Thermodynamic re-modeling of the Yb-Sb system aided by first-principles calculations

Palma, Jorge Paz Soldan; Chong, Xiaoyu; Wang, Yi; Shang, Shun‐Li; Liu, Zhe

doi:10.1016/j.calphad.2023.102541

Cited by 3 publications

(1 citation statement)

References 58 publications

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“…), bulk modulus, molar volume, and symmetry functions of atomic positions extracted from the results of calculations in the framework of density functional theory [21]. Paz Soldan Palma et al [22] used calculated formation enthalpies from the materials project to determine materials stability in terms of convex hulls. Kruthika and Ravindran [23] extracted the data for 90 perovskites from materials project and ICSD databases to predict optoelectronic properties.…”

Section: Introductionmentioning

confidence: 99%

Machine Learning-Based Prediction of Elastic Properties Using Reduced Datasets of Accurate Calculations Results

Sidnov,

Konov,

Smirnova

et al. 2024

Metals

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In this paper, the applicability of machine learning for predicting the elastic properties of binary and ternary bcc Ti and Zr disordered alloys with 34 different doping elements is explored. The original dataset contained 3 independent elastic constants, bulk moduli, shear moduli, and Young’s moduli of 1642 compositions calculated using the EMTO-CPA method and PAW-SQS calculation results for 62 compositions. The architecture of the system is made as a pipeline of a pair of predicting blocks. The first one took as the input a set of descriptors of the qualitative and quantitative compositions of alloys and approximated the EMTO-CPA data, and the second one took predictions of the first model and trained on the results of the PAW-SQS calculations. The main idea of such architecture is to achieve prediction accuracy at the PAW-SQS level, while reducing the resource intensity for obtaining the training set by a multiple of the ratio of the training subsets sizes corresponding to the two used calculation methods (EMTO-CPA/PAW-SQS). As a result, model building and testing methods accounting for the lack of accurate training data on the mechanical properties of alloys (PAW-SQS), balanced out by using predictions of inaccurate resource-effective first-principle calculations (EMTO-CPA), are demonstrated.

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Section: Introductionmentioning

confidence: 99%

Machine Learning-Based Prediction of Elastic Properties Using Reduced Datasets of Accurate Calculations Results

Sidnov,

Konov,

Smirnova

et al. 2024

Metals

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Multifunctional Yb₃Si₂C₂ with High‐Performance Terahertz Shielding for Future 6G Communications

Qiu,

Zhou,

Huang

et al. 2024

Adv Funct Materials

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The development of next‐generation 6G communications is anticipated to expand into extreme environments, necessitating superior terahertz (THz) electromagnetic interference (EMI) shielding materials. Herein, structural stability, electronic and optical properties of rare earth silicide carbide Yb3Si2C2 are investigated using first principles density functional calculations and semi‐classical Boltzmann transport theory. The calculation results show Yb3Si2C2 is determined to be experimentally synthesized with high temperature stability with a certain fluctuating C2 pair orientation. In addition, Yb3Si2C2 is identified as a soft, tough, and damage‐resistant ceramic with low shear deformation resistance and easy cleavage, ensuring its durability in irradiation environments. Due to the layered structure and excellent electrical conductivity, Yb3Si2C2 demonstrates high reflectivity and low transmittance for terahertz electromagnetic waves, along with 62% solar absorptivity and 33% IR emissivity. Remarkably, the total shielding effectiveness of Yb3Si2C2 with thicknesses of 5 µm and above follows the widely‐used Simon's formula. The average total shielding effectiveness of 5 µm‐thick and 10 µm‐thick Yb3Si2C2 across the entire THz region reaches 63 and 110 dB, respectively, which turns out to be the top compared to the results reported. Therefore, the multifunctional intrinsic properties of Yb3Si2C2 materials hold great promise for miniaturized, high‐performance terahertz EMI shielding, even in extreme environments.

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Study on In Situ Formation of Intermetallic Compounds and Oxygen Adsorption of Ni/Al Coating

Zhang

et al. 2023

J Therm Spray Tech

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Thermodynamic re-modeling of the Yb-Sb system aided by first-principles calculations

Cited by 3 publications

References 58 publications

Machine Learning-Based Prediction of Elastic Properties Using Reduced Datasets of Accurate Calculations Results

Machine Learning-Based Prediction of Elastic Properties Using Reduced Datasets of Accurate Calculations Results

Multifunctional Yb₃Si₂C₂ with High‐Performance Terahertz Shielding for Future 6G Communications

Study on In Situ Formation of Intermetallic Compounds and Oxygen Adsorption of Ni/Al Coating

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Thermodynamic re-modeling of the Yb-Sb system aided by first-principles calculations

Cited by 3 publications

References 58 publications

Machine Learning-Based Prediction of Elastic Properties Using Reduced Datasets of Accurate Calculations Results

Machine Learning-Based Prediction of Elastic Properties Using Reduced Datasets of Accurate Calculations Results

Multifunctional Yb3Si2C2 with High‐Performance Terahertz Shielding for Future 6G Communications

Study on In Situ Formation of Intermetallic Compounds and Oxygen Adsorption of Ni/Al Coating

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Product

Resources

About

Multifunctional Yb₃Si₂C₂ with High‐Performance Terahertz Shielding for Future 6G Communications