The microstructure of the as-cast AlCoCrFeNi high entropy alloy has been investigated by transmission electron microscopy and atom probe tomography. The alloy shows a very pronounced microstructure ...with clearly distinguishable dendrites and interdendrites. In both regions a separation into an Al–Ni rich matrix and Cr–Fe-rich precipitates can be observed. Moreover, fluctuations of single elements within the Cr–Fe rich phase have been singled out by three dimensional atom probe measurements. The results of investigations are discussed in terms of spinodal decomposition of the alloying elements inside the Cr–Fe-rich precipitates.
► The Alloy separates into an Al–Ni rich matrix and Cr–Fe-rich precipitates. ► Concentration depth profiles in the Cr–Fe rich regions show opposite fluctuations. ► They have been attributed to the spinodal decomposition of Fe- and Cr-rich phases. ► The Al–Ni rich region corresponds well to the Al–Ni rich phases observed in the 6 component AlCoCrCuFeNi alloy.
Homogenizing at 1220°C for 20 h and subsequent aging at 900°C for 5 h and 50 h of a novel Al
10
Co
25
Cr
8
Fe
15
Ni
36
Ti
6
compositionally complex alloy (high-entropy alloy) produces a ...microstructure consisting of an L1
2
ordered
γ
′ phase embedded in a face-centered cubic solid-solution
γ
matrix together with needle-like B2 precipitates (NiAl). The volume fraction of
γ
′ phase is ~46% and of needle-like B2 precipitates <5%, which is in accordance with the prediction of calculation of phase diagram method (CALPHAD using Thermo-Calc software with TTNi7 database; Thermo-Calc Software, Stockholm, Sweden). The high-temperature tensile tests were carried out at room temperature, 600°C, 700°C, 800°C, and 1000°C. The tensile strength as well as the elongation to failure of both heat-treated specimens is very high at all tested temperatures. The values of tensile strength has been compared with literature data of well-known Alloy 800H and Inconel 617, and is discussed in terms of the observed microstructure.
Aims and background:Mutations in the TARDBP gene, which encodes the TAR DNA binding protein (TDP-43), have been described in individuals with familial and sporadic amyotrophic lateral sclerosis ...(ALS). We screened the TARDBP gene in 285 French sporadic ALS patients to assess the frequency of TARDBP mutations in ALS.Results:Six individuals had potentially deleterious mutations of which three were novel including a Y374X truncating mutation and P363A and A382P missense mutations. This suggests that TARDBP mutations may predispose to ALS in approximately 2% of the individuals followed in this study.Conclusion:Our findings, combined with those from other collections, brings the total number of mutations in unrelated ALS patients to 17, further suggesting that mutations in the TARDBP gene have an important role in the pathogenesis of ALS.
► High entropy alloys are investigated by three dimensional atom probe. ► The brittle Al23Co15Cr23Cu8Fe15Ni16 alloy decomposes into two body centred cubic phases. ► Ductile Al8Co17Cr17Cu8Fe17Ni33 ...shows two prominent face-centred cubic phases. ► Results are compared with equilibrium phases predicted by Thermo-Calc.
Al23Co15Cr23Cu8Fe15Ni16 and Al8Co17Cr17Cu8Fe17Ni33 high entropy alloys were investigated by scanning electron microscopy, transmission electron microscopy and three dimensional atom probe. While the brittle Al23Co15Cr23Cu8Fe15Ni16 alloy decomposes during solidification mainly into two body centred cubic phases, the ductile Al8Co17Cr17Cu8Fe17Ni33 shows two prominent face-centred cubic phases. Al23Co15Cr23Cu8Fe15Ni16 consists of Fe–Cr-rich and Cu-rich intermetallic phases embedded in an Al–Ni-rich solid solution matrix. The microstructure of Al8Co17Cr17Cu8Fe17Ni33 is mainly characterized by two phases. Nano-sized precipitates enriched mainly in Ni are embedded in a matrix depleted in Al and Cu. The phases observed in both high entropy alloys are compared with the equilibrium phases predicted by Thermo-Calc simulation.
Driver behavior refers to the actions and attitudes of individuals behind the wheel of a vehicle. Poor driving behavior can have serious consequences, including accidents, injuries, and fatalities. ...One of the main disadvantages of poor driving behavior is the increased risk of road accidents, higher insurance premiums, fines, and even criminal charges. The primary aim of our study is to detect driver behavior early with high-performance scores. The publicly available smartphone motion sensor data is utilized to conduct our study experiments. A novel LR-RFC (Logistic Regression Random Forest Classifier) method is proposed for feature engineering. The proposed LR-RFC method combines the logistic regression and random forest classifier for feature engineering from the motion sensor data. The original smartphone motion sensor data is input into the LR-RFC method, generating new probabilistic features. The newly extracted probabilistic features are then input to the applied machine learning methods for predicting driver behavior. The study results show that the proposed LR-RFC approach achieves the highest performance score. Extensive study experiments demonstrate that the random forest achieved the highest performance score of 99% using the proposed LR-RFC method. The performance is validated using k-fold cross-validation and hyperparameter optimization. Our novel proposed study has the potential to revolutionize the early detection of driver behavior to avoid road accidents.
Bio-based composites with passive control layers were investigated by means of a comprehensive set of experiments. The structure, composed of an exterior layer of PLA/Flax and an inserted rubber ...layer, were manufactured using 3D printing technology. Tensile tests on PLA/Flax and rubber specimens revealed that it exhibited higher stiffness, whereas rubber demonstrated superior elongation. Additionally, three-point bending tests were conducted on 3D-printed composites with varying viscoelastic layer thicknesses (VL) to assess their bending performance. However, the composite with a single 1-mm thick viscoelastic layer (V
1
t
1
) showed optimal deflection and stiffness compared to counterparts with different viscoelastic layers. Furthermore, resonance vibration experiments were performed to investigate dynamic parameters such as frequencies and modal loss factors. Based on the experiments, it was determined that V
1
t
1
was the composite that offered the optimal compromise between mechanical and vibration behavior due to its excellent damping characteristics.
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