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At present, research on the preparation of corrosion inhibitors using modified pyrimidine derivatives is still blank. The purpose of this study is to synthesize a new cationic mercaptopyrimidine derivative quaternary ammonium salt, known as DTEBTAC, that can be used as a corrosion inhibitor to slow down the metal corrosion problems encountered in oil and gas extraction processes.

A new corrosion inhibitor was synthesized by the reaction of anti-Markovnikov addition and nucleophilic substitution. The weight loss method was used to study the corrosion inhibition characteristics of synthetic corrosion inhibitors. Electrochemical and surface topography analyses were used to determine the type of inhibitor and the adsorption state formed on the surface of N80 steel. Molecular dynamics simulations and quantum chemistry calculations were used to investigate the synthetic corrosion inhibitor’s molecular structure and corrosion inhibition mechanisms.

The results of the weight loss method show that when the dosage of DTEBTAC is 1%, the corrosion rate of N80 steel in hydrochloric acid solution at 90? is 3.3325 g m-2 h-1. Electrochemical and surface morphology analysis show that DTEBTAC can form a protective layer on the surface of N80 steel, and is a hybrid corrosion inhibitor that can inhibit the main anode. Quantum chemical parameter calculation shows that DTEBTAC has a better corrosion inhibition effect than DTP. The molecular dynamics simulation results show that DTEBTAC has stronger binding energy than DTP, and forms a network packing structure through hydrogen bonding, and the adsorption stability is enhanced.

A novel cationic mercaptopyrimidine derivative quaternium-ammonium salt corrosion inhibitor was designed and provided. Compared with the prior art, the preparation method of the synthesized mercaptopyrimidine derivative quaternary ammonium salt corrosion inhibitor is simple, and the presence of nitrogen-positive ions, sulfur atoms and nitrogen-rich atoms has an obvious corrosion inhibition effect, which can be used to inhibit metal corrosion during oil and gas field exploitation. It not only expands the application field of new materials but also provides a new idea for the research and development of new corrosion inhibitors.

The classical advection-dispersion equation (ADE) model cannot accurately depict the gas transport process in natural geological formations. This paper aims to study the behavior of CO₂ transport in fractal porous media by using an effective Hausdorff fractal derivative advection-dispersion equation (HFDADE) model.

Anomalous dispersion behaviors of CO₂ transport are effectively characterized by the investigation of time and space Hausdorff derivatives on non-Euclidean fractal metrics. The numerical simulation has been performed with different Hausdorff fractal dimensions to reveal characteristics of the developed fractal ADE in fractal porous media. Numerical experiments focus on the influence of the time and space fractal dimensions on flow velocity and dispersion coefficient.

The physical mechanisms of parameters in the Hausdorff fractal derivative model are analyzed clearly. Numerical results demonstrate that the proposed model can well fit the history of gas production data and it can be a powerful technique for depicting the early arrival and long-tailed phenomenon by incorporating a fractal dimension.

To the best of the authors’ knowledge, first time these results are presented.

To improve the localization accuracy of the magnetically controlled capsule endoscope (MCCE), a new localization method, based on the magnetic dipole model, is proposed, where the anti-disturbance permanent magnet (APM) is used as the source of stable magnetic field, thus reducing the interference of the geomagnetic field or the electric conductor magnetic field in the system.

The coupling magnetic force model between the APM and the capsule endoscope is established to obtain the magnetic force relationship and magnetic induction intensity. Along the three axes, magnetic induction intensity data are collected by a 3 × 3 sensor array composed of nine magnetic field intensity sensors, while the data are uploaded to the main computer by the STM32F103C8T6 control board over a ESP8266 WIFI module connection. Next, the axial magnetic induction intensity data are decoupled to obtain the measurement trajectory, whereas the error function is established based on the calculated trajectory parameters. Finally, the Levenberg–Marquardt (L-M) algorithm is used to solve the position information of the MCCE.

Experiments show that the average localization error of an MCCE in a straight and circular bend tube is 4.76 mm, whereas in a U-bend tube, it is 6.82 mm.

The optimized simulation value in the linear and bending environment is in good agreement with the experimental value, which verifies the accuracy of the MCCE localization system based on magnetic field sensor array, exhibiting good performance in localization and position tracking while providing a theoretical basis for the subsequent research.