Complexing agent-assisted Cr(VI) removal in a continuous fixed-bed system with nanoscale Fe0/NaA molecular sieve membrane supported on nickel foam.

Complexing agents (CAs) can be used for the removal of Cr(VI) via nanoscale Fe0 (nZVI) reduction in cost-effective manner. However, nZVI is prone to aggregation and passivation, and some conventional CAs are toxic and difficult to biodegrade, potentially causing secondary pollution. Therefore, selecting an environmentally friendly CA for assisting in the removal of Cr(VI) via supported nZVI is imperative. Herein, NaA molecular sieve membrane-supported nZVI (nZVI/NaA-NF) was prepared via the secondary growth and liquid-phase reduction method using nickel foam (NF) as the carrier. The physicochemical characteristics of nZVI/NaA-NF before and after reaction were analysed via SEM, EDS, and XPS. A CA-improved nZVI/NaA-NF was used for the effective removal of Cr(VI) in a continuous fixed-bed system. Furthermore, the influences of various experimental factors including the CA type, CA concentration, solution pH, space velocity, and inlet Cr(VI) concentration on Cr(VI) removal were systematically investigated. The results demonstrated that nZVI particles were homogeneously immobilized on the NaA molecular sieve membrane/NF for fresh nZVI/NaA-NF, and tetrasodium iminidisuccinate (IDS-4Na) inhibited the aggregation of Cr(III)/Fe(III) (hydr)oxide precipitates during the reaction. IDS-4Na demonstrated excellent promotive effect on Cr(VI) removal via nZVI/NaA-NF. The breakthrough time for Cr(VI) in the addition of IDS-4Na was considerably longer than that of nZVI/NaA-NF alone. The breakthrough concentration of Cr(VI) only reached 1.1% and 9.9% of the inlet concentration at 220 and 240 min, with an IDS-4Na concentration of 4 mM, a pH of 2.5, and a space velocity of 0.265 min-1. The Bohart-Adams model was appropriate to predict the initial part of Cr(VI) breakthrough curves in the nZVI/NaA-NF fixed bed. The saturated concentration (N0) increased with an increase in inlet Cr(VI) concentration. The Yoon-Nelson model afforded good fitting results for all breakthrough curves of Cr(VI). The k´ value increased with an increase in space velocity, and the τ value decreased.

Improving estimation efficiency of case-cohort studies with interval-censored failure time data.

The case-cohort design is a commonly used cost-effective sampling strategy for large cohort studies, where some covariates are expensive to measure or obtain. In this paper, we consider regression analysis under a case-cohort study with interval-censored failure time data, where the failure time is only known to fall within an interval instead of being exactly observed. A common approach to analyzing data from a case-cohort study is the inverse probability weighting approach, where only subjects in the case-cohort sample are used in estimation, and the subjects are weighted based on the probability of inclusion into the case-cohort sample. This approach, though consistent, is generally inefficient as it does not incorporate information outside the case-cohort sample. To improve efficiency, we first develop a sieve maximum weighted likelihood estimator under the Cox model based on the case-cohort sample and then propose a procedure to update this estimator by using information in the full cohort. We show that the update estimator is consistent, asymptotically normal, and at least as efficient as the original estimator. The proposed method can flexibly incorporate auxiliary variables to improve estimation efficiency. A weighted bootstrap procedure is employed for variance estimation. Simulation results indicate that the proposed method works well in practical situations. An application to a Phase 3 HIV vaccine efficacy trial is provided for illustration.

Estimation of phloem conductance at tree level in young, middle-aged and old-aged Scots pine trees growing in different climatic conditions in boreal forests.

In forests, a significant proportion of the carbon fixed by trees during photosynthesis is transported belowground along the conducting phloem, so variations in phloem anatomy can lead to variations in transport capacity. Phloem conductance at tree level (Ktree) is also affected by tree height. Both the phloem anatomy and the tree size change during ontogeny, and also differ under different environmental conditions. The goal of our work was to identify the main drivers of variation in Ktree in Scots pine trees growing in natural boreal forests. We conducted a phloem anatomical study and calculated Ktree in trees of three age groups growing in different climatic conditions along a latitudinal gradient from south to north. We found that Ktree was maintained at the same level in actively growing pine trees (25-80-years-old) but increased in old-aged trees (180-190-years-old), possibly reflecting the shift in source-sink relationships of aboveground and belowground parts of trees. Trees of the same age group growing in different climatic conditions demonstrated similar values of Ktree due to coordinated changes in the phloem anatomy and the tree height. In general, the negative influence of tree height on Ktree is offset by the positive influence of phloem width (or trunk diameter) and sieve cell diameter. The exception was young trees growing in the transition zone of the northern taiga subzone to the tundra, where Ktree was the highest in its age group and even exceeded Ktree of middle-aged trees.

Metabolomics analysis based on UHPLC-QTOF-MS/MS to explore the synthesis mechanism and culture conditions optimization of Penicillium EF-2 exopolysaccharide.

Penicillium exopolysaccharide (EPS) inhibits galactose lectins and enhances immunity. However, EPS production is low and its synthesis mechanism remains unclear. Penicillium EF-2 strains with high EPS production were selected for this study, and Penicillium fermentation conditions were subsequently improved. The optimal culture conditions were 30 g/L lactose, 6 g/L yeast extract powder, 4 d seed age, 10 % inoculation amount, 3 d of secondary fermentation time, and the final EPS yield was 3.97 g/L. UHPLC-Q-TOF-MS/MS was used to explore the mechanism of EPS synthesis at the metabolic level. Optimal carbon source: lactose and optimal nitrogen source: yeast extract can provide precursors for EPS synthesis through related metabolic pathways. Moreover, regulating the energy, vitamin, and lipid metabolic pathways created favourable conditions for EPS synthesis and secretion. These findings explain the mechanism of EPS synthesis at the metabolic level and provide a theoretical basis for optimising and industrialising EPS production.

High-Porosity Sieve-Type Neural Electrodes for Motor Function Recovery and Nerve Signal Acquisition.

In this study, the effects of electrode porosity on nerve regeneration and functional recovery after sciatic nerve transection in rats was investigated. A sieve-type neural electrode with 70% porosity was designed and compared with an electrode with 30% porosity. Electrodes were fabricated from photosensitive polyimide and implanted into the transected sciatic nerves. Motor function recovery was evaluated using the Sciatic Function Index. The number of active channels and their signal quality were recorded and analyzed to assess the sensory neural signal acquisition. Electrical impedance spectroscopy was used to evaluate the electrode performance. The group implanted with the 70% porosity electrode demonstrated significantly enhanced nerve regeneration and motor function recovery, approaching control group levels by the fifth week. In contrast, the group with the 30% porosity electrode exhibited limited improvement. Immunohistochemical analysis confirmed extensive nerve fiber growth within the 70% porous structure. Moreover, the 70% porosity electrode consistently acquired neural signals from more channels compared to the 30% porosity electrode, demonstrating its superior performance in sensory signal detection. These findings emphasize the importance of optimizing electrode porosity in the development of advanced neural interfaces, with the potential to enhance clinical outcomes in peripheral nerve repair and neuroprosthetic applications.

Enhanced Ni(II) Removal from Wastewater Using Novel Molecular Sieve-Based Composites.

This study focuses on the efficient removal of Ni(II) from spent lithium-ion batteries (LIBs) to support environmental conservation and sustainable resource management. A composite material, known as molecular sieve (MS)-based metal-organic framework (MOF) composites (MMCs), consisting of a synthesized MS matrix with integrated MOFs, was developed for the adsorption of Ni(II). The structural and performance characteristics of the MMCs were evaluated using X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM), and N2 adsorption-desorption isotherms (BET). Batch adsorption experiments were conducted to assess the Ni(II) adsorption performance of the MMCs. The results revealed that, under conditions of pH 8 and a temperature of 298 K, the MMCs achieved near-equilibrium Ni(II) adsorption within 6 h, with a maximum theoretical adsorption capacity of 204.1 mg/g. Further analysis of the adsorption data confirmed that the adsorption process followed a pseudo-second-order kinetic model and Langmuir isotherm model, indicating a spontaneous, endothermic chemical adsorption mechanism. Importantly, the MMCs exhibited superior Ni(II) adsorption compared to the MS. This study provides valuable insights into the effective recovery and recycling of Ni(II) from spent LIBs, emphasizing its significance for environmental sustainability and resource circularity.

Synthesis of Ordered Mesoporous Molecular Sieve-Supported Cobalt Catalyst via Organometallic Complexation for Propane Non-Oxidative Dehydrogenation.

Co-based catalysts have shown great promise for propane dehydrogenation (PDH) reactions due to their merits of environmental friendliness and low cost. In this study, ordered mesoporous molecular sieve-supported CoOx species (CoOx/Al-SBA-15 catalyst) were prepared by one-step organometallic complexation. The catalysts show worm-like morphology with regular straight-through mesoporous pores and high external specific surface area. These typical features can substantially enhance the dispersion of CoOx species and mass transfer of reactants and products. Compared with the conventional impregnation method, the 10CSOC (10 wt.% Co/Al-SBA-15 prepared by the organometallic complexation method) sample presents a smaller CoOx size and higher Co2+/Co3+ ratio. When applied to PDH reaction, the 10CSOC delivers higher propane conversion and propylene selectivity. Under the optimal conditions (625 °C and 4500 h-1), 10CSOC achieves high propane conversion (43%) and propylene selectivity (83%). This is attributed to the smaller and better dispersion of CoOx nanoparticles, more suitable acid properties, and higher content of Co2+ species. This work paves the way for the rational design of high-performance catalysts for industrially important reactions.

Hybrid Molecular Sieve-Based Interfacial Layer with Physical Confinement and Desolvation Effect for Dendrite-free Zinc Metal Anodes.

The side reactions and dendrite growth at the interface of Zn anodes greatly limit their practical applications in Zn metal batteries. Herein, we propose a hybrid molecular sieve-based interfacial layer (denoted as Z7M3) with a hierarchical porous structure for Zn metal anodes, which contains 70 vol % microporous ZSM-5 molecular sieves and 30 vol % mesoporous MCM-41 molecular sieves. Through comprehensive molecular dynamics simulations, we demonstrate that the mesopores (∼2.5 nm) of MCM-41 can limit the disordered diffusion of free water molecules and increase the wettability of the interfacial layer toward aqueous electrolytes. In addition, the micropores (∼0.56 nm) of ZSM-5 can optimize the Zn2+ solvation structures by reducing the bonded water molecules, which simultaneously decrease the constraint force of solvated water molecules to Zn2+ ions, thus promoting the penetrability and diffusion kinetics of Zn2+ ions in Z7M3. The synergetic effects from the hybrid molecular sieves maintain a constant Zn2+ concentration on the surface of the Zn electrode during Zn deposition, contributing to dendrite-free Zn anodes. Consequently, Z7M3-coated Zn electrodes achieved excellent cycling stability in both half and full cells.

Estimation of accelerated hazards models based on case K informatively interval-censored failure time data.

The accelerated hazards model is one of the most commonly used models for regression analysis of failure time data and this is especially the case when, for example, the hazard functions may have monotonicity property. Correspondingly a large literature has been established for its estimation or inference when right-censored data are observed. Although several methods have also been developed for its inference based on interval-censored data, they apply only to limited situations or rely on some assumptions such as independent censoring. In this paper, we consider the situation where one observes case K interval-censored data, the type of failure time data that occur most in, for example, medical research such as clinical trials or periodical follow-up studies. For inference, we propose a sieve borrow-strength method and in particular, it allows for informative censoring. The asymptotic properties of the proposed estimators are established. Simulation studies demonstrate that the proposed inference procedure performs well. The method is applied to a set of real data set arising from an AIDS clinical trial.

The balanced discrete Burr-Hatke model and mixing INAR(1) process: properties, estimation, forecasting and COVID-19 applications.

The main concern of this paper is providing a flexible discrete model that captures every kind of dispersion (equi-, over- and under-dispersion). Based on the balanced discretization method, a new discrete version of Burr-Hatke distribution is introduced with the partial moment-preserving property. Some statistical properties of the new distribution are introduced, and the applicability of proposed model is evaluated by considering counting series. A new integer-valued autoregressive (INAR) process based on the mixing Pegram and binomial thinning operators with discrete Burr-Hatke innovations is introduced, which can model contagious data properly. The different estimation approaches of parameters of the new process are provided and compared through the Monte Carlo simulation scheme. The performance of the proposed process is evaluated by four data sets of the daily death counts of the COVID-19 in Austria, Switzerland, Nigeria and Slovenia in comparison with some competitor INAR(1) models, along with the Pearson residual analysis of the assessing model. The goodness of fit measures affirm the adequacy of the proposed process in modeling all COVID-19 data sets. The fundamental prediction procedures are considered for new process by classic, modified Sieve bootstrap and Bayesian forecasting methods for all COVID-19 data sets, which is concluded that the Bayesian forecasting approach provides more reliable results.

Recent Research Progress of Porous Graphene and Applications in Molecular Sieve, Sensor, and Supercapacitor.

Porous graphene, including 2D and 3D porous graphene, is widely researched recently. One of the most attractive features is the proper utilization of graphene defects, which combine the advantages of both graphene and porous materials, greatly enriching the applications of porous graphene in biology, chemistry, electronics, and other fields. In this review, the defects of graphene are first discussed to provide a comprehensive understanding of porous graphene. Then, the latest advancements in the preparation of 2D and 3D porous graphene are presented. The pros and cons of these preparation methods are discussed in detail, providing a direction for the fabrication of porous graphene. Moreover, various superior properties of porous graphene are described, laying the foundation for their promising applications. Owing to its abundant morphology, wide distribution of pore size, and remarkable properties benefited from porous structure, porous graphene can not only promote molecular diffusion and electron transfer but also expose more active sites. Consequently, a serious of applications containing gas sieving, liquid separation, sensors, and supercapacitors, are presented. Finally, the challenges confronted during preparation and characterization of porous graphene are discussed, offering guidance for the future development of porous graphene in fabrication, characterization, properties, and applications.

Selective biosorption of Li+ in aqueous solution by lithium ion-imprinted material on the surface of chitosan/attapulgite.

The extraction of Li+ from liquid lithium resources is a pivotal focus of current research endeavors. Attapulgite (ATP), characterized by its distinctive layered structure and inherent ion exchange properties, emerges as an exceptional material for fabricating lithium-ion sieve. Ion-imprinted chitosan/ATP composite materials are successfully synthesized, demonstrating efficacy in selectively absorbing Li+. The results emphasize the rich functional groups present in H-CTP-2, enhancing its absorbability and selectivity, with an adsorption capacity of 37.56 mg•g-1. The adsorption conforms to the Langmuir and pseudo-second-order kinetic model. Li+ coordination involves amino and hydroxyl group, indicating a chemisorption process. Furthermore, the substantial pore structure and significant specific surface area of ATP significantly promote Li+ adsorption, suggesting its participation not only in chemisorption but also in physical adsorption. The fabricated ion-imprinted materials boast substantial adsorption capacity, exceptional selectivity, and rapid kinetics, highlighting their potential for effectively separating Li+ from aqueous solution.

Fullerenol as a nano-molecular sieve additive enables stable zinc metal anodes.

Aqueous zinc batteries (AZBs) with the advantages of safety, low cost, and sustainability are promising candidates for large-scale energy storage devices. However, the issues of interface side reactions and dendrite growth at the zinc metal anode (ZMA) significantly harm the cycling lifespan of AZBs. In this study, we designed a nano-molecular sieve additive, fullerenol (C60(OH)n), which possesses a surface rich in hydroxyl groups that can be uniformly dispersed in the aqueous solution, and captures free water in the electrolyte, thereby suppressing the occurrence of interfacial corrosion. Besides, fullerenol can be further reduced to fullerene (C60) on the surface of ZMA, holding a unique self-smoothing effect that can inhibit the growth of dendritic Zn. With the synergistic action of these two effects, the fullerenol-contained electrolyte (FE) enables dendrite-free ZMAs. The Zn-Ti half-cell using FE exhibits stable cycling over 2500 times at 5 mA cm-2 with an average Coulombic efficiency as high as 99.8 %. Additionally, the Zn-NaV3O8 cell using this electrolyte displays a capacity retention rate of 100 % after 1000 cycles at -20 °C. This work provides important insights into the molecular design of multifunctional electrolyte additives.

Precise Control of Ultramicropores of Novel Carbons Molecule Sieves Derived from Coffee Bean for Efficient Sieving Propylene from Propane.

The development of granular carbon materials with outstanding selectivity for the separation of alkenes and alkanes is highly desirable in the petrochemical industry but remains a significant challenge due to closely similar molecular sizes and physical properties of adsorbates. Herein, we report a facile approach of using natural biomass to prepare novel granular carbon molecule sieves with a molecular recognition accuracy of 0.44 Å and propose a new three-region model for the pore size distribution of amorphous porous carbons. Coffee bean-based granule carbon molecular sieves (CFGCs) were prepared with precise micropore regulation with subangstrom accuracy and characterized using molecular probes to reveal the evolution of carbon structure during preparation. The CFGC-0.09-750 demonstrates exceptional selectivity adsorption toward C3H6 while excluding C3H8, with an uptake ratio of 106.75 and a C3H6 uptake of 1.88 mmol/g at 298 K and 100 kPa, showcasing its immense potential in industrial applications for separating C3H6 and C3H8. The novel three-region model established in this work can clearly and reasonably elucidate why the samples CFGCs can screen propylene from propane at the subangstrom level. This study provides important guidance for the development of new carbon molecular sieves with subangstrom accuracy in molecular recognition and separation capacity.

DNA tetrahedral molecular sieve for size-selective fluorescence sensing of miRNA 21 in living cells.

In situ monitoring of intracellular microRNAs (miRNAs) often encounters the challenges of surrounding complexity, coexistence of precursor miRNAs (pre-miRNAs) and the degradation of biological enzyme in living cells. Here, we designed a novel probe encapsulated DNA tetrahedral molecular sieve (DTMS) to realize the size-selective detection of intracellular miRNA 21 that can avoid the interference of pre-miRNAs. In such strategy, quencher (BHQ-1) labeled probe DNA (S6-BHQ 1) was introduced into the inner cavity of fluorophore (FAM) labeled DNA tetrahedral scaffolds (DTS) to prepare DTMS, making the FAM and BHQ-1 closely proximate, and resulting the sensor in a "signal-off" state. In the presence of miRNA 21, strand displacement reaction happened to form more stable DNA double-stranded structure, accompanied by the release of S6-BHQ 1 from the inner cavity of DTMS, making the sensor in a "signal-on" state. The DTMS based sensing platform can then realized the size-selective detection of miRNA 21 with a detection limit of 3.6 pM. Relying on the mechanical rigidity of DTS and the encapsulation of DNA probe using DTMS, such proposed method achieved preferable reproducibility and storage stability. Moreover, this sensing system exhibited good performance for monitoring the change of intracellular miRNA 21 level during the treatment with miRNA-related drugs, demonstrating great potential for biological studies and accurate disease diagnosis.

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.

Balancing the Kinetic and Thermodynamic Synergetic Effect of Doped Carbon Molecular Sieves for Selective Separation of C2H4/C2H6.

Selective separation of ethylene and ethane (C2H4/C2H6) is a formidable challenge due to their close molecular size and boiling point. Compared to industry-used cryogenic distillation, adsorption separation would offer a more energy-efficient solution when an efficient adsorbent is available. Herein, a class of C2H4/C2H6 separation adsorbents, doped carbon molecular sieves (d-CMSs) is reported which are prepared from the polymerization and subsequent carbonization of resorcinol, m-phenylenediamine, and formaldehyde in ethanol solution. The study demonstrated that the polymer precursor themselves can be a versatile platform for modifying the pore structure and surface functional groups of their derived d-CMSs. The high proportion of pores centered at 3.5 Å in d-CMSs contributes significantly to achieving a superior kinetic selectivity of 205 for C2H4/C2H6 separation. The generated pyrrolic-N and pyridinic-N functional sites in d-CMSs contribute to a remarkable elevation of Henry selectivity to 135 due to the enhancement of the surface polarity in d-CMSs. By balancing the synergistic effects of kinetics and thermodynamics, d-CMSs achieve efficient separation of C2H4/C2H6. Polymer-grade C2H4 of 99.71% purity can be achieved with 75% recovery using the devised d-CMSs as reflected in a two-bed vacuum swing adsorption simulation.

[Semiparametric analysis of nonparametric proportional hazards models with mixed dependent censored data].

OBJECTIVE: To construct a nonparametric proportional hazards (PH) model for mixed informative interval-censored failure time data for predicting the risks in heart transplantation surgeries. METHODS: Based on the complexity of mixed informative interval-censored failure time data, we considered the interdependent relationship between failure time process and observation time process, constructed a nonparametric proportional hazards (PH) model to describe the nonlinear relationship between the risk factors and heart transplant surgery risks and proposed a two-step sieve estimation maximum likelihood algorithm. An estimation equation was established to estimate frailty variables using the observation process model. Ⅰ-spline and B-spline were used to approximate the unknown baseline hazard function and nonparametric function, respectively, to obtain the working likelihood function in the sieve space. The partial derivative of the model parameters was used to obtain the scoring equation. The maximum likelihood estimation of the parameters was obtained by solving the scoring equation, and a function curve of the impact of risk factors on the risk of heart transplantation surgery was drawn. RESULTS: Simulation experiment suggested that the estimated values obtained by the proposed method were consistent and asymptotically effective under various settings with good fitting effects. Analysis of heart transplant surgery data showed that the donor's age had a positive linear relationship with the surgical risk. The impact of the recipient's age at disease onset increased at first and then stabilized, but increased against at an older age. The donor-recipient age difference had a positive linear relationship with the surgical risk of heart transplantation. CONCLUSION: The nonparametric PH model established in this study can be used for predicting the risks in heart transplantation surgery and exploring the functional relationship between the surgery risks and the risk factors.

Hydrothermal synthesis of high crystallinity ZSM-5 zeolite from coal gasification coarse slag and mother liquor circulation for efficient coal chemical wastewater purification.

A hydrothermal synthesis method was developed to produce high crystallinity ZSM-5 zeolite using coal gasification coarse slag (CGCS) as the raw material. Instead of the expensive NaOH(s.), Na2SiO3(s.) was utilized to activate, depolymerize, and recombine Si and Al elements in the CGCS. The mother liquor circulation technology was employed to recover and reuse raw materials and residual reagents (Na2SiO3(aq.) and TPABr), reducing waste emissions and enhancing resource utilization efficiency. The synthesized ZSM-5 had a specific surface area of 455.675 m2 g-1, pore volume of 0.284 cm3 g-1, and pore diameter of 2.496 nm. The influence of various factors on the morphology and crystallinity of ZSM-5 was investigated, resulting in the production of ZSM-5 with higher specific surface area and pore volume. Adsorption experiments showed that WU-ZSM-5 exhibited a removal efficiency of 85% for ammonia nitrogen (NH4+-N(aq.)), validating its effectiveness in coal chemical wastewater purification. The mother liquor recycling technology enabled zero-emission utilization of solid waste resources and improved the utilization rate of alkali and template to 90%. These results demonstrate the potential application of the developed method in the efficient treatment of coal chemical wastewater.

High-Level Disordered Metal-Organic Frameworks Synthesized by Interference-Oriented Attachment for Electrochemical Anion Sieve.

Disordered MOFs seamlessly amalgamate the robust stability and pore tunability inherent in crystalline MOFs with the advantages derived from abundant defects and active sites present in amorphous structures. This study pioneers the use of the interference-oriented attachment (IOA) mechanism to meticulously craft the morphology and crystal growth of MIL-101(Cr) (Cr-MOF), resulting in the successful synthesis of a high-level disordered Cr-MOF boasting an enhanced array of active sites and exceptional electrochemical properties. The correlation between disordered structures and the electrochemical properties of MOFs are elucidated using the lattice distortion index and fractal dimension. The high-level disordered MOF electrode showcases a remarkable fluoride sieving effect, outperforming conventional fluoride removal materials with a remarkable fluoride adsorption capacity of 41.04 mgNaF gelectrodes -1. First-principles calculations, in conjunction with relevant experiments, provided further validation that the disordered structure significantly enhances the defluorination performance of the material. This study introduces a novel approach for the direct bottom-up synthesis of high-level disordered MOFs, showcasing their potential for applications in electrochemical water treatment.