

Aqueous nonmetallic ion batteries have garnered significant interest due to their cost-effectiveness, environmental sustainability, and inherent safety features. Specifically, ammonium ion (NH4+) as a charge carrier has garnered more and more attention recently. However, one of the persistent challenges is enhancing the electrochemical properties of vanadium dioxide (VO2) with a tunnel structure, which serves as a highly efficient NH4+ (de)intercalation host material. Herein, a novel architecture, wherein carbon-coated VO2 nanobelts (VO2@C) with a core-shell structure are engineered to augment NH4+ storage capabilities of VO2. In detail, VO2@C is synthesized via the glucose reduction of vanadium pentoxide under hydrothermal conditions. Experimental results manifest that the introduction of the carbon layer on VO2 nanobelts can enhance mass transfer, ion transport and electrochemical kinetics, thereby culminating in the improved NH4+ storage efficiency. VO2@C core-shell composite exhibits a remarkable specific capacity of ∼300 mAh/g at 0.1 A/g, which is superior to that of VO2 (∼238 mAh/g) and various other electrode materials used for NH4+ storage. The NH4+ storage mechanism can be elucidated by the reversible NH4+ (de)intercalation within the tunnel of VO2, facilitated by the dynamic formation and dissociation of hydrogen bonds. Furthermore, when integrated into a full battery with polyaniline (PANI) cathode, the VO2@C//PANI full battery demonstrates robust electrochemical performances, including a specific capacity of ∼185 mAh·g-1 at 0.2 A·g-1, remarkable durability of 93 % retention after 1500 cycles, as well as high energy density of 58 Wh·kg-1 at 5354 W·kg-1. This work provides a pioneering approach to design and explore composite materials for efficient NH4+ storage, offering significant implications for future battery technology enhancements.

Lightweight, Strong, and Transparent Wood Films Produced by Capillary Driven Self-Densification.

Wood delignification and densification enable the production of high strength and/or transparent wood materials with exceptional properties. However, processing needs to be more sustainable and besides the chemical delignification treatments, energy intense hot-pressing calls for alternative approaches. Here, this study shows that additional softening of delignified wood via a mild swelling process using an ionic liquid-water mixture enables the densification of tube-line wood cells into layer-by-layer sheet structures without hot-pressing. The natural capillary force induces self-densification in a simple drying process resulting in a transparent wood film. The as-prepared films with ≈150 µm thickness possess an optical transmittance ≈70%, while maintaining optical haze >95%. Due to the densely packed sheet structure with a large interfacial area, the reassembled wood film is fivefold stronger and stiffer than the delignified wood in fiber direction. Owing to a low density, the specific tensile strength and elastic modulus are as high as 282 MPa cm3 g-1 and 31 GPa cm3 g-1. A facile and highly energy efficient wood nanotechnology approach are demonstrated toward more sustainable materials and processes by directly converting delignified wood into transparent wood omitting polymeric matrix infiltration or mechanical pressing.

One-pot assay using a target-driven split aptamer recognition and assembly strategy for convenient and rapid detection of gliotoxin.

An aptamer targeting gliotoxin (GTX) was optimized to increase the binding affinity by approximately 20 times and achieve higher structural stability and targeting specificity. Molecular dynamics simulations were used to explore the molecular mechanism and key action sites underlying the recognition of GTX by the optimized aptamer. Subsequently, the optimized aptamer was split into two fragments and a convenient and rapid one-pot assay for GTX detection was successfully established using a target-driven split aptamer recognition and assembly strategy. The method exhibited a good linear range of 0.128 nM to 2 µM, a low detection limit of 0.07 nM, and excellent selectivity for GTX. Furthermore, the method had good accuracy and stability in real sample analysis. Therefore, the developed one-pot method provides a reliable, convenient, and cost-effective approach for the widespread application of GTX detection.

Characterization of zinc finger protein 536, a neuroendocrine regulator, using pan-cancer analysis.

BACKGROUND: Previous studies suggested that zinc finger protein 536 (ZNF536) was abundant in the central brain and regulated neuronal differentiation. However, the role of ZNF536 in cancer has remained unclear. METHODS: ZNF536 mutation, copy number alteration, DNA methylation, and RNA expression were explored using public portals. Data from The Cancer Genome Atlas (TCGA) were utilized to analyze pathways and tumor microenvironment (TME), with a focus on prognosis in both TCGA and immunotherapy pan-cancer cohorts. Methylated ZNF536 from small cell lung cancer (SCLC) cell lines were utilized to train with probes for conducting enrichment analysis. Single-cell RNA profile demonstrated the sublocalization and co-expression of ZNF536, and validated its targets by qPCR. RESULTS: Genetic alterations in ZNF536 were found to be high-frequency and a single sample could harbor different variations. ZNF536 at chromosome 19q12 exerted a bypass effect on CCNE1, supported by CRISPR data. For lung cancer, ZNF536 mutation was associated with longer survival in primary lung adenocarcinoma (LUAD), but its prognosis was poor in metastatic LUAD and SCLC. Importantly, ZNF536 mutation and amplification had opposite prognoses in Stand Up To Cancer-Mark Foundation (SU2C-MARK) LUAD cohort. ZNF536 mutation altered the patterns of genomic alterations in tumors, and had distinct impacts on the signaling pathways and TME compared to ZNF536 amplification. Additionally, ZNF536 expression was predominantly in endocrine tumors and brain tissues. High-dimensional analysis supported this finding and further revealed regulators of ZNF536. Considering that the methylation of ZNF536 was involved in the synaptic pathway associated with neuroendocrine neoplasms, demonstrating both diagnostic and prognostic value. Moreover, we experimentally verified ZNF536 upregulated neuroendocrine markers. CONCLUSIONS: Our results showed that ZNF536 alterations in cancer, including variations in copy number, mutation, and methylation. We proved the involvement of ZNF536 in neuroendocrine regulation, and identified highly altered ZNF536 as a potential biomarker for immunotherapy.

A flexible time-varying coefficient rate model for panel count data.

Panel count regression is often required in recurrent event studies, where the interest is to model the event rate. Existing rate models are unable to handle time-varying covariate effects due to theoretical and computational difficulties. Mean models provide a viable alternative but are subject to the constraints of the monotonicity assumption, which tends to be violated when covariates fluctuate over time. In this paper, we present a new semiparametric rate model for panel count data along with related theoretical results. For model fitting, we present an efficient EM algorithm with three different methods for variance estimation. The algorithm allows us to sidestep the challenges of numerical integration and difficulties with the iterative convex minorant algorithm. We showed that the estimators are consistent and asymptotically normally distributed. Simulation studies confirmed an excellent finite sample performance. To illustrate, we analyzed data from a real clinical study of behavioral risk factors for sexually transmitted infections.

Electrochemical Knocking-Down of Zn Metal Clusters into Single Atoms.

Single Atoms Catalysts (SACs) have emerged as a class of highly promising heterogeneous catalysts, where the traditional bottom-up synthesis approaches often encounter considerable challenges in relation to aggregation issues and poor stability. Consequently, achieving densely dispersed atomic species in a reliable and efficient manner remains a key focus in the field. Herein, we report a new facile electrochemical knock-down strategy for the formation of SACs, whereby the metal Zn clusters are transformed into single atoms. While a defect-rich substrate plays a pivotal role in capturing and stabilizing isolated Zn atoms, the feasibility of this novel strategy is demonstrated through a comprehensive investigation, combining experimental and theoretical studies. Furthermore, when studied in exploring for potential applications, the material prepared shows a remarkable improvement of 58.21% for the Li+ storage and delivers a capacity over 300 Wh kg-1 after 500 cycles upon the transformation of Zn clusters into single atoms.

Diagnostic performance of contrast-enhanced mammography for suspicious findings in dense breasts: A systematic review and meta-analysis.

PURPOSE: Contrast-enhanced spectral imaging (CEM) is a new mammography technique, but its diagnostic value in dense breasts is still inconclusive. We did a systematic review and meta-analysis of studies evaluating the diagnostic performance of CEM for suspicious findings in dense breasts. MATERIALS AND METHODS: The PubMed, Embase, and Cochrane Library databases were searched systematically until August 6, 2023. Prospective and retrospective studies were included to evaluate the diagnostic performance of CEM for suspicious findings in dense breasts. The QUADAS-2 tool was used to evaluate the quality and risk of bias of the included studies. STATA V.16.0 and Review Manager V.5.3 were used to meta-analyze the included studies. RESULTS: A total of 10 studies (827 patients, 958 lesions) were included. These 10 studies reported the diagnostic performance of CEM for the workup of suspicious lesions in patients with dense breasts. The summary sensitivity and summary specificity were 0.95 (95% CI, 0.92-0.97) and 0.81 (95% CI, 0.70-0.89), respectively. Enhanced lesions, circumscribed margins, and malignancy were statistically correlated. The relative malignancy OR value of the enhanced lesions was 28.11 (95% CI, 6.84-115.48). The relative malignancy OR value of circumscribed margins was 0.17 (95% CI, 0.07-0.45). CONCLUSION: CEM has high diagnostic performance in the workup of suspicious findings in dense breasts, and when lesions are enhanced and have irregular margins, they are often malignant.

Predicting potential therapeutic targets and small molecule drugs for early-stage lung adenocarcinoma.

Lung cancer is a leading cause of cancer-related mortality worldwide, with non-small cell lung cancer (NSCLC) constituting the majority, and its main subtype being lung adenocarcinoma (LUAD). Despite substantial advances in LUAD diagnosis and treatment, early diagnostic biomarkers inadequately fulfill clinical requirements. Thus, we conducted bioinformatics analysis to identify potential biomarkers and corresponding therapeutic drugs for early-stage LUAD patients. Here we identified a total of 10 differentially expressed genes (DEGs) with survival significance through the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). Subsequently, we identified a promising small molecule drug, Aminopurvalanol A, based on the 10 key genes using the L1000FWD application, which was validated by molecular docking followed by in vivo and in vitro experiments. The results highlighted TOP2A, CDH3, ASPM, CENPF, SLC2A1, and PRC1 as potential detection biomarkers for early LUAD. We confirmed the efficacy and safety of Aminopurvalanol A, providing valuable insights for the clinical management of LUAD.

Regression analysis of longitudinal data with random change point.

A great deal of literature has been established for regression analysis of longitudinal data and in particular, many methods have been proposed for the situation where there exist some change points. However, most of these methods only apply to continuous response and focus on the situations where the change point only occurs on the response or the trend of the individual trajectory. In this article, we propose a new joint modeling approach that allows not only the change point to vary for different subjects or be subject-specific but also the effect heterogeneity of the covariates before and after the change point. The method combines a generalized linear mixed effect model with a random change point for the longitudinal response and a log-linear regression model for the random change point. For inference, a maximum likelihood estimation procedure is developed and the asymptotic properties of the resulting estimators, which differ from the standard asymptotic results, are established. A simulation study is conducted and suggests that the proposed method works well for practical situations. An application to a set of real data on COVID-19 is provided.

Neoadjuvant versus adjuvant radiotherapy for resectable locally advanced gastric cancer: A SEER population analysis.

Background: There is a lack of evidence on whether resectable locally advanced gastric cancer (LAGC) patients could benefit from neoadjuvant or adjuvant radiotherapy (RT). Methods: Patients with surgically diagnosed LAGC from 2004 to 2015 were retrieved from the SEER database. Kaplan-Meier method and the log-rank test were used to evaluate survival analysis between neoadjuvant and adjuvant RT. Univariate Cox regression was used to evaluate the hazard ratio (HR) and 95 % confidence interval (CI). Results: A total of 4790 LAGC patients who treated with surgery and RT were identified, including 3187 patients with intestinal subtype and 1603 patients with diffuse subtype. For patients with both intestinal and diffuse subtypes, median cancer-specific survival (mCSS) was better with adjuvant RT or neoadjuvant RT. Moreover, patients benefited more from adjuvant RT than neoadjuvant RT (intestinal subtype: mCSS 49 vs. 36 months, P < 0.001; diffuse subtype: mCSS 32 vs. 26 months, P = 0.050). Further analyses showed that patients with intestinal subtype and T1-2N+, T3N-, T3N+ subgroups, as well as patients with diffuse subtype and T1-2N+ and T3N+ subgroups benefited more from adjuvant RT than those with neoadjuvant RT. Patients in the diffuse subtype and T3N- subgroups also tended benifit from adjuvant RT and survive. There was no difference in survival between the T4N- and T4N + subgroups of the two subtypes. After propensity score matching, subgroup analysis identified an improved survival in favor of adjuvant RT in the age ≥65 years and female subgroups in diffuse subtypes and T4N+ patients. Conclusions: For patients with resectable LAGC in the T1-2N+, T3N-, T3N+ clinical subgroups, adjuvant RT yields more benefits than neoadjuvant RT or no RT, which is worthy of prospective clinical trial.

Nanofiltration Ceramic Membranes as a Feasible Two-Pronged Approach toward Desalination and Lithium Recovery.

Ceramic membranes are taking center stage for separation technologies in water treatment. Among them, ceramic nanofiltration membranes are at the forefront of membrane technologies. The desalination of seawater using ceramic nanofiltration membranes is a potential application toward increasing the global water supply and tackling water scarcity. However, while the high fabrication cost poses a challenge to their large-scale applications, high-value separation applications can help to offset the overall cost. In this regard, ceramic nanofiltration membranes can also be explored as a viable option for high-value lithium extraction from the waste seawater brine. In order to determine the potential of nanofiltration ceramic membranes for desalination and lithium recovery from seawater, the current efficiency of salt rejection across various operation parameters must be thoroughly evaluated. Specifically, the interactions between the Donnan exclusion, steric exclusion, zeta potential, and salt concentration play an important role in determining the salt rejection efficiency. Several strategies are then proposed to guide ceramic nanofiltration membranes toward potentially practical applications regarding desalination and lithium recovery.

High-resolution transcriptomics analysis of CXCL13+ EPSTI1+ CDK1+ cells with a specific focus on lung adenocarcinoma.

Background: Programmed cell death ligand 1 (PD-L1) blocking therapy has transformed the treatment of lung adenocarcinoma (LUAD), which has significantly changed the landscape of immunotherapy. We aimed to explore specific cell subpopulations to understand tumor progression and identify markers of response to PD-L1 blocking therapy. Methods: Bulk, fluorescence-activated cell sorting (FACS), and single-cell RNA (scRNA) sequencing were used to profile CXCL13, EPSTI1, and CDK1. The gene set variation analysis (GSVA) R package was utilized for score calculation, and prognostic analyses included receiver operating characteristic (ROC) curves, Cox proportional hazard models, and meta-analysis. Additionally, we analyzed tumor microenvironment (TME), genomics, compound perturbations, and clinical indicators. The high-dimensional analysis captured the intrinsic characteristics of the subpopulation. Furthermore, subpopulation differential genes were used for enrichment analysis of transcription factors and compounds. Results: Literature and website analyses supported the essential role of CXCL13, CDK1, and EPSTI1 in immunotherapy. This led us to focus specifically on LUAD by representing a pan-cancer profile of immune-sensitive genes. Logically, the high-characteristic population may consist of samples positive for CXCL13, EPSTI1, and CDK1. The three-gene signature was a favorable indicator of immunotherapy response in the Stand Up to Cancer-Mark Foundation (SU2C-MARK) LUAD cohort but showed a poor prognosis before treatment in the Lung Cancer Explorer (LCE) database. Further mechanistic exploration revealed specific mutations associated with the three-gene signature in SU2C-MARK LUAD, such as STK11. In The Cancer Genome Atlas (TCGA)-LUAD cohort, the high-scoring group exhibited a higher tumor mutational burden (TMB) and global methylation but a lower fraction genome altered (FGA) and estimated tumor purity. Moreover, dasatinib demonstrated sensitivity in the high-scoring group. The co-localization of the CXCL13, EPSTI1, and CDK1 subpopulation was validated through spatial transcriptome and immunohistochemical databases. Assessment of the subpopulation depicted high-resolution intercellular communication. Maintenance of specific pathways, such as TNF, CD74, and CD44, contributed to immunotherapy sensitivity. Finally, the subpopulation-enriched targets and drugs were confirmed through ConnectivityMap (CMAP) analysis and multi-omics, respectively. Conclusions: In this study, positive samples for CXCL13, EPSTI1, and CDK1 exhibited poor prognostic significance in treatment-naïve LUAD cases but demonstrated benefits from PD-L1 blockade and dasatinib therapies.

Population-based high-dimensional analyses identify multiple intrinsic characters for cancer vaccines against lung squamous cell carcinoma.

In lung squamous cell carcinoma (LUSC), current cancer vaccines show promising effects, despite a lack of benefit for a large number of patients. We first identified the tumor antigens into shared and private antigens, and determined the population by clustering analysis in public datasets. For vaccine development, The Cancer Genome Atlas (TCGA) and Clinical Proteomic Tumor Analysis Consortium (CPTAC) were collected. WGCNA method was furthermore applied to construct a consensus gene co-expression network based on TCGA and CPTAC datasets. The main analyses in bulk sequencing included survival, clinical features, tumor microenvironment (TME), and pathways enrichment. In addition, single-cell RNA (scRNA) analysis of cancer epithelium dissected consensus subtype. We identified the ideal population for cancer vaccines, and candidate neoantigens including AOC1, COL5A2, LGI2, and POSTN. According to subtype analysis, Lung squamous 1 (LSQ1) type exhibited a higher tumor mutational load (TMB) and copy number but no immune infiltration, whereas lung squamous 2 (LSQ2) tumors had a higher global methylation level and more fibroblasts but had less stemness. Meanwhile, trajectory analysis further revealed that the evolution of TME influenced prognosis. We emphasized specific pathways or targets with the potential for combination immunotherapy by consensus network and single-cell RNA analyses. Anti-androgen therapy has been validated in vitro experiments of LUSC as proof of concept. In conclusion, LSQ1 was linked to immune exclusion and might be utilized for vaccination, while LSQ2 was linked to immune dysfunction and could be used for programmed cell death protein 1 (PD1) blocking therapy.

METTL3-dependent N6-methyladenosine modification is involved in berberine-mediated neuroprotection in ischemic stroke by enhancing the stability of NEAT1 in astrocytes.

Ischemic stroke (IS) is one of the principal causes of disability and death worldwide. Berberine (BBR), derived from the traditional Chinese herbal medicine Huang Lian, has been reported to inhibit the progression of stroke, but the specific mechanism whereby BBR modulates the progression of ischemic stroke remains unclear. N6-methyladenosine (m6A) modification is the most typical epigenetic modification of mRNA post-transcriptional modifications, among which METTL3 is the most common methylation transferase. During the study, the middle cerebral artery occlusion/reperfusion (MCAO/R) was established in mice, and the mice primary astrocytes and neurons induced by oxygen-glucose deprivation/reoxygenation (OGD/R) was simulated in vitro. Level of LncNEAT1, miR-377-3p was detected via RT-qPCR. The levels of Nampt and METTL3 were measured by Western blot. CCK8 and LDH assay was performed to detect cell viability. Here, we found that berberine alleviates MCAO/R-induced ischemic injury and up-regulates the expression of Nampt in astrocytes, miR-377-3p inhibits the expression of Nampt in astrocytes after OGD/R, thus promoting neuronal injury. NEAT1 binds to miR-377-3p in OGD/R astrocytes and plays a neuronal protective role as a ceRNA. METTL3 can enhance NEAT1 stability in OGD/R astrocytes by modulating m6A modification of NEAT1. Taken together, our results demonstrate that berberine exerts neuroprotective effects via the m6A methyltransferase METTL3, which regulates the NEAT1/miR-377-3p/Nampt axis in mouse astrocytes to ameliorate cerebral ischemia/reperfusion (I/R) injury.

Switch Volmer-Heyrovsky to Volmer-Tafel Pathway for Efficient Acidic Electrocatalytic Hydrogen Evolution by Correlating Pt Single Atoms with Clusters.

As cost-effective catalysts, platinum (Pt) single-atom catalysts (SACs) have attracted substantial attention. However, most studies indicate that Pt SACs in acidic hydrogen evolution reaction (HER) follow the slow Volmer-Heyrovsky (VH) mechanism instead of the fast kinetic Volmer-Tafel (VT) pathway. Here, this work propose that the VH mechanism in Pt SACs can be switched to the faster VT pathway for efficient HER by correlating Pt single atoms (SAs) with Pt clusters (Cs). Our calculations reveal that the correlation between Pt SAs and Cs significantly impacts the electronic structure of exposed Pt atoms, lowering the adsorption barrier for atomic hydrogen and enabling a faster VT mechanism. To validate these findings, this work purposely synthesize three catalysts: l-Pt@MoS2 , m-Pt@MoS2 and h-Pt@MoS2 with low, moderate, and high Pt-loading, having different distributions of Pt SAs and Cs. The m-Pt@MoS2 catalyst with properly correlating Pt SAs and Cs exhibits outstanding performance with an overpotential of 47 mV and Tafel slope of 32 mV dec-1 . Further analysis of the Tafel values confirms that the m-Pt@MoS2 sample indeed follows the VT reaction mechanism, aligning with the theoretical findings. This study offers a deep understanding of the synergistic mechanism, paving a way for designing novel-advanced catalysts.

Efficient estimation of Cox model with random change point.

In clinical studies, the risk of a disease may dramatically change when some biological indexes of the human body exceed some thresholds. Furthermore, the differences in individual characteristics of patients such as physical and psychological experience may lead to subject-specific thresholds or change points. Although a large literature has been established for regression analysis of failure time data with change points, most of the existing methods assume the same, fixed change point for all study subjects. In this paper, we consider the situation where there exists a subject-specific change point and two Cox type models are presented. The proposed models also offer a framework for subgroup analysis. For inference, a sieve maximum likelihood estimation procedure is proposed and the asymptotic properties of the resulting estimators are established. An extensive simulation study is conducted to assess the empirical performance of the proposed method and indicates that it works well in practical situations. Finally the proposed approach is applied to a set of breast cancer data.

Interfacial Synergy in Mo2C/MoC Heterostructure Promoting Sequential Polysulfide Conversion in High-Performance Lithium-Sulfur Battery.

A rational design of sulfur host is the key to conquering the"polysulfide shuttle effects" by accelerating the polysulfide conversion. Since the process involves solid-liquid-solid multistep phase transitions, purposely-engineered heterostructure catalysts with various active regions for catalyzing conversion steps correspondingly are beneficial to promote the overall conversion process. However, the functionalities of the materials surface and interface in heterostructure catalysts remain unclear. In this work, an Mo2C/MoC catalyst with abundant Mo2C surface-interface-MoC surface tri-active-region is developed by in situ converting the MoZn-metal organic framework. The experimental and simulation studies demonstrate the interface can catch long-chain polysulfides and promote their conversion. Instead, the Mo2C and MoC tend to accommodate the short-chain polysulfide and accelerate their conversion and the Li2S dissociation. Benefitting from the high catalytic ability, the Li-S battery assembled with the Mo2C/MoC-S cathode shows more discrete redox reactions and delivers a high initial capacity of 1603.6 mAh g-1 at 1 C charging-discharging rate, which is over twofolds of the one assembled using individual hosts, and 80.4% capacity can be maintained after 1000 cycles at 3 C rate. This work has demonstrated a novel synergy between the interface and material surface, which will help the future design of high-performance Li-S batteries.

Click Chemistry in Lithium-Metal Batteries.

Lithium-metal batteries (LMBs) are considered the "holy grail" of the next-generation energy storage systems, and solid-state electrolytes (SSEs) are a kind of critical component assembled in LMBs. However, as one of the most important branches of SSEs, polymer-based electrolytes (PEs) possess several native drawbacks including insufficient ionic conductivity and so on. Click chemistry is a simple, efficient, regioselective, and stereoselective synthesis method, which can be used not only for preparing PEs with outstanding physical and chemical performances, but also for optimizing the stability of solid electrolyte interphase (SEI) layer and elevate the cycling properties of LMBs effectively. Here it is primarily focused on evaluating the merits of click chemistry, summarizing its existing challenges and outlining its increasing role for the designing and fabrication of advanced PEs. The fundamental requirements for reconstructing artificial SEI layer through click chemistry are also summarized, with the aim to offer a thorough comprehension and provide a strategic guidance for exploring the potentials of click chemistry in the field of LMBs.

Accelerating Sulfur Redox Kinetics by Electronic Modulation and Drifting Effects of Pre-Lithiation Electrocatalysts.

Efficient catalyst design is crucial for addressing the sluggish multi-step sulfur redox reaction (SRR) in lithium-sulfur batteries (LiSBs), which are among the promising candidates for the next-generation high-energy-density storage systems. However, the limited understanding of the underlying catalytic kinetic mechanisms and the lack of precise control over catalyst structures pose challenges in designing highly efficient catalysts, which hinder the LiSBs' practical application. Here, drawing inspiration from the theoretical calculations, the concept of precisely controlled pre-lithiation SRR electrocatalysts is proposed. The dual roles of channel and surface lithium in pre-lithiated 1T'-MoS2 are revealed, referred to as the "electronic modulation effect" and "drifting effect", respectively, both of which contribute to accelerating the SRR kinetics. As a result, the thus-designed 1T'-Lix MoS2 /CS cathode obtained by epitaxial growth of pre-lithiated 1T'-MoS2 on cubic Co9 S8 exhibits impressive performance with a high initial specific capacity of 1049.8 mAh g-1 , excellent rate-capability, and remarkable long-term cycling stability with a decay rate of only 0.019% per cycle over 1000 cycles at 3 C. This work highlights the importance of precise control in pre-lithiation parameters and the synergistic effects of channel and surface lithium, providing new valuable insights into the design and optimization of SRR electrocatalysts for high-performance LiSBs.

Frameworked Electrolytes: A Pathway Towards Solid Future of Batteries.

All-solid-state batteries (ASSBs) represent a highly promising next-generation energy storage technology owing to their inherently high safety, device reliability, and potential for achieving high energy density in the post-ara of lithium-ion batteries, and therefore extensive searches are ongoing for ideal solid-state electrolytes (SSEs). Though promising, there is still a huge barrier that limits the large-scale applications of ASSBs, where there are a couple of bottleneck technical issues. In this perspective, a novel category of electrolytes known as frameworked electrolytes (FEs) are examined, where the solid frameworks are intentionally designed to contain 3D ionic channels at sub-nano scales, rendering them macroscopically solid. The distinctive structural design of FEs gives rise to not only high ionic conductivity but also desirable interfaces with electrode solids. This is achieved through the presence of sub-nano channels within the framework, which exhibit significantly different ion diffusion behavior due to the confinement effect. This perspective offers a compelling insight into the potential of FEs in the pursuit of ASSBs, where FEs offer an exciting opportunity to overcome the limitations of traditional solid-state electrolytes and propel the development of ASSBs as the holy grail of energy storage technology.