Fabric multifunctionality offers resource savings and enhanced human comfort. This study innovatively integrates cooling, heating, and antimicrobial properties within a Janus fabric, surpassing previous research focused solely on cooling or heating. Different effects are achieved by applying distinct coatings to each side of the fabric. One graphene oxide (GO) coating exhibits exceptional light-to-heat conversion, absorbing and transforming light energy into heat, thereby elevating fabric temperature by 15.4 ℃, 22.7 ℃, and 43.7 ℃ under 0.2, 0.5, and 1 sun irradiation, respectively. Conversely, a hydrogel coating on one side absorbs water, facilitating heat dissipation through evaporation upon light exposure, reducing fabric temperature by 5.9 ℃, 8.4 ℃, and 7.1 ℃ in 0.2, 0.5, and 1 sun irradiation, respectively. Moreover, both sides of Janus fabric exhibit potent antimicrobial properties, ensuring fabric hygiene. This work presents a feasible solution to address crucial challenges in fabric thermal regulation, providing a smart approach for intelligent adjustment of body comfort in both summer and winter. By integrating heating and cooling capabilities along with antimicrobial properties, this study promotes sustainable development in textile techniques.

This study delves into the intricate deposition dynamics of submicron particles within electric-flow coupled fields, underscoring the unique challenges posed by their minuscule size, aggregation tendencies, and biological reactivity. Employing an operando investigation system that synergizes microfluidic technology with advanced micro-visualization techniques within a lab-on-a-chip framework enables a meticulous examination of the dynamic deposition phenomena. The incorporation of object detection and deep learning methodologies in image processing streamlines the automatic identification and swift extraction of crucial data, effectively tackling the complexities associated with capturing and mitigating these hazardous particles. Combined with the analysis of the growth behavior of particle chain under different applied voltages, it established that a linear relationship exists between the applied voltage and θ. And there is a negative correlation between the average particle chain length and electric field strength at the collection electrode surface (4.2×10⁵ to 1.6×10⁶ V·m^-1). The morphology of the deposited particle agglomerate at different electric field strengths is proposed: dendritic agglomerate, long chain agglomerate, and short chain agglomerate.

Dynamic control is essential to guarantee the stable performance of continuous chromatography. AutoMAb dynamic control strategy has been developed to ensure a consistent protein load in twin-column CaptureSMB continuous capture by integrating the UV signal of breakthrough. In this study, the process risk of CaptureSMB continuous capture under AutoMAb control towards the feedstock variations was assessed by a mechanistic model developed by us. The effects of target protein and impurities under the variation range of ±10 mAU·min^-1 on load amount, protein loss, process productivity, and resin capacity utilization were investigated. The results showed that the CaptureSMB process could be successfully controlled by AutoMAb towards increased or slightly decreased concentration of feedstock. However, the load process would be out of control with drastically decreased target protein or impurities, and the decreased impurities would lead to protein loss. It was found that AutoMAb control would cause 44.7% non-operational areas and 18.3% protein loss areas in the variation range of ±10 mAU·min^-1. To improve the stability of the CaptureSMB process, a modified AutoMAb control that would stop the load procedure when the absolute value of the integral area reached the preset value, was proposed to reduce the risk of protein loss and the non-operational area.

A series of BiOBr@biomass carbon derived from locust leaves materials (BiOBr@BC) were fabricated and the photocatalytic property was investigated for photocatalytic degradation of rhodamine B (RhB) under visible light. The morphology, structure and photoelectrochemical properties of the photocatalysts were characterized by means of SEM, TEM, XRD, XPS, FT-IR, BET, PL, UV-vis/DRS, and EIS techniques. The results showed that the introduction of BC significantly enhanced the photocatalytic activity. When the content of biomass carbon (BC) in a composite is 3% (based on the mass of BiOBr), the obtained BiOBr@BC-3 exhibits excellent photocatalytic activity, degrading 99% of RhB within 20 min. The excellent degradation efficiency after the introduction of BC can be attributed to the enhanced visible light absorption, narrower band gap, and fast electron-hole pair separation rate. The photocatalytic mechanism on the degradation of RhB was illustrated based on the radicals' trapping experiments and semiconductor energy band position. The proposed material is expected to be of significant application value in the field of wastewater treatment.

In order to find the optimal combination method of secondary utilization of fly ash and graphite-phase carbon nitride (g-C₃N₄) modification, an efficient composite photocatalyst of γ-Al₂O₃/g-C₃N₄ was obtained by calcining the composite precursors of Al(OH)₃/ dicyandiamide (DCDA). The introduction of Al(OH)₃ prepared by combining fly ash into the precursors causes hydrogen-bonding interactions between Al(OH)₃ and DCDA, which facilitate the removal of N atoms from the edges of the CN framework of g-C₃N₄ during condensation, and the composites prepared possess more cyano defects. In addition, γ-Al₂O₃ and g-C₃N₄ form a chemical bond at the interface, and this chemical bonding causes the density of the electron cloud in the vicinity of the N atoms to increase. Among them, the strongest chemical bonding between Al₂O₃ and g-C₃N₄ was observed in ACN-1, whereas the most cyanine defects were formed in ACN-1, which made ACN-1 exhibit the best photocatalytic degradation of methylene blue, which is 2.48 times higher than that of the pristine g-C₃N₄.

The gasification and combustion of activated fuels produced from fluidized beds are beneficial for achieving clean and efficient coal utilization. In this study, a high-calcium coal was used for the activation process, carried out in a high-temperature vertical fluidized bed. The carbon and ash characteristics of activated fuels were studied. The reactivity of activated fuels was characterized using Raman test, and scanning electron microscopy coupled with energy-dispersive spectrometry (SEM-EDS). Inorganic components were characterized using X-ray diffraction (XRD) and X-ray fluorescence spectrometry (XRF). With the increase in temperature and equivalence ratio (ER), the graphitization degree of activated fuels decreases, and a higher proportion of active sites leads to, a better activation effect. The activation effect is optimized at the equivalence ratio of 0.45. As the temperature rises, the calcium-containing minerals in the raw coal are gradually transformed into anorthite (CaAl₂SiO₇), and the anhydrite (CaSO₄) reacts with the reducing gas (CO) to produce oldhamite (CaS); Fe₂O₃, as a fluxing agent, is prone to melting with silica-aluminates at high temperature. As the particle size of activated fuel increased, the relative enrichment index (REI) of heavy metals decreased.

Dye pollution is a common pollutant in wastewater that poses a serious threat to human health. Layered double hydroxide (LDH) is a commonly used adsorbent for dye removal. However, its adsorption efficiency is significantly limited by the limited adsorption active sites of the adsorbent. In this paper, a defects-rich MgFe LDH adsorbent for anionic dye wastewater was synthesized by a simple hydrothermal method and alkaline etching. Different analytical techniques, such as XRD, FT-IR, SEM, TEM, XPS, and N₂ adsorption-desorption isotherm, were used to verify the chemical composition and surface characteristics of the materials, and the effects of pH, temperature, and contact time on the adsorption effect of methyl orange and the adsorption mechanism were analyzed. Alkaline etching of Al and Zn in the laminate generated defects that expose unsaturated coordination centers and create abundant adsorption sites, which can electrostatically attract and coordinate with dye ions. At 25 °C, the adsorption capacity of MgFe LDH with Al etched and MgFe LDH with Zn etched for methyl orange dye reached 1722 mg·g^-1 and 1685 mg·g^-1, respectively, much higher than that of MgFe LDH (544 mg·g^-1). This work provides a promising method for the removal of dye wastewater by adsorption and a new idea for the design and development of high-performance dye wastewater adsorbents.

Photosynthetic cyanobacteria have shown great potential as “autotrophic cell factories” for the synthesis of fuels and chemicals. However, poor tolerance to various environmental stressors such as high light and heavy metals is an important factor limiting their economic viability. While numerous studies have focused on the tolerance mechanism of cyanobacteria to individual stressors, their response to simultaneous stresses remains to be recovered. To investigate the mechanism of cross tolerance to heavy-metal Cd²⁺ and high light, the model cyanobacterium Synechocystis sp. PCC 6803 tolerant to both Cd²⁺ and high light was obtained via about 800 days’ cross-adaptive laboratory evolution. Three evolutionary strains capable of tolerating both 5.5 μmol·L^-1 Cd²⁺ and 600 μmol·m^-2·s^-1 high light were successfully obtained, achieving about 83% enhancement of Cd²⁺ tolerance compared with the parent strain. The different response of parent and evolutionary strains to Cd²⁺ was elucidated via metabolomics. Furthermore, a total of 15 genes that were mutated during evolution were identified by whole-genome re-sequencing. Finally, by single-gene knockout and complementation analysis, four genes including ssl2615, sll1732, ssr1480, and sll1659 involved in the improvement of Cd²⁺ tolerance under high-light condition were successfully identified. This work explored the tolerance mechanism of Synechocystis sp. PCC 6803 to cadmium under high-light condition and provided valuable reference for deciphering multi-tolerance mechanism of cyanobacteria in the future.

The isobaric energy recovery device can significantly reduce the energy consumption of the seawater reverse osmosis system by recycling the residual pressure energy of high-pressure concentrated brine. Three-cylinder valve-controlled energy recovery device (TC-ERD) solves the fluid pulsation of traditional two-cylinder devices, but the use of a “liquid piston” exacerbates the mixing between brine and seawater. Herein, the evolutionary law of “liquid piston” and the relationship between volumetric mixing degree and operating conditions are explored. The results show that the “liquid piston” first axially expands and then gradually stabilizes, isolating the brine and seawater. Additionally, as long as the volume utilization ratio (U_R) of the pressure exchange cylinder remains constant, there will not be much difference in the volumetric mixing degree after stabilization of the “liquid piston” (V_m-max) regardless of changes in the processing capacity (Q) and cycle time (T₀). Therefore, the equation for V_m-max with respect to the operating parameters (Q, T₀) is derived, which can not only predict the V_m-max of the TC-ERD, but also provide an empirical reference for the design of other valve-controlled devices with “liquid piston”. When the V_m-max is 6%, the efficiency of the TC-ERD at design conditions (30 m³·h^-1, 5.0 MPa) is 97.53%.

DFT calculations have been performed to discover the mechanism for the synthesis of dimethyl adipate (DMA) by 1,3-butadiene (BD) dicarbonylation catalyzed by a complex consisting of palladium and a bidentate diphosphine ligand. The computational results indicate that BD dicarbonylation involves two catalytic stages with the same reaction mechanism including terminal alkenyl insertion, CO migratory insertion, and methanolysis. Four different reaction routes have been explored, the pathway yielding linear DMA has the lowest alkenyl C-H insertion barrier with an overall barrier of 13.4 kcal·mol^-1 (1 kcal·mol^-1 = 4.184 kJ·mol^-1). The regioselectivity of the BD dicarbonylation depends mainly on the barrier of the alkenyl insertion into the palladium-hydrogen complex site. The computations well reproduced the experimentally observed linear selectivity.

Graphene oxide (GO) filler containing diversified Nafion-based proton exchange membrane (PEM) is studied to know the unique physical and chemical properties and performances of PEM. Nafion-SPEEK 1%-GO 0.75% (NSG-0.75%) composite shows the highest proton conductivity of 0.327 S·cm^-1 at 90 °C and 100% RH (relative humidity) among all the PEM investigated. The descending order of significant proton conductivity is found as; Nafion-sPGO(1%) 0.306 S·cm^-1 > Nafion/ZIF-8@GO 0.280 S·cm^-1 > Nafion/PGO (2%) 0.277 S·cm^-1 > Nafion/GO-sulfur (3%) 0.232 S·cm^-1 > Nafion/GO-poly-SPM-co-PEGMEMA(1%) 0.229 S·cm^-1 > Nafion/Ce-sPGO(1%) 0.215 S·cm^-1. The proton conductivity, water uptake capacity and ion exchange capacity, hydration number, thermal and oxidative stability, mechanical integrity (tensile strength), maximum power, and current density are found to be increased while activation energy and fuel crossover show a decrement as GO or modified GO is incorporated in the Nafion matrix. Principal component analysis (PCA) predicted a significant correlation between the proton conductivity and the properties; the water uptake capacity, ion exchange capacity, hydration number, maximum power density, and maximum current density are 0.598%, 0.688%, 0.894%, 0.980%, and 0.852% accordingly. A multiple linear model equation of proton conductivity is defined with the parameters of water uptake capacity, ion exchange capacity, hydration number, maximum power density, and maximum current density whereas the regression coefficient is 0.9923.

A synergistic solvent extraction system comprising trioctylamine (TOA) and ligands with hydroxyl and carboxyl groups can efficiently recover boric acid (H₃BO₃) and separate boron isotopes. However, the structure of ligands might impact H₃BO₃ extraction, boron isotope separation, and solvent loss, which has not been thoroughly investigated. This study initially evaluated the influence of ligand's type, pK_a, and substituents on H₃BO₃ extraction efficiency, as well as the impact of the B₍₄₎-O structure (boron is bound to four oxygen atoms) in the organic phase on isotope separation efficiency. Subsequently, by synthesizing the highly hydrophobic 2-hydroxydodecanoic acid (HYA), the extraction performance and mechanism of the TOA/HYA system were investigated. The findings highlight the superior extraction efficiency when employing di-phenolic hydroxyl, phenolic hydroxyl + carbinol hydroxyl, and alcoholic hydroxyl + carboxyl ligands compared to phenolic hydroxyl + carboxyl, phenolic hydroxyl + ethanol hydroxyl, diol hydroxyl, and dicarboxylic ligands. The organic phase anion complex, exclusively comprising the B₍₄₎-O structure, enhances isotope separation effectiveness. The TOA/HYA system achieves an 80% single-stage extraction efficiency for H₃BO₃. H₃BO₃ and HYA are extracted into the organic phase at a ratio of 1:2, with the anion complex solely containing the B₍₄₎-O structure. This study paves the way for the construction of novel boric acid extraction and boron isotope separation systems.

The long hydrate induction time and limited gas-liquid contact area leads to slow hydrate formation rate and low water-hydrate conversion rate. Porous media are often used to promote hydrate formation because of their large specific surface area. Consequently, we used 3A molecular sieve as a water-carrying solid in this work, and investigated the dynamic renewal of the gas-liquid interface and its effect on hydrate formation. The formation kinetics of ethane hydrate was first measured in an aqueous molecular sieve system. Then the separation of (H₂+CH₄+C₂H₆+C₃H₈) gas mixture was conducted via hydrate formation. The results show that the formation rate and gas storage capacity of ethane hydrate can be greatly improved by using aqueous molecular sieve. Compared with a pure water system under the same temperature and pressure, aqueous molecular sieve has obvious advantages in separation effect and energy consumption for separating gas mixtures.

In this study, the fluid flow and mixing process in an impinging stream-rotating packed bed (IS-RPB) is simulated by using a new three-dimensional computational fluid dynamics model. Specifically, the gas-liquid flow is simulated by the Euler-Euler model, the hydrodynamics of the reactor is predicted by the RNG k-ε method, and the high-gravity environment is simulated by the sliding mesh model. The turbulent mass transfer process is characterized by the concentration variance $\overline{c^2}$ and its dissipation rate ε formulations, and therefore the turbulent mass diffusivity can be directly obtained. The simulated segregation index X_s is in agreement with our previous experimental results. The simulated results reveal that the fringe effect of IS can be offset by the end effect at the inner radius of RPB, so the investigation of the coupling mechanism between IS and RPB is critical to intensify the mixing process in IS-RPB.

The concentric internally heat-integrated distillation column (HIDiC) has advantages of low energy consumption and high thermodynamic efficiency. However, its drawbacks of limited heat transfer area, complex internal structure, and large number of control parameters hinder its widespread industrial applications. To solve these challenges, in this work a novel sleeve-like concentric heat-integrated separation column, namely temperature-controlled phase change column (TCPC), was developed to separate liquid mixtures in a more effective and energy-saving way with reflux section being moved and trays being replaced with spiral corrugation blades. The comprehensive performances of TCPC in ethanol-water system was firstly evaluated by experiments. The results showed that TCPC performs well in ethanol-water separation due to the internal spiral corrugation significantly reducing the vapor-liquid contact in separation section. Meanwhile, compared to the concentric HIDiC, TCPC has a higher total heat transfer coefficient due to the larger heat transfer area. Computational fluid dynamics simulation reveals the internal design of TCPC inducing secondary vortices of the vapor, enhancing condensation heat transfer and separation efficiency. Further, increasing the mass flow rate within a certain range would enhance the comprehensive performance factor and lead to more effective separation.

5-Hydroxymethylfurfural (5-HMF) is one of the important bio-based platform compounds, and the catalytic conversion of glucose to 5-HMF is a highly desirable approach that is receiving increasing attention. Herein, we reported the synthesis of lignin-derived carbon supported tin oxides (SnO/LC) catalyst via a two-step hydrothermal-pyrolytic method using wheat straw alkali lignin as a cost-effective carbon source with high carbon content. The key preparation conditions of the catalyst and its catalytic conditions for the conversion of glucose to 5-HMF were investigated, respectively. Results show that under the preparation conditions of tin tetrachloride dosage of 3.0 mmol and pyrolysis temperature of 500 ℃, the optimized catalyst (3.0-SnO/LC-500) with a high yield of 63.4% exhibits good catalytic performance of 5-HMF yield of 50.1% and reaction selectivity of 86.0% under the optimum conditions of reaction temperature and time of 190 ℃ and 3 h, initial glucose concentration of 10 %(mass), 3.0-SnO/LC-500 dosage of 100 mg in a biphasic solvent system of volume ratio of water to tetrahydrofuran of 1:4. In addition, 3.0-SnO/LC-500 exerts an excellent reusability in a five-cycle experiment. Furthermore, SnO/LC was characterized in detail using X-ray diffraction patterns (XRD), X-ray photoelectron spectroscopy (XPS), Brunauer-Emmett-Teller (BET), ammonia temperature-programmed-desorption (NH₃-TPD), pyridine adsorption infrared spectroscopy (Py-FTIR), scanning electron microscope (SEM) and thermal gravimetric analysis (TGA). Results indicate that Brønsted acid sites and Lewis acid sites coexist on 3.0-SnO/LC-500, and more Sn⁴⁺, as well as a proper ratio of weak acidity to medium acidity, are conductive to its catalytic performance in glucose-to-5-HMF reaction.

Bimetallic CuCo catalysts with different Cu to Co ratios on N-doped porous carbon materials (N-C) were achieved using impregnation method and applied in the hydrogenation of furfural (FAL) to furfuryl alcohol (FOL). The high hydrogenation activity of FAL over Cu₁Co₁/N-C was originated from the synergistic interactions of Cu and Co species, where Co⁰ and Cu⁰ simultaneously adsorb and activate H₂, and Cu⁺ served as Lewis acid sites to activate C＝O. Meanwhile, electrons transfer from Cu to Co promoted the formation of Cu⁺. In situ Fourier transform infrared spectroscopy analysis indicated that Cu₁Co₁/N-C adsorbed FAL with a tilted η¹-(O) configuration. The superior Cu₁Co₁/N-C showed excellent adsorbed ability towards H₂ and FAL, but weak adsorption for FOL. Therefore, Cu₁Co₁/N-C possessed 93.1% FAL conversion and 99.0% FOL selectivity after 5 h reaction, which also exhibited satisfactory reusability in FAL hydrogenation for five cycles.

The distribution of adsorbent particle sizes typically has a significant impact on adsorption performance. Most fixed-bed adsorption studies adopt the assumption of average particle size to simplify the adsorption model, but this does not eliminate the deviation between experiments and simulations caused by particle size distribution in practice. In this study, the population balance equation (PBE) and fixed-bed adsorption kinetics model were combined to simulate the adsorption process in a fixed-bed reactor, modeling the distribution of adsorbate uptake over time on adsorbent particles of different sizes. We integrated and optimized the PBE and fixed-bed mass transfer model in the algorithm, and the resulting combined model adopts a variable time step size, which can achieve a balance between computational efficiency and error while ensuring computational convergence. By slicing the model in the spatial dimension, multiple sets of PBE can be calculated in parallel, improving computational efficiency. The adsorption process of single-component and multi-component CO₂/CH₄/N₂ on 4A zeolite without binder was simulated, and the influence of adsorbent particle size distribution was analyzed. Simulation results show that the assumption of average adsorbent particle size, which was commonly made in published work, will underestimate the time required for adsorbates to break through the fixed bed compared with the assumption of uniform adsorbent particle size. This model helps to consider the impact of adsorbent particle size distribution on the adsorption process, thereby improving the prediction accuracy of adsorbent performance.

The rising motion of single bubble in still liquid is a natural phenomenon, which has high theoretical research significance and engineering application prospect. Experimental observations and numerical simulations for prediction of the rising trajectory of a single bubble in still liquid are being carried out, while the concise but accurate theoretical or mechanism model is still not well developed. In this article, a theoretical model of a single bubble based on experimental observation of flow around bluff body is proposed to predict the rising trajectory of zigzagging bubbles in still water. The prediction correlation of bubble lateral movement frequency and bubble steer angle are established based on three degrees of freedom frame. The model has achieved good trajectory prediction effect in the bubble rising experiment. The average simulation time per unit moving time of bubble is 2.5 s.

The selection of chemical reactions is directly related to the quality of synthesis pathways, so a reasonable reaction evaluation metric plays a crucial role in the design and planning of synthesis pathways. Since reaction conditions also need to be considered in synthesis pathway design, a reaction metric that combines reaction time, temperature, and yield is required for chemical reactions of different reaction agents. In this study, a chemical reaction graph descriptor which includes the atom-atom mapping relationship is proposed to effectively describe reactions. Then, through pre-training using graph contrastive learning and fine-tuning through supervised learning, we establish a model for generating the probability of reaction superiority (RSscore). Finally, to validate the effectiveness of the current evaluation index, RSscore is applied in two applications, namely reaction evaluation and synthesis routes analysis, which proves that the RSscore provides an important agents-considered evaluation criterion for computer-aided synthesis planning (CASP).

Hydroxylation of inert benzene through the activation of the C_sp2-H bond is a representative reaction about the transformation of C-H bonds to C-O bonds, which has far-reaching guiding significance but remains a challenging scientific problem. To overcome this problem, a series of VO-Ga₂O₃/SiO₂-Al₂O₃ were prepared to achieve an efficient and economical hydroxylation path of benzene to phenol. The results showed that the phenol yield was 72.89% (selectivity > 98.1%) under the optimum conditions. The reason is that the C-H bond in the benzene ring is activated by heterolysis over a VO-Ga₂O₃/SiO₂-Al₂O₃ catalyst. Meanwhile, the introduction of aluminum (Al) and gallium (Ga) made a qualitative change in the catalyst, enhancing the electron motion and spin motion of vanadium species, resulting in the increase of V⁴⁺/V⁵⁺ ratio. In addition, the catalyst can provide an optimal acidic environment and a three-dimensional cross-linked surface structure that facilitates product diffusion.

The optimization of process parameters in polyolefin production can bring significant economic benefits to the factory. However, due to small data sets, high costs associated with parameter verification cycles, and difficulty in establishing an optimization model, the optimization process is often restricted. To address this issue, we propose using a transfer learning Bayesian optimization strategy to improve the efficiency of parameter optimization while minimizing resource consumption. Specifically, we leverage Gaussian process (GP) regression models to establish an integrated model that incorporates both source and target grade production task data. We then measure the similarity weights of each model by comparing their predicted trends, and utilize these weights to accelerate the solution of optimal process parameters for producing target polyolefin grades. In order to enhance the accuracy of our approach, we acknowledge that measuring similarity in a global search space may not effectively capture local similarity characteristics. Therefore, we propose a novel method for transfer learning optimization that operates within a local space (LSTL-PBO). This method employs partial data acquired through random sampling from the target task data and utilizes Bayesian optimization techniques for model establishment. By focusing on a local search space, we aim to better discern and leverage the inherent similarities between source tasks and the target task. Additionally, we incorporate a parallel concept into our method to address multiple local search spaces simultaneously. By doing so, we can explore different regions of the parameter space in parallel, thereby increasing the chances of finding optimal process parameters. This localized approach allows us to improve the precision and effectiveness of our optimization process. The performance of our method is validated through experiments on benchmark problems, and we discuss the sensitivity of its hyperparameters. The results show that our proposed method can significantly improve the efficiency of process parameter optimization, reduce the dependence on source tasks, and enhance the method's robustness. This has great potential for optimizing processes in industrial environments.

The characterization of a particle ensemble (rather than a single particle) is of paramount significance to various particle technologies and has long been a fundamental subject in the fluidization realm. However, many of such bulk characterizations as loosely-packed density (ρ_bl), minimum fluidization velocity (U_mf), sphericity (φ), discharge rate through orifice (q), angle of repose (β), and segregation index (S), were found to be poorly reproducible, making the reported results seldom comparable. Since these bulk characterizations started from the packed state of particles, such poor reproducibility was ascribed to the polymorphism of packed particles in this work. We observed that in the fluidized bed, the settled/packed state of particles varied monotonously with the settling rate (α) from complete fluidization to zero. This phenomenon confirmed the polymorphic characteristic of packed particles and further enabled us to systematically disclose/clarify its influences on the aforementioned bulk characterizations. Such influences could be comprehensively and intuitively reflected by the impacts induced by α. With the decrease of α, ρ_bl, φ and q first increased, then decreased, and finally leveled off while U_mf and β showed an opposite trend. On the other hand, S first increased and then remained invariant. As per these findings and definitions of these bulk characterizations, benchmarks were indicated to unify the selection of settled state among future scholars and further make their outcomes become fairly comparable. Additionally, most packed states of the particle ensemble were proved to be metastable with their formation and behavior being identical to those of the amorphous state.

In this work, we utilize a cocrystallization technique to solve the problem of high hygroscopicity of the high-energy oxidant ammonium dinitramide (ADN). For this purpose, a non-hygroscopic oxidant, triaminoguanidine nitrate (TAGN), is selected as the cocrystallization ligand. The ADN/TAGN system is simulated by using Material Studio 5.5 software, and the DFT of ADN and TAGN molecules are calculated by Gaussian09 software. The most stable molar ratio of the ADN/TAGN cocrystallization is determined to be 1:1, and the hydrogen bonding between the H atom of ADN and the O atom in the TAGN is the driving force for the formation of cocrystals in this system. Moreover, the electrostatic potential interaction pairing energy difference (△E_pair) < 0 kJ·mol^-1 (-12.71 kJ·mol^-1) for n_ADN:n_TAGN = 1:1 again indicates cocrystallization at this molar ratio. The crystal structure and crystal morphology is predicted. And the hygroscopicity of ADN/TAGN cocrystal at 20 °C and 40% relative humidity is calculated to be only 0.45%. The mechanism of hygroscopicity is investigated by examining the roughness of each crystal surface. Overall, the more hygroscopic it is in terms of surface roughness, with the roughest crystal surface (0 1 $\overline{2}$) having a hygroscopicity of 1.78, which corresponds to a saturated hygroscopicity of 0.61%. The results show that the (0 0 1) crystal surface has the smallest band gap (1.06 eV) and the largest sensitivity. Finally, the oxygen equilibrium value for the ADN/TAGN system is calculated to be -8.2%.

The urgent need to mitigate climate change impacts and achieve net zero emissions has led to extensive research on carbon dioxide (CO₂)-capture technologies. This study focuses on the kinetics of CO₂ capture using solid adsorbents specifically through thermal gravimetric analysis (TGA). The research explores the principles behind TGA and its application in analyzing adsorbent performance and the significance of kinetics in optimizing CO₂-capture processes. Solid adsorbents have gained significant attention due to their potential for efficient and cost-effective CO₂ capture. Therefore, three different types of adsorbents, namely calcium-, tin-, and zirconium-based ones (quicklime: CaO, potassium stannate: K₂SnO₃, and sodium zirconate: Na₂ZrO₃), in adsorbing high-temperature carbon dioxide were investigated; their quality and performance by various factors such as price, stability, non-toxicity, and efficiency are different. The diffusion models and geometrical contraction models were the best-fitted models to explain the kinetic of these solid adsorbents for high-temperature CO₂ sorption; it means the morphology is important for solid adsorbent performance. The minimum energy needed to start a reaction for K₂SnO₃, Na₂ZrO₃, and CaO, is 73.55, 84.33, and 86.23 kJ·mol^-1, respectively; with the lowest value being for potassium stannate. The high-temperature CO₂ adsorption performance of various solid adsorbents in regard with the rate of reaction followed the order of K₂SnO₃ > CaO >> Na₂ZrO₃, based on experiments and kinetic studies.

Two-dimensional (2D) catalytic ozonation membranes are promising for the treatment of micropollutants in wastewater due to simultaneous ozone-catalyzed degradation and membrane filtration processes. However, it remains challenging for 2D catalytic ozonation membranes to efficiently degrade micropollutants due to low mass-transfer efficiency and poor catalytic activity. Herein, Fe/Mn bimetallic metal-organic framework (MOF) intercalated lamellar MnO₂ membranes with fast and robust ozone-catalyzed mass-transfer channels were developed on the surface of the hollow fiber ceramic membrane (HFCM) to obtain 2D Fe/Mn-MOF@MnO₂-HFCM for efficiently degrading micropollutants in wastewater. The intercalation of Fe/Mn-MOF expanded the interlayer spacing of the MnO₂ membrane, thereby providing abundant transport channels for rapid passage of water. More notably, the Fe/Mn-MOF provided enriched reactive sites as well as high electron transfer efficiency based on the redox cycling between Mn³⁺/Mn⁴⁺ and Fe²⁺/Fe³⁺, ensuring the effective catalytic oxidative degradation of micropollutants including tetracycline hydrochloride (TCH), methylene blue, and methyl blue. Moreover, the carboxyl groups on the MOF formed covalent bonds (-COO-) with the hydroxyl groups in MnO₂ between layers, which increased the interaction between MnO₂ nanosheets to form stable interlayer channels. Specifically, the optimal composite membrane achieved a high removal rate of TCH micropollutant (93.4%), high water treatment capacity (282 L·m^-2·h^-1·MPa^-1), and excellent long-term stability (1200 min). This study provides a simple and easily scalable strategy to construct fast, efficient, and stable 2D catalytic mass-transfer channels for the efficient treatment of micropollutants in wastewater.

The widespread use of pesticides has caused serious harm to ecosystems, necessitating effective and environmentally friendly treatment methods. Bioremediation stands out as a promising approach for pollutant treatment, wherein the metabolic activities of microorganisms can transform toxic pesticides into compounds with lower or no toxicity. In this study, we obtained eight pesticide-degrading strains from pesticide-contaminated sites through continuous enrichment and screening. Four highly efficient pesticide-degrading strains (degradation ratios exceeding 80%) were identified. Among them, Pseudomonas sp. BL5 exhibited the strongest growth (exceeding 10⁹ CFU·ml^-1) and outstanding degradation of benzene derivatives and chlorinated hydrocarbons at both laboratory and pilot scales, with degradation ratios exceeding 98% and 99.6%, respectively. This research provides new tools and insights for the bioremediation of pesticide-related pollutants.

In recent years, the integration of stochastic techniques, especially those based on artificial neural networks, has emerged as a pivotal advancement in the field of computational fluid dynamics. These techniques offer a powerful framework for the analysis of complex fluid flow phenomena and address the uncertainties inherent in fluid dynamics systems. Following this trend, the current investigation portrays the design and construction of an important technique named swarming optimized neuro-heuristic intelligence with the competency of artificial neural networks to analyze nonlinear viscoelastic magneto-hydrodynamic Prandtl-Eyring fluid flow model, with diffusive magnetic layers effect along an extended sheet. The currently designed computational technique is established using inverse multiquadric radial basis activation function through the hybridization of a well-known global searching technique of particle swarm optimization and sequential quadratic programming, a technique capable of rapid convergence locally. The most appropriate scaling group involved transformations that are implemented on governing equations of the suggested fluidic model to convert it from a system of nonlinear partial differential equations into a dimensionless form of a third-order nonlinear ordinary differential equation. The transformed/reduced fluid flow model is solved for sundry variations of physical quantities using the designed scheme and outcomes are matched consistently with Adam's numerical technique with negligible magnitude of absolute errors and mean square errors. Moreover, it is revealed that the velocity of the fluid depreciates in the presence of a strong magnetic field effect. The efficacy of the designed solver is depicted evidently through rigorous statistical observations via exhaustive numerical experimentation of the fluidic problem.

Sodium hypochlorite and synthesized sodium trititanate nanorods (Na₂Ti₃O₇, 186 nm×1270 nm) were used as the oxidant and adsorbents for in situ oxidative adsorption treatment of actual electroplating wastewater containing Cr(VI) (2.6-5.2 mg·L^-1), Cu²⁺ (2.7-5.4 mg·L^-1), and Ni²⁺ (0.2705-0.541 mg·L^-1) ions at pH of 8.8-9.1 and 20-60 ℃. The as-synthesized sodium trititanate nanorods were characterized by XRD, HRTEM, N₂ adsorption/desorption, SEM, EDX, and zeta potential techniques. The concentrations of heavy metal ions in wastewater were analyzed by ICP technique. After in situ oxidative adsorption treatment under the concentrations of 25 g·L^-1 for sodium hypochlorite and 125 mg·L^-1 for sodium trititanate nanorods at 60 ℃ for 5 h, the heavy metal ion concentrations could be reduced from initial value of 2.6 to final value of 1.92 mg·L^-1 for Cr(VI), 3.6 to 0.17 mg·L^-1 for Cu²⁺, and from 0.2705 to 0.097 mg·L^-1 for Ni²⁺, respectively. Cr(VI), Cu²⁺ and Ni²⁺ ions could be effectively removed by the in situ oxidative adsorption method. The in situ oxidative adsorption processes of Cr(VI), Cu²⁺ and Ni²⁺ ions are satisfactorily simulated by the pseudo-second order adsorption kinetics and Langmuir adsorption isotherm, respectively. Adsorption thermodynamics analyses reveal that the oxidative adsorption processes of Cr(VI), Cu²⁺ and Ni²⁺ ions are spontaneous and endothermic. The oxidation degree of metal-contained complexes influences the values of thermodynamics functions.