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Principal component analysis (PCA) is a widely used dimension reduction tool in the analysis of many kind of high-dimensional data. It is used in signal processing, mechanical engineering, psychometrics, and other fields under different…

统计方法学 · 统计学 2014-01-15 Ngoc Mai Tran , Maria Osipenko , Wolfgang Karl Haerdle

Multi-principal-element alloys, including high-entropy alloys, experience segregation or partially-ordering as they are cooled to lower temperatures. For Ti$_{0.25}$CrFeNiAl$_{x}$, experiments suggest a partially-ordered B2 phase, whereas…

材料科学 · 物理学 2021-05-11 Prashant Singh , A. V. Smirnov , Aftab Alam , Duane D. Johnson

Order versus disorder in the structure of materials plays a key role in the theoretical prediction of their properties. However, this structural description appears to be ineffective for new families of materials such as high entropy alloys…

Coherent perfect absorption (CPA) is an interferometric effect that guarantees full absorption in a lossy layer independently of its intrinsic losses. To date, it has been observed only at a single wavelength or narrow bandwidths, whereupon…

A general method is proposed for calculating a fully k-dependent, continuous, and causal spectral function A(k,E) within the recently introduced nonlocal version of the coherent-potential approximation (NLCPA). The method involves the…

材料科学 · 物理学 2009-11-11 G. M. Batt , D. A. Rowlands

Under plastic flow, multi-element high/medium-entropy alloys (HEAs/MEAs) commonly exhibit complex intermittent and collective dislocation dynamics owing to inherent lattice distortion and atomic-level chemical complexities. Using atomistic…

材料科学 · 物理学 2023-10-09 Kamran Karimi , Amin Esfandiarpour , Stefanos Papanikolaou

The binary Re$_{1-x}$Mo$_x$ alloys, known to cover the full range of solid solutions, were successfully synthesized and their crystal structures and physical properties investigated via powder x-ray diffraction, electrical resistivity,…

超导电性 · 物理学 2019-02-08 T. Shang , D. J. Gawryluk , J. A. T. Verezhak , E. Pomjakushina , M. Shi , M. Medarde , J. Mesot , T. Shiroka

Estimating the diffusion coefficients experimentally in a four-component inhomogeneous alloy following the conventional diffusion couple method by intersecting three couples at the same composition is difficult unless a small composition…

材料科学 · 物理学 2020-05-19 Anuj Dash , Neelamegan Esakkiraja , Aloke Paul

We present a new technique called contrastive principal component analysis (cPCA) that is designed to discover low-dimensional structure that is unique to a dataset, or enriched in one dataset relative to other data. The technique is a…

机器学习 · 统计学 2017-11-23 Abubakar Abid , Martin J. Zhang , Vivek K. Bagaria , James Zou

The Kubo-Greenwood equation, in combination with the first-principles Korringa-Kohn-Rostoker Coherent Potential Approximation (KKR-CPA) can be used to calculate the DC residual resistivity of random alloys at T = 0 K. We implemented this…

材料科学 · 物理学 2021-09-24 Vishnu Raghuraman , Yang Wang , Michael Widom

Conventional crystalline alloys usually possess a low atomic size difference in order to stabilize its crystalline structure. However, in this article, we report a single phase chemically complex alloy which possesses a large atomic size…

The successful synthesis of high entropy alloy (HEA) nanoparticles, a long-sought goal in materials science, opens a new frontier in materials science with applications across catalysis, electronics, structural alloys, and energetic…

材料科学 · 物理学 2021-05-27 Wissam A. Saidi , Waseem Shadid , Götz Veser

Recently, there has been a trend to combine independent component analysis and canonical polyadic decomposition (ICA-CPD) for an enhanced robustness for the computation of CPD, and ICA-CPD could be further converted into CPD of a 5th-order…

机器学习 · 统计学 2016-12-30 Xiao-Feng Gong , Cheng-Yuan Wang , Ya-Na Hao , Qiu-Hua Lin

Tensor robust principal component analysis (TRPCA) has received a substantial amount of attention in various fields. Most existing methods, normally relying on tensor nuclear norm minimization, need to pay an expensive computational cost…

数值分析 · 计算机科学 2017-12-29 Jonathan Q. Jiang , Michael K. Ng

We address the electron transport characteristics in bulk half-Heusler alloys with their compositions tuned to the borderline between topologically nontrivial semi-metallic and trivial semiconducting phases. The precise first-principles…

材料科学 · 物理学 2016-05-03 J. Kiss , S. W. D'Souza , L. Wollmann , C. Felser , K. Chadova , D. Ködderitzsch , J. Minár , H. Ebert , S. Chadov

Independent component analysis (ICA) is popular in many applications, including cognitive neuroscience and signal processing. Due to computational constraints, principal component analysis is used for dimension reduction prior to ICA…

统计方法学 · 统计学 2017-10-03 Benjamin B. Risk , David S. Matteson , David Ruppert

The structural parameters with stability upon Si incorporation and elastic, electronic, thermodynamic and optical properties of Ti3Al1-xSixC2 (0 \leq x \leq 1) are investigated systematically by the plane wave psedudopotential method based…

材料科学 · 物理学 2015-06-05 M. S. Ali , A. K. M. A. Islam , M. M. Hossain , F. Parvin

In this communication we have studied the electronic structure, magnetic and optical properties of bcc \fecr alloys in the ferromagnetic phase. We have used the augmented space recursion technique coupled with tight-binding linearized…

无序系统与神经网络 · 物理学 2007-06-12 Kartick Tarafder , Atisdipankar Chakrabarti , Subhradip Ghosh , Biplab Sanyal , Olle Eriksson , Abhijit Mookerjee

Properties of Cu-Ni solid solutions have long been studied in physical and materials sciences. Yet, their many-body properties have not been well understood. Here, we investigate ultrafast luminescence in near infrared region for…

Continuing our previous research on color image compression, we move towards spectral image compression. This enormous amount of data needs more space to store and more time to transmit. To manage this sheer amount of data, researchers have…

多媒体 · 计算机科学 2015-06-05 Muhammad Safdar , Ming Ronnier Luo , Xiaoyu Liu
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