Green Treatment of Cyanide Tailings Using a “Filter Press BackWash–Chemical Precipitation–Gaseous Membrane Absorption” Method

Based on a “filter press backwash–chemical precipitation–gaseous membrane absorption” process, treatment of harmless cyanide tailings was conducted using cyanide tailings from a gold smelting enterprises (Yunnan Province, China) as the research object. The effects of air-drying time, backwash water parameters, initial pH of acidification, NaHS dosage, cyanide-containing water flow rate, and gaseous membrane stages on the process were investigated. Chemical composition, X-ray diffraction, and X-ray photoelectron spectroscopy analyses of the copper products were carried out. Results showed that the copper content in the copper product was 54.56%, and the chemical composition was mainly CuSCN, CuS, Cu2S, and CaSO4. Five cycles of experiments were carried out under optimal conditions; the results showed that the process can make the treated cyanide tailings meet the requirements of the technical specification for pollution control of cyanide leaching residue in the gold industry (TSPC) standard for storage in a tailings pond and a have certain stability. The average recovery rate of copper and total cyanide in elution water was 97.8% and 99.89%, respectively, and the average removal rate of thiocyanate was 94.09%.

Modelling Spatial Scales of Dose Deposition and Radiolysis Products from Gold Nanoparticle Sensitisation of Proton Therapy in A Cell: From Intracellular Structures to Adjacent Cells

Gold nanoparticle (GNP) enhanced proton therapy is a promising treatment concept offering increased therapeutic effect. It has been demonstrated in experiments which provided indications that reactive species play a major role. Simulations of the radiolysis yield from GNPs within a cell model were performed using the Geant4 toolkit. The effect of GNP cluster size, distribution and number, cell and nuclear membrane absorption and intercellular yields were evaluated. It was found that clusters distributed near the nucleus increased the nucleus yield by 91% while reducing the cytoplasm yield by 7% relative to a disperse distribution. Smaller cluster sizes increased the yield, 200 nm clusters had nucleus and cytoplasm yields 117% and 35% greater than 500 nm clusters. Nuclear membrane absorption reduced the cytoplasm and nucleus yields by 8% and 35% respectively to a permeable membrane. Intercellular enhancement was negligible. Smaller GNP clusters delivered near sub-cellular targets maximise radiosensitisation. Nuclear membrane absorption reduces the nucleus yield, but can damage the membrane providing another potential pathway for biological effect. The minimal effect on adjacent cells demonstrates that GNPs provide a targeted enhancement for proton therapy, only effecting cells with GNPs internalised. The provided quantitative data will aid further experiments and clinical trials.

Modeling and Simulation of the Simultaneous Absorption/Stripping of CO2 with Potassium Glycinate Solution in Membrane Contactor

Global warming is an environmental problem caused mainly by one of the most serious greenhouse gas, CO2 emissions. Subsequently, the capture of CO2 from flue gas and natural gas is essential. Aqueous potassium glycinate (PG) is a promising novelty solvent used in the CO2 capture compared to traditional solvents; simultaneous solvent regeneration is associated with the absorption step. In present work, a 2D mathematical model where radial and axial diffusion are considered is developed for the simultaneous absorption/stripping process. The model describes the CO2/PG absorption/stripping process in a solvent–gas membrane absorption process. Regeneration data of rich potassium glycinate solvent using a varied range of acid gas loading (mol CO2 per mol PG) were used to predict the reversible reaction rate constant. A comparison of simulation results and experimental data validated the accuracy of the model predictions. The stripping reaction rate constant of rich potassium glycinate was determined experimentally and found to be a function of temperature and PG concentration. Model predictions were in good agreement with the experimental data. The results reveal that the percent removal of CO2 is directly proportional to CO2 loading and solvent stripping temperature.