Computational Discovery of Stable Heteroanionic Oxychalcogenides ABXO (A, B = Metals; X = S, Se, and Te) and Their Potential Applications

He, Jiangang; Yao, Zhenpeng; Hegde, V.; Shen, Jiahong; Bushick, Kyle; Wolverton, Christopher

doi:10.1021/acs.chemmater.0c01902

Cited by 27 publications

(35 citation statements)

References 136 publications

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“…Also, there are other valleys with energies close to VBM or CBM, which could further increase band degeneracy if the compounds can be properly doped. These characteristics resemble what has been observed in the excellent thermoelectric material BiCuSeO and other Bi-based compounds with the ZrCuSiAs-type structure, where the VBM and CBM are mainly from Bi 6s and 6p orbitals, respectively [38,76]. Similar exploration can be performed for the other structure types discovered in this work, and more promising thermoelectric materials could be potentially discovered.…”

Section: IVsupporting

confidence: 84%

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Exploring low lattice thermal conductivity materials using chemical bonding principles

He,

Xia,

Lin

et al. 2021

Preprint

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Semiconductors with very low lattice thermal conductivities are highly desired for applications relevant to thermal energy conversion and management, such as thermoelectrics and thermal barrier coatings. Although the crystal structure and chemical bonding are known to play vital roles in shaping heat transfer behavior, material design approaches of lowering lattice thermal conductivity using chemical bonding principles are uncommon. In this work, we present an effective strategy of weakening interatomic interactions and therefore suppressing lattice thermal conductivity based on chemical bonding principles and develop a high-efficiency approach of discovering low κL materials by screening the local coordination environments of crystalline compounds. The followed first-principles calculations uncover 30 hitherto unexplored compounds with (ultra)low lattice thermal conductivities from thirteen prototype crystal structures contained in the inorganic crystal structure database. Furthermore, we demonstrate an approach of rationally designing high-performance thermoelectrics by additionally incorporating cations with stereochemically active lone-pair electrons. Our results not only provide fundamental insights into the physical origin of the low lattice thermal conductivity in a large family of copper-based compounds but also offer an efficient approach to discovery and design materials with targeted thermal transport properties.

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Section: IVsupporting

confidence: 84%

“…Meanwhile, it is still possible that some of these compounds have not been fully characterized or synthesized yet. Therefore, we expect that many low κ L compounds could be discovered by decorating these structures with elements that are similar to the existing ones, which has been commonly used to predict new compounds [76,77].…”

Section: IVmentioning

confidence: 99%

Exploring low lattice thermal conductivity materials using chemical bonding principles

He,

Xia,

Lin

et al. 2021

Preprint

Self Cite

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show abstract

Section: Discussionmentioning

confidence: 99%

“…Therefore, we expect that many low κ L compounds could be discovered by decorating these structures with elements that are similar to the existing ones, which has been commonly used to predict new compounds. [80,81] With our material design strategy of suppressing κ L , we can also rationally design as-yet synthesized thermoelectric materials by combining it with the methods focused on improving power factor. It is known that the s-orbital of the cations with lone-pair electrons can dramatically increase the band degeneracy of a semiconductor, [25] which is desired for enhancing power factors of thermoelectric materials.…”

Section: Discussionmentioning

confidence: 99%

Accelerated Discovery and Design of Ultralow Lattice Thermal Conductivity Materials Using Chemical Bonding Principles

Xia

Lin

et al. 2021

Adv Funct Materials

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Semiconductors with very low lattice thermal conductivities are highly desired for applications relevant to thermal energy conversion and management, such as thermoelectrics and thermal barrier coatings. Although the crystal structure and chemical bonding are known to play vital roles in shaping heat transfer behavior, material design approaches of lowering lattice thermal conductivity using chemical bonding principles are uncommon. In this work, an effective strategy of weakening interatomic interactions and therefore suppressing lattice thermal conductivity based on chemical bonding principles is presented and a high-efficiency approach of discovering low κ L materials by screening the local coordination environments of crystalline compounds is developed. The resulting first-principles calculations uncover 30 hitherto unexplored compounds with (ultra)low lattice thermal conductivities from 13 prototype crystal structures contained in the Inorganic Crystal Structure Database. Furthermore, an approach of rationally designing high-performance thermoelectrics is demonstrated by additionally incorporating cations with stereochemically active lone-pair electrons. These results not only provide atomic-level insights into the physical origin of the low lattice thermal conductivity in a large family of copper/silver-based compounds but also offer an efficient approach to discover and design materials with targeted thermal transport properties.

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“…Another strategy to generate hypothetical crystal structures is to first generate the compositions, using our composition generative machine learning model (MatGAN) [6], which can generate hypothetical crystal material compositions by learning implicit chemical composition rules. Our model can be used to generate millions of new hypothetical materials compositions, with the potential to significantly expand the chemical design space for inorganic material design and large-scale computational screening [2,23]. It is of great significance to analyze their physical and chemical properties, which depend on the availability of their structures.…”

Section: Introductionmentioning

confidence: 99%

Crystal structure prediction using age-fitness multi-objective genetic algorithm and coordination number constraints

Yang,

Siriwardane,

2021

Preprint

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Crystal structure prediction (CSP) has emerged as one of the most important approaches for discovering new materials. CSP algorithms based on evolutionary algorithms and particle swarm optimization have discovered a great number of new materials. However, these algorithms based on ab initio calculation of free energy are inefficient. Moreover, they have severe limitations in terms of scalability. We recently proposed a promising crystal structure prediction method based on atomic contact maps, using global optimization algorithms to search for the Wyckoff positions by maximizing the match between the contact map of the predicted structure and the contact map of the true crystal structure. However, our previous contact map based CSP algorithms have two major limitations: (1) the loss of search capability due to getting trapped in local optima; (2) it only uses the connection of atoms in the unit cell to predict the crystal structure, ignoring the chemical environment outside the unit cell, which may lead to unreasonable coordination environments. Herein we propose a novel multi-objective genetic algorithms for contact map-based crystal structure prediction by optimizing three objectives, including contact map match accuracy, the individual age, and the coordination number match. Furthermore, we assign the age values to all the individuals of the GA and try to minimize the age aiming to avoid the premature convergence problem. Our experimental results show that compared to our previous CMCrystal algorithm, our multi-objective crystal structure prediction algorithm (CMCrystalMOO) can reconstruct the crystal structure with higher quality and alleviate the problem of premature convergence.

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Computational Discovery of Stable Heteroanionic Oxychalcogenides ABXO (A, B = Metals; X = S, Se, and Te) and Their Potential Applications

Cited by 27 publications

References 136 publications

Exploring low lattice thermal conductivity materials using chemical bonding principles

Exploring low lattice thermal conductivity materials using chemical bonding principles

Accelerated Discovery and Design of Ultralow Lattice Thermal Conductivity Materials Using Chemical Bonding Principles

Crystal structure prediction using age-fitness multi-objective genetic algorithm and coordination number constraints

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