New phosphides of IVa and Va group metals with TiNiSi-type

Lomnytska, Ya. F.; Kuz’ma, Yu. B.

doi:10.1016/s0925-8388(98)00134-0

Cited by 14 publications

(7 citation statements)

References 6 publications

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“…34 As such, they present an excellent opportunity to investigate whether machine learning can be applied to predict polymorph formation. Polymorphism is particularly prevalent in binary metal-rich (M) phosphides with the general formula M 2 P, which tend to crystallize in either the Co 2 Si-or Fe 2 P-type structure, depending on M. 35 As illustrated in Figure 1, both structures can be described as two-dimensional homologues based on the parent AlB 2 -type structure, with the key structural motif being tricapped trigonal prisms having M atoms at the corners and P atoms at the center. The different threedimensional connectivity of these prisms leads to two structure types: the orthorhombic Co 2 Si-type structure contains zigzag sheets of corner-sharing trigonal prisms, whereas the hexagonal Fe 2 P-type structure contains six-membered rings enclosing an isolated prism.…”

Section: ■ Introductionmentioning

confidence: 99%

“…38 In most ternary MM′P phosphides, the larger metal atoms prefer the corner-shared site of the trigonal prism, and the smaller metal atoms prefer the unshared corner site. 35 The TiNiSi-and ZrNiAl-type structures are extremely common not only for phosphides but also for the overwhelming number of equiatomic ternary phases; remarkably, these two structure types encompass over 69% of all reported equiatomic phases regardless of composition. Adding the next five most common structure types (PbFCl, LiGaGe, YPtAs, UGeTe, LaPtSi) increases the coverage to 91% of all reported equiatomic phases.…”

Section: ■ Introductionmentioning

confidence: 99%

“…As such, they present an excellent opportunity to investigate whether machine learning can be applied to predict polymorph formation. Polymorphism is particularly prevalent in binary metal-rich ( M ) phosphides with the general formula M 2 P, which tend to crystallize in either the Co 2 Si- or Fe 2 P-type structure, depending on M . As illustrated in Figure , both structures can be described as two-dimensional homologues based on the parent AlB 2 -type structure, with the key structural motif being tricapped trigonal prisms having M atoms at the corners and P atoms at the center.…”

Section: Introductionmentioning

confidence: 99%

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Disentangling Structural Confusion through Machine Learning: Structure Prediction and Polymorphism of Equiatomic Ternary Phases ABC

et al. 2017

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A method to predict the crystal structure of equiatomic ternary compositions based only on the constituent elements was developed using cluster resolution feature selection (CR-FS) and support vector machine (SVM) classification. The supervised machine-learning model was first trained with 1037 individual compounds that adopt the most populated ternary 1:1:1 structure types (TiNiSi-, ZrNiAl-, PbFCl-, LiGaGe-, YPtAs-, UGeTe-, and LaPtSi-type) and then validated using an additional 519 compounds. The CR-FS algorithm improves class discrimination and indicates that 113 variables including size, electronegativity, number of valence electrons, and position on the periodic table (group number) influence the structure preference. The final model prediction sensitivity, specificity, and accuracy were 97.3%, 93.9%, and 96.9%, respectively, establishing that this method is capable of reliably predicting the crystal structure given only its composition. The power of CR-FS and SVM classification is further demonstrated by segregating the crystal structure of polymorphs, specifically to examine polymorphism in TiNiSi- and ZrNiAl-type structures. Analyzing 19 compositions that are experimentally reported in both structure types, this machine-learning model correctly identifies, with high confidence (>0.7), the low-temperature polymorph from its high-temperature form. Interestingly, machine learning also reveals that certain compositions cannot be clearly differentiated and lie in a "confused" region (0.3-0.7 confidence), suggesting that both polymorphs may be observed in a single sample at certain experimental conditions. The ensuing synthesis and characterization of TiFeP adopting both TiNiSi- and ZrNiAl-type structures in a single sample, even after long annealing times (3 months), validate the occurrence of the region of structural uncertainty predicted by machine learning.

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Section: ■ Introductionmentioning

confidence: 99%

Section: ■ Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Disentangling Structural Confusion through Machine Learning: Structure Prediction and Polymorphism of Equiatomic Ternary Phases ABC

et al. 2017

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“…With the exception of ZrNiP (Ni 2 In type)24 and HfNiP, these Zr and Hf compounds are always isostructural. Only few examples are known with Zr or Hf and a second early transition metal, namely the phosphides ZrTiP,12 ZrVP and HfVP,13 ZrNbP and HfNbP14 (all Co 2 Si type), while the arsenides known to date form the La 2 Sb type (i.e. ZrTiAs and ZrVAs7,8).…”

Section: Resultsmentioning

confidence: 99%

“…This work deals with the new hafnium phosphides and arsenides Hf 1−δ Ti 1+δ P, Hf 1−δ Ti 1+δ As, and Hf 1−δ V 1+δ As. As illustrated in Table 1, the power product f clearly places these three new materials into the Co 2 Si domain, together with ZrTiP,12 ZrVP and HfVP,13 ZrNbP and HfNbP,14 and V 2 P15 and in contrast to ZrTiAs and ZrVAs (as well as La 2 Sb16 and Zr 2 Sb17). Our investigations confirmed the Co 2 Si type in all three new cases introduced.…”

Section: Introductionmentioning

confidence: 93%

The Predicted Structures of the New Pnictides HfMQ in Contrast to ZrMQ (M = Ti, V; Q = P, As)

2004

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The new pnictides HfTiP, HfTiAs and HfVAs have been prepared through arc-melting. These arsenides form the predicted structures with (distorted) TiAs 4 and VAs 4 tetrahedra, while the structures of both Zr analogs (ZrTiAs and ZrVAs) are comprised of TiAs 4 and VAs 4 square planes, respectively. These differences stem from significant differences in the metal atom substructures. On the other hand, HfTiP and ZrTiP are isostructural. These variations were predicted by utilizing a structure map for metal-rich pnictides and chalco- IntroductionThe ternary equiatomic early transition-metal pnictides MMЈQ (M, MЈ: element of groups 3Ϫ5; Q: P, As, Sb) typically occur in one of two common crystal structures. These structures differ in the metalϪnonmetal coordination spheres (but with the same coordination numbers) as well as in the metalϪmetal bonding, while the nonmetal atoms are always surrounded by nine metal atoms in form of a tricapped trigonal prism, and the larger M atoms are situated in a square pyramid formed by five Q atoms. In the first variant, the Co 2 Si type (ordered variant: TiNiSi [1] ), the smaller MЈ atoms are tetrahedrally coordinated by four Q atoms, whereas in the second variant, the La 2 Sb type (ordered variant: CeScSi [2] ), the MЈQ 4 polyhedra are best described as square planes.These differences may be understood to stem from different metal atom substructures, which contain stronger MϪM and MϪMЈ bonds in case of the Co 2 Si structures. As shown earlier, [3] the major structure determining factors for such metal-rich pnictides and chalcogenides are the valence-electron concentration of M, the relative extension of the d orbitals of M (reflected in the principal quantum number), the radius ratio r M /r Q , and the electron deficit of the Q atoms. As for the metal atoms, higher valence-electron concentration, larger d orbitals and larger atomic radii all facilitate stronger MϪM bonding. On the other hand, larger atomic sizes and larger electron deficits of the Q atoms would lead to larger coordination numbers for the Q [a]

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ChemInform Abstract: New Phosphides of IVa and Va Group Metals with TiNiSi‐Type.

Lomnytska

Kuz’ma

1998

ChemInform

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New phosphides of IVa and Va group metals with TiNiSi-type

Cited by 14 publications

References 6 publications

Disentangling Structural Confusion through Machine Learning: Structure Prediction and Polymorphism of Equiatomic Ternary Phases ABC

Disentangling Structural Confusion through Machine Learning: Structure Prediction and Polymorphism of Equiatomic Ternary Phases ABC

The Predicted Structures of the New Pnictides HfMQ in Contrast to ZrMQ (M = Ti, V; Q = P, As)

ChemInform Abstract: New Phosphides of IVa and Va Group Metals with TiNiSi‐Type.

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