Half-Heusler thermoelectrics: Advances from materials fundamental to device engineering

Joule, Год журнала: 2024, Номер 8(5), С. 1274 - 1311

Опубликована: Апрель 22, 2024

Язык: Английский

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High‐Throughput Strategies in the Discovery of Thermoelectric Materials

Advanced Materials, Год журнала: 2024, Номер 36(13)

Опубликована: Янв. 4, 2024

Searching for new high-performance thermoelectric (TE) materials that are economical and environmentally friendly is an urgent task TE society, but the advancements greatly limited by time-consuming high cost of traditional trial-and-error method. The significant progress achieved in computing hardware, efficient methods, advance artificial intelligence algorithms, rapidly growing material data have brought a paradigm shift investigation materials. Many electrical thermal performance descriptors proposed high-throughput (HTP) calculation methods developed with purpose to quickly screen potential from databases. Some HTP experiment also which can increase density information obtained single less time lower cost. In addition, machine learning (ML) introduced thermoelectrics. this review, strategies discovery systematically summarized. applications descriptor, calculation, experiment, ML reviewed. challenges possible directions future research discussed.

Язык: Английский

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SnSe: The rise of the ultrahigh thermoelectric performance material

Bulletin of the Korean Chemical Society, Год журнала: 2024, Номер 45(3), С. 186 - 199

Опубликована: Янв. 29, 2024

Abstract Thermoelectric materials can generate electric power from dissipating heat without releasing any undesirable chemicals. They thus increase global energy efficiency and reduce the use of fossil fuels that are a major resource for generating energy, thereby concurrently addressing environmental crises seriously threatening humanity. Increasing thermoelectric figure merit, ZT, has been prime goal in thermoelectrics because an generation low until very recently. The recent development ultrahigh performance polycrystalline SnSe‐based is one most prominent breakthroughs history thermoelectrics. show exceptionally high ZT ~3.1 at 783 K average ~2.0 400 to K, which highest bulk systems. Here we review advances SnSe thermoelectrics, greatly changing paradigm studies applications technology.

Язык: Английский

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Dealing with the big data challenges in AI for thermoelectric materials

Science China Materials, Год журнала: 2024, Номер 67(4), С. 1173 - 1182

Опубликована: Март 8, 2024

Язык: Английский

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Exploiting chemical bonding principles to design high-performance thermoelectric materials

Nature Reviews Chemistry, Год журнала: 2025, Номер unknown

Опубликована: Март 25, 2025

Язык: Английский

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High-Entropy Engineering in Thermoelectric Materials: A Review

Crystals, Год журнала: 2024, Номер 14(5), С. 432 - 432

Опубликована: Апрель 30, 2024

Thermoelectric (TE) materials play a crucial role in converting energy between heat and electricity, essentially for environmentally friendly renewable conversion technologies aimed at addressing the global crisis. Significant advances TE performance have been achieved over past decades various through key approaches, such as nanostructuring, band engineering, high-entropy engineering. Among them, design of has recently emerged forefront strategy to achieve significantly low thermal conductivity, attributed severe lattice distortion microstructure effects, thereby enhancing materials’ figure merit (zT). This review reveals progress developed decade. It discusses high-entropy-driven structural stabilization maintain favorable electrical transport properties, achieving impact high entropy on mechanical properties. Furthermore, explores theoretical development material potential strategies future advancements this field interactions among experimental studies.

Язык: Английский

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Machine learning assisted adsorption performance evaluation of biochar on heavy metal

Frontiers of Environmental Science & Engineering, Год журнала: 2024, Номер 18(5)

Опубликована: Янв. 20, 2024

Язык: Английский

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The application of machine learning in 3D/4D printed stimuli-responsive hydrogels

Advances in Colloid and Interface Science, Год журнала: 2024, Номер 336, С. 103360 - 103360

Опубликована: Ноя. 27, 2024

Язык: Английский

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Interpretable Machine Learning Model on Thermal Conductivity Using Publicly Available Datasets and Our Internal Lab Dataset

Chemistry of Materials, Год журнала: 2024, Номер 36(14), С. 7089 - 7100

Опубликована: Июль 3, 2024

Язык: Английский

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Machine-learning-assisted discovery of 212-Zintl-phase compounds with ultra-low lattice thermal conductivity

Journal of Materials Chemistry A, Год журнала: 2023, Номер 12(2), С. 1157 - 1165

Опубликована: Дек. 1, 2023

Machine-learning-assisted discovery of 212-Zintl-phase compounds with ultra-low lattice thermal conductivity.

Язык: Английский

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