Rational Design of Highly Porous Donor-Acceptor Based Conjugated Microporous Polymer for Photocatalytic Benzylamine Coupling Reaction.

Conjugated microporous polymers (CMPs) are an important class of organic materials with several useful features like, inherent nanoscale porosity, large specific surface area and semiconducting properties, which are very demanding for various sustainable applications. Carbazole building blocks are extensively used in designing photocatalysts due to easy electron donation and hole transportation. In the current study, a new CMP material CBZ-CMP containing carbazole unit used for photocatalytic C═N coupling reaction under blue light irradiation is designed. The CBZ-CMP framework is made through the polycondensation of 4,4'-di(9H-carbazol-9-yl)-1,1'-biphenyl using FeCl3 as a catalyst. The CBZ-CMP shows very high BET surface area of 1536 m2 g-1 together with unimodal porosity (ca. 1.7 nm supermicropore), nanowire-like particle morphology (16-18 nm diameter), and low band gap property. The bi-phenyl moiety functions as the electron accepting center and the carbazole unit acts as the donor center, which accounts for the low band gap energy of CBZ-CMP. This nanoporous semiconducting CBZ-CMP material for photocatalytic benzylamine coupling reaction is explored, where it shows good conversion together with high selectivity under mild reaction conditions. This study offers simple method of preparation of a D-A-D-based porous photocatalyst for sustainable synthesis of value-added organics.

Effect of Nano-Zinc Oxide, Rice Straw Compost, and Gypsum on Wheat (Triticum aestivum L.) Yield and Soil Quality in Saline-Sodic Soil.

The salinity and alkalinity of soils are two fundamental factors that limit plant growth and productivity. For that reason, a field study conducted at Sakha Agric. Res. Station in Egypt during the 2022-2023 winter season aimed to assess the impact of gypsum (G), compost (C), and zinc foliar application in two images, traditional (Z1 as ZnSO4) and nanoform (Z2 as N-ZnO), on alleviating the saline-sodic conditions of the soil and its impact on wheat productivity. The results showed that the combination of gypsum, compost, and N-ZnO foliar spray (G + C + Z2) decreased the soil electrical conductivity (EC), sodium adsorption ratio (SAR), and exchangeable sodium percentage (ESP) by 14.81%, 40.60%, and 35.10%, respectively. Additionally, compared to the control, the G + C + Z2 treatment showed improved nutrient content and uptake as well as superior wheat biomass parameters, such as the highest grain yield (7.07 Mg ha-1), plant height (98.0 cm), 1000-grain weight (57.03 g), and straw yield (9.93 Mg ha-1). Interestingly, foliar application of N-ZnO was more effective than ZnSO4 in promoting wheat productivity. Principal component analysis highlighted a negative correlation between increased grain yield and the soil EC and SAR, whereas the soil organic matter (OM), infiltration rate (IR), and plant nutrient content were found to be positively correlated. Furthermore, employing the k-nearest neighbors technique, it was predicted that the wheat grain yield would rise to 7.25 t ha-1 under certain soil parameters, such as EC (5.54 dS m-1), ESP (10.02%), OM (1.41%), bulk density (1.30 g cm-3), infiltration rate (1.15 cm h-1), and SAR (7.80%). These results demonstrate how adding compost and gypsum to foliar N-ZnO can improve the soil quality, increase the wheat yield, and improve the nutrient uptake, all of which can support sustainable agriculture.

Nano silica-mediated stabilization of heavy metals in contaminated soils.

Soil contamination with heavy metals presents a substantial environmental peril, necessitating the exploration of innovative remediation approaches. This research aimed to investigate the efficiency of nano-silica in stabilizing heavy metals in a calcareous heavy metal-contaminated soil. The soil was treated with five nano-silica levels of 0, 100, 200, 500, and 1000 mg/kg and incubated for two months. The results showed that nano-silica had a specific surface area of 179.68  m 2 / g . At 1000 mg/kg, the DTPA-extractable concentrations of Pb, Zn, Cu, Ni, and Cr decreased by 12%, 11%, 11.6%, 10%, and 9.5% compared to the controls, respectively. Additionally, as the nano-silica application rate increased, both soil pH and specific surface area increased. The augmentation of nano-silica adsorbent in the soil led to a decline in the exchangeable (EX) and carbonate-bound fractions of Pb, Cu, Zn, Ni, and Cr, while the distribution of heavy metals in fractions bonded with Fe-Mn oxides, organic matter, and residue increased. The use of 1000 mg/kg nano-silica resulted in an 8.0% reduction in EX Pb, 4.5% in EX Cu, 7.3% in EX Zn, 7.1% in EX Ni, and 7.9% in EX Cr compared to the control treatment. Overall, our study highlights the potential of nano silica as a promising remediation strategy for addressing heavy metal pollution in contaminated soils, offering sustainable solutions for environmental restoration and ecosystem protection.

Preparation of Hierarchical Porous Monoliths With High Surface Areas by a Solvent Knitting Strategy.

Hierarchical porous hypercrosslinked monoliths (PolyHIPE-HCP) with ultrahigh specific surface areas are prepared via a solvent knitting strategy. Compared to previous work, the solvent knitting strategy is carried out in a relatively low air-controlled atmosphere with gradient heating starting from low temperature while using DCM (Dichloromethane) as both a solvent and a cross-linker, allowing for a slow and controlled cross-linking process, thereby achieving a BET surface area ranging from 514 to 728 m2 g-1. Scanning electron microscopy (SEM) shows that the knitting process does not affect the presence of macroporous structure in the PolyHIPE. With the introduction of mesopores and micropores, these hierarchical porous monoliths exhibit significant potential for applications in gas adsorption and water treatment. Hence, a universal, simple and low-cost method to synthesize polymeric monoliths with hierarchically porous structure and higher surface area is proposed, which has fascinating prospects in industrialization.

Adsorption of Bichromate and Arsenate Anions by a Sorbent Based on Bentonite Clay Modified with Polyhydroxocations of Iron and Aluminum by the "Co-Precipitation" Method.

The physicochemical properties of natural bentonite and its sorbents were studied. It has been established the modification of natural bentonites using polyhydroxoxides of iron (III) (mod.1_Fe_5-c) and aluminum (III) (mod.1_Al_5-c) by the "co-precipitation" method led to changes in their chemical composition, structure, and sorption properties. It was shown that modified sorbents based on natural bentonite are finely porous (nanostructured) objects with a predominance of pores of 1.5-8.0 nm in size. The modification of bentonite with iron (III) and aluminum compounds by the "co-precipitation" method also leads to an increase in the sorption capacity of the obtained sorbents with respect to bichromate and arsenate anions. A kinetic analysis showed that, at the initial stage, the sorption process was controlled by an external diffusion factor, that is, the diffusion of the sorbent from the solution to the liquid film on the surface of the sorbent. The sorption process then began to proceed in a mixed diffusion mode when it limited both the external diffusion factor and the intra-diffusion factor (diffusion of the sorbent to the active centers through the system of pores and capillaries). To clarify the contribution of the chemical stage to the rate of adsorption of bichromate and arsenate anions by the sorbents under study, kinetic curves were processed using equations of chemical kinetics (pseudo-first-order, pseudo-second-order, and Elovich models). It was found that the adsorption of the studied anions by the modified sorbents based on natural bentonite was best described by a pseudo-second-order kinetic model. The high value of the correlation coefficient for the Elovich model (R2 > 0.9) allows us to conclude that there are structural disorders in the porous system of the studied sorbents, and their surfaces can be considered heterogeneous. Considering that heterogeneous processes occur on the surface of the sorbent, it is natural that all surface properties (structure, chemical composition of the surface layer, etc.) play an important role in anion adsorption.

Conversion of high moisture biomass to hierarchical porous carbon via molten base carbonisation and activation for electrochemical double layer capacitor.

Biomass-derived carbon for supercapacitors faces the challenge of achieving hierarchical porous carbon with graphitic structure and specific heteroatoms through a single-stage thermal process that minimises resource input. Herein, molten base carbonisation and activation is proposed. The process utilises the inherent moisture of Moso bamboo shoots, coupled with a low amount of KOH, to form potassium organic salts before drying. The resultant potassium salts promote in-situ activation during single-stage heating process, yielding hierarchical porous, large specific surface area, and partially graphitised carbon with heteroatoms (N, O). As an electrode material, this carbon exhibits a specific capacitance of 327F g-1 in 6 M KOH and 182F g-1 in 1 M TEABF4/AN, demonstrating excellent cycling stability over 10,000 cycles at 2 A/g. Overall, this study presents a straightforward process that avoids pre-drying of biomass, minimises base consumption, and employs single-stage heating to fabricate electrode carbon suitable for supercapacitors.

Determination of specific surface area of biomass activated carbon vial headspace gas chromatography technique.

This paper introduces a method for determining the specific surface area (SSA) of biomass activated carbon (BAC) using a tracer-based headspace gas chromatography (HS-GC) technique. The method relies on the adsorption equilibrium of methanol on BAC samples at elevated temperature. A mathematical model allows for the calculation of SSA from the methanol signal obtained during the headspace analysis. The results demonstrate high precision (relative standard deviation < 2.44%) and strong accuracy (correlation with the conventional BET-N2 adsorption method, R² = 0.986). This method offers several advantages over traditional techniques, including ease of operation, significant time efficiency, and the the ability to perform batch determinations of SSA, as multiple samples can be processed simultaneously during the phase equilibrium step.

A Novel Approach for Preparing Sepiolite Micron Powder Based on Steam Pressure Changes.

As a common method for preparing micron powder in industrial operations, the mechanical extrusion method simply pursues the particle size without considering the microstructure characteristics of sepiolite, which leads to problems such as bundles of sepiolite not being effectively dispersed, and thus the disruption of fibers is inevitably caused. In this work, a new micronization method for disaggregating these bundles while preserving the original structural integrity of the fibers is proposed based on steam pressure changes. The effects of steam pressure changes on the particle size distribution, microstructure, and properties of treated sepiolite are studied using X-ray fluorescence spectrometer (XRF), X-ray diffractometer (XRD), Field Emission Scanning Electron Microscopy (FESEM), Transmission Electron Microscopy (TEM), and a specific surface area and aperture analyzer (BET). The experimental results show that the particle size of sepiolite powder depends greatly on steam pressure, and sepiolite powder with mass ratio of 91.6% and a particle size D97 of 21.27 µm is obtained at a steam pressure of 0.6 MPa. Compared to the sepiolite after mechanical extrusion, the sepiolite treated with steam pressure changes can maintain the integrity of its crystalline structure. The specific surface area of sepiolite enhanced from 80.15 m2 g-1 to 141.63 m2 g-1 as the steam pressure increased from 0.1 to 0.6 MPa, which is about 1.6 times that of the sample treated with mechanical extrusion.

Investigation of the Compressive Strength and Void Analysis of Cement Pastes with Superabsorbent Polymer.

This study aimed to experimentally investigate the compressive strength and air voids of cement pastes with varying dosages of Superabsorbent Polymer (SAP) and water-to-cement (w/c) ratios. Cement pastes were prepared using three different w/c ratios of 0.4, 0.5, and 0.6, along with different dosages of SAP ranging from 0.2% to 0.5% by weight of cement. Additionally, SAP was introduced in two forms: dry and wet. After casting the cubes, two distinct curing conditions were employed: curing at a temperature of 20 °C with a Relative Humidity (RH) of 60% (Curing 1), and water curing (Curing 2). The results revealed that the addition of SAP increased early strength when subjected to Curing 1, followed by a decrease in later strength. On the other hand, samples with SAP and water curing exhibited higher strength compared to those without SAP, especially with w/c ratios of 0.4 and 0.5. However, at a w/c ratio of 0.6, nearly all samples showed a reduction in strength compared to those without SAP. Furthermore, air void analysis was performed on all samples cured for 28 days using an image analysis technique. The samples containing wet SAP resulted in a higher total air content compared to the samples with dry SAP. Additionally, the incorporation of wet SAP in cement paste led to lower specific surface areas and a higher spacing factor than the samples with dry SAP. These findings suggest that the clumping of wet SAP particles during presoaking resulted in coarser air voids compared to the samples containing dry SAP.

Predicting and refining acid modifications of biochar based on machine learning and bibliometric analysis: Specific surface area, average pore size, and total pore volume.

Acid-modified biochar is a modified biochar material with convenient preparation, high specific surface area, and rich pore structure. It has great potential for application in the heavy metal remediation, soil amendments, and carrying catalysts. Specific surface area (SSA), average pore size (APS), and total pore volume (TPV) are the key properties that determine its adsorption capacity, reactivity, and water holding capacity, and an intensive study of these properties is essential to optimize the performance of biochar. But the complex interactions among the preparation conditions obstruct finding the optimal modification strategy. This study collected dataset through bibliometric analysis and used four typical machine learning models to predict the SSA, APS, and TPV of acid-modified biochar. The results showed that the extreme gradient boosting (XGB) was optimal for the test results (SSA R2 = 0.92, APS R2 = 0.87, TPV R2 = 0.96). The model interpretation revealed that the modification conditions were the major factors affecting SSA and TPV, and the pyrolysis conditions were the major factors affecting APS. Based on the XGB model, the modification conditions of biochar were optimized, which revealed the ideal preparation conditions for producing the optimal biochar (SSA = 727.02 m2/g, APS = 5.34 nm, TPV = 0.68 cm3/g). Moreover, the biochar produced under specific conditions verified the generalization ability of the XGB model (R2 = 0.99, RMSE = 12.355). This study provides guidance for optimizing the preparation strategy of acid-modified biochar and promotes its potentiality for industrial application.

Enhancing the properties of swelling soils with lime, fly ash, and expanded polystyrene -A review.

This paper discusses efforts made by past researchers to steady the expansive (problematic) soils using mechanical and chemical techniques - specifically with EPS beads, lime and fly ash. Administering swelling of problematic soils is critical for civil engineers to prevent structural distress. This paper summarizes studies on reduction of swelling potential using EPS, lime and fly ash individually. Chemical stabilization with lime and fly ash are conventional methods for expansive soil stabilization, with known merits and demerits. This paper explores the suitability of different materials under various conditions and stabilization mechanisms, including cation exchange, flocculation, and pozzolanic reactions. The degree of stabilization is influenced by various factors such as the type and amount of additives, soil mineralogy, curing temperature, moisture content during molding, and the presence of nano-silica, organic matter, and sulfates. Additionally, expanded polystyrene (EPS) improves structural integrity by compressing when surrounded clay swells, reducing overall swelling. Thus, EPS addresses limitations of chemicals by mechanical means. Combining EPS, lime and fly ash creates a customized system promoting efficient, long-lasting, cost-effective and eco-friendly soil stabilization. Chemicals address EPS limitations like poor stabilization. This paper benefits civil engineers seeking to control expansive soil swelling and prevent structural distress. It indicates potential of an EPS-lime-fly ash system and concludes by identifying research gaps for further work on such combinatorial stabilizer systems.

AI-assisted deep learning segmentation and quantitative analysis of X-ray microtomography data from biomass ashes.

X-ray microtomography is a non-destructive method that allows for detailed three-dimensional visualisation of the internal microstructure of materials. In the context of using phosphorus-rich residual streams in combustion for further ash recycling, physical properties of ash particles can play a crucial role in ensuring effective nutrient return and sustainable practices. In previous work, parameters such as surface area, porosity, and pore size distribution, were determined for ash particles. However, the image analysis involved binary segmentation followed by time-consuming manual corrections. The current work presents a method to implement deep learning segmentation and an approach for quantitative analysis of morphology, porosity, and internal microstructure. Deep learning segmentation was applied to microtomography data. The model, with U-Net architecture, was trained using manual input and algorithm prediction.•The trained and validated deep learning model could accurately segment material (ash) and air (pores and background) for these heterogeneous particles.•Quantitative analysis was performed for the segmented data on porosity, open pore volume, pore size distribution, sphericity, particle wall thickness and specific surface area.•Material features with similar intensities but different patterns, intensity variations in the background and artefacts could not be separated by manual segmentation - this challenge was resolved using the deep learning approach.

Effect of Thermal Activation on the Structure and Electrochemical Properties of Carbon Material Obtained from Walnut Shells.

A simple activation method has been used to obtain porous carbon material from walnut shells. The effect of the activation duration at 400 °C in an atmosphere with limited air access on the structural, morphological, and electrochemical properties of the porous carbon material obtained from walnut shells has been studied. Moreover, the structure and morphology of the original and activated carbon samples have been characterized by SAXS, low-temperature adsorption porosimetry, SEM, and Raman spectroscopy. Therefore, the results indicate that increasing the duration of activation at a constant temperature results in a reduction in the thickness values of interplanar spacing (d002) in a range of 0.38-0.36 nm and lateral dimensions of the graphite crystallite from 3.79 to 2.52 nm. It has been demonstrated that thermal activation allows for an approximate doubling of the specific SBET surface area of the original carbon material and contributes to the development of its mesoporous structure, with a relative mesopore content of approximately 75-78% and an average pore diameter of about 5 nm. The fractal dimension of the obtained carbon materials was calculated using the Frenkel-Halsey-Hill method; it shows that its values for thermally activated samples (2.52, 2.69) are significantly higher than for the original sample (2.17). Thus, the porous carbon materials obtained were used to fabricate electrodes for electrochemical capacitors. Electrochemical investigations of these cells in a 6 M KOH aqueous electrolyte were conducted by cyclic voltammetry, galvanostatic charge/discharge, and impedance spectroscopy. Consequently, it was established that the carbon material activated at 400 °C for 2 h exhibits a specific capacity of approximately 110-130 F/g at a discharge current density ranging from 4 to 100 mA/g.

Accelerated Design for Perovskite-Oxide-Based Photocatalysts Using Machine Learning Techniques.

The rapid discovery of photocatalysts with desired performance among tens of thousands of potential perovskites represents a significant advancement. To expedite the design of perovskite-oxide-based photocatalysts, we developed a model of ABO3-type perovskites using machine learning methods based on atomic and experimental parameters. This model can be used to predict specific surface area (SSA), a key parameter closely associated with photocatalytic activity. The model construction involved several steps, including data collection, feature selection, model construction, web-service development, virtual screening and mechanism elucidation. Statistical analysis revealed that the support vector regression model achieved a correlation coefficient of 0.9462 for the training set and 0.8786 for the leave-one-out cross-validation. The potential perovskites with higher SSA than the highest SSA observed in the existing dataset were identified using the model and our computation platform. We also developed a webserver of the model, freely accessible to users. The methodologies outlined in this study not only facilitate the discovery of new perovskites but also enable exploration of the correlations between the perovskite properties and the physicochemical features. These findings provide valuable insights for further research and applications of perovskites using machine learning techniques.

Specific surface area of mannitol rather than particle size dominant the dissolution rate of poorly water-soluble drug tablets: A study of binary mixture.

The dissolution behavior of tablets, particularly those containing poorly water-soluble drugs, is a critical factor in determining their absorption and therapeutic efficacy. Traditionally, the particle size of excipients has been considered a key property affecting tablet dissolution. However, lurasidone hydrochloride (LH) tablets prepared by similar particle size mannitol, namely M200 (D90 = 209.68 ± 1.42 µm) and 160C (D90 = 195.38 ± 6.87 µm), exhibiting significant differences in their dissolution behavior. In order to find the fundamental influential factors of mannitol influencing the dissolution of LH tablets, the properties (particle size, water content, true density, bulk density, tapped density, specific surface area, circularity, surface free energy, mechanical properties and flowability) of five grades mannitol including M200 and 160C were investigated. Principal component analysis (PCA) was used to establish a relationship between mannitol properties and the dissolution behavior of LH. The results demonstrated that specific surface area (SSA) emerged as the key property influencing the dissolution of LH tablets. Moreover, our investigation based on the percolation theory provided further insights that the SSA of mannitol influences the probability of LH-LH bonding and LH infinite cluster formation, resulting in the different percolation threshold states, then led to different dissolution behaviors. Importantly, it is worth noting that these findings do not invalidate previous conclusions, as reducing particle size generally increases SSA, thereby affecting the percolation threshold and dissolution behavior of LH. Instead, this study provides a deeper understanding of the underlying role played by excipient SSA in the dissolution of drug tablets. This study provides valuable guidance for the development of novel excipients aimed at improving drug dissolution functionality.

A Refined Thin-Film Model for Drug Dissolution Considering Radial Diffusion - Simulating Powder Dissolution.

PURPOSE: We aim to present a refined thin-film model describing the drug particle dissolution considering radial diffusion in spherical boundary layer, and to demonstrate the ability of the model to describe the dissolution behavior of bulk drug powders. METHODS: The dissolution model introduced in this study was refined from a radial diffusion-based model previously published by our laboratory (So et al. in Pharm Res. 39:907-17, 2022). The refined model was created to simulate the dissolution of bulk powders, and to account for the evolution of particle size and diffusion layer thickness during dissolution. In vitro dissolution testing, using fractionated hydrochlorothiazide powders, was employed to assess the performance of the model. RESULTS: Overall, there was a good agreement between the experimental dissolution data and the predicted dissolution profiles using the proposed model across all size fractions of hydrochlorothiazide. The model over-predicted the dissolution rate when the particles became smaller. Notably, the classic Nernst-Brunner formalism led to an under-estimation of the dissolution rate. Additionally, calculation based on the equivalent particle size derived from the specific surface area substantially over-predicted the dissolution rate. CONCLUSION: The study demonstrated the potential of the radial diffusion-based model to describe dissolution of drug powders. In contrast, the classic Nernst-Brunner equation could under-estimate drug dissolution rate, largely due to the underlying assumption of translational diffusion. Moreover, the study indicated that not all surfaces on a drug particle contribute to dissolution. Therefore, relying on the experimentally-determined specific surface area for predicting drug dissolution is not advisable.

Fast Joule Heating for the Scalable and Green Production of Graphene with a High Surface Area.

The rapid development of electric vehicles, unmanned aerial vehicles, and wearable electronic devices has led to great interest in research related to the synthesis of graphene with a high specific surface area for energy applications. However, the problem of graphene synthesis scalability, as well as the lengthy duration and high energy intensity of the activation processes of carbon materials, are significant disadvantages. In this study, a novel reactor was developed for the green, simple, and scalable electrochemical synthesis of graphene oxide with a low oxygen content of 14.1%. The resulting material was activated using the fast joule heating method. The processing of mildly oxidized graphene with a high-energy short electrical pulse (32 ms) made it possible to obtain a graphene-based porous carbon material with a specific surface area of up to 1984.5 m2/g. The increase in the specific surface area was attributed to the rupture of the original graphene flakes into smaller particles due to the explosive release of gaseous products. In addition, joule heating was able to instantly reduce the oxidized graphene and decrease its electrical resistance from >10 MΩ/sq to 20 Ω/sq due to sp2 carbon structure regeneration, as confirmed by Raman spectroscopy. The low energy intensity, simplicity, and use of environment-friendly chemicals rendered the proposed method scalable. The resulting graphene material with a high surface area and conductivity can be used in various energy applications, such as Li-ion batteries and supercapacitors.

Formation of Polyimide Membranes via Non-Solvent Induced Phase Separation: Insight from Molecular Dynamics Simulations.

Molecular dynamics simulations were applied to investigate the formation of P84 polyimide membranes through the non-solvent induced phase separation (NIPS) process, considering two scenarios: one using a conventional organic solvent like n-methyl-2-pyrrolidone (NMP) and the other a greener alternative, γ-butyrolactone (GBL), with water serving as the non-solvent. Different compositions of polymer solutions were established along the binodal boundaries of the respective systems, derived from experimental cloud point data on the ternary phase diagram. The resulting polymer membranes were analyzed and compared in terms of their morphology. The wettability of their surfaces was notably affected by the polymer content in the initial casting solution and demonstrated a correlation with the Brunauer-Emmet-Teller (BET) specific surface area of the associated polymer nanostructures. The GBL solvent systems produced porous polymers qualitatively similar to those obtained with NMP, albeit with slightly narrower pore size distributions.

Synthesis and utilization of polyol-modified high specific surface area Ca(OH)2: an investigation.

Calcium hydroxide (Ca(OH)2) finds widespread use in the petrochemical industry, particularly in flue gas desulfurization applications. However, its conventional usage is limited by its inherently low specific surface area, hampering its efficiency. To address this limitation, this study aims to develop a simple and industrially scalable preparation process for Ca(OH)2 with a high specific surface area, thereby enhancing its effectiveness in various applications. This study aimed to develop a preparation process for making Ca(OH)2 with a high specific surface area, suitable for industry and easy to make. Ca(OH)2 with a specific surface area of 41.555 m2/g was successfully synthesized by incorporating polyols during lime digestion. The prepared high specific surface area Ca(OH)2 is more than five times the specific surface area of ordinary Ca(OH)2. Incorporation of polyols within the lime digestion process induces a reduction in both Ca(OH)2 grain size and particle dimensions, concurrently amplifying the specific surface area and optimizing mass transfer efficiency. Specifically, the desulfurization breakthrough time for Ca(OH)2 subject to a 15% triethanolamine modification was notably extended to 879 s, surpassing the desulfurization breakthrough time of unaltered Ca(OH)2 by more than tenfold. Moreover, the modified Ca(OH)2 exhibited remarkable efficacy in neutralizing acidic wastewater. A new approach for the preparation of high-performance Ca(OH)2 is proposed in this study, which could facilitate the industrial production of Ca(OH)2 with high specific surface area.

Constructing Efficient CuO-Based CO Oxidation Catalysts with Large Specific Surface Area Mesoporous CeO2 Nanosphere Support.

CeO2 is an outstanding support commonly used for the CuO-based CO oxidation catalysts due to its excellent redox property and oxygen storage-release property. However, the inherently small specific surface area of CeO2 support restricts the further enhancement of its catalytic performance. In this work, the novel mesoporous CeO2 nanosphere with a large specific surface area (~190.4 m2/g) was facilely synthesized by the improved hydrothermal method. The large specific surface area of mesoporous CeO2 nanosphere could be successfully maintained even at high temperatures up to 500 °C, exhibiting excellent thermal stability. Then, a series of CuO-based CO oxidation catalysts were prepared with the mesoporous CeO2 nanosphere as the support. The large surface area of the mesoporous CeO2 nanosphere support could greatly promote the dispersion of CuO active sites. The effects of the CuO loading amount, the calcination temperature, mesostructure, and redox property on the performances of CO oxidation were systematically investigated. It was found that high Cu+ concentration and lattice oxygen content in mesoporous CuO/CeO2 nanosphere catalysts greatly contributed to enhancing the performances of CO oxidation. Therefore, the present mesoporous CeO2 nanosphere with its large specific surface area was considered a promising support for advanced CO oxidation and even other industrial catalysts.