Refined Crystal Structures of SrLnCuS3 (Ln = Er, Yb)

Русейкина, А. В.; Соловьев, Л. А.; Grigor’ev, M. V.

doi:10.1134/s0036023618090140

Cited by 7 publications

(12 citation statements)

References 17 publications

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“…It is also evident that some of the predicted stable compounds have a combination of alkali and alkaline earth metals (e.g., KMgHoTe 3 ) and more than one alkali metals (e.g., KLiHfS 3 ). These chemical trends are unique to this newly discovered compounds and are absent in the experimentally known [32][33][34][35][36][37][38][39] and the previously [45] discovered AMM'Q 3 compounds.…”

Section: Design and Discovery Of New Materialsmentioning

confidence: 73%

“…The experimentally known AMM'Q 3 compounds [32][33][34][35][36][37][38][39] crystallize in seven structural prototypes (Figures 2a-2g) in four different space groups (SGs): KCuZrSe 3 (SG: Cmcm, No. 63), Eu 2 CuS 3 (SG: Pnma, No.…”

Section: Design and Discovery Of New Materialsmentioning

confidence: 99%

“…In this work, we use an ML method to explore the vast phase space spanned by a family of experimentally known quaternary chalcogenides (AMM'Q 3 ) [32][33][34][35][36][37][38][39] that possess diverse structure types and chemistry. Some of these compounds are shown to exhibit very low lattice thermal conductivity [40,41], promising thermeoelectric performance [42,43] and high photovoltaic efficiency [44].…”

Section: Introductionmentioning

confidence: 99%

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Scale-invariant Machine-learning Model Accelerates the Discovery of Quaternary Chalcogenides with Ultralow Lattice Thermal Conductivity

Pal¹,

Park²,

Yi³

et al. 2021

Preprint

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Intrinsically low lattice thermal conductivity (κ l ) is a desired requirement in many crystalline solids such as thermal barrier coatings and thermoelectrics. Here, we design an advanced machinelearning (ML) model based on crystal graph convolutional neural network that is insensitive to volumes (i.e., scale) of the input crystal structures to discover novel quaternary chalcogenides, AMM'Q3 (A/M/M'=alkali, alkaline-earth, post-transition metals, lanthanides, Q=chalcogens). Upon screening the thermodynamic stability of ∼ 1 million compounds using the ML model iteratively and performing density functional theory (DFT) calculations for a small fraction of compounds, we discover 99 compounds that are validated to be stable in DFT. Taking several DFT-stable compounds, we calculate their κ l using phonon-Boltzmann transport equation, which reveals ultralow-κ l (< 2 Wm −1 K −1 at room-temperature) due to their soft elasticity and strong phonon anharmonicity. Our work demonstrates the high-efficiency of scale-invariant ML model in predicting novel compounds and presents experimental research opportunities with these new compounds. K.P. and C.W.P. contributed equally.

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Section: Design and Discovery Of New Materialsmentioning

confidence: 73%

Section: Design and Discovery Of New Materialsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Scale-invariant Machine-learning Model Accelerates the Discovery of Quaternary Chalcogenides with Ultralow Lattice Thermal Conductivity

Pal¹,

Park²,

Yi³

et al. 2021

Preprint

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show abstract

“…Polycrystalline samples of SrLnCuS 3 were obtained by the melting of a stoichiometric ratio of sulfides SrS, Ln 2 S 3 and Cu 2 S, followed by annealing at 970–1170 K for 2–3 (!) months [ 22 , 34 , 35 , 36 , 43 , 44 , 45 ]. Single-crystal samples were synthesized from elemental Sr, Cu and Ln (Ln = Nd, Y, Sc) using a halide flux at 1070 K for 8 days [ 46 , 47 ].…”

Section: Introductionmentioning

confidence: 99%

“…In the literature, the crystal structures of some SrLnCuS 3 have already been reported [ 21 , 22 , 34 , 35 , 36 , 43 , 44 , 45 , 46 , 47 ]. For SrLnCuS 3 , two types of orthorhombic crystal structures with Pnma symmetry and one type with Cmcm symmetry were revealed [ 22 ].…”

Section: Introductionmentioning

confidence: 99%

A Challenge toward Novel Quaternary Sulfides SrLnCuS3 (Ln = La, Nd, Tm): Unraveling Synthetic Pathways, Structures and Properties

Русейкина

Grigoriev

Solovyov

et al. 2022

IJMS

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We report on the novel heterometallic quaternary sulfides SrLnCuS3 (Ln = La, Nd, Tm), obtained as both single crystals and powdered samples. The structures of both the single crystal and powdered samples of SrLaCuS3 and SrNdCuS3 belong to the orthorhombic space group Pnma but are of different structural types, while both samples of SrTmCuS3 crystallize in the orthorhombic space group Cmcm with the structural type KZrCuS3. Three-dimensional crystal structures of SrLaCuS3 and SrNdCuS3 are formed from the (Sr/Ln)S7 capped trigonal prisms and CuS4 tetrahedra. In SrLaCuS3, alternating 2D layers are stacked, while the main backbone of the structure of SrNdCuS3 is a polymeric 3D framework [(Sr/Ln)S7]n, strengthened by 1D polymeric chains (CuS4)n with 1D channels, filled by the other Sr2+/Ln3+ cations, which, in turn, form 1D dimeric ribbons. A 3D crystal structure of SrTmCuS3 is constructed from the SrS6 trigonal prisms, TmS6 octahedra and CuS4 tetrahedra. The latter two polyhedra are packed together into 2D layers, which are separated by 1D chains (SrS6)n and 1D free channels. In both crystal structures of SrLaCuS3 obtained in this work, the crystallographic positions of strontium and lanthanum were partially mixed, while only in the structure of SrNdCuS3, solved from the powder X-ray diffraction data, were the crystallographic positions of strontium and neodymium partially mixed. Band gaps of SrLnCuS3 (Ln = La, Nd, Tm) were found to be 1.86, 1.94 and 2.57 eV, respectively. Both SrNdCuS3 and SrTmCuS3 were found to be paramagnetic at 20–300 K, with the experimental magnetic characteristics being in good agreement with the corresponding calculated parameters.

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Unravelling the rare-earth (RE) element-induced magnetic and optical properties in the structures of quaternary selenides SrRECuSe3

Русейкина

Grigoriev

Solovyov

et al. 2023

Inorganic Chemistry Communications

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Refined Crystal Structures of SrLnCuS3 (Ln = Er, Yb)

Cited by 7 publications

References 17 publications

Scale-invariant Machine-learning Model Accelerates the Discovery of Quaternary Chalcogenides with Ultralow Lattice Thermal Conductivity

Scale-invariant Machine-learning Model Accelerates the Discovery of Quaternary Chalcogenides with Ultralow Lattice Thermal Conductivity

A Challenge toward Novel Quaternary Sulfides SrLnCuS3 (Ln = La, Nd, Tm): Unraveling Synthetic Pathways, Structures and Properties

Unravelling the rare-earth (RE) element-induced magnetic and optical properties in the structures of quaternary selenides SrRECuSe3

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