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The prediction of construction project cost plays a core role in engineering construction projects. However, the current prediction involves a multi-dimensional and dynamically variable system, and each major category can be further subdivided into many specific factors. Meanwhile, variables’ relationships present a complex network of nonlinearity and interaction, which seriously affected the prediction accuracy. To solve this problem, we proposed a dual-stacking construction cost prediction method based on variable stacking and model stacking (DSCostPred). This method emphasizes that classifying variables and applying different algorithms respectively can avoid the impact of variables’ functional differences. First, the variables are pre-classified to avoid mutual interference among them. Then, to learn the attribute and function positioning, as well as the complex interaction among them, different types of models are utilized to learn the variables. In algorithm design, to achieve the organic combination of multiple attributes and multiple models, a variable stacking is introduced into stacking ensemble learning to form collaborative predictions with model stacking. This method was compared with the classical method on real data, and the results show the superior performance. In addition, the ablation experiments and SHAP analysis also demonstrated the feasibility of the double-stacking idea we proposed.

High-entropy alloys (HEAs) are an intriguing new class of metallic materials due to their unique mechanical behavior. Achieving a detailed understanding of structure–property relationships in these materials has been challenged by the compositional disorder that underlies their unique mechanical behavior. Accordingly, in this work, we employ first-principles calculations to investigate the nature of local chemical order and establish its relationship to the intrinsic and extrinsic stacking fault energy (SFE) in CrCoNi medium-entropy solid-solution alloys, whose combination of strength, ductility, and toughness properties approaches the best on record. We find that the average intrinsic and extrinsic SFE are both highly tunable, with values ranging from −43 to 30 mJ·m−2 and from −28 to 66 mJ·m−2, respectively, as the degree of local chemical order increases. The state of local ordering also strongly correlates with the energy difference between the face-centered cubic (fcc) and hexagonal close-packed (hcp) phases, which affects the occurrence of transformation-induced plasticity. This theoretical study demonstrates that chemical short-range order is thermodynamically favored in HEAs and can be tuned to affect the mechanical behavior of these alloys. It thus addresses the pressing need to establish robust processing–structure–property relationships to guide the science-based design of new HEAs with targeted mechanical behavior.

Mechanical properties are fundamental to structural materials, where dislocations play a decisive role in describing their mechanical behavior. Although the high-yield stresses of multiprincipal element alloys (MPEAs) have received extensive attention in the last decade, the relation between their mechanistic origins remains elusive. Our multiscale study of density functional theory, atomistic simulations, and high-resolution microscopy shows that the excellent mechanical properties of MPEAs have diverse origins. The strengthening effects through Shockley partials and stacking faults can be decoupled in MPEAs, breaking the conventional wisdom that low stacking fault energies are coupled with wide partial dislocations. This study clarifies the mechanistic origins for the strengthening effects, laying the foundation for physics-informed predictive models for materials design.

Landslide disasters occur frequently in the mountainous areas in southwest China, which pose serious threats to the local residents. Interferometry Synthetic Aperture Radar (InSAR) provides us the ability to identify active slopes as potential landslides in vast mountainous areas, to help prevent and mitigate the disasters. Quickly and accurately identifying potential landslides based on massive SAR data is of great significance. Taking the national highway near Wenchuan County, China, as study area, this paper used a Stacking-InSAR method to quickly and qualitatively identify potential landslides based on a total of 40 Sentinel SAR images acquired from November 2017 to March 2019. As a result, 72 active slopes were successfully detected as potential landslides. By comparing the results from Stacking-InSAR with the results from the traditional SBAS-InSAR (Small Baselines Subset) time series method, it was found that the two methods had a high consistency, with 81.7% potential landslides identified by both of the two methods. A detailed comparison on the detection differences was performed, revealing that Stacking-InSAR, compared to SBAS-InSAR may miss a few active slopes with small spatial scales, small displacement levels and the ones affected by the atmosphere, while it has good performance on poor-coherence regions, with the advantages of low technical requirements and low computation labor. The Stacking-InSAR method would be a fast and powerful method to qualitatively and effectively identify potential landslides in vast mountainous areas, with a comprehensive understanding of its specialty and limitations.

This paper focuses on the impact of gate stacking (SiO2+HfO2) on dopingless vertical nanowire TFET (designed with gate-on-source technique) with an equivalent oxide thickness (EOT) of 0.8 nm and SiO2 thickness of 0.5 nm. Here, the charge plasma technique is used for doping on an intrinsic silicon substrate by using platinum (with work function of 5.93 eV) on the source side metal and hafnium (with work function of 3.9 eV) as the gate 1 metal. The proposed gate-stacked charge plasma vertical nanowire tunnel FET (GS-CPVNWTFET) device is simulated in ATLAS-2D, and the performance metrics are investigated. The paper compares three different combinations of SiO2 and HfO2 (with SiO2 thicknesses of 0.3 nm, 0.4 nm and 0.5 nm) and then the analog and RF parameters, such as ID-VGS and ID-VDS characteristics, input transconductance (gm), transconductance to drive current ratio (gm/ID), gate to source capacitance (CGS), gate to drain capacitance (CGD), total gate capacitance (CGG), unity gain cut-off frequency (fT), output transconductance (gd), output resistance (rO), early voltage (VEA), intrinsic gain (AV) and gain bandwidth product (GBP), and the structural performance for all three combinations are obtained. The proposed GS-CPVNWTFET device exhibits ION of 19.182 µA/µm, IOFF of 7.05 × 10−17 A/µm, ratio of ON current to OFF current (ION/IOFF) ~ 2.72 × 1011, subthreshold slope (SS) of 10.80 mV/decade and DIBL of 3.17 mV/V. Later, a comparison is carried out between conventional CPVNWTFET and gate-stacked CPVNWTFET, and it is observed that the proposed GS-CPVNWTFET device with gate-on-source technique shows better analog and structural performance.

Materials with low stacking fault energies have been long sought for their many desirable mechanical attributes. Although there have been many successful reports of low stacking fault alloys (for example Cu-based and Mg-based), many have lacked sufficient strength to be relevant for structural applications. The recent discovery and development of multicomponent equiatomic alloys (or high-entropy alloys) that form as simple solid solutions on ideal lattices has opened the door to investigate changes in stacking fault energy in materials that naturally exhibit high mechanical strength. We report in this article our efforts to determine the stacking fault energies of two- to five-component alloys. A range of methods that include ball milling, arc melting, and casting, is used to synthesize the alloys. The resulting structure of the alloys is determined from x-ray diffraction measurements. First-principles electronic structure calculations are employed to determine elastic constants, lattice parameters, and Poisson’s ratios for the same alloys. These values are then used in conjunction with x-ray diffraction measurements to quantify stacking fault energies as a function of the number of components in the equiatomic alloys. We show that the stacking fault energies decrease with the number of components. Nonequiatomic alloys are also explored as a means to further reduce stacking fault energy. We show that this strategy leads to a means to further reduce the stacking fault energy in this class of alloys.

To enhance performance under low‐velocity impact (LVI), the ply stacking sequence of a composite laminate must be carefully selected. To guarantee that the laminate can sustain the projected impact energy, the impact load should be carefully evaluated during the design phase. To obtain an optimized stacking layup orientation, the damage behaviors of excellent specific strength carbon fiber–reinforced polymer (CFRP) composite laminates with stacking sequences of [0°] 8 (unidirectional), [0°/90°] 2s (cross‐ply), [0°/+45°/−45°/90°] s (quasi‐isotropic), and [0°/−30°/−60°/−90°/90°/60°/30°/0°] (antisymmetric) were numerically investigated under LVI. Throughout the investigation, 1 to 2 kg of impactors were employed at a velocity of 3.835 m/s. The damage initiations in composite laminates were assessed using both Hashin’s criteria and the Puck–Schurmann criterion. For predicting delamination between composite plies, the quadratic nominal stress delamination failure criteria were applied. For the study of composite damage behavior under LVI, the time‐dependent changes in impact‐resisting force, force versus displacement, and time‐dependent variations in the internal energy of the composite laminates were taken into consideration. The predicted results show that in comparison with the other three configurations, the composite laminate with a ply arrangement of [0°/+45°/−45°/90°] s (quasi‐isotropic) exhibited a stronger impact‐resisting force, smaller peak displacement, fewer deformations, and a smaller amount of damage with superior rebound energy.

In this work, the effect of ply stacking sequence of carbon/epoxy laminates subjected to flexural, tensile and impact loading was investigated. Five laminates with different stacking configurations were produced using the hand-laying-up technique. This includes a unidirectional laminate, cross-ply laminates, and quasi-isotropic laminates. Following the autoclave curing process, the responses of the composites to bending, tension and impact force were determined according to ASTM standards, and their corresponding strength, stiffness as well as impact energy were evaluated. Likewise, the flexural failure mode associated with each laminate was characterised using an optical microscope. The unidirectional laminates have higher flexural and tensile strength compared to the cross-ply and quasi-isotropic laminates. Moreover, as a result of material symmetry, the flexural and tensile modulus of symmetric cross-ply laminate improved by 59.5% and 3.97% compared to the unsymmetric counterpart. Furthermore, the quasi-isotropic laminates with absorption energy of 116.2 kJ/m2 and 115.12 kJ/m2, respectively have higher impact resistance compared to other samples.

Multilayer graphene and its stacking order provide both fundamentally intriguing properties and technological engineering applications. Several approaches to control the stacking order have been demonstrated, but a method of precisely controlling the number of layers with desired stacking sequences is still lacking. Here, we propose an approach for controlling the layer thickness and crystallographic stacking sequence of multilayer graphene films at the wafer scale via Cu–Si alloy formation using direct chemical vapour deposition. C atoms are introduced by tuning the ultra-low-limit CH4 concentration to form a SiC layer, reaching one to four graphene layers at the wafer scale after Si sublimation. The crystallographic structure of single-crystalline or uniformly oriented bilayer (AB), trilayer (ABA) and tetralayer (ABCA) graphene are determined via nano-angle-resolved photoemission spectroscopy, which agrees with theoretical calculations, Raman spectroscopy and transport measurements. The present study takes a step towards the layer-controlled growth of graphite and other two-dimensional materials.Well-controlled multilayer graphene up to four layers thick with a defined stacking sequence is synthesized via SiC alloy formation on a Cu(111) substrate.

The layer stacking order in 2D materials strongly affects functional properties and holds promise for next-generation electronic devices. In bulk, octahedral MoTe 2 possesses two stacking arrangements, the ferroelectric Weyl semimetal T d phase and the higher-order topological insulator 1T′ phase. However, in thin flakes of MoTe 2 , it is unclear if the layer stacking follows the T d , 1T′, or an alternative stacking sequence. Here, we use atomic-resolution scanning transmission electron microscopy to directly visualize the MoTe 2 layer stacking. In thin flakes, we observe highly disordered stacking, with nanoscale 1T′ and T d domains, as well as alternative stacking arrangements not found in the bulk. We attribute these findings to intrinsic confinement effects on the MoTe 2 stacking-dependent free energy. Our results are important for the understanding of exotic physics displayed in MoTe 2 flakes. More broadly, this work suggests c -axis confinement as a method to influence layer stacking in other 2D materials. The layer stacking order in 2D materials can be used to control functional properties. Here, the authors find a thickness effect, where thin flakes of MoTe 2 display stacking arrangements different from bulk crystals.