Cu3ErTe3: a new promising thermoelectric material predicated by high-throughput screening

Wang, T.; Xiong, Yan; Wang, Y.; Qiu, Pengfei; Song, Qingfeng; Zhao, Keli; Yang, Jiong; Xiao, Jianping; Shi, Xun; Chen, L.

doi:10.1016/j.mtphys.2020.100180

Cited by 21 publications

(35 citation statements)

References 42 publications

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“…The results at 300 K are listed in Table SI. They range from 0.20 W•m -1 •K -1 to 0.48 W•m -1 •K -1 , which are very low values as compared with those for the state-of-the-art TE materials [44][45][46][47][48][49]. The proximity to the cubic superionic phase is responsible for the low κ L values observed in these orthorhombic and monoclinic phases [23].…”

Section: Researchmentioning

confidence: 99%

Crystalline Structure-Dependent Mechanical and Thermoelectric Performance in Ag2Se1‐xSx System

et al. 2020

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Self-powered wearable electronics require thermoelectric materials simultaneously with a high dimensionless figure of merit (zT) and good flexibility to convert the heat discharged by the human body into electricity. Ag2(S,Se)-based semiconducting materials can well satisfy these requirements, and thus, they are attracting great attention in thermoelectric society recently. Ag2(S,Se) crystalizes in an orthorhombic structure or monoclinic structure, depending on the detailed S/Se atomic ratio, but the relationship between its crystalline structure and mechanical/thermoelectric performance is still unclear to date. In this study, a series of Ag2Se1‐xSx (x=0, 0.1, 0.2, 0.3, 0.4, and 0.45) samples were prepared and their mechanical and thermoelectric performance dependence on the crystalline structure was systematically investigated. x=0.3 in the Ag2Se1‐xSx system was found to be the transition boundary between orthorhombic and monoclinic structures. Mechanical property measurement shows that the orthorhombic Ag2Se1‐xSx samples are brittle while the monoclinic Ag2Se1‐xSx samples are ductile and flexible. In addition, the orthorhombic Ag2Se1‐xSx samples show better electrical transport performance and higher zT than the monoclinic samples under a comparable carrier concentration, most likely due to their weaker electron-phonon interactions. This study sheds light on the further development of flexible inorganic TE materials.

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Section: Researchmentioning

confidence: 99%

Crystalline Structure-Dependent Mechanical and Thermoelectric Performance in Ag2Se1‐xSx System

et al. 2020

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“…Taking advantage of the large atomic mass is straightforward and has been utilized to screen new thermoelectric materials with low κ L recently. [ 21 ] However, bond strength is more complicated and correlated to the electronegativities of constituent atoms and local coordination of a crystal structure. Generally, the bond in the environment with a higher coordination number (CN) is weaker than that in a lower CN one due to the longer bond length between cation and anion in the high CN case, reflecting Pauling's second rule.…”

Section: Introductionmentioning

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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“…Based on the results reached by the experimental validation shown above, a screening process has to be done in order to test the prediction validity of the built model. For the screening of LTC values, recent work by Wang et al employed traditional screening for LTC using common descriptors such as atomic weight; 28 our work, on the other hand, focuses on employing the established RF-based model in the prediction process with the reduced feature space that has been generated earlier. The RF-based model was used to predict the LTCs at 300 K for 32,116 compounds present in the ICSD, and here, the relaxed features were initially used.…”

Section: ■ Results and Discussionmentioning

confidence: 99%

Lattice Thermal Conductivity: An Accelerated Discovery Guided by Machine Learning

Jaafreh

Kang

Hamad

2021

ACS Appl. Mater. Interfaces

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In the present work, we used machine learning (ML) techniques to build a crystal-based model that can predict the lattice thermal conductivity (LTC) of crystalline materials. To achieve this, first, LTCs of 119 compounds at various temperatures (100− 1000 K) were obtained based on density functional theory (DFT) and phonon calculations, and then, these data were employed in the next learning process to build a predictive model using various ML algorithms. The ML results showed that the model built based on the random forest (RF) algorithm with an R 2 score of 0.957 was the most accurate compared with the models built using other algorithms. Additionally, the accuracy of this model was validated using new cases of four compounds, which was not seen for the model before, where a good matching between calculated and predicted LTCs of the new compounds was found. To find candidates with ultralow LTCs (<1 W m −1 K −1 ) at room temperature, the model was used to screen compounds (32116) in the Inorganic Crystal Structure Database. From the screened compounds, Cs 2 SnI 6 and SrS were selected to validate the ML prediction using the counterpart theoretical calculations (DFT and phonon), and it was found that the outcome behaviors by both methods (ML prediction and DFT/phonon calculations) are fairly consistent. Considering the type of employed feature, the prime novelty in this work is that the built model can credibly predict the LTC−temperature behaviors of new compounds that are constructed based on prototype structures and chemical compositions, without the use of any DFT-relaxed structure parameters. Accordingly, using the periodic table, prototype structures, and the RF-based model, the LTC−temperature behavior of a huge number of compounds can be predicated.

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Cu3ErTe3: a new promising thermoelectric material predicated by high-throughput screening

Cited by 21 publications

References 42 publications

Crystalline Structure-Dependent Mechanical and Thermoelectric Performance in Ag2Se1‐xSx System

Crystalline Structure-Dependent Mechanical and Thermoelectric Performance in Ag2Se1‐xSx System

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

Lattice Thermal Conductivity: An Accelerated Discovery Guided by Machine Learning

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