Superhard Rhenium/Tungsten Diboride Solid Solutions

Lech, Andrew T.; Turner, Christopher L.; Lei, Jialin; Mohammadi, Reza; Tolbert, Sarah H.; Kaner, Richard B.

doi:10.1021/jacs.6b08616

Cited by 54 publications

(38 citation statements)

References 68 publications

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“…Borides of certain transition metals form a new class of hard materials. [1][2][3][4] Being metals, these borides easily cut with electric discharge machining and thus appear as an attractive alternative to diamond. The governing principles for the design of ultra hard borides have been proposed to be the combination of high electron density at the Fermi level (E F ) coming from the metal, making borides incompressible, and a rigid covalent boron skeleton resisting the shear stress.…”

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confidence: 99%

Mystery of Three Borides: Differential Metal–Boron Bonding Governing Superhard Structures

et al. 2017

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Some transition metal borides are ultra hard. While not harder than diamond, they are easier to process and can be cheaper, sparking intense interest. However, we so far cannot predict which particular borides should be ultra hard. A striking example is the three structurally similar diborides of Ti, Re, and Os, among which only ReB 2 is ultra hard. For this trio, using a combination of theory and experiment done on both the solids and small cluster models, we show that the nature of the metal-boron bonds is the key to hardness, in contrast to the existing theory, which overlooks metal-boron interactions. Ti-B bonding is purely ionic in TiB 2 , and the material yields to shear stress like graphite. OsB 2 is highly covalent, with both bonding and antibonding Os-B backbonds present, which weaken the Bnetwork, and ease the OsB 2 yield to compression. ReB 2 has only the bonding Re-B σ-backbond, which strengthens the material against both shear and compression. A general strategy for ultra hard boride design is proposed.

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confidence: 99%

Mystery of Three Borides: Differential Metal–Boron Bonding Governing Superhard Structures

et al. 2017

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“…The site compositions and formula are represented using chemical descriptors (e.g., electronegativity, number of valence electrons, or position on the periodic table) available on the Citrination platform. [39][40][41][42][43] A heuristic bond length estimate generated by summing the average atomic radii for the sites was also calculated as an additional descriptor. Machine-learning and data mining algorithms is a significant step forward for the current single crystal-based approach, compared to previous automated crystal structure solutions; for example, solving structures from powder diffraction data in a hybrid DFT-experimental way.…”

Section: Foundation Of the Scar Methods And Creation Of Data Driven Momentioning

confidence: 99%

Single Crystal Automated Refinement (SCAR): A Data-Driven Method for Solving Inorganic Structures

Viswanathan¹,

Oliynyk²,

Antono³

et al. 2019

Preprint

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Single crystal diffraction is one of the most common experimental techniques in chemistry for determining a crystal structure. However, the process of crystal structure solution and refinement is not always straightforward. Methods to simplify and rationalize the path to the most optimal crystal structure model have been incorporated into various data processing and crystal structure solution software, with the focus generally on aiding macromolecular or protein structure solution. In this work, we propose a new method that uses single crystal data to solve the crystal structures of inorganic, extended solids called “Single Crystal Automated Refinement (SCAR).” The approach was developed using data mining and machine-learning methods and considers several structural features common in inorganic solids, like atom assignment based on physically reasonable distances, atomic statistical mixing, and crystallographic site deficiency. The output is a tree of possible solutions for the data set with a corresponding fit score indicating the most reasonable crystal structure. Here, the foundation for SCAR is presented followed by the implementation of SCAR to solve two newly synthesized and previously unreported phases, ZrAu0.5Os0.5 and Nd4Mn2AuGe4. The structure solutions are found to be comparable with manually solving the data set, including the same refined mixed occupancies and atomic deficiency, supporting the validity of this automatic structure solution method. The proposed SCAR program is thusly verified to be a fast and reliable assistant in solving even complex single crystal diffraction data for extended inorganic solids.

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“…Note that the occurrence of cuboctahedral clusters in WB 4 is at most one for every four metal atoms, whereas it is one per metal atom in MB 12 structures. Moreover, both the slightly longer red boron–boron bond distances and the shorter green bond distances in Figure b for MB 12 are shorter than those in WB 4 and ReB 2 , suggesting the potential for high hardness in MB 12 . Indeed, Akopov et al have recently synthesized ZrB 12 , YB 12 , and Zr 1− x Y x B 12 solid solutions at ambient pressure by arc‐melting.…”

Section: Introductionmentioning

confidence: 99%

Radial X‐Ray Diffraction Study of Superhard Early Transition Metal Dodecaborides under High Pressure

Lei

Akopov

Yeung

et al. 2019

Adv Funct Materials

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The deformation behavior of the three metal dodecaborides (YB 12 , ZrB 12 , and Zr 0.5 Y 0.5 B 12 ) is investigated using radial X-ray diffraction under nonhydrostatic compression up to ≈60 GPa with a goal of understanding how bonding and metal composition control hardness. Zr 0.5 Y 0.5 B 12 , which has the highest Vickers hardness (Hv = 45.8 ± 1.3 GPa at 0.49 N load), also shows the highest bulk modulus (K 0 = 320 ± 5 GPa). The 0.49 N hardness for ZrB 12 and YB 12 are both lower and very similar, and both show lower bulk moduli (K 0 = 276 ± 7 GPa, and K 0 = 238 ± 6 GPa, respectively). Differential stress is then measured to study the strength and strength anisotropy. Zr 0.5 Y 0.5 B 12 supports the highest differential stress, in agreement with its high hardness, a fact that likely arises from atomic size mismatch between Zr and Y combined with the rigid network of boron cages. The (200) plane for all samples supports the largest differential strain, while the (111) plane supports the smallest, consistent with the theoretically predicted slip system of {111} [ 1 11 12 2 ]. Strain softening is also observed for ZrB 12 . Finally, the full elastic stiffness tensors for ZrB 12 and YB 12 are solved. ZrB 12 is the most isotropic, but the extent of elastic anisotropy for all dodecaborides studied is relatively low due to the highly symmetric boron cage network.

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Superhard Rhenium/Tungsten Diboride Solid Solutions

Cited by 54 publications

References 68 publications

Mystery of Three Borides: Differential Metal–Boron Bonding Governing Superhard Structures

Mystery of Three Borides: Differential Metal–Boron Bonding Governing Superhard Structures

Single Crystal Automated Refinement (SCAR): A Data-Driven Method for Solving Inorganic Structures

Radial X‐Ray Diffraction Study of Superhard Early Transition Metal Dodecaborides under High Pressure

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