CAREER: SusChEM: Data Mining to Reduce the Risk in Discovering New Sustainable Thermoelectric Materials

非技术总结：人类在21世纪面临着许多重大的工程挑战，从使太阳能变得负担得起，到为科学发现发明新的工具，再到防止核恐怖等等。许多这些挑战的一个共同要求是需要发现新材料，但传统材料的发现是缓慢、低效和昂贵的。显然，需要一种新的工具来更快地开发新材料，并且成本要低得多。一种可能性是依靠大数据来加速材料的发现。该项目通过使用数据挖掘工具为新的可持续热电材料创建材料推荐引擎，为国家利益服务。该引擎将根据所需性能的统计概率为新材料提供建议。科学家们将能够使用这个工具来指导实验工作，以探索全新的化合物，否则这些化合物的研究风险太大。由于热电是一种可以将废热转化为电能的装置，因此这个项目对美国的潜在好处是巨大的。目前，近三分之二的能源以废热的形式损失掉了，用新的热电材料回收其中的一小部分也将节省大量的能源。PI也将利用这个研究机会来补充他的教学和推广工作。学生将构建新型热电设备，并使用这些设备对盐湖城的少数民族高中和初中学生进行西班牙语/英语双语外展。技术概述：发现新材料是缓慢、低效和昂贵的。这些因素使得从化学空白空间中寻找新颖的新材料具有很高的风险。相反，大多数新的开发是在已知的或已建立的结构类型、化学和系统中逐渐发生的。然而，利用新兴的材料信息学领域，可以减轻与探索新化合物化学空白空间相关的风险。在本提案中，将使用热电材料推荐引擎提出新颖的、可持续的热电成分。该引擎仅使用成分来对性能进行概率估计，而不是进行计算上昂贵的计算，后者通常需要先验地了解晶体结构。避免将晶体结构作为初始输入意味着可以使用该工具发现全新的化合物。引擎输出是在期望性能范围内的组合物的概率。因此，这个项目将把这些预测与现有的化合物应该在哪里形成的预测结合起来，实验探索新的热电材料。算法和描述符开发的训练数据集将通过包含性能较差、中等和良好的材料来改进，以克服文献中对高性能材料的偏见。实验合成和表征将进行建议的化合物和算法验证。

NON-TECHNICAL SUMMARY:Humanity faces a number of grand challenges in engineering in the 21st century ranging from making solar energy affordable, to inventing new tools for scientific discovery, to preventing nuclear terror and more. A common requirement to many of these challenges is the need to discover new materials but traditional materials discovery is slow, inefficient, and expensive. Clearly, a new tool is required to develop new materials faster and at a fraction of the cost. One possibility is to rely on big data to accelerate materials discovery. This project serves the national interest by using data mining tools to create a materials recommendation engine for new sustainable thermoelectric materials. This engine will provide recommendations for new materials based off of statistical probability of desired performance. Scientists will be able to use this tool to guide experimental efforts to explore totally new compounds that would be too risky to investigate otherwise. Since thermoelectrics are devices that can convert waste heat to electricity the potential for this project to benefit the United States is significant. Currently close to two thirds of energy is lost as waste heat and recovering even a small fraction of this with new thermoelectric materials would amount to enormous energy savings. The PI will also leverage this research opportunity to supplement his teaching and outreach efforts. Students will construct novel thermoelectric devices and use these devices to perform bilingual Spanish/English outreach to minority-majority high school and junior high students in Salt Lake City.TECHNICAL SUMMARY:Discovering new materials is slow, inefficient, and expensive. These factors make searching for novel new materials from chemical white space very high risk. Instead, most new developments occur incrementally in already known or established structure types, chemistries, and systems. However, the risk associated with exploring chemical white space for new compounds can be mitigated by utilizing the emergent field of materials informatics. In this proposal novel, sustainable thermoelectric compositions will be suggested using a materials recommendation engine for thermoelectrics. The engine uses composition only to make probabilistic estimates of performance rather than computationally expensive calculations which generally require knowledge of the crystal structure a priori. Avoiding crystal structure as an initial input means entirely new compounds can be discovered with this tool. The engine output is a probability of compositions lying within a desired performance range. Therefore, this project will combine these predictions with existing predictions of where compounds should form to experimentally explore novel thermoelectric materials. The training data set for algorithm and descriptor development will be improved by inclusion of performance of poor, mediocre, as well as good materials to overcome the bias in literature for high-performing materials. Experimental synthesis and characterization will be carried out on suggested compounds and for algorithm validation.