Jianqiao Yu^1,*, Hongxia Qiao^1,2, Theogene Hakuzweyezu¹, Feifei Zhu¹

Journal of Renewable Materials, Vol.10, No.11, pp. 2973-2987, 2022, DOI:10.32604/jrm.2022.019620

Abstract This study was designed to solve the problem of magnesium hazards due to potash extraction in the salt lake region. Using basalt fiber (BF) as the reinforcement material and magnesium oxychloride cement (MOC) as the gelling material, a BF/MOC composite material was prepared. Firstly, the effect of BF addition content on the basic mechanical properties of the composites was investigated. Then, through the salt spray corrosion test, the durability damage deterioration evaluation analysis was carried out from both macroscopic and microscopic aspects using mass change, relative dynamic modulus of elasticity (RDME) change, SEM analysis and FT-IR analysis. Finally, a GM(1,… More >

Xupeng Chen^1,*, Zhuowen Sun², Jianyong Pang¹

Journal of Renewable Materials, Vol.10, No.9, pp. 2489-2508, 2022, DOI: 10.32604/jrm.2022.019404

Abstract Mineral admixture concrete is a renewable material. It requires less cement than ordinary concrete and is thus beneficial for economical use of resources and environmental protection. To examine the impact of chloride salt on the durability of mineral admixture concrete under various conditions, in this study, test blocks are divided into two major groups: in one group, the test block is eroded by chloride salt on the interior and by sulphate/ magnesium salts on the exterior, and in the second group, the test block is eroded by external chloride/sulphate/ magnesium salts. Clean water is considered the control group. Dry-wet alternation… More > Graphic Abstract

Jiakun Shi¹, Bizhu Zhang¹, Xin Zhou¹, Runxian Liu¹, Jun Hu^1,2,*, Huaan Zheng¹, Zhong Chen^3,*

Journal of Renewable Materials, Vol.10, No.5, pp. 1239-1255, 2022, DOI:10.32604/jrm.2022.018045

Abstract As a passive anti-icing strategy, properly designed superhydrophobic coatings can demonstrate outstanding performances. However, common preparation strategies for superhydrophobic coatings often lead to environmental pollution, high energy-consumption, high-cost and other undesirable issues. Besides, the durability of superhydrophobic coating also plagues its commercial application. In this paper, we introduced a facile and environment-friendly technique for fabricating abrasion-resistant superhydrophobic surfaces using thermoplastic polyurethane (TPU) and modified SiO₂ particles (SH-SiO₂). Both materials are non-toxicity, low-cost, and commercial available. Our methodology has the following advantages: use of minimal amounts of formulation, take the most streamlined technical route, and no waste material. These advantages make… More > Graphic Abstract

Yun Wang¹, Tiantian Wang², Bei Wang¹, Wei Chang³, Jiangli Cao¹, Lihua Hu³, Minxu Lu¹, Lei Zhang^1,*

Journal of Renewable Materials, Vol.10, No.2, pp. 301-327, 2022, DOI:10.32604/jrm.2021.015518

Abstract A novel and effective water-soluble aldehydes (β-HA) as corrosion inhibitor was synthesized for N80 steel corrosion in 15% HCl solution, and the corrosion inhibition performance was evaluated by using weight loss, electrochemical measurements, scanning electron microscope (SEM), quantum chemical calculation and molecular dynamics simulation (MDS). The results show that synthesized β-HA showed excellent corrosion performance compared with MHB and PE for carbon steel in 15% HCl solution compared with MHB and PE, and the inhibition efficiency increased with increasing concentration of the inhibitor. The inhibition efficiency of β-HA at 8 mmol/L reached the maximum value 94.08%. The inhibitor acted as… More >

Ying Wang^*, Haoran Shi, Shibo Ren

CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.3, pp. 967-983, 2021, DOI:10.32604/cmes.2021.015792

Abstract The corrosion of reinforcement in the concrete will cause the effective cross-sectional area of reinforcement to be weakened and the performance of reinforcement to change and lead to the degradation of the bond behavior between reinforcement and concrete, which can seriously affect the mechanical properties of the structural elements. Therefore, it is of great practical significance to accurately simulate the corrosion morphology and the corrosion products of reinforcement. This paper improves the previous cellular automata models and establishes a new cellular automata model framework for simulating the random pitting corrosion process of reinforcement in concrete. This model defines the detailed… More >

Yuhao Jiang, Jialan Yao, Chengfei Zhu^*

Journal of Renewable Materials, Vol.10, No.1, pp. 135-148, 2022, DOI:10.32604/jrm.2021.016304

Abstract Poly(urea-formaldehyde) (PUF) microcapsules were prepared by in-situ polymerization with four different processes in this paper. The chemical composition, surface morphology, particle size distribution, and thermal stability were characterized by FTIR, SEM, particle size analyzer, and TGA, respectively. The results demonstrated that the agglomeration of the PUF microcapsules was related to the agglomeration of the emulsion particles caused by the changes of emulsion interface during the shell polymerization. Due to the slow deposition of the shell material, the PUF microcapsules with the core-shell structure prepared by the process with ammonium chloride as the last additive showed good dispersibility with an average… More > Graphic Abstract

D. Saber^1,*, Ibrahim B. M. Taha², Kh. Abd El-Aziz³

Intelligent Automation & Soft Computing, Vol.29, No.3, pp. 757-769, 2021, DOI:10.32604/iasc.2021.018516

Abstract In this study, optimal regression learner methods were used to predict the corrosion behavior of aluminum–silicon alloys (Al–Si) with various Si ratios in different media. Al–Si alloys with 0, 1%, 8%, 11.2%, and 15% Si were tested in different media with different pH values at different stirring speeds (0, 300, 600, 750, 900, 1050, and 1200 rpm). Corrosion behavior was evaluated via electrochemical potentiodynamic test. The corrosion rates (CRs) obtained from the corrosion tests were utilized in the formation of datasets of various machine regression learner optimization (MRLO) methods, namely, decision tree, support vector machine, Gaussian process regression, and ensemble… More >

Yong Wang, Yongyan Wang^*, Nan Qin, Sa Huang, Le Chang, Shunzheng Hou

Computer Systems Science and Engineering, Vol.39, No.1, pp. 121-131, 2021, DOI:10.32604/csse.2021.014464

Abstract The work presented in this paper was conducted to quantify the relationship between the pore characteristics and mechanical properties of white sandstone. The study include tests carried out under the coupling effects of chemical corrosion, temperature, nuclear magnetic resonance, and mechanical tests. Computer fractal theory was employed to describe and quantify the characteristics of the growth of pores in white sandstone under the same coupling effect. A custom developed program code, in the MATLAB software platform, was used for calculating the growths of the pores in white sandstone when subjected to coupling effects. The correlation between the computer fractal dimension… More >

Enas H. Ali, Juman A. Naser^*, Zainab W. Ahmed, Taki A. Himdan

Journal of Renewable Materials, Vol.9, No.11, pp. 1927-1939, 2021, DOI:10.32604/jrm.2021.015624

Abstract Polymeric nanofibers are a promising technology to protect the metal surfaces from corrosion. Through the literature search, the use of polyacrylonitrile nanofibres (PANNFs) as a corrosion inhibitor coating for aluminum alloys has not been evaluated. This work includes the development of a new, lightweight, high surface area and efficient coating of PANNFs that produced using electrospinning process to resist the corrosion of aluminum alloys (AA5083) which immersed in 0.6 M NaCl at alkaline medium (pH = 12) and acidic medium (pH = 1) at a range of temperatures (293–323) K. The PANNFs coating was successfully deposited on AA 5083 specimens,… More >

Phyu Hnin Thike^{1, 2}, Zhaoyang Zhao¹, Peng Liu¹, Feihu Bao¹, Ying Jin¹, Peng Shi^{1, *}

CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2091-2109, 2020, DOI:10.32604/cmc.2020.011608

Abstract The optimization of network topologies to retain the generalization ability by deciding when to stop overtraining an artificial neural network (ANN) is an existing vital challenge in ANN prediction works. The larger the dataset the ANN is trained with, the better generalization the prediction can give. In this paper, a large dataset of atmospheric corrosion data of carbon steel compiled from several resources is used to train and test a multilayer backpropagation ANN model as well as two conventional corrosion prediction models (linear and Klinesmith models). Unlike previous related works, a grid searchbased hyperparameter tuning is performed to develop multiple… More >