Two-Dimensional Modeling of Nano Zero-Valent Iron Transport and Retention before and after Phosphate Adsorption.

The mobility of nano zero-valent iron (nZVI) will greatly affect its practical application as a remediation material for contaminated groundwater. One-dimensional (1D) column tests are commonly used in previous work to study its migration behavior, but the two-dimensional (2D) test is still very limited. This study reports a novel research system to study the 2D transport and retention behavior of colloids and solutes, which includes a 2D model test setup and the corresponding image analysis method. The transport behaviors of methyl orange (MO), nZVI, and phosphate-loaded nZVI (PnZVI) are studied using this system. The results show that the research system can reasonably describe the tempo-spatial concentration distribution of colloids and solutes. After phosphate adsorption, the mobility of nZVI is enhanced due to the increase in negative surface charge, which implies a potential environmental risk of nZVI to facilitate contaminant transport. The migration of PnZVI is not significantly influenced by its density, which is faster than MO in the longitudinal direction. The range of the plume of PnZVI in the longitudinal direction is larger than that of MO, which implies that PnZVI has a stronger longitudinal dispersion than MO.

Prediction of gas production rate from shale gas reservoirs using a micro-macro analysis.

Shale gas has become one of the important contributors to the global energy supply. The declining pattern of the gas production rate with time from an unconventional gas reservoir is due to the depletion of shale gas stored in the nanovoids of the shale formation. However, there are only limited ways to predict the variation of the gas production rate with time from an unconventional gas reservoir. This is due to the multiple transport mechanisms of gas in nano-scale pores and changes in shale gas permeability with pressures in nano-scale pores, which is impacted by the pore structure of the shale. In this study, the permeability-pressure (K-p) relationship for different shales (Eagle Ford, Haynesville, Longmaxi and Opalinus) were determined using an equivalent anisotropic pore network model (PNM). This PNM has REV-scale shale gas flow in randomly generated nanovoids and their connection in the shale matrix, and the multiphase flow of shale gas including viscous flow, slip flow and Knudsen diffusion. These predicted K-p correlations were then used in a finite element model (FEM) to predict the variation of the gas production rate with time (flux-time curves) at the macroscale. The simulation results show that the flux-time curves can be simplified to two linear segments in logarithmic coordinates, which are influenced by the fracture length and initial gas pressure. The predicted results using the PNM-FEM were validated by comparing them with the reported field test data. The method described in this study can be used to upscale the gas transport process from micro- to macroscale, which can provide a predictive tool for the gas production in shales.

Dynamic QTL mapping revealed primarily the genetic structure of photosynthetic traits in castor (Ricinus communis L.).

High photosynthetic efficiency is the basis of high biomass and high harvest index in castor (Ricinus communis L.). Understanding the genetic law of photosynthetic traits will facilitate the breeding for high photosynthetic efficiency. In this study, the dynamic QTL mapping was performed with the populations F2 and BC1 derived from 2 parents with significant difference in net photosynthetic rate (Pn) at 3 stages, in order to reveal the genetic structure of photosynthetic traits. In F2 population, 26 single-locus QTLs were identified, including 3/3/1 (the QTL number at stage I/II/III, the same below), 1/2/0, 1/2/2, 1/3/1, 0/1/1, and 1/1/2 QTLs conferring Pn, water use efficiency (Wue), transpiration rate (Tr), stomatal conductance (Gs), intercellular CO2 concentration (Ci) and chlorophyll content (Cc), with a phenotypic variation explained (PVE) of 8.40%/8.91%/6.17%, 5.36%/31.74%/0, 7.31%/12.80%/15.15%, 1.60%/6.44%/0.02%, 0/1.10%/0.70% and 2.77%/3.96%/6.50% respectively. And 53 epistatic QTLs (31 pairs) were identified, including 2/2/5, 5/6/3, 4/4/2, 6/3/2, 3/2/0 and 4/0/0 ones conferring the above 6 traits, with a PVE of 6.52%/6.47%/19.04%, 16.72%/15.67%/14.12%, 18.57%/15.58%/7.34%, 21.72%/8.52%/7.13%, 13.33%/4.94%/0 and 7.84%/0/0 respectively. The QTL mapping results in BC1 population were consistent with those in F2 population, except fewer QTLs detected. Most QTLs identified were minor-effect ones, only a few were main-effect ones (PVE > 10%), focused on 2 traits, Wue and Tr, such as qWue1.1, qWue1.2, FqTr1.1, FqTr6, BqWue1.1 and BqTr3; The epistatic effects, especially those related to the dominance effects were the main genetic component of photosynthetic traits, and all the epistatic QTLs had no single-locus effects except qPn1.2, FqGs1.2, FqCi1.2 and qCc3.2; The detected QTLs underlying each trait varied at different stages except stable QTLs qGs1.1, detected at 3 stages, qWue2, qTr1.2 and qCc3.2, detected at 2 stages; 6 co-located QTLs were identified, each of which conferring 2-5 different traits, demonstrated the gene pleiotropy between photosynthetic traits; 2 QTL clusters, located within the marker intervals RCM1842-RCM1335 and RCM523-RCM83, contained 15/5 (F2/BC1) and 4/4 (F2/BC1) QTLs conferring multiple traits, including co-located QTLs and main-effect QTLs. The above results provided new insights into the genetic structure of photosynthetic traits and important references for the high photosynthetic efficiency breeding in castor plant.

An anisotropic pore-network model to estimate the shale gas permeability.

The permeability of shale is a significant and important design parameter for shale gas extraction. The shale gas permeability is usually obtained based on Darcy flow using standard laboratory permeability tests done on core samples, that do not account for different transport mechanisms at high pressures and anisotropic effects in shales due to nano-scale pore structure. In this study, the permeability of shale is predicted using a pore network model. The characteristics of pore structure can be described by specific parameters, including porosity, pore body and pore throat sizes and distributions and coordination numbers. The anisotropy was incorporated into the model using a coordination number ratio, and an algorithm that was developed for connections of pores in the shale formation. By predicting hydraulic connectivity and comparing it with several high-pressure permeability tests, the proposed three-dimensional pore network model was verified. Results show that the prediction from the anisotropic pore network model is closer to the test results than that based on the isotropic pore network model. The predicted permeability values from numerical simulation using anisotropic pore network model for four shales from Qaidam Basin, China are quite similar to those measured from laboratory tests. This study confirmed that the developed anisotropic three-dimensional pore network model could reasonably represent the natural gas flow in the actual shale formation so that it can be used as a prediction tool.