Neural network-based intrinsic structure relationship of TC20 titanium alloy for medical applications

Isothermal constant strain rate compression experiments were carried out on TC20 titanium alloy using a Gleeble- 1500 thermal simulation tester to investigate its high temperature flow behaviour at deformation temperatures of 750 - 900 °C and strain rates of 0,001 - 1 s-1. The results show that the flow stress basically decreases with increasing deformation temperature and increases with increasing strain rate. The correlation coefficients and mean relative errors were 0,998 and 5,06 % respectively, proving that the BP neural network-based intrinsic structure model is effective in predicting the flow stress of the alloy

Neural network-based intrinsic structure relationship of TC20 titanium alloy for medical applications

Isothermal constant strain rate compression experiments were carried out on TC20 titanium alloy using a Gleeble- 1500 thermal simulation tester to investigate its high temperature flow behaviour at deformation temperatures of 750 - 900 °C and strain rates of 0,001 - 1 s-1. The results show that the flow stress basically decreases with increasing deformation temperature and increases with increasing strain rate. The correlation coefficients and mean relative errors were 0,998 and 5,06 % respectively, proving that the BP neural network-based intrinsic structure model is effective in predicting the flow stress of the alloy

The Role of Atomic Structures on the Oxygen Corrosion of Polycrystalline Copper Surface

AbstractThe mechanical property of materials for pressure vessel, like steel, Ti, Cu and their alloys always turns out to be poor in the severely corrosive environment. The knowledge of oxygen corrosion on metal surface at atomic level is still lack. Using reactive molecular dynamic simulation, the oxygen corrosion behavior on polycrystalline copper is studied at the early stage of oxidation. Results indicate a higher reactivity at the grain boundary. The preferential dissociation of oxygen molecules at grain boundary is ascribed to the diffusion-related trapping effect and dissociation barriers. In addition, the difference of oxygen corrosion between grain boundary and grain on copper surface is elucidated in terms of the atomic-structure-related radial distribution functions. This study directly shows us the origin of intergranular oxygen corrosion and provides us useful information for the corrosion prevention, especially in the situation that the atomic structure changes under the thermal or mechanical loadings

Predicting Indoor Temperature Distribution Based on Contribution Ratio of Indoor Climate (CRI) and Mobile Sensors

In practical building control, quickly obtaining detailed indoor temperature distribution is necessary for providing satisfying personal comfort and improving building energy efficiency. The aim of this study is to propose a fast prediction method for indoor temperature distribution without knowing the thermal boundary conditions in practical applications. In this method, the index of contribution ratio of indoor climate (CRI), which represents the independent contribution of each heat source to the temperature distribution, has been combined with the air temperature collected by one mobile sensor at the height of the working area. Based on a typical office model, the effectiveness of using mobile sensors was discussed, and the influence of its acquisition height and acquisition distance on the prediction accuracy was analyzed as well. The results showed that the proposed prediction method was effective. When the sensors fixed on the wall were used to predict the indoor temperature distribution, the maximum average relative error was 27.7%, whereas when the mobile sensor was used to replace the fixed sensors, the maximum average relative error was 4.8%. This indicates that using mobile sensors with flexible acquisition location can help promote both reliability and accuracy of temperature prediction. In the human activity area, data from a set of mobile sensors were used to predict the temperature distribution at four heights. The prediction accuracy was 2.1%, 2.1%, 2.3%, and 2.7%, respectively. However, the influence of acquisition distance of mobile sensors on prediction accuracy cannot be ignored. The distance should be large enough to disperse the distribution of the acquisition points. Due to the influence of airflow, some distance between the acquisition points and the room boundaries should be given

Insights into the role of silicon and graphite in the electrochemical performance of silicon/graphite blended electrodes with a multi-material porous electrode model

Silicon/graphite blended electrodes are promising candidates to replace graphite in lithium ion batteries, benefiting from the high capacity of silicon and the good structural stability of carbon. Models have proven essential to understand and optimise batteries with new materials. However, most previous models treat silicon/graphite blends as a single “lumped” material, offering limited understanding of the behaviors of the individual materials and thus limited design capability. Here, we present a multi-material model for silicon/graphite electrodes with detailed descriptions of the contributions of the individual active materials. The model shows that silicon introduces voltage hysteresis to silicon/graphite electrodes and consequently a “plateau shift” during delithiation of the electrodes. There will also be competition between the silicon and graphite lithiation reactions depending on silicon/graphite ratio. A dimensionless competing factor is derived to quantify the competition between the two active materials. This is demonstrated to be a useful indicator for active operating regions for each material and we demonstrate how it can be used to design cycling protocols for mitigating electrode degradation. The multi-material electrode model can be readily implemented into full-cell models and coupled with other physics to guide further development of lithium ion batteries with silicon-based electrodes

Nodes Effect on the Bending Performance of Laminated Bamboo Lumber Unit

This research studied the ultimate bearing capacity of laminated bamboo lumber (LBL) unit and thereby calculated the maximum bending moment. The load-displacement chart for all specimens was obtained. Then the flexural capacity of members with and without bamboo nodes in the middle section was coMPared. The bending experiment phenomenon of LBL unit was concluded. Different failure modes of bending components were analysed and concluded. Finally, the bending behaviour of LBL units is coMPared with other bamboo and timber products. It is shown that the average ultimate load of BS members is 866.1 N, the average flexural strength is 101 MPa, the average modulus of elasticity is 8.3 GPa, and the average maximum displacement is 17.02 mm. The average ultimate load of BNS members is 1008.1 N, the average flexural strength is 118.02 MPa, the average modulus of elasticity is 9.9 GPa, and the average maximum displacement is 18.26 mm. Laminated bamboo lumber (LBL) unit without bamboo nodes (BNS) has relatively higher flexural strength coMPared with LBL unit with bamboo nodes (BS). The presence of bamboo nodes reduces the strength of the entire structure. Three failure modes were concluded for BS members, and two failure modes were observed for BNS members during the experimental process. According to a coMParison between the LBL unit and other products, the flexural strength and bending modulus of elasticity of the LBL unit are similar as bamboo scrimber and raw bamboo components, which is much higher than timber components

Quantum entangled Sagnac interferometer

SU(1,1) interferometer (SUI) is a novel type of interferometer that uses directly entangled quantum fields for sensing phase change. For rotational sensing, Sagnac geometry is usually adopted. However, because SUI depends on the phase sum of the two arms, traditional Sagnac geometry, when applied to SUI, will result in null signal. In this paper, we modify the traditional Sagnac interferometer by nesting SU(1,1) interferometers inside. We show that the rotational signal comes from two parts labeled as "classical" and "quantum", respectively, and the quantum part, where quantum entangled fields are used for sensing, has rotational signal enhanced by a factor related to the gain of the SUI.Comment: 5 pages, 3 figure

Single-step separation scheme and high-precision isotopic ratios analysis of Sr–Nd–Hf in silicate materials

Thermal ionization mass spectrometry and multiple-collector inductively coupled plasma mass spectrometry are considered to be “gold standards” for the determination of the isotope ratios of Sr–Nd and Hf in geological samples because of the extremely high precision and accuracy of these methods. However, the sample throughputs are hindered by time-consuming and tedious chemical procedures. Three-step ion exchange resin separation is traditionally employed to purify Sr–Nd–Hf from matrix elements. In this study, a one-step Sr–Nd–Hf separation scheme was developed to process geological samples. The separation scheme is based on the combined use of conventional AG50W-X12 cation-exchange resin and LN Spec extraction chromatographic material without any intervening evaporation step. The protocol not only prevents cross-contamination during operation using multiple-stage ion exchange resins but also significantly improves the efficiency of sample preparation. The stability of our chemical procedure was demonstrated by replicate measurements of 87Sr/86Sr, 143Nd/144Nd, and 176Hf/177Hf ratios in six international reference materials of silicate rocks. The analytical results obtained for these standard rocks compare well with the published data. The external reproducibility (2 SD, n = 10) of a BCR-2 standard sample was ±0.000018 for 87Sr/86Sr, ±0.000010 for 143Nd/144Nd, and ±0.000014 for 176Hf/177Hf

Ce–Nd separation by solid-phase micro-extraction and its application to high-precision 142Nd/144Nd measurements using TIMS in geological materials

In view of the low initial abundance of 146Sm, 142Nd anomalies are expected to be extremely small (less than 40 ppm), and their detection requires ultra-precise 142Nd/144Nd measurements. A rapid solid-phase micro-extraction (SPME) technique, using HEHEHP resin as sorbent, is established to completely separate Ce from rare earth element (REE) mixtures. This technique is applied to ultra-high-precision 142Nd/144Nd measurements in geological materials. In contrast to the traditional liquid–liquid micro-extraction (LLME) technique, the benefits of the SPME tandem column are high Nd recovery, low residual Ce (Ce/Nd 3.0. Thus, 142Ce interferences on 142Nd never exceed 1.3 ppm. Ultra-high-precision thermal ionization mass spectrometry analyses of silicate standards show that the internal precision of all runs are better than 4 ppm (2 RSE) for 142Nd/144Nd values. 142Nd/144Nd values for JNdi-1, JR-3, and BCR-2 have external precisions of ±4.8, ±4.4, and ±3.9 ppm (2 RSD), respectively. The external reproducibility is sufficient to distinguish and resolve 5 ppm anomalies in 142Nd/144Nd values