Advanced Powder Technology最新文献

Affinity between partially hydrophobic silica nanoparticles and organic solvents (ethanol and hexane) as dispersing medium has been characterized with change in the relaxation time obtained by a time-domain nuclear magnetic resonance (TD-NMR). Different chain lengths (denoted as C3, C6, and C12) were utilized as surface modifiers for the particles and the modification ratio was controlled. For ethanol, the longer chain length and higher modification ratio showed the higher affinity while for hexane, vice versa even though a quite poor affinity appeared in whole conditions. We hypothesize that the ethanol molecules could be attracted to residual silanol groups among long-chain length-functional groups. In order to prove, affinity of the partially hydrophobic silica nanoparticles with ethanol/hexane mixture has been investigated. In the range from 60 to 80 vol% of hexane, relaxation time of the C12-modified silica nanoparticles (modification ratio was 1.4 /nm²) quickly decreased. When the residual silanol was additionally modified with C3, the corresponding decrease disappeared. The TD-NMR has an effective tool to detect the change in the surface affinity of the partially hydrophobic nanoparticles even if they showed the same hydrophobicity.

Interest in applying non-parametric methods to analyze particle size distribution (PSD) is growing. Previous studies have demonstrated the effectiveness of the bootstrap method in evaluating percentile values and confidence intervals for number-based PSD data. In this study, the application of the method to mass-based (volume-based) distribution was extended. The performance of the parametric method, which uses the Hatch-Choate equation for lognormal distribution, was compared with that of the non-parametric method in evaluating mass-based distribution data converted from number-based distribution. The superior performance of the parametric method underscores the importance of prior distribution function knowledge. For non-parametric methods, “real repeat” simulations involving 5000 repetitions of individual samplings were conducted as a reference for the bootstrap method. It was found that there exists a critical sample size, beyond which larger samples are necessary to accurately represent the population through non-parametric analysis. This critical size requires that the maximum size in the dataset exceeds the target size (e.g., the 90th percentile value) for direct evaluation of existing data. When the sample size range surpasses the critical size, bootstrap provides a good approximation to the “real repeat” experiments. Therefore, it is essential to have a diagnostic strategy to determine whether the sample size is sufficiently large for non-parametric analysis. A simple method using multi-scale bootstrap is proposed in this regard.

Bandgap engineering has been effectively used to reduce the shallow-trap defects (e.g. antisite defects), but there are still rare reports on the removal of deep-trap defects (e.g. oxygen defects). In this work, our proposed strategy of In³⁺ substitution for Lu³⁺ via the formation of continuous (Lu,In)₂O₃ solid solutions can be used to widely tailored the bandgap energy. These solid solutions prepared from the chemical co-precipitation route presented the rounded morphology and their particle sizes increased at a higher In³⁺ content. The (Lu,In)₂O₃:Tm phosphor powders exhibited characteristic Tm³⁺ emissions arising from its intra‐4f¹² multi‐transitions upon UV excitation into strong broad charge transfer bands. The luminescence intensity reached the highest level at 15 at.% In³⁺ concentration. The In³⁺ incorporation was found to red-shift the charge transfer bands and shortened the florescence lifetimes. The luminescence quenching was dominated by exchange interaction while the theoretical and experimental quenching concentration of Tm³⁺ coincided well with each other (both ∼1 at.%). The trap depth in the In³⁺ free Lu₂O₃:Tm phosphor was determined to be ∼0.61 eV and these electron traps could be almost fully buried at the In³⁺ concentration above 5 at.%. Both the (Lu_0.99Tm_0.01)₂O₃ and (Lu_0.84In_0.15Tm_0.01)₂O₃ phosphors exhibited good thermal stability with high thermal-quenching activation energies (∼0.45 eV for the former and ∼0.39 eV for the latter). However, the (Lu_0.99Tm_0.01)₂O₃ phosphor presented abnormal thermal quenching effect.

Depressant starch (NS) was generally used in hematite flotation, while the adsorption mechanism of the macromolecular polymer onto mineral surfaces remained in question. In this study, novel detection approaches and computational chemistry methods were introduced to update the widely-accepted acid-base interaction theory. Microflotation tests confirm that the hematite flotation recovery was easily depressed by NS under the acid or alkaline conditions rather than the neutral condition. Zeta potential measurement shows that NS could change the zeta potential of hematite, while the shift amplitude ranked as alkaline > acid > neutral, indicating the most suitable pH range is the alkaline condition. XPS analysis reveals that NS could chemisorbed onto Fe atoms of hematite surface via C-O groups in the whole studied pH range. It was further verified using AFM tests, in which the NS has a stronger interaction force under the alkaline environment. MDS further indicates that the interaction energy between NS and the (0 0 1) hematite surface was three times greater than others under alkaline conditions. In general, the interaction force at the interface between the hematite surface and NS was a strong chemical adsorption at the alkaline conditions while there was weak chemisorption and hydrogen bonding under the neutral or acidic conditions.

To improve vertical mill performance, a vertical stirred mill is used as the research object. Firstly, an electromechanical multi-body dynamic model (EMBD) of the vertical stirred mill is established, followed by the establishment of a discrete element method (DEM) analysis model of the grinding media, and then the DEM-EMBD coupling model is formed. The feasibility of the DEM-EMBD coupling model is verified through experiments. On this basis, the stress distribution state of the helical agitator is analysed based on the coupling method of the discrete element method and finite element method (DEM-EMBD-FEM). The DEM-EMBD coupling model can better reflect the dynamic characteristics of the vertical stirred mill by comparing it with the DEM model and the coupling method of discrete element method and computational fluid dynamics (DEM-CFD) respectively. Finally, the effects of vertical stirred mill structural parameters, operating parameters and grinding media size on mill performance are investigated by the DEM-EMBD and DEM-EMBD-FEM coupling models. The approach then provides insights into the structural design of vertical stirred mills, motor selection, and the welding process between the helical blades and screw.

Computation of blood flow containing ferrofluid would be useful for analysis of drug carrier motion for cancer therapy. A thorough understanding nanoparticles behavior is challenging and needs to be addressed by developing sophisticated theoretical methods. A hybrid modeling for analysis of blood motion containing ferrofluid was implemented via mechanistic modeling combined with artificial intelligence. The system of analysis also considered external magnetic force for control of nanoparticles motion in the blood vessel. This research focuses on the analysis of velocity field based on a dataset consisting of variables x(m), y(m), and U(m/s). The objective is to develop accurate predictive models using Gaussian Process Regression (GPR), Kernel ridge regression (KRR), and Polynomial Regression (PR). The Dragonfly Algorithm (DA) was employed for hyper-parameter optimizing. The results demonstrate the performance of these models in relation to R² score, RMSE, and MAE. The GPR model achieves the highest score of 0.99603 in terms of R², indicating excellent predictive accuracy. It also exhibits the lowest RMSE of 7.1443x10^-3 and MAE of 5.35436 x10^-3, suggesting minimal deviations between the expected and predicted velocity values. The PR model also has a significant performance with an R² test score of 0.99348, RMSE of 9.1376 x10^-3, and MAE of 7.22828 x10^-3. The aforementioned results underscore the effectiveness of these models in accurately forecasting velocity based on the provided input variables.

Calcite is a common gangue mineral in tin ore, which seriously affects the flotation of fine-grained cassiterite. The enhanced flotation separation of fine-grained cassiterite and calcite with cetylpyridine bromide (CPB) as a dispersant were investigated in the study. The CPB significantly improved the flotation separation efficiency of fine-grained cassiterite and calcite, and it exhibited an excellent dispersion effect and relieved the coating phenomenon of calcite particles on the surface of cassiterite particles. The CPB changed the surface potential of cassiterite from negative value to positive value when the pH was in the range of 3.4–11.5. However, regardless of treatment with CPB, the surface potential of calcite was positive when the pH was below 11.5. The O on the surface of cassiterite reacted with CPB, promoting the chemical adsorption of CPB on the surface of cassiterite. There was weak physical adsorption between CPB and calcite. The covering between cassiterite and calcite without CPB was mainly dependent on van der Waals interaction energy and electrostatic interaction energy. When CPB was in the presence, cassiterite and calcite were repelled by the hydrophobic interaction energy and electrostatic interaction energy.

Addressing the persistent challenge of separating smithsonite from calcite using flotation method, this study explores the impact of carboxymethyl chitosan (CMCS) on selective separation using sodium oleate (NaOL) assisted flotation. Results indicated a substantial reduction in calcite recovery to 2.25 % with the addition of 40 mg/L CMCS at pH 9, while recovery of smithsonite remained essentially unchanged at 94.78 %. Moreover, we found that using CMCS as the depressant can effectively separate smithsonite from calcite, based on the flotation testing results with artificially mixed minerals. Contact angle tests results showed that CMCS can significantly lower the surface hydrophobicity of calcite without any negative effect on that of smithsonite when using NaOL as a collector. TOC, FTIR, AFM, and ToF-SIMS analyses demonstrated stronger adsorption of CMCS on the surface of calcite compared to smithsonite. XPS data, solution chemical analysis and DFT revealed interaction between –COO- in CMCS with Ca sites on the surface of calcite because of the electrostatic adsorption and chemical adsorption, forming −COOCa. It leaded to shielding effects on the NaOL adsorption stemming, which makes NaOL more adsorbed on smithsonite surface.