Grain Boundary in Oxide Scale During High-Temperature Metal Processing

Grain boundary in oxide scale has profound influences on the deformation behaviour and tribological properties of metal alloys at high temperature. This chapter introduces some recent progress to quantify microstructure and interface quality, providing examples of possible property variations. Some fundamental issues of oxidation mechanism have been given, consisting of crystal structures of iron oxides and oxidation of steel alloys. Two main things are addressed: One is what the characters of grain boundaries are developed in the oxide scale, which is associated with grain shape and size, microtexture, and special grain boundaries such as coincident site lattice (CSL) boundaries. Another is the role of grain boundaries played during metal processing, including initial oxidation via grain boundary diffusion, stress and deformation processing, and tribological properties of oxide scale at metal processing. Finally, a more extensive effort was also made to summarise the experimental techniques used to investigate oxide scale

Experimental study on adhesion of oxide scale on hot-rolled steel strip

An experimental method was developed to study the adherence properties of the oxide scale formed on microalloyed low carbon steel after hot strip rolling. The evolution of the oxide scale during laminar cooling was investigated using Gleeble 3500 Thermal-Mechanical Simulator connected with a humid air generator. After the sample cooled down to ambient temperature, the oxide scale was protected by lacquer to prevent the scale from losing. Physicochemical characteristics of the oxide scale were examined and the adherence mechanism was discussed. Decomposed wustite a mixture of α-iron and magnetite (Fe3O4), can substantially improve the integrity of oxide scale. However, large quantities of hematite (Fe2O3) or retained wustite (FeO) were found detrimental to the adhesion of the oxide scale. It is found that the adherence of oxide scales significantly depends on the phase composition of oxide scales with different thickness

Effect of total flavonoids from Drynaria rhizome on bone loss in ovariectomized rats

Purpose: To determine the potential effect of total flavonoids from Drynaria rhizome on bone loss in ovariectomized (OVX) rats. Methods: The rats were divided into four groups: normal control, ovariectomized (OVX) control, and two Drynaria rhizome (DR) flavonoids treatments. Post-operation, osteoporotic OVX rats were given Drynaria rhizome total flavonoids for 3 months. Thereafter, the expressions of bone-related genes and biochemical indices were investigated in samples taken from the serum and bone of the rats. Results: Treatment with total flavonoids from Drynaria rhizome prevented bone mineral loss and improved some related biochemical indices associated with osteoporosis: alkaline phosphatase (ALP), tartrate-resistant acid phosphatase (TRAP), bone gla protein (BGP) and estradiol (E2). Reverse transcription-polymerase chain reaction (RT-PCR) data showed that treatment with the total flavonoids significantly downregulated mRNA expression of Wnt10b, β-catenin, recombinant human bone morphogenetic protein-2 (BMP2) and BMP4 in OVX rats, but significantly reversed OVX-induced downregulation of dickkopf1 (Dkk1) mRNA expression. Conclusion: These results indicate that total flavonoids from Drynaria rhizome exert anti-osteoporotic effects in rats via WNT signaling and BMP-2 signaling pathways

Extraction optimization of Eucommia ulmoides Oliver and its effect on bone quality in OVX rats

Purpose: To maximize the yield of extract from Eucommia ulmoides Oliver and its effect on bone quality. Methods: Different extraction indices were optimized with response surface methodology (RSM) for maximization of extract yield from Eucommia ulmoides Oliver. Box–Behnken design (BBD) was used to identify the effects of temperature, time, and liquid to solid ratio on extract yield from Eucommia ulmoides Oliver. After 4-week acclimatization, thiry-two rats were randomly assigned to 4 groups (n = 8): group 1 (sham) given vehicle only; group 2 (OVX rats given Eucommia ulmoides Oliver extract at a dose of 4 g/kg; group 3 (OVX + vehicle); group 4 (OVX + EUOE), i.e., OVX rats given Eucommia ulmoides Oliver extract (4 g/kg). Sham rats had intact ovaries. After surgery, the rats received gentamicin intramuscularly for 3 successive days. Two months after surgery, blood and trabecular bones was taken for analysis. Results: Temperature and liquid-to-solid ratio had marked impact on extract yield from Eucommia ulmoides Oliver, with the best conditions being temperature of 88 °C, time of 137 min, and liquid to solid ratio 16:1. Using these optimized conditions, the maximum yield of extract obtained experimentally (2.53%) was very close to the predicted value of 2.49 %. There was a good fit between the mathematical model evolved and the data on extract yield. The extract significantly (p < 0.01) increased the Ca and P and Cr levels in OVX + EUOE group compared to those in OVX control. Moreover, the extract significantly (p < 0.01) increased macro-mechanical indices of trabecular bone in OVX+EUOE group, relative to those in OVX control. Conclusion: The yield of Eucommia ulmoides Oliver extract has been successfully optimized using RSM. The extract exhibited strong effects on bone quality. Keywords: Optimization, Eucommia ulmoides, Box–Behnken design, Response surface methodology, Bone loss, Gen

Forward and Backward Information Retention for Accurate Binary Neural Networks

Weight and activation binarization is an effective approach to deep neural network compression and can accelerate the inference by leveraging bitwise operations. Although many binarization methods have improved the accuracy of the model by minimizing the quantization error in forward propagation, there remains a noticeable performance gap between the binarized model and the full-precision one. Our empirical study indicates that the quantization brings information loss in both forward and backward propagation, which is the bottleneck of training accurate binary neural networks. To address these issues, we propose an Information Retention Network (IR-Net) to retain the information that consists in the forward activations and backward gradients. IR-Net mainly relies on two technical contributions: (1) Libra Parameter Binarization (Libra-PB): simultaneously minimizing both quantization error and information loss of parameters by balanced and standardized weights in forward propagation; (2) Error Decay Estimator (EDE): minimizing the information loss of gradients by gradually approximating the sign function in backward propagation, jointly considering the updating ability and accurate gradients. We are the first to investigate both forward and backward processes of binary networks from the unified information perspective, which provides new insight into the mechanism of network binarization. Comprehensive experiments with various network structures on CIFAR-10 and ImageNet datasets manifest that the proposed IR-Net can consistently outperform state-of-the-art quantization methods