梯度成分块体热电材料快速制备与表征

Exploration of novel high-performance thermoelectric materials is one of the most important issues in the field of thermoelectrics. However, it is inefficient to prepare and characterize the sample by the traditional techniques, which hampers the development of new thermoelectric materials. In view of the above problem, this project proposes a new ideal for the rapid preparation and characterization of bulk thermoelectric materials with composition gradient. We will investigate and develop new techniques for the preparation of raw material rod with composition gradient, rapid fabrication of bulk thermoelectric material with composition gradient, discretization of the sample composition, and rapid measurement of the electrical and thermal transport properties. We will also solve the critical questions, including the diffusion control during the sintering of the composition-gradient sample, development of rapid measurement technique for heat-conducting property, and so on. Finally, a set of technologies applicable to the rapid preparation and characterization of bulk thermoelectric materials with composition gradient will be developed. Based on these technologies, the composition-structure-property relationship of the sample can be constructed quickly, which is very effective on searching out high-efficiency thermoelectric materials. Thus, these technologies will speed up the process of new materials research and development.

高性能新材料探索是热电材料研究领域的最重要任务之一，但是传统块体材料制备和表征手段效率较低，限制了热电新材料的研发速度。本项目针对该问题，提出了梯度成分块体热电材料快速制备与表征的新思路。通过研究和开发梯度成分原料棒自动化制备、梯度成分块体热电材料快速制备、样品成分离散化处理、以及电热输运性能快速检测等技术，并解决梯度成分样品烧结过程中的扩散以及后续导热性能快速检测等关键问题，发展出一套适用于新型热电材料探索的快速制备与表征一体化技术。基于该技术，能够快速准确构建样品不同区域的成分-结构-性能之间关系，从而有效地筛选出高性能热电材料，显著加速热电新材料的研发进程。

本项目开发了全链条的块体热电材料高通量制备及表征一体化技术。1）以制备成分准连续的块体样品为目标，开发了梯度原料棒自动化配制技术与装备、基于相图和热力学预测的优选烧结方案、以及退火与区熔等扩散控制工艺，制备出成分准连续变化的样品。在多个主流热电材料体系中，实现了多组分（不少于三种元素）、准连续成分分布（单个样品可划分出100个以上成分区域）块体样品的制备。2）开发了自动化智能配料装置，实现了自动化加样、高精度称量（±0.2 mg）、自动混料及压坯、远程控制等功能，显著提高了样品制备效率。3）开发了基于红外热成像法的非接触式热性能快速筛选技术。自主开发了热性能红外筛选系统，能够在真空或指定气氛条件下，实现从室温至600 ℃的样品热性能原位变温表征，实时提供样品温度分布及各微区温度随时间变化信息，实现了热性能的非接触式快速筛选。结合商用扫描探针获得的电性能分布，再利用统计学方法将塞贝克系数、电导率和热导率的空间分布数据整合分析，构建了样品热电性能的空间分布图像，实现了对目标材料的快速筛选。4）基于本项目开发的块体热电材料高通量实验筛选技术和装备，成功地对多个热电材料体系进行了高通量实验筛选，不仅有效地验证了开发的高通量技术方案及研制的科学装置的可行性与实用性，还筛选出了873K时热电优值高达1.6的高性能Cu掺杂PbSe-PbS材料。项目执行期间，发表SCI论文27篇；申请中国发明专利9项，已授权1项；培养博士研究生和硕士研究生9名。