Conventional Vickers and true instrumented indentation hardness determined by instrumented indentation tests

We evaluate Vickers hardness and true instrumented indentation test (IIT) hardness of 24 metals over a wide range of mechanical properties using just IIT parameters by taking into account the real contact morphology beneath the Vickers indenter. Correlating the conventional Vickers hardness, indentation contact morphology, and IIT parameters for the 24 metals reveals relationships between contact depths and apparent material properties. We report the conventional Vickers and true IIT hardnesses measured only from IIT contact depths; these agree well with directly measured hardnesses within ±6% for Vickers hardness and ±10% for true IIT hardness

Assessing the estimated life of UD drum of automatic transmission using material properties evaluated by stress rupture testing

High-cycle fatigue testing under different stress conditions must be performed in fatigue test methodology, and this requires expenditure both of money and time. The high-cycle fatigue test methodology also has the limitation of being a statistical approach to assessing estimated life that is not based on material properties. Thus to evaluate the estimated life of structural materials in transmissions in use, we need a novel assessment method that is economical, effective, easy to apply, and based on the material properties. In this study, we derive the relation between rupture stress and tensile properties taking into account fatigue rupture time, and developed a methodology for evaluating the estimated life of structural materials of transmission. Using this methodology, we performed stress rupture and fatigue tests for automatic transmission UD drum steels.Web of Science22358457

Nickel phosphide polymorphs with an active (001) surface as excellent catalysts for water splitting

Since the emergence of hydrogen generation by water-splitting as a core renewable-energy technology, the development of related catalysts with high efficiency, long-term stability, and low cost has been vigorously pursued. We report the temperature-controlled synthesis of two nickel phosphide polymorphs, Ni 2 P and Ni 5 P 4 , by phosphorization of Ni foil or foam using phosphine gas. The hexagonal phase Ni 2 P nanowires and Ni 5 P 4 nanosheets were grown on Ni substrates with vertical alignment, and uniformly exposed active (001) planes. The Ni 5 P 4 nanosheets possess significant stacking faults along the [0001] direction. Both Ni 2 P and Ni 5 P 4 exhibit excellent electrocatalytic activity toward the hydrogen evolution reaction (HER). Their overpotential for 10 mA cm −2 was 0.126 and 0.114 V, and the Tafel slope was 42 and 34 mV dec −1 in 0.5 M H 2 SO 4 electrolyte, respectively. A decrease in HER performance was observed for Ni 5 P 4 , but the change was negligible for Ni 2 P. Strain mapping using a precession-assisted nanobeam electron diffraction technique showed that only Ni 5 P 4 underwent degradation of basal (001) planes during HER, which explains the lower stability of catalytic activity. Furthermore, the Ni 2 P nanowires demonstrated excellent catalytic activity toward overall water splitting, which could be attributed to the stable surface as well as the highly conductive crystal structures

Clinical outcome prediction from analysis of microelectrode recordings using deep learning in subthalamic deep brain stimulation for Parkinson`s disease.

BackgroundDeep brain stimulation (DBS) of the subthalamic nucleus (STN) is an effective treatment for improving the motor symptoms of advanced Parkinson's disease (PD). Accurate positioning of the stimulation electrodes is necessary for better clinical outcomes.ObjectiveWe applied deep learning techniques to microelectrode recording (MER) signals to better predict motor function improvement, represented by the UPDRS part III scores, after bilateral STN DBS in patients with advanced PD. If we find the optimal stimulation point with MER by deep learning, we can improve the clinical outcome of STN DBS even under restrictions such as general anesthesia or non-cooperation of the patients.MethodsIn total, 696 4-second left-side MER segments from 34 patients with advanced PD who underwent bilateral STN DBS surgery under general anesthesia were included. We transformed the original signal into three wavelets of 1-50 Hz, 50-500 Hz, and 500-5,000 Hz. The wavelet-transformed MER was used for input data of the deep learning. The patients were divided into two groups, good response and moderate response groups, according to DBS on to off ratio of UPDRS part III score for the off-medication state, 6 months postoperatively. The ratio were used for output data in deep learning. The Visual Geometry Group (VGG)-16 model with a multitask learning algorithm was used to estimate the bilateral effect of DBS. Different ratios of the loss function in the task-specific layer were applied considering that DBS affects both sides differently.ResultsWhen we divided the MER signals according to the frequency, the maximal accuracy was higher in the 50-500 Hz group than in the 1-50 Hz and 500-5,000 Hz groups. In addition, when the multitask learning method was applied, the stability of the model was improved in comparison with single task learning. The maximal accuracy (80.21%) occurred when the right-to-left loss ratio was 5:1 or 6:1. The area under the curve (AUC) was 0.88 in the receiver operating characteristic (ROC) curve.ConclusionClinical improvements in PD patients who underwent bilateral STN DBS could be predicted based on a multitask deep learning-based MER analysis

Evaluation of high-temperature Vickers hardness using instrumented indentation system

Instrumented indentation testing is more advanced than conventional hardness testing in measuring various mechanical properties of materials. To evaluate these mechanical properties, information about indentation contact area is required. In particular, the deformation behavior of metals at high-temperatures seems to differ from that at room temperature, and thus for accurate evaluation of mechanical characteristics at high-temperatures, the high-temperature contact area should be used. In this study, an instrumented indentation system for high-temperatures was developed and measurement-errors caused by equipment temperature were calibrated. In addition, the pileup effect during indentation was studied at different temperatures. A new equation for the high-temperature contact area is proposed. For verification, conventional hardness testing was performed to compare the results with high-temperature instrumented indentation testing.close0

In Situ Temperature-Dependent Transmission Electron Microscopy Studies of Pseudobinary m GeTe·Bi2Te3 (m = 3-8) Nanowires and First-Principles Calculations

Phase-change nanowires (NWs) have emerged as critical materials for fast-switching nonvolatile memory devices. In this study, we synthesized a series of mGeTe·Bi2Te3 (GBT) pseudobinary alloy NWs - Ge3Bi2Te6 (m = 3), Ge4Bi2Te7 (m = 4), Ge5Bi2Te8 (m = 5), Ge6Bi2Te9 (m = 6), and Ge8Bi2Te11 (m = 8) - and investigated their composition-dependent thermal stabilities and electrical properties. As m decreases, the phase of the NWs evolves from the cubic (C) to the hexagonal (H) phase, which produces unique superlattice structures that consist of periodic 2.2-3.8 nm slabs for m = 3-8. In situ temperature-dependent transmission electron microscopy reveals the higher thermal stability of the compositions with lower m values, and a phase transition from the H phase into the single-crystalline C phase at high temperatures (400°C). First-principles calculations, performed for the superlattice structures (m = 1-8) of GBT and mGeTe·Sb2Te3 (GST), show an increasing stability of the H phase (versus the C phase) with decreasing m; the difference in stability being more marked for GBT than for GST. The calculations explain remarkably the phase evolution of the GBT and GST NWs as well as the composition-dependent thermal stabilities. Measurement of the current-voltage curves for individual GBT NWs shows that the resistivity is in the range 3-25 mΩ·cm, and the resistivity of the H phase is lower than that of the C phase, which has been supported by the calculations

Polymorphism of GeSbTe superlattice nanowires

Scaling-down of phase change materials to a nanowire (NW) geometry is critical to a fast switching speed of nonvolatile memory devices. Herein, we report novel composition-phase-tuned GeSbTe NWs, synthesized by a chemical vapor transport method, which guarantees promising applications in the field of nanoscale electric devices. As the Sb content increased, they showed a distinctive rhombohedral-cubic-rhombohedral phase evolution. Remarkable superlattice structures were identified for the Ge8Sb 2Te11, Ge3Sb2Te6, Ge 3Sb8Te6, and Ge2Sb 7Te4 NWs. The coexisting cubic-rhombohedral phase Ge 3Sb2Te6 NWs exhibited an exclusively uniform superlattice structure consisting of 2.2 nm period slabs. The rhombohedral phase Ge3Sb8Te6 and Ge2Sb 7Te4 NWs adopted an innovative structure; 3Sb2 layers intercalated the Ge3Sb2Te6 and Ge 2Sb1Te4 domains, respectively, producing 3.4 and 2.7 nm period slabs. The current-voltage measurement of the individual NW revealed that the vacancy layers of Ge8Sb2Te11 and Ge3Sb2Te6 decreased the electrical conductivity. © 2013 American Chemical Society

In Situ Temperature-Dependent Transmission Electron Microscopy Studies of Psedobinary mGeTe center dot Bi2Te3 (m=3-8) Nanowires and First-Principles Calculations

Phase-change nanowires (NWs) have emerged as critical materials for fast-switching nonvolatile memory devices. In this study, we synthesized a series of mGeTe.Bi2Te3 (GBT) pseudobinary alloy NWsGe(3)Bi(2)Te(6) (m = 3), Ge4Bi2Te7 (m = 4), Ge5Bi2Te8 (m = 5), Ge6Bi2Te9 (m = 6), and Ge8Bi2Te11 (m = 8)and investigated their composition-dependent thermal stabilities and electrical properties. As m decreases, the phase of the NWs evolves from the cubic (C) to the hexagonal (H) phase, which produces unique superlattice structures that consist of periodic 2.2-3.8 nm slabs for m = 3-8. In situ temperature-dependent transmission electron microscopy reveals the higher thermal stability of the compositions with lower m values, and a phase transition from the H phase into the single-crystalline C phase at high temperatures (400 degrees C). First-principles calculations, performed for the superlattice structures (m = 1-8) of GBT and mGeTe.Sb2Te3 (GST), show an increasing stability of the H phase (versus the C phase) with decreasing m; the difference in stability being more marked for GBT than for GST. The calculations explain remarkably the phase evolution of the GBT and GST NWs as well as the composition-dependent thermal stabilities. Measurement of the current-voltage curves for individual GBT NWs shows that the resistivity is in the range 3-25 mO.cm, and the resistivity of the H phase is lower than that of the C phase, which has been supported by the calculations.X1167sciescopu