Tuning Thermoelectric Conversion Performance of BiSbTe/Epoxy Flexible Films with Dot Magnetic Arrays.

ACS Appl Mater Interfaces

State Key Laboratory of Advanced Technology for Materials Synthesis and Processing, Wuhan University of Technology, Wuhan430070, China.

Published: February 2023

Embedding of magnetic functional units into the thermoelectric (TE) materials has been demonstrated to be an effective way to enhance the TE conversion performance. However, the magnetic functional units in TE materials are all randomly distributed. In this paper, to explore the effect of the ordering of the magnetic functional units on TE conversion performance, a series of BiSbTe/epoxy flexible thermoelectromagnetic (TEM) films with dot magnetic arrays were successfully prepared by a two-step screen printing combined with a hot pressing process. TEM films with dot magnetic arrays can achieve high carrier mobility, while the carrier concentration increases due to large coercivity. Therefore, its electrical conductivities are significantly improved on the condition that it maintains a high Seebeck coefficient. The TEM film with hexagonal-dot magnetic arrays exhibits the best electrical transport properties, for which the room-temperature power factor reaches 1.51 mW·m·K, increased by 33.6 and 36.1% as compared with those of the pristine TE film and the TEM film with a continuous magnetic layer, respectively. This work provides a new way to enhance the TE conversion performance of flexible TEM films through the ordered magnetic arrays.

Download full-text PDF

Source
http://dx.doi.org/10.1021/acsami.2c20348DOI Listing

Publication Analysis

Top Keywords

magnetic arrays
20
conversion performance
16
films dot
12
dot magnetic
12
magnetic functional
12
functional units
12
tem films
12
magnetic
9
bisbte/epoxy flexible
8
enhance conversion
8

Similar Publications

Clinical motion analysis plays an important role in the diagnosis and treatment of mobility-limiting diseases. Within this assessment, relative (point-to-point) tracking of extremities could benefit from increased accuracy. Given the limitations of current wearable sensor technology, supplementary spatial data such as distance estimates could provide added value.

View Article and Find Full Text PDF

This research investigates potential mechanisms of novel magnetic field (MF) treatments in inhibiting cell-wall-degrading enzymes, aiming to reduce weight loss and preserve the post-harvest quality of tomatoes ( L.) as a climacteric fruit. The optimization of the processing parameters, including MF intensity (1, 2, 3 mT), frequency (0, 50, 100 Hz), and duration (10, 20, 30 min), was accomplished by applying an orthogonal array design.

View Article and Find Full Text PDF

The capture of magnetic nanoparticles (MNPs) is essential in the separation and detection of MNPs for applications such as magnetic biosensing. The sensitivity of magnetic biosensors inherently depends upon the distribution of captured MNPs within the sensing area. We previously demonstrated that the distribution of MNPs captured from evaporating droplets by ferromagnetic antidot nanostructures can be controlled via an external magnetic field.

View Article and Find Full Text PDF

The study of transient and variable events, including novae, active galactic nuclei, and black hole binaries, has historically been a fruitful path for elucidating the evolutionary mechanisms of our universe. The study of such events in the millimeter and submillimeter is, however, still in its infancy. Submillimeter observations probe a variety of materials, such as optically thick dust, which are hard to study in other wavelengths.

View Article and Find Full Text PDF

Synthetic data have emerged as an attractive option for developing machine-learning methods in human neuroimaging, particularly in magnetic resonance imaging (MRI)-a modality where image contrast depends enormously on acquisition hardware and parameters. This retrospective paper reviews a family of recently proposed methods, based on synthetic data, for generalizable machine learning in brain MRI analysis. Central to this framework is the concept of domain randomization, which involves training neural networks on a vastly diverse array of synthetically generated images with random contrast properties.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!