Adsorption characteristics and mechanisms of Cd(II) from wastewater by modified chicken manure biochar.

Due to the threat to food supply and human health posed by cadmium-contaminated wastewater, a highly effective adsorbent is under necessary development to remove cadmium from wastewater. In this study, four new types of modified biochars with different modifier concentrations were prepared from chicken manure using K2FeO4 as a modifier, and the modified biochar KFBC1 with the best adsorption effect was obtained through optimal experiments. Various characterization analyses have shown that KFBC1 has a rough surface structure, abundant pore structure, and a large number of functional groups. Additionally, iron oxides are introduced on the surface of the biochar, which provided a favorable condition for the adsorption of Cd(II) in wastewater. The adsorption performance of Cd(II) on the biochar before and after modification was investigated through batch adsorption experiments. The adsorption kinetic model of KFBC1 to Cd(II) in solution was in accordance with the quasi-secondary kinetic model, and the adsorption isothermal model was in accordance with the Langmuir model, with a maximum adsorption capacity of 330.06 mg/g, which was 5.15 fold of pristine BC. Meanwhile, the adsorption rate of Cd(II) by KFBC1 was positively correlated with dosage and pH. Pore adsorption, ion exchange, surface precipitation, interaction with -π electrons, and complexation of oxygen-containing functional groups on the surface were considered as important mechanisms for the removal of Cd(II) by KFBC1. According to the results, KFBC1 is a novel and efficient adsorbent that can be used as a treatment agent for cadmium-contaminated wastewater.

Compression-Softening Bond Model for Non-Water Reactive Foaming Polyurethane Grouting Material.

In this study, the uniaxial compression and cyclic loading and unloading experiments were conducted on the non-water reactive foaming polyurethane (NRFP) grouting material with a density of 0.29 g/cm3, and the microstructure was characterized using scanning electron microscope (SEM) method. Based on the uniaxial compression and SEM characterization results and the elastic-brittle-plastic assumption, a compression softening bond (CSB) model describing the mechanical behavior of micro-foam walls under compression was proposed, and it was assigned to the particle units in a particle flow code (PFC) model simulating the NRFP sample. Results show that the NRFP grouting materials are porous mediums consisting of numerous micro-foams, and with the increasing density, the diameter of the micro-foams increases and the micro-foam walls become thicker. Under compression, the micro-foam walls crack, and the cracks are mainly perpendicular to the loading direction. The compressive stress-strain curve of the NRFP sample contains the linear increasing stage, yielding stage, yield plateau stage, and strain hardening stage, and the compressive strength and elastic modulus are 5.72 MPa and 83.2 MPa, respectively. Under the cyclic loading and unloading, when the number of cycles increases, the residual strain increases, and there is little difference between the modulus during the loading and unloading processes. The stress-strain curves of the PFC model under uniaxial compression and cyclic loading and unloading are consistent with the experimental ones, well indicating the feasibility of using the CSB model and PFC simulation method to study the mechanical properties of NRFP grouting materials. The failure of the contact elements in the simulation model causes the yielding of the sample. The yield deformation propagates almost perpendicular to the loading direction and is distributed in the material layer by layer, which ultimately results in the bulging deformation of the sample. This paper provides a new insight into the application of the discrete element numerical method in NRFP grouting materials.

The Identification of ECG Signals Using WT-UKF and IPSO-SVM.

The biometric identification method is a current research hotspot in the pattern recognition field. Due to the advantages of electrocardiogram (ECG) signals, which are difficult to replicate and easy to obtain, ECG-based identity identification has become a new direction in biometric recognition research. In order to improve the accuracy of ECG signal identification, this paper proposes an ECG identification method based on a multi-scale wavelet transform combined with the unscented Kalman filter (WT-UKF) algorithm and the improved particle swarm optimization-support vector machine (IPSO-SVM). First, the WT-UKF algorithm can effectively eliminate the noise components and preserve the characteristics of ECG signals when denoising the ECG data. Then, the wavelet positioning method is used to detect the feature points of the denoised signals, and the obtained feature points are combined with multiple feature vectors to characterize the ECG signals, thus reducing the data dimension in identity identification. Finally, SVM is used for ECG signal identification, and the improved particle swarm optimization (IPSO) algorithm is used for parameter optimization in SVM. According to the analysis of simulation experiments, compared with the traditional WT denoising, the WT-UKF method proposed in this paper improves the accuracy of feature point detection and increases the final recognition rate by 1.5%. The highest recognition accuracy of a single individual in the entire ECG identification system achieves 100%, and the average recognition accuracy can reach 95.17%.

Quantitative characterization of non-classic polarization of cations on clay aggregate stability.

Soil particle interactions are strongly influenced by the concentration, valence and ion species and the pH of the bulk solution, which will also affect aggregate stability and particle transport. In this study, we investigated clay aggregate stability in the presence of different alkali ions (Li+, Na+, K+, and Cs+) at concentrations from10-5 to 10-1 mol L-1. Strong specific ion effects on clay aggregate stability were observed, and showed the order Cs+>K+>Na+>Li+. We found that it was not the effects of ion size, hydration, and dispersion forces in the cation-surface interactions but strong non-classic polarization of adsorbed cations that resulted in these specific effects. In this study, the non-classic dipole moments of each cation species resulting from the non-classic polarization were estimated. By comparing non-classic dipole moments with classic values, the observed dipole moments of adsorbed cations were up to 104 times larger than the classic values for the same cation. The observed non-classic dipole moments sharply increased with decreasing electrolyte concentration. We conclude that strong non-classic polarization could significantly suppress the thickness of the diffuse layer, thereby weakening the electric field near the clay surface and resulting in improved clay aggregate stability. Even though we only demonstrated specific ion effects on aggregate stability with several alkali ions, our results indicate that these effects could be universally important in soil aggregate stability.