查看更多>>摘要：A novel and efficient data mining method for the segmentation of microstructural images of low-carbon steel is presented. Microstructural characterization has been the focus of many works in the field of materials science because microstructure is the fundamental element in understanding the link between process and property. Recently, deep-learning-based methods have been actively employed for microstructural classification since it has shown outstanding performance for solving image classification problems. However, previous applications of deep learning models to microstructural classification revealed limitations in that not only do they require the time-consuming labeling process but it is also still difficult to obtain a satisfactory result, especially for steel microstructures containing substances developed by displacive transformation. In this study, we propose a rulebased segmentation method that not only works without labeled images but also requires no prior knowledge of the number of microstructural constituents in each image. This unsupervised inference algorithm captures the morphological features of each microstructure and automatically finds the optimal number of microstructures having similar characteristics using a Bayesian Gaussian mixture model. The viability of our method is demonstrated by qualitative and quantitative evaluations with optical microscopy images of steel composed of different microstructures taken under different imaging conditions.
Kas, J. J.Vila, F. D.Pemmaraju, C. D.Prange, M. P....
10页
查看更多>>摘要：Optical constants characterize the interaction of materials with light and are important properties in material design. Here we present a Python-based Corvus workflow for simulations of full spectrum optical constants from the visible and ultraviolet to hard x-ray wavelengths based on the real-space Green's function code FEFF10 and structural data from the Materials Project (MP). The Corvus workflow manager and its associated tools provide an interface to FEFF10 and the MP database. The workflow parallelizes the FEFF computations of optical constants over all absorption edges for each material in the MP database specified by a unique MP-ID. The workflow tools determine the distribution of computational resources needed for that case. Similarly, the optical constants for selected sets of materials can be computed in a single-shot. To illustrate the approach, we present results for several elemental solids in the periodic table, as well as a sample compound, and compare our predictions with experimental results. In addition, we provide a database of calculated results for all elements for which there is a stable elemental solid at standard conditions available in the Materials Project database. As in x-ray absorption spectra, these results are interpreted in terms of an atomic-like background and fine-structure contributions.
Miranda, Dayvid de Sousade Vasconcelos, Fabricio MoraisMeunier, VincentGirao, Eduardo Costa...
8页
查看更多>>摘要：A variety of graphene nanoribbons with complex edge structures have been synthesized over the last decade, including a rich set of structures where specific carbon atoms are substituted by heteroatoms. While a majority of existing studies have focused on nitrogen substitution, understanding how substitutional boron affects the electronic structure is a fundamental issue of interest, as boron is expected to offer complementary features relative to nitrogen when compared to carbon. We performed first-principles simulations to investigate the electronic properties of boron-substituted graphitic nanowiggles (GNWs). We show that the insertion of a B heteroatom induces marked changes in the electronic behavior of the nanoribbons, as well as the emergence of non-trivial spin-polarized distributions, resulting in systems with high potential for use in nanoscale devices.
查看更多>>摘要：The phase stability and mechanical properties of N-metallic carbides (N = 2-5) are assessed using entropy forming ability (EFA), mixing enthalpy, and Mazhnik-Oganov ab initio model of mechanical properties. EFA quantifies configurational disorder of solid solutions and is currently used to predict the phase stability and assess the hardness of high-entropy carbides with 5 transitional metals on the metallic sublattice. In this work, we use the concept of EFA for the 13 N-metallic carbides (N = 2-5), four of which are investigated for the first time. Additionally, we propose a semi-empiric version of the Mazhnik-Oganov model and perform micro-indentation testing of the investigated compositions to verify the model's capabilities. The proposed approach allows for a fast modeling and microindentation-based screening of the most promising carbide solid solutions for more detailed characterization.
Garcia-Cardona, CristinaFernandez-Godino, M. GiselleO'Malley, DanielBhattacharya, Tanmoy...
9页
查看更多>>摘要：Simulation of the crack network evolution on high strain rate impact experiments performed in brittle materials is very compute-intensive. The cost increases even more if multiple simulations are needed to account for the randomness in crack length, location, and orientation, which is inherently found in real-world materials. Constructing a machine learning emulator can make the process faster by orders of magnitude. There has been little work, however, on assessing the error associated with their predictions. Estimating these errors is imperative for meaningful overall uncertainty quantification. In this work, we extend the heteroscedastic uncertainty estimates to bound a multiple output machine learning emulator. We find that the response prediction is accurate within its predicted errors, but with a somewhat conservative estimate of uncertainty.
查看更多>>摘要：Nodal line semimetals/metals (NLSMs), hosting band-crossings in one dimension, are expected to exhibit exotic physical phenomena, like drumhead surface states. The conventional NLSMs host a linear energy dispersion around it. Recently, it has been predicted that NLs hosting a high-order energy dispersion may also be stabilized in nonmagnetic systems. However, it still remains challenges to find their counterpart in magnetic systems. Here, based on first-principles calculation and theoretical analysis, we predict for the first-time that RbFeF3, a ferromagnetic material, has a high-order NL without spin-orbital coupling (SOC). We give the symmetry conditions which stabilizes the quadratic nodal lines (QNLs), thus an effective Hamiltonian is constructed to demonstrate its existence. Different from the nonmagnetic nodal lines, they come from the same single spin channel, achieving a 100% spin polarization. Interestingly, it exhibits a "torus" drumhead surface states in the whole Brillouin zone, which is quite different from that of linear NL. Under symmetry breaking, the QNL could be reduced into a pair of linear type-II NLs by tuning the magnetization direction. Our work provides a ideal magnetic material with high-order NL which has not been observed before.
查看更多>>摘要：Gaussian process regression machine learning with a physically-informed kernel is used to model the phase compositions of nickel-base superalloys. The model delivers good predictions for laboratory and commercial superalloys, with R-2 > 0.8 for all but two components of each of the gamma and gamma' phases, and R-2 = 0.924 (RMSE = 0.063) for the gamma' fraction. For four benchmark SX-series alloys the methodology predicts the gamma' phase composition with RMSE = 0.006 and the fraction with RMSE = 0.020, superior to the 0.007 and 0.021 respectively from CALPHAD. Furthermore, unlike CALPHAD Gaussian process regression quantifies the uncertainty in predictions, and can be retrained as new data becomes available.
Papadopoulou, Konstantina A.Chroneos, AlexanderChristopoulos, Stavros-Richard G.
4页
查看更多>>摘要：Two-dimensional materials such as MXenes are being actively considered by the community for energy storage applications. Here, we employ Density Functional Theory (DFT) to model O and S terminated Zr2C MXenes. We find that the most energetically favourable positions for the termination atoms to sit are on top of the second-layer Zr atoms, in agreement with previous studies. Finally, arbitrarily placing a Li-ion on the surface of the MXenes, we apply the Bond Valence Sum (BVS) model to calculate Bond Valence Site Energies (BVSE). We show that BVS is a good substitute for DFT particularly for diffusion pathways, as it yields much faster results and with good accuracy, with the added advantage of not needing exact positions for the atoms. BVS can, therefore, be used as a quick filter when searching for low migration barriers in MXenes and two-dimensional materials.
查看更多>>摘要：A novel class of two-dimensional auxetic structures based on the pentagon motif is proposed. Their mechanical properties are investigated by combining molecular mechanics simulations with a simple three-parameter mechanical model which assumes perfectly elastic behavior. It is predicted that the proposed structures - termed as double re-entrant honeycomb - may possess unique mechanical characteristics, which include complete and perfect auxeticity, as well as the negative Poisson's ratio observed in both the tensile and compressive regimes. The behavior of the considered structures is explained in relation to well-known auxetic models. It is shown that the considered structures simultaneously implement three different mechanisms leading to a negative Poisson's ratio: the opening of the re-entrant units, the rotation of the squares, and the flattening effect.
NSTL
Elsevier