Facile Preparation of Magnetic Chitosan Coprecipitated by Ethanol/NH₃·H₂O for Highly Efficient Removal toward Cr(VI)

The adsorption ability of chitosan (CS) usually decreases with the introduction of magnetic particles, and thus magnetic CS has to be chemically modified further to improve its adsorption performance. Herein, a novel magnetic chitosan composite (Fe₃O₄–CS3) with porous structure and evenly distributed Fe₃O₄ was successfully prepared via the reduction of the solubility of CS by ethanol (physical reaction), and followed the coprecipitation of the mixture of FeCl₃/FeCl₂/CS by ethanol/NH₃·H₂O. Without any modification, its maximum adsorption capacity toward Cr­(VI) ions can achieve 242.1 mg/g (≈468.6 mg/g of CS). This significant progress could be ascribed to the very fast precipitate rate of CS due to the decrease in solubility induced by ethanol. Ethanol causes rigorous solidification of CS, so that there is not enough time to densify, resulting in a looser CS matrix with a larger pore size. After adsorption, this Fe₃O₄–CS3 could not only be easily separated but also be effectively regenerated by NaOH solution in a rather wider concentration range, showing great potential in the field of heavy metal wastewater treatment

Understanding Quantitative Relationship between Methane Storage Capacities and Characteristic Properties of Metal–Organic Frameworks Based on Machine Learning

Metal–organic frameworks (MOFs) are one category of emerging porous materials, which are promising competitors applied in gas storage and separation due to their high porosity and high surface area. It is still time consuming to search for optimal materials for methane storage from a large number of candidates by traditional methods such as molecular simulations and quantum mechanics. Recently, machine learning (ML) algorithms were gradually used to accelerate the discovery of high-performance MOFs. In this work, Henry’s coefficient besides other characteristic parameters was computed and appended into the previously reported data set of hypothetical metal–organic frameworks (hMOFs) for methane storage. The new data set with 37 features and 130 397 samples was then randomly split into a training set and a test set in the ratio of 7:3, which were applied for ML training and testing with three different algorithms, including support vector machine, random forest regression (RFR), and gradient boosting regression tree (GBRT). The results indicate that the GBRT model demonstrates the best generalization ability to predict nontrained data set, whereas the RFR model results in the best predictive power in the training set. The analysis of feature importance from machine learning algorithms confirms that the high generalization ability of the GBRT model is attributed to the model extracting more information from a wider range of features. The RFR model results in the highest prediction accuracy with Pearson correlation coefficient (r2) of 0.9984 and root mean square error (RMSE) of 3.93 in the training set of absolute gravimetric uptakes. The GBRT model results in the highest prediction accuracy with r2 of 0.9908 and RMSE of 9.40 in the test set of absolute gravimetric uptakes, which is the highest prediction accuracy among the up-to-date reports. According to volumetric capacities for methane storage, the optimal hMOFs exhibit ϕ of 0.65–0.88, liquid-crystal display of ∼7.5 Å, VSA of ∼2250 m2 cm–3, etc

Facile Hydrothermal Synthesis of Hierarchical Boehmite: Sulfate-Mediated Transformation from Nanoflakes to Hollow Microspheres

An interesting morphological evolution from single nanoflakes to nanoflake assemblies, flower-like structures, and hollow microspheres is reported for the first time for boehmite prepared from Al(NO3)3·9H2O with addition of urea and different amounts of KAl(SO4)2·12H2O under hydrothermal conditions. The microstructure, morphology, and textural properties of the boehmite materials were characterized by X-ray powder diffraction, Fourier-transform infrared spectroscopy, scanning electron microscopy, transmission electron microscopy, and nitrogen adsorption. It was found that the resulting hierarchical boehmite materials composed of nanoflakes were transformed from featureless material to irregular particles and solid microspheres. To better understand this transformation, different sulfate additivesAlNH4(SO4)2·12H2O, Al2(SO4)3·18H2O, Na2SO4, (NH4)2SO4, and MgSO4·7H2Owere used to synthesize boehmite and magnesia-incorporated boehmite hollow microspheres. This study shows that the sulfate-mediated transformation strategy can be extended for the preparation of other hierarchical metal oxides with controlled morphological and textural properties for catalysis, adsorption, and separation applications

Facile Synthesis of Novel Rare-Earth Elements-Modified SiO₂ Films for Effective Cr(VI) Removal from Electroplating Effluent

The rare-earth elements (La, Ce, and Y)-modified SiO2 films for effective Cr­(VI) removal from electroplating effluent were synthesized by a convenient sol–gel method successfully. X-ray diffraction, Fourier transform infrared spectra (FT-IR), scanning electron microscope, energy-dispersive system, and X-ray photoelectron spectroscopy (XPS) were applied to characterize their physicochemical properties. The adsorption isotherms showed that the adsorption capacity of SiO2 modified by La3+ (64.43 mg g–1) is the best, followed by Ce3+ (53.45 mg g–1) and Y3+ (47.83 mg g–1) because of the different ion-exchange capacities of La/Ce/Y–(OH), whereas that of SiO2 film without modification is only 38.54 mg g–1. Their adsorption processes could be well depicted by the pseudo-second-order kinetic model. The thermodynamics study showed that the adsorption process of the La/SiO2 film is spontaneous. The adsorption mechanism includes the ion exchange and electrostatic effect. Furthermore, the conversion of Cr­(VI) to Cr­(III) during the in situ reduction process was verified by both macro (optical photographs) and micro (FT-IR and XPS) levels. Importantly, the La/SiO2 film showed high adsorption selectivity and high removal efficiency of 97.4% toward Cr­(VI) from initial concentration of 41.7 mg L–1 to residual concentration of 1.1 mg L–1 in the real electroplating effluent, indicating its potential industrial value for pretreatment of heavy metal wastewater

Low-Temperature Catalytic Dry Reforming of Methane over Pd Promoted Ni–CaO–Ca₁₂Al₁₄O₃₃ Multifunctional Catalyst

The dry reforming of methane (DRM) suffers from high energy consumption and catalyst deactivation over time on stream at high operating temperatures (>800 °C). Here, we demonstrate that DRM is effectively catalyzed at 600 °C by Pd promoted Ni–CaO–Ca12Al14O33 multifunctional adsorbent/catalyst materials with 67% CO2 conversion, 68% CH4 conversion, and a H2/CO ratio close to unity. Notably, the catalyst shows no sign of deactivation at 600 °C for a 50 h continuous on-stream DRM reaction. The high performance is ascribed to the enhanced CH4 dissociation activity with the presence of Pd. CH4 reformed with CaCO3 achieved the transformation between bulk CaCO3 and nanoparticles of CaO. The dynamic transformation may allow for reversible encapsulation and release of Ni particles, thereby suppressing Ni sintering. Furthermore, the coke formed on the catalyst is mainly the active carbon species which is easily removed by CO2 and CaCO3, thus ensuring the long-term stability. The results demonstrated herein shed light on a new paradigm to design low-temperature DRM reaction catalysts

Facile Synthesis of Ordered Mesoporous Alumina and Alumina-Supported Metal Oxides with Tailored Adsorption and Framework Properties

The evaporation-induced self-assembly (EISA) in ethanolic solution of a triblock copolymer (Pluronic P123) is explored for the synthesis of ordered mesoporous alumina (MA) and MA-supported metal oxides, using aluminum isopropoxide, aluminum chloride, and aluminum nitrate nonahydrate as aluminum precursors, and nickel, magnesium, iron, chromium, copper, cerium, lanthanum, yttrium, calcium, tin chlorides, or nitrates as metal precursors. The as-synthesized mesoporous oxides were characterized by a variety of techniques, such as thermogravimetry, Fourier transform infrared spectroscopy, nitrogen adsorption, small- and wide-angle X-ray diffraction, high-resolution transmission electron microscopy, energy-dispersive X-ray spectrometry, elemental mapping, and CO2 and NH3 temperature-programmed desorption. It is shown that the EISA strategy in the presence of polymeric template not only is well-suited for the synthesis of ordered MAs and MA-supported metal oxides with tailored adsorption and framework properties, but also ensures a homogeneous distribution of metal species within inorganic framework with the aluminum/metal atomic ratio close to this used in the synthesis mixture. The aluminum and other metal precursors used in EISA have a significant impact on the pore structure, surface area, and basic and acidic properties of the resulting mixed oxides. For instance, the use of inexpensive aluminum nitrate nonahydrate in the synthesis leads to the significantly enlarged mesopores (ranging from ∼7 nm to 16 nm), improved ordering of the oxides, and enhanced adsorption affinity toward CO2, while the aluminum chloride precursor affords MA-supported metal oxides with a bimodal pore size distribution, with peaks located in the ranges of 2−4 nm and 5−9 nm, respectively. It is also shown that the use of inexpensive aluminum and metal salts as precursors instead of aluminum alkoxides affords MA-supported metal oxides with tailorable properties, in terms of the surface area, porosity, and surface basicity and acidity, which determine the performance of these materials in various applications, including adsorption and catalysis