Topologically close-packed phases: Deposition and formation mechanism of metastable β-W in thin films

Liu, J.; Barmak, K.

doi:10.1016/j.actamat.2015.11.049

Cited by 38 publications

(23 citation statements)

References 24 publications

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“…Prior work had shown that the introduction of nitrogen during sputter deposition of tungsten promotes the formation of -W phase. 15 The N 2 pressure was calibrated in the absence of Ar by filling the load-lock chamber to a given pressure and determining the nitrogen pressure in the deposition chamber at the steady-state leak rate through the gate valve separating the deposition chamber from the load-lock chamber. The N 2 pressure in the deposition chamber was 1.2 ⇥ 10 5 Torr for the current study.…”

Section: A Experimentsmentioning

confidence: 99%

“…The N 2 pressure in the deposition chamber was 1.2 ⇥ 10 5 Torr for the current study. 15 Following the deposition of the trilayer stack of Cu/SiO 2 / -W and prior to lift-off to generate free-standing films for DSC measurements, the films were examined by ✓-2✓ X-ray diffraction (XRD) scans. The scans were done out-of-plane, i.e., with the scattering vector normal to the film plane, using a Rigaku Ultima III diffractometer at the Center for Functional Nanomaterials at Brookhaven National Laboratory.…”

Section: A Experimentsmentioning

confidence: 99%

“…Recently, a promising method for preparation of -W films that allows deposition of this phase with thicknesses as small as a few nanometers and as large as 1 µm has been reported. 15 Micrometer-thick, free-standing films have been successfully used for thermodynamic and kinetic studies in a number of systems. 16,17 This approach is used in the current work to characterize the to ↵ transformation of W. As will be shown, the experimentally measured transformation enthalpy compares well with the difference in the density functional theory computed energies of -W relative to ↵-W, validating the experimental methodology.…”

Section: Introductionmentioning

confidence: 99%

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Transformation of topologically close-packed β-W to body-centered cubic α-W: Comparison of experiments and computations

Barmak

Liu

Harlan

et al. 2017

The Journal of Chemical Physics

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The enthalpy and activation energy for the transformation of the metastable form of tungsten, β-W, which has the topologically close-packed A15 structure (space group Pm3¯n), to equilibrium α-W, which is body-centered cubic (A2, space group Im3¯m), was measured using differential scanning calorimetry. The β-W films were 1 μm-thick and were prepared by sputter deposition in argon with a small amount of nitrogen. The transformation enthalpy was measured as -8.3 ± 0.4 kJ/mol (-86 ± 4 meV/atom) and the transformation activation energy as 2.2 ± 0.1 eV. The measured enthalpy was found to agree well with the difference in energies of α and β tungsten computed using density functional theory, which gave a value of -82 meV/atom for the transformation enthalpy. A calculated concerted transformation mechanism with a barrier of 0.4 eV/atom, in which all the atoms in an A15 unit cell transform into A2, was found to be inconsistent with the experimentally measured activation energy for any critical nucleus larger than two A2 unit cells. Larger calculations of eight A15 unit cells spontaneously relax to a mechanism in which part of the supercell first transforms from A15 to A2, creating a phase boundary, before the remaining A15 transforms into the A2 phase. Both calculations indicate that a nucleation and growth mechanism is favored over a concerted transformation. More consistent with the experimental activation energy was that of a calculated local transformation mechanism at the A15-A2 phase boundary, computed as 1.7 eV using molecular dynamics simulations. This calculated phase transformation mechanism involves collective rearrangements of W atoms in the disordered interface separating the A15 and A2 phases.

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Section: A Experimentsmentioning

confidence: 99%

Section: A Experimentsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Transformation of topologically close-packed β-W to body-centered cubic α-W: Comparison of experiments and computations

Barmak

Liu

Harlan

et al. 2017

The Journal of Chemical Physics

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“…For preparation of β‐W films, it is a simple procedure for both magnetron sputtering and chemical vapor deposition (CVD) . During deposition, impurities, such as oxygen, nitrogen, carbon, silicon, and germanium from environment or reaction atmosphere, are generally beneficial for preferred nucleation and growth of metastable β phase. However, in situ substrate heating (>300 °C) is indispensable to attain α‐W films based on CVD methods .…”

Section: Introductionmentioning

confidence: 99%

On‐Demand Preparation of α‐Phase‐Dominated Tungsten Films for Highly Qualified Thermal Reflectors

Wang

Zang

Gao

et al. 2019

Adv Materials Inter

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Phase‐structure diversity affords tungsten thin films with fascinating physical/chemical properties for varied applications. However, the on‐demand preparation of W films with specific phase is still an important but unmet scientific issue. In this report, an easy‐to‐achieve preparation recipe is implemented for addressing the phase tailoring of tungsten films. The phase transformation evolution during deposition is governed by enhanced diffusion of W adatoms and selective atomic etching on the crystal planes. It is experimentally demonstrated that the orientation relation between {210}β and {110}α planes plays a vital role in coupling with the competitive growth behaviors between β‐ and α‐W. The phase‐dependent electrical/optical properties of W films are experimentally observed and unambiguously figured out by theoretical simulations. Alpha‐phase‐dominated W films are prepared successfully under relatively tolerant conditions, demonstrating a low resistivity of ≈13.6 µΩ cm and a high infrared reflectance larger than 93%. Alpha‐W also serves as thermal reflector to construct a solar absorber, exhibiting a low thermal emissivity of ≈9.8%@500 °C. Understanding the (α, β) phase transformation mechanism means a big step forward in the development of the on‐demand preparation, which allows to build a scalable platform for making W films with specific phase in a more controllable way.

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“…TCP phases are of particular interest in high-performance materials such a Ni-base superalloys [27] as their formation significantly influences the materials properties [28]. In tungsten, the transformation between the A15 and bcc phase has recently attracted increased attention [29,30] since for applica-arXiv:1905.01536v1 [cond-mat.mtrl-sci]…”

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confidence: 99%

Neural-Network-Based Path Collective Variables for Enhanced Sampling of Phase Transformations

2019

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We propose a rigorous construction of a 1D path collective variable to sample structural phase transformations in condensed matter. The path collective variable is defined in a space spanned by global collective variables that serve as classifiers derived from local structural units. A reliable identification of local structural environments is achieved by employing a neural network based classification. The 1D path collective variable is subsequently used together with enhanced sampling techniques to explore the complex migration of a phase boundary during a solid-solid phase transformation in molybdenum.Efficient sampling of high-dimensional conformational spaces represented by rough potential energy landscapes constitutes a significant challenge in the computational molecular sciences, particularly when different basins on the landscape are separated by energy barriers significantly higher than k B T . In order to address this challenge, various enhanced sampling techniques have been developed including accelerated molecular dynamics [1][2][3][4][5], transition path sampling [6-9], metadynamics [10][11][12][13], and (driven) adiabatic free energy dynamics (d-AFED) [14][15][16] or temperature accelerated molecular dynamics (TAMD) [17] and combinations of these [18,19]. In many cases the sampling, and in essentially all cases the analysis of the resulting high-dimensional free-energy landscapes, requires a projection onto a low-dimensional collective variable (CV) space. Indeed, the choice of the CVs is not always intuitive, but a meaningful representation in the low-dimensional space is crucial for capturing the correct mechanisms.Machine learning (ML) can provide a powerful approach to address the aforementioned challenges. The last decade has seen significant advances in the use of electronic structure calculations to train ML potentials for atomistic simulations capable of reaching large systems sizes and long time scales with accurate and reliable energies and forces. More recently, ML approaches have proved useful in learning high-dimensional freeenergy surfaces (FESs) [20,21], and in providing a lowdimensional set of CVs [22,23]. In such approaches, however, it is often difficult to interpret the low-dimensional CVs that emerge from the learning procedure as they emerge as abstract outputs of the ML model employed.In this letter, we overcome this difficulty by exploiting an ML model to identify local atomic structures and then using the ML output to construct a physically motivated one-dimensional CV. The latter is then employed with an enhanced configurational sampling scheme to char-acterise structural phase transformations in condensed matter. The basic idea of our approach is generally applicable to tackle different kinds of phases transformations.A structural phase transformation can be viewed as a global change of the entire system that is associated with and driven by changes in the local structural environment around each atom (or other structural building blocks such as molecules). Furthermore, f...

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Topologically close-packed phases: Deposition and formation mechanism of metastable β-W in thin films

Cited by 38 publications

References 24 publications

Transformation of topologically close-packed β-W to body-centered cubic α-W: Comparison of experiments and computations

Transformation of topologically close-packed β-W to body-centered cubic α-W: Comparison of experiments and computations

On‐Demand Preparation of α‐Phase‐Dominated Tungsten Films for Highly Qualified Thermal Reflectors

Neural-Network-Based Path Collective Variables for Enhanced Sampling of Phase Transformations

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