The Sn-Ag-Cu (SAC) solder alloys with a low Ag (Ag < 3 wt.%) content have attracted great attention owing to their low cost, increased ability in bulk compliance, and plastic energy dissipation. However, some of their mechanical properties are generally lower than the SAC alloys with a higher Ag content. Adding alloying elements is an effective approach for improving the mechanical properties of the SAC alloys. In this study, the effect of Bi, Sb, and Ti on Sn-1 wt.%Ag-0.5 wt.%Cu (SAC105) solder alloys was investigated. The SAC solders with four compositions: SAC105-1 wt.%Bi, SAC105-1 wt.%Sb, SAC105-1 wt.%Bi-1 wt.%Sb, SAC105-1 wt.%Bi-1 wt.%Sb-0.4 wt.%Ti were prepared. The microstructure and phase compositions were characterized using electron scanning microscopy, and X-ray diffraction. The thermal properties and wettability were also examined. Uniaxial tensile tests and nano-indentation tests were conducted to evaluate the mechanical properties. The results show that adding Bi or Sb could increase the strength of SAC105 alloys mainly due to the solid solution strengthening effect. The creep resistance of SAC105 alloys was also improved with the additions of Bi and Sb. The co-additions of Bi and Sb into SAC105 alloys exhibit an enhanced creep resistance than that calculated by the theoretical calculation. The further addition of Ti into SAC105-1Bi-1Sb alloys demonstrated a much-improved creep resistance, which could be attributed to the synergistic effects of both solid solution strengthening and the precipitation hardening effects.

In electronic packaging, Sn-Zn lead-free solder has great application prospects. Sn-9Zn-xBi alloys were obtained by smelting. This paper details a systematic study of the effect of Bi on the microstructure, melting behavior, wettability, mechanical behavior, antioxidant properties, and electrical conductivity of Sn-9Zn-xBi alloy, as well as the interfacial reaction in Sn-9Zn-xBi/Cu joints. The coarse Zn-rich phase became larger with an increase in the addition of Bi, which is harmful to the oxidation resistance of the solders. The melting temperature, solidus temperature, and liquidus temperature decreased with the increase in the addition of Bi, but the melting range increased. Adding a proper amount of Bi could substantially improve the spreading rate of Sn-9Zn, but reduce its oxidation resistance. Because of the solid solution effect of Bi element, the tensile strength of the Sn-9Zn solders could be enhanced, but the plastic and electrical conductivity was decreased. The IMC layer of the Sn-9Zn and Cu joints consisted of the ε-CuZn₅ phase and the γ-Cu₅Zn₈ phase. With an increase in the Bi element, the thickness of the interfacial reaction layer was firstly increased. When the Bi element content exceeded 3 wt.%, the inhibitory effect of the aggregated Bi elements on the formation of IMC was greater than the positive effect of the longer reaction time, and the thickness of the IMC decreased.

Energy consumption forecasting plays an important role in energy management, conservation, and optimization in manufacturing companies. Aiming at the tin smelting process with multiple types of energy consumption and a strong coupling with energy consumption, the traditional prediction model cannot be applied to the multi-output problem. Moreover, the data collection frequency of different processes is inconsistent, resulting in few effective data samples and strong nonlinearity. In this paper, we propose a multi-kernel multi-output support vector regression model optimized based on a differential evolutionary algorithm for the prediction of multiple types of energy consumption in tin smelting. Redundant feature variables are eliminated using the distance correlation coefficient method, multi-kernel learning is introduced to improve the multi-output support vector regression model, and a differential evolutionary algorithm is used to optimize the model hyperparameters. The validity and superiority of the model was verified using the energy consumption data of a non-ferrous metal producer in Southwest China. The experimental results show that the proposed model outperformed multi-output Gaussian process regression (MGPR) and a multi-layer perceptron neural network (MLPNN) in terms of measurement capability. Finally, this paper uses a grey correlation analysis model to discuss the influencing factors on the integrated energy consumption of the tin smelting process and gives corresponding energy-saving suggestions.

The synergistic inhibition effect of sodium phytate (PA) and benzotriazole (BTA) on 20SiMn steel in 3.5 wt-% NaCl solutions was studied using electrochemical methods, SEM, FTIR, XPS and quantum chemical calculations based on density functional theory (DFT). Results indicate that a protective bi-layer film is formed with the presence of the mixture of PA and BTA: the inner layer consists of iron oxides_, while the outer one is an adsorption layer of BTA and PA. Based on the analysis of XPS and DFT, the function of BTA belongs to chemisorption, while that of PA obeys Langmuir adsorption isotherm and could be mainly assigned to physisorption. The inhibition efficiency of the mixture inhibitor is 99.12%, with a synergism parameter of 3.62, which could be ascribed to a cross-linking structure containing more BTA promoted by PA through hydrogen bonds.