Related papers: Efficient technique for computational design of th…
The discovery of high-performance thermoelectric (TE) materials for advancing green energy harvesting from waste heat is an urgent need in the context of looming energy crisis and climate change. The rapid advancement of machine learning…
Thermoelectric materials create an electric potential when subject to a temperature gradient and vice versa hence they can be used to harvest waste heat into electricity and in thermal management applications. However, finding highly…
We investigated the accelerated prediction of the thermal conductivity of materials through end- to-end structure-based approaches employing machine learning methods. Due to the non-availability of high-quality thermal conductivity data, we…
Thermoelectrics are a promising class of materials for renewable energy owing to their capability to generate electricity from waste heat, with their performance being governed by a competition between charge and thermal transport. A…
The experimental search for new thermoelectric materials remains largely confined to a limited set of successful chemical and structural families, such as chalcogenides, skutterudites, and Zintl phases. In principle, computational tools…
Thermoelectric (TE) technology enables direct heat-to-electricity conversion and is gaining attention as a clean, fuel-saving, and carbon-neutral solution for industrial, automotive, and marine applications. Despite nearly a century of…
We report the machine learning (ML)-based approach allowing thermoelectric generator (TEG) efficiency evaluation directly from 5 parameters: 2 physical properties - carriers density and energy gap, and 3 engineering parameters - external…
Thermoelectric materials intrigue much interest due to their wide range of application such as power generators and refrigerators. The efficiency of thermoelectric materials is quantified by the figure of merit, and a figure greater than…
The growing market for sensors, internet of things, and wearable devices is fueling the development of low-cost energy-harvesting materials and systems. Film based thermoelectric (TE) devices offer the ability to address the energy…
In this work, we first perform a systematic search for high-efficiency three-dimensional (3D) and two-dimensional (2D) thermoelectric materials by combining semiclassical transport techniques with density functional theory (DFT)…
Since the implementation of the Materials Genome Project by the Obama administration in the United States, the development of various computational materials databases has fundamentally expanded the choices of industries such as materials…
In this Letter, we show thermoelectric conversion efficiency is \emph{exactly} determined by \emph{three} independent material parameters $Z_{\rm gen}$, $\tau$, and $\beta$. Each parameter is a figure of merit hence improving $\tau$ or…
Thermoelectric properties of Half Heusler alloys are predicted by adopting an ensemble modelling approach, specifically the stacking model integrated using Random Forest and XGBoost scheme. Leveraging a diverse dataset encompassing thermal…
Dielectric structures composed of many inclusions that manipulate light in ways the bulk materials cannot are commonly seen in the field of metamaterials. In these structures, each inclusion depends on a set of parameters such as location…
The principles of the thermoelectric phenomenon, including Seebeck effect, Peltier effect, and Thomson effect are discussed. The dependence of the thermoelectric devices on the figure of merit, Seebeck coefficient, electrical conductivity,…
We introduce a first-principles method for predicting the magnetothermal properties of solid-state materials, which we call Sampled Effective Local Field Estimation. This approach achieves over two orders of magnitude improvement in sample…
Whether porosity can effectively improve thermoelectric performance is still an open question. Herein we report that thermoelectric performance can be significantly enhanced by creating porosity in n-type Mg3.225Mn0.025Sb1.5Bi0.49Te0.01,…
Thermoelectric performance is of interest for numerous applications such as waste heat recovery and solid state energy conversion, and will be seen to be closely connected to topological insulator behavior. In this context we here report…
Thermoelectric (TE) air cooling is a solid-state technology that has the potential to replace conventional vapor compression-based air conditioning. In this paper, we present a detailed system-level modeling for thermoelectric air…
A system responding to a stochastic driving signal can be interpreted as computing, by means of its dynamics, an implicit model of the environmental variables. The system's state retains information about past environmental fluctuations,…