2016
DOI: 10.1088/0965-0393/24/3/035013
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Ab initiocalculations of grain boundaries in bcc metals

Abstract: In this study we compute grain boundary (GB) properties for a large set of GBs in bcc transition metals with a special focus on W, Mo, Fe and W25at%Re using ab initio density functional theory (DFT) and semi-empirical second nearest neighbour modified embedded atom method (2NN-MEAM) potentials. The GB properties include GB energies, surface energies, work of separation and GB excess volume. We first identify the best simulation setup to evaluate these properties and then analyse them and compare them to variou… Show more

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Cited by 133 publications
(66 citation statements)
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“…The EAMs have also been shown to reproduce general trends in grain boundaries, but do not always reproduce the ground state structure and energy found with ab initio DFT methods [185]. DFT will give the most accurate description of the interaction of hydrogen with grain boundaries; however, the computationally expensive quantum mechanical treatment of the system means that grain boundary systems are limited to around a hundred atoms compared to thousands that can be simulated with empirical potentials.…”
Section: Atomistic Simulations Supporting the Hid Mechanismmentioning
confidence: 99%
“…The EAMs have also been shown to reproduce general trends in grain boundaries, but do not always reproduce the ground state structure and energy found with ab initio DFT methods [185]. DFT will give the most accurate description of the interaction of hydrogen with grain boundaries; however, the computationally expensive quantum mechanical treatment of the system means that grain boundary systems are limited to around a hundred atoms compared to thousands that can be simulated with empirical potentials.…”
Section: Atomistic Simulations Supporting the Hid Mechanismmentioning
confidence: 99%
“…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%
“…As can be seen in Figure 3, the Σ5 (210) [100] GB already used in [31] represents a reasonable compromise due to its minimal structure size (40 atoms) and due to the fact that its GB energy falls in the midrange of special GBs formation energies in Cr. There is a large offset between DFT and 2NN-MEAM data in the case of the Σ5 (210) [100] GB, but a similar deviation of 2NN-MEAM data from DFT has been observed in the case of Fe calculations, which can be traced back to a fitting of the 2NN-MEAM potentials to experimental surface energies that are in general below the values found with DFT [16]. However, as it has been shown also in [16], MEAM and DFT provide qualitatively the same results for Fe.…”
Section: Choice Of Representative Grain Boundary and Segregationmentioning
confidence: 84%
“…There is a large offset between DFT and 2NN-MEAM data in the case of the Σ5 (210) [100] GB, but a similar deviation of 2NN-MEAM data from DFT has been observed in the case of Fe calculations, which can be traced back to a fitting of the 2NN-MEAM potentials to experimental surface energies that are in general below the values found with DFT [16]. However, as it has been shown also in [16], MEAM and DFT provide qualitatively the same results for Fe. Therefore, 2NN-MEAM results may be used for a relative energy analysis.…”
Section: Choice Of Representative Grain Boundary and Segregationmentioning
confidence: 84%