scholarly journals High Thermoelectric Performance of Cu-Doped PbSe-PbS System Enabled by High-Throughput Experimental Screening

Research ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Li You ◽  
Zhili Li ◽  
Quanying Ma ◽  
Shiyang He ◽  
Qidong Zhang ◽  
...  
Keyword(s):  
Experimental Technique ◽  
High Throughput ◽  
Thermoelectric Materials ◽  
High Performance ◽  
Large Scale ◽  
Transport Model ◽  
Thermoelectric Performance ◽  
Trial And Error ◽  
Lead Chalcogenides ◽  
Experimental Discovery

Recent advances in high-throughput (HTP) computational power and machine learning have led to great achievements in exploration of new thermoelectric materials. However, experimental discovery and optimization of thermoelectric materials have long relied on the traditional Edisonian trial and error approach. Herein, we demonstrate that ultrahigh thermoelectric performance in a Cu-doped PbSe-PbS system can be realized by HTP experimental screening and precise property modulation. Combining the HTP experimental technique with transport model analysis, an optimal Se/S ratio showing high thermoelectric performance has been efficiently screened out. Subsequently, based on the screened Se/S ratio, the doping content of Cu has been subtly adjusted to reach the optimum carrier concentration. As a result, an outstanding peak zT~1.6 is achieved at 873 K for a 1.8 at% Cu-doped PbSe0.6S0.4 sample, which is the superior value among the n-type Te-free lead chalcogenides. We anticipate that current work will stimulate large-scale unitization of the HTP experimental technique in the thermoelectric field, which can greatly accelerate the research and development of new high-performance thermoelectric materials.

Designing high-performance n-type Mg3Sb2-based thermoelectric materials through forming solid solutions and biaxial strain

2018 ◽  
Vol 6 (41) ◽  
pp. 20454-20462 ◽  
Author(s):  
Juan Li ◽  
Shuai Zhang ◽  
Boyi Wang ◽  
Shichao Liu ◽  
Luo Yue ◽  
...  
Keyword(s):  
Solid Solutions ◽  
Thermoelectric Materials ◽  
High Performance ◽  
Thermoelectric Performance ◽  
Biaxial Strain

Thermoelectric performance can be largely enhanced by forming solid solutions and biaxial strain.

Nanostructure controlled construction of high-performance thermoelectric materials of polymers and their composites

2018 ◽  
Vol 6 (45) ◽  
pp. 22381-22390 ◽  
Author(s):  
Yufeng Xue ◽  
Chunmei Gao ◽  
Lirong Liang ◽  
Xin Wang ◽  
Guangming Chen
Keyword(s):  
Thermoelectric Materials ◽  
High Performance ◽  
Thermoelectric Performance ◽  
Recent Advances

This review discusses recent advances in controlled fabrication of nanostructures and the enhanced thermoelectric performance of polymers and their composites.

Large Scale Solid State Synthetic Technique for High Performance Thermoelectric Materials: Magnesium-Silicide-Stannide

2020 ◽  
Vol 3 (3) ◽  
pp. 2130-2136
Author(s):  
Daniel C. Ramirez ◽  
Leilane R. Macario ◽  
Xiaoyu Cheng ◽  
Michael Cino ◽  
Daniel Walsh ◽  
...  
Keyword(s):  
Solid State ◽  
Thermoelectric Materials ◽  
High Performance ◽  
Large Scale ◽  
Magnesium Silicide

High thermoelectric performance in low-cost SnS0.91Se0.09 crystals

Science ◽  
2019 ◽  
Vol 365 (6460) ◽  
pp. 1418-1424 ◽  
Author(s):  
Wenke He ◽  
Dongyang Wang ◽  
Haijun Wu ◽  
Yu Xiao ◽  
Yang Zhang ◽  
...  
Keyword(s):  
Thermoelectric Materials ◽  
High Performance ◽  
Carrier Mobility ◽  
Figure Of Merit ◽  
Toxic Elements ◽  
Low Cost ◽  
Thermoelectric Performance ◽  
Tin Sulfide ◽  
Temperature Dependent ◽  
Earth Abundant

Thermoelectric technology allows conversion between heat and electricity. Many good thermoelectric materials contain rare or toxic elements, so developing low-cost and high-performance thermoelectric materials is warranted. Here, we report the temperature-dependent interplay of three separate electronic bands in hole-doped tin sulfide (SnS) crystals. This behavior leads to synergistic optimization between effective mass (m*) and carrier mobility (μ) and can be boosted through introducing selenium (Se). This enhanced the power factor from ~30 to ~53 microwatts per centimeter per square kelvin (μW cm−1 K−2 at 300 K), while lowering the thermal conductivity after Se alloying. As a result, we obtained a maximum figure of merit ZT (ZTmax) of ~1.6 at 873 K and an average ZT (ZTave) of ~1.25 at 300 to 873 K in SnS0.91Se0.09 crystals. Our strategy for band manipulation offers a different route for optimizing thermoelectric performance. The high-performance SnS crystals represent an important step toward low-cost, Earth-abundant, and environmentally friendly thermoelectrics.

High-throughput computational screening of 2D materials for thermoelectrics

2020 ◽  
Vol 8 (37) ◽  
pp. 19674-19683
Author(s):  
Sevil Sarikurt ◽  
Tuğbey Kocabaş ◽  
Cem Sevik
Keyword(s):  
Renewable Energy ◽  
High Throughput ◽  
Thermoelectric Materials ◽  
High Performance ◽  
2D Materials ◽  
Energy Applications ◽  
Computational Screening

High-performance thermoelectric materials are critical in recuperating the thermal losses in various machinery and promising in renewable energy applications.

scholarly journals Metallization and Diffusion Bonding of CoSb3-Based Thermoelectric Materials

Materials ◽  
2020 ◽  
Vol 13 (5) ◽  
pp. 1130 ◽  
Author(s):  
Hangbin Feng ◽  
Lixia Zhang ◽  
Jialun Zhang ◽  
Wenqin Gou ◽  
Sujuan Zhong ◽  
...  
Keyword(s):  
Thermoelectric Materials ◽  
Diffusion Bonding ◽  
High Performance ◽  
Large Scale ◽  
Coefficient Of Thermal Expansion ◽  
Good Thermal Stability ◽  
Metallization Layer ◽  
Low Temperature Annealing ◽  
Specific Contact ◽  
Bonding Method

CoSb3-based skutterudite alloy is one of the most promising thermoelectric materials in the middle temperature range (room temperature—550 °C). However, the realization of an appropriate metallization layer directly on the sintered skutterudite pellet is indispensable for the real thermoelectric generation application. Here, we report an approach to prepare the metallization layer and the subsequent diffusion bonding method for the high-performance multi-filled n-type skutterudite alloys. Using the electroplating followed by low-temperature annealing approaches, we successfully fabricated a Co-Mo metallization layer on the surface of the skutterudite alloy. The coefficient of thermal expansion of the electroplated layer was optimized by changing its chemical composition, which can be controlled by the electroplating temperature, current and the concentration of the Mo ions in the solution. We then joined the metallized skutterudite leg to the Cu-Mo electrode using a diffusion bonding method performed at 600 °C and 1 MPa for 10 min. The Co-Mo/skutterudite interfaces exhibit extremely low specific contact resistivity of 1.41 μΩ cm2. The metallization layer inhibited the elemental inter-diffusion to less than 11 µm after annealing at 550 °C for 60 h, indicating a good thermal stability. The current results pave the way for the large-scale fabrication of CoSb3-based thermoelectric modules.

Discovery of High Performance Thermoelectric Chalcogenides Through First-Principles High-Throughput Screening

2021 ◽  
Author(s):  
Tao Fan ◽  
Artem R. Oganov
Keyword(s):  
Transport Properties ◽  
High Throughput ◽  
Thermoelectric Materials ◽  
First Principles ◽  
High Throughput Screening ◽  
High Performance ◽  
Energy Conversion Efficiency ◽  
High Energy ◽  
Energy And Environment ◽  
High Energy Conversion Efficiency

Searching for thermoelectric materials with high energy conversion efficiency is important to solve the energy and environment issues of our society. In this work, we studied the thermoelectric-related transport properties...

scholarly journals High-performance computing service for bioinformatics and data science

2018 ◽  
Vol 106 (4) ◽  
Author(s):  
Jean-Paul Courneya ◽  
Alexa Mayo
Keyword(s):  
Open Source ◽  
High Throughput ◽  
High Performance ◽  
Large Scale ◽  
Data Science ◽  
Wet Work ◽  
High Throughput Data ◽  
Guided Learning ◽  
Computational Resources ◽  
Performance Computing

Despite having an ideal setup in their labs for wet work, researchers often lack the computational infrastructure to analyze the magnitude of data that result from “-omics” experiments. In this innovative project, the library supports analysis of high-throughput data from global molecular profiling experiments by offering a high-performance computer with open source software along with expert bioinformationist support. The audience for this new service is faculty, staff, and students for whom using the university’s large scale, CORE computational resources is not warranted because these resources exceed the needs of smaller projects. In the library’s approach, users are empowered to analyze high-throughput data that they otherwise would not be able to on their own computers. To develop the project, the library’s bioinformationist identified the ideal computing hardware and a group of open source bioinformatics software to provide analysis options for experimental data such as scientific images, sequence reads, and flow cytometry files. To close the loop between learning and practice, the bioinformationist developed self-guided learning materials and workshops or consultations on topics such as the National Center for Biotechnology Information’s BLAST, Bioinformatics on the Cloud, and ImageJ. Researchers apply the data analysis techniques that they learned in the classroom in an ideal computing environment.

scholarly journals Large-scale HPC deployment of Scalable CyberInfrastructure for Artificial Intelligence and Likelihood Free Inference (SCAILFIN)

2020 ◽  
Vol 245 ◽  
pp. 09011
Author(s):  
Michael Hildreth ◽  
Kenyi Paolo Hurtado Anampa ◽  
Cody Kankel ◽  
Scott Hampton ◽  
Paul Brenner ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Data Analysis ◽  
High Performance Computing ◽  
High Throughput ◽  
High Performance ◽  
Large Scale ◽  
Starting Point ◽  
Virtual Clusters ◽  
Analysis Platform ◽  
Performance Computing

The NSF-funded Scalable CyberInfrastructure for Artificial Intelligence and Likelihood Free Inference (SCAILFIN) project aims to develop and deploy artificial intelligence (AI) and likelihood-free inference (LFI) techniques and software using scalable cyberinfrastructure (CI) built on top of existing CI elements. Specifically, the project has extended the CERN-based REANA framework, a cloud-based data analysis platform deployed on top of Kubernetes clusters that was originally designed to enable analysis reusability and reproducibility. REANA is capable of orchestrating extremely complicated multi-step workflows, and uses Kubernetes clusters both for scheduling and distributing container-based workloads across a cluster of available machines, as well as instantiating and monitoring the concrete workloads themselves. This work describes the challenges and development efforts involved in extending REANA and the components that were developed in order to enable large scale deployment on High Performance Computing (HPC) resources. Using the Virtual Clusters for Community Computation (VC3) infrastructure as a starting point, we implemented REANA to work with a number of differing workload managers, including both high performance and high throughput, while simultaneously removing REANA’s dependence on Kubernetes support at the workers level.

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