Effect of Curing Temperature on the Properties of a MgO-SiO2-H2O System Prepared Using Dead-Burned MgO

The hydration of M-S-H prepared using silica fume (SF) and dead-burned MgO cured at 20 °C, 50 °C, and 80 °C was investigated, and the properties and performance of this M-S-H were measured. The formation of M-S-H was characterized using XRD, FTIR, TGA, and ²⁹Si MAS-NMR. Results show that the compressive strength of paste prepared using MgO calcined at 1450 °C for 2 h reached 25 MPa after 28 d. The shrinkage of mortar made with low reactivity MgO was lower than that made with high reactivity MgO. The pH value of MgO/SF paste mixed with dead-burned MgO did not exceed 10.4 at room temperature. The shrinkage of M-S-H prepared using dead-burned MgO was less than that prepared using more active MgO, and its strength did not decrease over time. No (or only a small amount of) Mg(OH)₂ was formed, which is why the strength of M-S-H prepared with dead-burned MgO continually increased, without decreasing. The promotion of curing temperature favor process of MgO hydration and is beneficial for degree of silica polymerization. The sample cured in 50 °C water showed the highest relative degree of reaction.     

A Comparative Study on Microstructure and Properties of Ultra-High-Speed Laser Cladding and Traditional Laser Cladding of Inconel625 Coatings

In this study, ultra-high-speed laser cladding (UHSLC) and traditional low-speed laser cladding (LSLC) were employed to prepare high-quality Inconel625 coatings on 27SiMn substrates. UHSLC has cladding speeds of 30 m/min, which are 15 times faster than those of LSLC, and it produces a much greater cladding efficiency, which is 13.9 times greater than LSLC. The microstructure of the Inconel625 coatings was investigated in detail utilizing field emission scanning electron microscopy (FESEM) and electron probe microanalyzer (EPMA). According to the FESEM results, UHSLC Inconel625 coatings have more refined crystals than LSLC Inconel625 coatings. Nevertheless, the EPMA results indicate that the UHSLC Inconel625 coatings exhibit much more severe elemental segregation. Moreover, the hardness, wear and corrosion resistance of Inconel625 coatings are significantly enhanced by increasing the laser cladding speed. Furthermore, the reasons for the differences in microstructure and properties of Inconel625 coatings prepared by UHSLC and LSLC were clarified by finite element simulation. UHSLC technique is, therefore, more suitable for preparing Inconel625 coatings on 27SiMn steel surfaces than LSLC.     

A Dual-Input Neural Network for Online State-of-Charge Estimation of the Lithium-Ion Battery throughout Its Lifetime

Online state-of-charge (SOC) estimation for lithium-ion batteries is one of the most important tasks of the battery management system in ensuring its operation safety and reliability. Due to the advantages of learning the long-term dependencies in between the sequential data, recurrent neural networks (RNNs) have been developed and have shown their superiority over SOC estimation. However, only time-series measurements (e.g., voltage and current) are taken as inputs in these RNNs. Considering that the mapping relationship between the SOC and the time-series measurements evolves along with the battery degradation, there still remains a challenge for RNNs to estimate the SOC accurately throughout the battery’s lifetime. In this paper, a dual-input neural network combining gated recurring unit (GRU) layers and fully connected layers (acronymized as a DIGF network) is developed to overcome the above-mentioned challenge. Its most important characteristic is the adoption of the state of health (SOH) of the battery as the network input, in addition to time-series measurements. According to the experimental data from a batch of LiCoO₂ batteries, it is validated that the proposed DIGF network is capable of providing more accurate SOC estimations throughout the battery’s lifetime compared to the existing RNN counterparts. Moreover, it also shows greater robustness against different initial SOCs, making it more applicable for online SOC estimations in practical situations. Based on these verification results, it is concluded that the proposed DIGF network is feasible for estimating the battery’s SOC accurately throughout the battery’s lifetime against varying initial SOCs.     

Microstructure and Properties of a Graphene Reinforced Cu–Cr–Mg Composite

To improve the graphene/copper interfacial bonding and the strength of the copper matrix, Cu–Cr–Mg alloy powder and graphene nanosheets (GNPs) have been used as raw materials in the preparation of a layered graphene/Cu–Cr–Mg composite through high-energy ball-milling and fast hot-pressing sintering. The microstructure of the composite after sintering, as well as the effect of graphene on the mechanical properties and conductivity of the composite, are also studied. The results show that the tensile strength of the composite material reached a value of 349 MPa, which is 46% higher than that of the copper matrix, and the reinforcement efficiency of graphene is as large as 136. Furthermore, the electrical conductivity of the composite material was 81.6% IACS, which is only 0.90% IACS lower than that of the copper matrix. The Cr and Mg elements are found to diffuse to the interface of the graphene/copper composite during sintering, and finely dispersed chromium carbide particles are found to significantly improve the interfacial bonding strength of the composite. Thus, graphene could effectively improve the mechanical properties of the composite while maintaining a high electrical conductivity.     

Fabrication of P/N/B-Based Intumescent Flame-Retardant Coating for Polyester/Cotton Blend Fabric

Polyester/cotton (T/C) blend fabrics are highly flammable due to the particular “scaffolding effect”. In this work, an intumescent flame retardant (IFR) agent containing P, N, and B was designed and synthesized using bio-based phytic acid, pentaerythritol, boric acid, and urea. The IFR compounds were deposited onto a T/C blend fabric by the surface-coating route. The chemical structure of IFR agent and its potential cross-linking reactions with T/C fibers were characterized. The morphology, thermal stability, heat-release ability, flame retardancy, and mechanism of coated T/C blend fabrics were explored. The self-extinguishing action was observed for the coated T/C blend fabric with a weight gain of 13.7%; the limiting oxygen index (LOI) value increased to 27.1% versus 16.9% for a pristine one. Furthermore, the intumescent flame retardant (IFR) coating imparted T/C blend fabrics with high thermal stability and significantly suppressed heat release by nearly 50%. The char residue analyses on morphology and element content confirmed the intumescent FR action for coated T/C blend fabrics. The prepared IFR coating has great potential to serve as an eco-friendly approach for improving the flame retardancy of T/C blend textiles.     

High-Efficiency Iron Extraction from Low-Grade Siderite via a Conveyor Bed Magnetization Roasting–Magnetic Separation Process: Kinetics Research and Applications

Upgrading and utilizing low-grade iron ore is of great practical importance to improve the strategic security of the iron ore resource supply. In this study, a thermal analysis–infrared (IR) analysis–in-situ IR method was used to investigate the reaction mechanism and kinetics of Daxigou siderite. Experiments were conducted using a conveyor bed magnetization roasting process (CBMRP) to investigate the magnetization of siderite. Multi-stage magnetic separation processes were adopted to extract magnetite. The results show that simultaneously the iron carbonate in siderite decomposes, and magnetite is formed between 364 °C and 590 °C under both inert and reducing atmospheres. The activation energy of the magnetization roasting reaction is 106.1 kJ/mol, consistent with a random nucleation and growth reaction mechanism. Magnetization roasting at 750–780 °C for approximately 3.5 s in the CBMRP results in a magnetic conversion rate of >0.99 of the iron minerals in the siderite. A beneficiation process of one roughing, one sweeping, and three cleaning processes was adopted. A dissociation particle size of −400 mesh accounting for 94.78%, a concentrate iron grade of 62.8 wt.%, and a recovery of 68.83% can be obtained. Overall, a theoretical and experimental basis is presented for the comprehensive utilization of low-grade siderite.     

A Novel Design Concept of Cemented Paste Backfill (CPB) Materials: Biobjective Optimization Approach by Applying an Evolved Random Forest Model

For cemented paste backfill (CPB), uniaxial compressive strength (UCS) is the key to ensuring the safety of stope construction, and its cost is an important part of the mining cost. However, there are a lack of design methods based on UCS and cost optimization. To address such issues, this study proposes a biobjective optimization approach by applying a novel evolved random forest (RF) model. First, the evolved RF model, based on the beetle search algorithm (BAS), was constructed to predict the UCS of CPB. The consistency between the predicted value and the actual value is high, which proves that the hybrid machine learning model has a good effect on the prediction of the UCS of CPB. Then, considering the linear relationship between the costs and the components of CPB, a mathematical model of the cost is constructed. Finally, based on the weighted sum method, the biobjective optimization process of the UCS and cost of CPB is conducted; the Pareto front optimal solutions of UCS and the cost of CPB can be obtained by the sort of solution set. When the UCS or the cost of CPB is constant, the Pareto front optimal solutions can always have a lower cost or a higher UCS compared with the actual dataset, which proves that the biobjective optimization approach has a good effect.