相关论文: Unlocking Thermoelectric Potential: A Machine Lear…
Predictive models of thermodynamic properties of mixtures are paramount in chemical engineering and chemistry. Classical thermodynamic models are successful in generalizing over (continuous) conditions like temperature and concentration. On…
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)…
Half Heusler (HH) alloys with 18 valence electron count have attracted significant interest in the area of research related to thermoelectrics. Understanding the novel transport properties exhibited by these systems with semiconducting…
Calculating thermodynamic potentials and observables efficiently and accurately is key for the application of statistical mechanics simulations to materials science. However, naive Monte Carlo approaches, on which such calculations are…
This study introduces a language transformer-based machine learning model to predict key mechanical properties of high-entropy alloys (HEAs), addressing the challenges due to their complex, multi-principal element compositions and limited…
Stacking fault energy (SFE) is of the most critical microstructure attribute for controlling the deformation mechanism and optimizing mechanical properties of austenitic steels, while there are no accurate and straightforward computational…
We investigated six heavy element bismuth-based 18-VEC half-Heusler alloys CoTiBi, CoZrBi, CoHfBi, FeVBi, FeNbBi, and FeTaBi by first principles approach, in search of better thermoelectric prospects. The motivation is driven by expected…
Wildfires present intricate challenges for prediction, necessitating the use of sophisticated machine learning techniques for effective modeling\cite{jain2020review}. In our research, we conducted a thorough assessment of various machine…
Half-Heusler (HH) alloys have attracted considerable interest as promising thermoelectric (TE) materials in the temperature range around 700 K and above, which is close to the temperature range of most industrial waste heat sources. The…
Half-Heusler compounds (space group Fm3m) has garnered increasing attention in recent years in the thermoelectric community. Three decades ago, refractory RNiSn half-Heusler compounds (R represents refractory metals such as Hf, Zr, Ti) were…
Accurate knowledge of temperatures in power semiconductor modules is crucial for proper thermal management of such devices. Precise prediction of temperatures allows to operate the system at the physical limit of the device avoiding…
Ternary half Heusler alloys are under intense investigations recently towards achieving high thermoelectric figure-of-merit (ZT). Of particular interest is the ZrNiPb based half Heusler (HH) alloy where an optimal value of ZT = 0.7 at 773 K…
Half-Heusler (HH) phases (space group F43m, Clb) are increasingly gaining attention as promising thermoelectric materials in view of their thermal stability, scalability, and environmental benignity as well as efficient power output. Until…
Predicting and interpreting thermal performance under oscillating flow in porous structures remains a critical challenge due to the complex coupling between fluid dynamics and geometric features. This study introduces a data-driven…
The thermoelectric properties of n type semiconductor, TiNiSn is optimized by partial substitution with metallic, MnNiSb in the half Heusler structure. Herein, we study the transport properties and intrinsic phase separation in the system.…
Heusler compounds have emerged as important thermoelectric materials due to their combination of promising electronic transport properties, mechanical robustness and chemical stability -- key aspects for practical device integration. While…
While thermoelectric material performances can be estimated using the ZT, predicting the performance of thermoelectric generator modules (TGMs) is complex due to the non-linearity and non-locality of the thermoelectric differential…
We obtained the analytical expression for the effective thermoelectric properties and dimensionless figure of merit of a composite with interfacial electrical and thermal resistances using a micromechanics-based homogenisation. For the…
High-temperature alloy design requires a concurrent consideration of multiple mechanisms at different length scales. We propose a workflow that couples highly relevant physics into machine learning (ML) to predict properties of complex…
We analyze closed one-dimensional chains of weakly coupled many level systems, by means of the so-called Hilbert space average method (HAM). Subject to some concrete conditions on the Hamiltonian of the system, our theory predicts energy…