Effect of transition metal impurities on the strength of grain boundaries in vanadium

Wu, Xiaoxiao; Kong, Xiang-Shan; You, Yu-Wei; Liu, Wei; Liu, C. S.; Chen, Junling; Luo, Guang–Nan

doi:10.1063/1.4961867

Cited by 21 publications

(3 citation statements)

References 57 publications

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“…The near future DFT applications for investigations of material properties and for prediction of novel materials with tailored technological specifications may be foreseen, and has already started, in four basic directions (for each area we provide several references, which coin the path): 1) finite temperature effects, [37,38,125,127,129,[131][132][133][134]160] 2) extended defects (grain boundaries, stacking faults, dislocations, etc. ), [8,98,[193][194][195][196][197][198][199][200][201][202][203][204][205][206][207][208][209] 3) materials of relevance for real applications (complex compositions, realistic conditions, etc. ), [31,63,68,159,160,176,179,[210][211][212][213][214][215] and 4) high-throughput search for novel materials [13,[215]…”

Section: Discussionmentioning

confidence: 99%

Atomistic Modeling‐Based Design of Novel Materials

Holec¹,

Zhou

Riedl

et al. 2017

Adv Eng Mater

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Modern materials science increasingly advances via a knowledge-based development rather than a trialand-error procedure. Gathering large amounts of data and getting deep understanding of non-trivial relationships between synthesis of materials, their structure and properties is experimentally a tedious work. Here, theoretical modeling plays a vital role. In this review paper we briefly introduce modeling approaches employed in materials science, their principles and fields of application. We then focus on atomistic modeling methods, mostly quantum mechanical ones but also Monte Carlo and classical molecular dynamics, to demonstrate their practical use on selected examples. of the Deutsche Forschungsgemeinschaft (DFG). D.M. acknowledges the Collaborative Research Center SFB-TR 87/2 "Pulsed high power plasmas for the synthesis of nanostructured functional layers" of the DFG. The computational results presented have been achieved in part using the Vienna Scientific Cluster (VSC).

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Section: Discussionmentioning

confidence: 99%

Atomistic Modeling‐Based Design of Novel Materials

Holec¹,

Zhou

Riedl

et al. 2017

Adv Eng Mater

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“…A detailed understanding of the atomistic mechanisms that improve the strength of Cu through the addition of small amounts of Ti can be achieved by using theoretical and computational modeling. Kohn–Sham , density functional theory (DFT) and other quantum mechanics-based calculation methods that provide highly accurate electronic structure measurements for alloys. , Several theoretical studies highlight the strengthening effect of metallic solutes when they are introduced into the grain boundaries (GBs) of metals, such as Cu, Ni, V, and Au . These calculations are limited to systems with only ∼100 atoms due to their computational cost .…”

Section: Introductionmentioning

confidence: 99%

“…Kohn–Sham 11 , 12 density functional theory (DFT) and other quantum mechanics-based calculation methods that provide highly accurate electronic structure measurements for alloys. 13 , 14 Several theoretical studies highlight the strengthening effect of metallic solutes when they are introduced into the grain boundaries (GBs) of metals, such as Cu, 15 Ni, 16 V, 17 and Au. 18 These calculations are limited to systems with only ∼100 atoms due to their computational cost.…”

Section: Introductionmentioning

confidence: 99%

Modeling the Effects of Varying the Ti Concentration on the Mechanical Properties of Cu–Ti Alloys

Fotopoulos,

O’Hern,

Shattuck

et al. 2024

ACS Omega

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The mechanical properties of CuTi alloys have been characterized extensively through experimental studies. However, a detailed understanding of why the strength of Cu increases after a small fraction of Ti atoms are added to the alloy is still missing. In this work, we address this question using density functional theory (DFT) and molecular dynamics (MD) simulations with the modified embedded atom method (MEAM) interatomic potentials. First, we performed calculations of the uniaxial tension deformations of small bicrystalline Cu cells using DFT static simulations. We then carried out uniaxial tension deformations on much larger bicrystalline and polycrystalline Cu cells by using MEAM MD simulations. In bicrystalline Cu, the inclusion of Ti increases the grain boundary separation energy and the maximum tensile stress. The DFT calculations demonstrate that the increase in the tensile stress can be attributed to an increase in the local charge density arising from Ti. MEAM simulations in larger bicrystalline systems have shown that increasing the Ti concentration decreases the density of the stacking faults. This observation is enhanced in polycrystalline Cu, where the addition of Ti atoms, even at concentrations as low as 1.5 atomic (at.) %, increases the yield strength and elastic modulus of the material compared to pure Cu. Under uniaxial tensile loading, the addition of small amounts of Ti hinders the formation of partial Shockley dislocations in the grain boundaries of Cu, leading to a reduced level of local deformation. These results shed light on the role of Ti in determining the mechanical properties of polycrystalline Cu and enable the engineering of grain boundaries and the inclusion of Ti to improve degradation resistance.

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High‐Throughput First‐Principles Calculations and Machine Learning of Grain Boundary Segregation in Metals

Scheiber,

Razumovskiy,

Peil

et al. 2024

Adv Eng Mater

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The segregation of solute elements to defects in metals plays a fundamental role for microstructure evolution and the materials performance. However, the available computational data is scattered and inconsistent due to the use of different simulation parameters and methods. We present a high throughput study on grain boundary and surface segregation together with their effect on grain boundary embrittlement using a consistent first‐principles methodology. The data is evaluated for most technologically relevant metals including Al, Cu, Fe, Mg, Mo, Nb, Ni, Ta, Ti, W with the majority of the elements from the periodic table treated as segregating elements. Trends amongst the solute elements are analysed and explained in terms of phenomenological models and the computed data is compared to available literature data. The computed first‐principles data is used for a machine learning investigation showing the capabilities for extrapolation from first‐principles calculation to the whole periodic table of solutes. The present work allows for comprehensive screening of new alloys with improved interface properties.This article is protected by copyright. All rights reserved.

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Effect of transition metal impurities on the strength of grain boundaries in vanadium

Cited by 21 publications

References 57 publications

Atomistic Modeling‐Based Design of Novel Materials

Atomistic Modeling‐Based Design of Novel Materials

Modeling the Effects of Varying the Ti Concentration on the Mechanical Properties of Cu–Ti Alloys

High‐Throughput First‐Principles Calculations and Machine Learning of Grain Boundary Segregation in Metals

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