Effect of bubble morphology and behavior on power consumption in non-Newtonian fluids’aeration process

Due to a prolonged operation time and low mass transfer efficiency, the primary challenge in the aeration process of non-Newtonian fluids is the high energy consumption, which is closely related to the form and rate of impeller, ventilation, rheological properties and bubble morphology in the reactor. In this perspective, through optimal computational fluid dynamics models and experiments, the relationship between power consumption, volumetric mass transfer rate(kLa) and initial bubble size(d0) was constructed to establish an efficient operation mode for the aeration process of non-Newtonian fluids. It was found that reducing the d0could significantly increase the oxygen mass transfer rate, resulting in an obvious decrease in the ventilation volume and impeller speed. When d0was regulated within 2-5 mm,an optimal kLa could be achieved, and 21% of power consumption could be saved, compared to the case of bubbles with a diameter of 10 mm.

A review of ^(17)O isotopic labeling techniques for solid-state NMR structural studies of metal oxides in lithium-ion batteries

Recent advances in utilizing ^(17)O isotopic labeling methods for solid-state nuclear magnetic resonance(NMR)investigations of metal oxides for lithium-ion batteries have yielded extensive insights into their structural and dynamic details.Herein,we commence with a brief introduction to recent research on lithium-ion battery oxide materials studied using ^(17)O solid-state NMR spectroscopy.Then we delve into a review of ^(17)O isotopic labeling methods for tagging oxygen sites in both the bulk and surfaces of metal oxides.At last,the unresolved problems and the future research directions for advancing the ^(17)O labeling technique are discussed.

Machine learning assisted prediction of charge transfer properties in organic solar cells by using morphology-related descriptors

Charge transfer and transport properties are crucial in the photophysical process of exciton dissociation and recombination at the donor/acceptor(D/A)interface.Herein,machine learning(ML)is applied to predict the charge transfer state energy(ECT)and identify the relationship between ECT and intermolecular packing structures sampled from molecular dynamics(MD)simulations on fullerene-and non-fullerene-based systems with different D/A ratios(RDA),oligomer sizes,and D/A pairs.The gradient boosting regression(GBR)exhibits satisfactory performance(r=0.96)in predicting ECT withπ-packing related features,aggregation extent,backbone of donor,and energy levels of frontier molecular orbitals.The charge transport property affected byπ-packing with different RDA has also been investigated by space-charge-limited current(SCLC)measurement and MD simulations.The SCLC results indicate an improved hole transport of non-fullerene system PM6/Y6 with RDA of 1.2:1 in comparison with the 1:1 counterpart,which is mainly attributed to the bridge role of donor unit in Y6.The reduced energetic disorder is correlated with the improved miscibility of polymer with RDA increased from 1:1 to 1.2:1.The morphology-related features are also applicable to other complicated systems,such as perovskite solar cells,to bridge the gap between device performance and microscopic packing structures.

Synergistic regulation of intermolecular interactions to control chiral structures for chiral recognition

Understanding the regulatory mechanism of self-assembly processes is a necessity to modulate nanostructures and their properties. Herein, we have studied the mechanism of self-assembly in the C3 symmetric 1,3,5-benzentricarboxylic amino acid methyl ester enantiomers(TPE) in a mixed solvent system consisting of methanol and water. The resultant chiral structure was used for chiral recognition. The formation of chiral structures from the synergistic effect of multiple noncovalent interaction forces was confirmed by various techniques. Molecular dynamics simulations were used to characterize the time evolution of TPE structure and properties in solution. The theoretical results were consistent with the experimental results. Furthermore, the chiral structure assembled by the building blocks of TPE molecules was highly stereoselective for diamine compounds.

Micro-interface enhanced mass transfer sodium carbonate absorption carbon dioxide reaction

Micro-interface intensified reactor(MIR)can be applied in series/parallel in the absorption of CO_(2)in industrial gases by Na_(2)CO_(3)due to the ability to produce large numbers of stable microbubbles.This work focuses on the variation pattern of mass transfer characteristics parameters of the reaction gas in Na_(2)CO_(3) solution under the influence of different solution properties and operating parameters in the reaction of CO_(2)absorption by Na2CO3.The mass transfer characteristics parameters include bubble Sauter mean diameter,gas holdup,interfacial area,liquid side mass transfer coefficient,and liquid side volume mass transfer coefficient kLa.The solution properties and operating parameters include Na2CO3 concentration(0.05–2.0 mol·L^(-1)),superficial gas velocity(0.00221–0.01989 m·s^(-1)),superficial liquid velocity(0.00332–0.02984 m·s^(-1)),and ionic strength(1.42456–1.59588 mol·kg^(-1)).And volumetric mass transfer coeffi-cients kLa and superficial reaction rates r of the MIR and the bubble column reactor are compared in the reaction of sodium carbonate absorption of carbon dioxide,and the former shows a greater improvement under different solution properties and operating parameters.The enhanced role of MIR in mass transfer in non-homogeneous reactions is verified and the feasibility of industrial practical applications of MIR is demonstrated.

Highly selective catalytic reduction of NO_x by MnO_x–CeO_2–Al_2O_3 catalysts prepared by self-propagating high-temperature synthesis

We first present preparation of MnOx–CeO_2–Al_2O_3 catalysts with varying Mn contents through a self-propagating high-temperature synthesis(SHS) method, and studied the application of these catalysts to the selective catalytic reduction of NOxwith NH3(NH_3-SCR).Using the catalyst with 18 wt.% Mn(18 MnCe1Al2), 100% NO conversion was achieved at 200°C and a gas hourly space velocity of 15384 hr-1, and the high-efficiency SCR temperature window, where NO conversion is greater than 90%, was widened to a temperature range of 150–300°C. 18 MnCe1Al2 showed great resistance to SO_2(100 ppm)and H_2O(5%) at 200°C. The catalysts were characterized using X-ray diffraction, X-ray photoelectron spectroscopy, Brunauer–Emmett–Teller(BET) analysis, scanning electron microscopy, Fourier transform infrared spectroscopy, and H_2 temperature programmed reduction. The characterization results showed that the surface atomic concentration of Mn increased with increasing Mn content, which led to synergism between Mn and Ce and improved the activity in the SCR reaction. 18 MnCe1Al2 has an extensive pore structure,with a BET surface area of approximately 135.4 m^2/g, a pore volume of approximately 0.16 cm^3/g, and an average pore diameter of approximately 4.6 nm. The SCR reaction on 18 MnCe1Al2 mainly followed the Eley-Rideal mechanism. The performances of the MnOx–CeO_2–Al_2O_3 catalysts were good, and because of the simplicity of the preparation process,the SHS method is applicable to their industrial-scale manufacture.

Advanced non-precious electrocatalyst of the mixed valence CoO_x nanocrystals supported on N-doped carbon nanocages for oxygen reduction

Taking advantage of the nitrogen(N)-participation and large surface area of N-doped carbon nanocages(NCNCs),the Co Ox nanocrystals are conveniently immobilized onto the NCNCs with high dispersion.The Co Ox/NCNCs hybrid exists in the mixed valence with predominant Co O over Co3O4 and demonstrates superb oxygen reduction reaction activity and stability remaining^94%current density even after operation over 100 h.These results suggest a promising strategy to develop advanced electrocatalysts with the novel NCNCs or even beyond.

DFT study on adduct reaction paths of GaN MOCVD growth

The adduct reaction paths for GaN growth by metal organic chemical vapor deposition (MOCVD) were studied by quantum chemical calculations employing density functional theory (DFT). Five possible adduct reaction paths with or without the ex-cess NH3were proposed and the corresponding potential energy surfaces were calculated. From the calculation results, it is concluded that after the formation of DMGNH2from TMG:NH3, the further decomposition paths have very slim probability because of the high energy barriers; whereas the oligomerization pathway to form oligomers [DMGNH2]x(x=2, 3) is probable,because of zero energy barrier. Since the oligomers tend to further polymerize, the nanoparticles are easily formed through this path. When NH3is in excess, TMG:NH3 tends to combine with the second NH3to form two new complexes: the coordination-bonded compound H3N:TMG:NH3and the hydrogen-bonded compound TMG:NH3 NH3. The formation of hydrogen-bonded compound TMG:NH3 NH3 will be more probable because of the lower energy than H3N:TMG:NH3. By comparing the potential energy surfaces in five adduct reaction paths, we postulate that, under the growth conditions of GaN MOCVD, the formation of hydrogen-bonded compound TMG:NH3 NH3 followed by the reversible decomposition may be the main reaction path for GaN thin film growth; while the adduct oligomerization path to generate oligomers [DMGNH2]2 and [DMGNH2]3might be the main reaction path for nanoparticles formation.

Boosting oxygen reduction activity of spinel CoFe2O4 by strong interaction with hierarchical nitrogen-doped carbon nanocages

The unique hierarchical nitrogen-doped carbon nanocages(h NCNC) are used as a new support to homogeneously immobilize spinel Co Fe_2O_4 nanoparticles by a facile solvothermal method. The so-constructed hierarchical Co Fe_2O_4/h NCNC catalyst exhibits a high oxygen reduction activity with an onset potential of0.966 V and half-wave potential of 0.819 V versus reversible hydrogen electrode, far superior to the corresponding 0.846 and 0.742 V for its counterpart of Co Fe_2O_4/h CNC with undoped hierarchical carbon nanocages(h CNC) as the support, which locates at the top level for spinel-based catalysts to date.Consequently, the Co Fe_2O_4/h NCNC displays the superior performance to the Co Fe_2O_4/h CNC, when used as the cathode catalysts in the home-made Al-air batteries. X-ray photoelectron spectroscopy characterizations reveal the more charge transfer from Co Fe_2O_4 to h NCNC than to h CNC, indicating the stronger interaction between Co Fe_2O_4 and h NCNC due to the nitrogen participation. The enhanced interaction and hierarchical morphology favor the high dispersion and modification of electronic states for the active species as well as the mass transport during the oxygen reduction process, which plays a significant role in boosting the electrocatalytic performances. In addition, we noticed the high sensitivity of O 1 s spectrum to the particle size and chemical environment for spinel oxides, which is used as an indicator to understand the evolution of ORR activities for all the Co Fe_2O_4-related contrast catalysts. Accordingly,the well-defined structure-performance relationship is demonstrated by the combination of experimental characterizations with theoretical calculations. This study provides a promising strategy to develop efficient, inexpensive and durable oxygen reduction electrocatalysts by tuning the interaction between spinel metal oxides and the carbon-based supports.

Transition-Metal-Free Defluorosilylation of Fluoroalkenes with Silylboronates

Silylated fluoroalkenes are important synthetic intermediates with complementary reactivity,which play a key role in the construction of natural products,pharmaceuticals,and manmade materials.Converting the normally highly stable fiuoroalkenes into silylated fluoroalkenes by selective defluorosilylation is a challenging task.Herein,we report a simple,inexpensive and robust defluorosilylation of a variety of fluoroalkenes with silylboronates in the presence of alkoxy base to directly synthesize various silylated fluoroalkenes.The protocol features mild and safe reaction conditions that avoid a catalyst,a transition metal,a ligand,and high reaction temperature and tolerates a wide scope of fluoroalkene substrates without compromising the efficiency.Density functional theory calculations show that transient silyl anion complex undergoes an SN2,or SNv substitution,which is responsible for this base-mediated defluorosilylation.

Recent progress in investigations of surface structure and properties of solid oxide materials with nuclear magnetic resonance spectroscopy

Solid oxide materials have widespread applications which are often associated with their surface structure and properties. Solid-state nuclear magnetic resonance（NMR） spectroscopy is one of the most powerful methods that give detailed local structural information of solid materials. Recent developments in dynamic nuclear polarization（DNP） NMR spectroscopy and17 O surface-selective isotopic labeling provide more opportunities in investigations of surface structure and properties of oxide materials. We describe in this review some of the latest progress in this field. DNP NMR can enhance the sensitivity of surface sites on the oxides by one to two order of magnitude, making very low concentrated species on the surface of oxides visible in NMR spectroscopy. On the basis of surface-selective17 O isotopic labeling,17 O NMR spectroscopy is now able to distinguish surface oxygen species on the different facets or different surface layers in oxide nanostructures. The nature of these facets can also be probed with help of31 P NMR spectroscopy along with phosphorous-containing probe molecules.

Field Effects on the Statistical Behavior of the Molecular Conductance in a Single Molecular Junction in Aqueous Solution

We have combined molecular dynamics simulations with first-principles calculations to study electron transport in a single molecular junction of perylene tetracarboxylic diimide (PTCDI) in aqueous solution under external electric gate fields. It is found that the statistics of the molecular conductance are very sensitive to the strength of the electric field. The statistics of the molecular conductance are strongly associated with the thermal fluctuation of the water molecules around the PTCDI molecule. Our simulations reproduce the experimentally observed three orders of magnitude enhancement of the conductance, as well as the temperature dependent conductance, under the electrochemical gates. The effects of the molecular polarization and the dipole rearrangement of the aqueous solution are also discussed.

Dissociative chemisorption dynamics of small molecules on metal surfaces

Much progress has been achieved for both experimental and theoretical studies on the dissociative chemisorption of molecules on surfaces.Quantum state-resolved experimental data has provided unprecedented details for these fundamental steps in heterogeneous catalysis,while the quantitative dynamics is still not fully understood in theory.An in-depth understanding of experimental observations relies on accurate dynamical calculations,in which the potential energy surface and adequate quantum mechanical implementation are desired.This article summarizes the current methodologies on the construction of potential energy surfaces and the quantum mechanical treatments,some of which are promising for future applications.The challenges in this field are also addressed.

Catalytic dehydrogenation of propane to propylene over highly active PtSnNa/γ-Al2O3 catalyst

PtSnNa/γ-Al2O3 catalyst is widely used in the dehydrogenation of light alkane. This paper reports a new fabrication method of the catalyst. In the work, γ-Al2O3, SnCl4 and NaCl were ball milled to upload Sn and Na＋ onto the support instead of the conventionally used immersion method. The subsequent baking procedures frimly fixed Sn onto the support, which could disperse Pt introduced by immersion. The effects of Sn and Na＋ additives on the catalytic performance of PtSnNa/y-Al2O3 catalyst were investigated. It was found that the appropriate molar ratio of Sn/Pt was 6：1 while the favorable weight percentage of Na＋ was 0.90%. Compared with the reaction catalyzed by the industrially employed PtSnNa/ γ-Al2O3 catalyst, the conversion of propane and the selectivity of propylene had been greatly improved, which were 26.97%; and 99.18% respectivelv after 12 h reaction.

Unprecedented synthesis of chiral calix[4](aza)crowns and its potent encapsulating methanol

Unprecedented synthesis of chiral (aza)crown ethers of calix[4]arene derivatives bearing a carboxyl amide bridge was described. The synthesis proceeds through condensation of the corresponding dinitriles with optically active 1,2-aminoalcohols,and is catalyzed by the ZnCl2 Lewis acid at elevated temperature in a very efficient one-pot process. The cavity of calix[4](aza)crowns can encapsulate methanol molecules by O-H...π interaction,which has been confirmed by X-ray crystal structures and ESI-MS.

Preparation and Field Emission Properties of Titanium Polysulfide Nanobelt Films

TiS_(3) nanobelt films,with widths of about 0.112μm,thickness of about 20250 nm,and lengths of up to 200μm,have been grown on Ti substrates by a surface-assisted chemical-vapor-transport at 450°C for 8 h.The TiS_(3) nanobelt films were converted into TiS_(1.71) nanobelt films by pyrolysis in a vacuum at 600°C for 2 h.The work functions of the two films were determined by ultraviolet photoelectron spectroscopy measurements to be 4.60 and 4.44 eV,respectively.Preliminary field emission experiments using the nanostructures as cold electron cathodes showed that both materials gave significant emission currents.The turn-on fields(defined as the electric field required to produce a current density of 10μA/cm^(2))were about 1.0 and 0.9 V/μm,respectively,whereas the threshold fields(defined as the electric field required to produce a current density of 1 mA/cm^(2))were about 5.6 and 4.0 V/μm,respectively.These data reveal that both materials have potential applications in field emission devices.

Comparison of some multireference electronic structure methods in illustrative applications

The performances of several multireference electronic structure methods including complete active space self-consistent field (CASSCF)-based second-order perturbation theory (CASPT2), multireference configuration interaction with single and double excitations (MR-CISD), MR-CISD with the Davidson correction (MR-CISD+Q), and the CASSCF-based block-correlated coupled cluster method (CAS-BCCC4) we developed recently are compared by applying them to study several different chemical problems involving computation of ground state potential energy surfaces, the singlet-triplet gaps in diradicals, reaction barriers, and the excitation energies of low-lying excited states. Comparison with the results from other highly accurate theoretical methods or the available experimental data demonstrate that for all the problems studied, the overall performance of CAS-BCCC4 is competitive with that of MR-CISD+Q, and better than that of CASPT2 and MR-CISD methods. Thus the CAS-BCCC4 approach is expected to be a promising theoretical method for quantitative descriptions of the electronic structures of molecules with noticeable multireference character.

Machine learning on properties of multiscale multisource hydroxyapatite nanoparticles datasets with different morphologies and sizes

Machine learning models for exploring structure-property relation for hydroxyapatite nanoparticles(HANPs)are still lacking.A multiscale multisource dataset is presented,including both experimental data(TEM/SEM,XRD/crystallinity,ROS,anti-tumor effects,and zeta potential)and computation results(containing 41,976 data samples with up to 9768 atoms)of nanoparticles with different sizes and morphologies at density functional theory(DFT),semi-empirical DFTB,and force field,respectively.Three geometric descriptors are set for the explainable machine learning methods to predict surface energies and surface stress of HANPs with satisfactory performance.To avoid the pre-determination of features,we also developed a predictive deep learning model within the framework of graph convolution neural network with good generalizability.Energies with DFT accuracy are achievable for largesized nanoparticles from the learned correlations and scale functions for mapping different theoretical levels and particle sizes.The simulated XRD spectra and crystallinity values are in good agreement with experiments.

Self-supported NiFe-LDH nanosheets on NiMo-based nanorods as high-performance bifunctional electrocatalysts for overall water splitting at industrial-level current densities

Efficient,durable and economic electrocatalysts are crucial for commercializing water electrolysis technology.Herein,we report an advanced bifunctional electrocatalyst for alkaline water splitting by growing NiFe-layered double hydroxide(NiFe-LDH)nanosheet arrays on the conductive NiMo-based nanorods deposited on Ni foam to form a three-dimensional(3D)architecture,which exhibits exceptional performances for both hydrogen evolution reaction(HER)and oxygen evolution reaction(OER).In overall water splitting,only the low operation voltages of 1.45/1.61 V are required to reach the current density of 10/500 mA·cm^(-2),and the continuous water splitting at an industrial-level current density of 500 mA·cm^(-2) shows a negligible degradation(1.8%)of the cell voltage over 1000 h.The outstanding performance is ascribed to the synergism of the HER-active NiMo-based nanorods and the OER-active NiFe-LDH nanosheet arrays of the hybridized 3D architecture.Specifically,the dense NiFe-LDH nanosheet arrays enhance the local pH on cathode by retarding OH-diffusion and enlarge the electrochemically active surface area on anode,while the conductive NiMo-based nanorods on Ni foam much decrease the charge-transfer resistances of both electrodes.This study provides an efficient strategy to explore advanced bifunctional electrocatalysts for overall water splitting by rationally hybridizing HER-and OER-active components.

Mesostructured carbon-based nanocages: an advanced platform for energy chemistry

The electrochemistry in energy conversion and storage(ECS) not only relies on the active species in catalysts or energy-storage materials, but also involves mass/ion transport around the active species and electron transfer to the external circuit. To realize high-rate ECS process, new architectures for catalysts or energy-storage electrodes are required to ensure more efficient mass/charge transport. 3 D porous mesostructured materials constructed by nanoscale functional units can form a continuous conductive network for electron transfer and an interconnected multiscale pores for mass/ion transport while maintaining the high surface area, showing great promise in boosting the ECS process. In this review, we summarize the recent progress on the design,construction and applications of 3 D mesostructured carbon-based nanocages for ECS. The role of the hierarchical architectures to the high rate performance is discussed to highlight the merits of the mesostructured materials. The perspective on future opportunities and challenges is also outlined for deepening and extending the related studies and applications.