PFI (ERI): Screening and Development of Doped Mixed Metal Oxides for Resistance-Heated Thermal Energy Storage

PFI (ERI)：用于电阻加热热能存储的掺杂混合金属氧化物的筛选和开发

• 批准号: 2138456
• 负责人: Stephen Lam
• 金额: $ 19.99万
• 依托单位: University of Massachusetts Lowell
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-05-01 至 2025-04-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2138456&HistoricalAwards=false
• 关键词: PFI; ERI; Screening; Development; Doped

The broader impact/commercial potential of this Partnerships for Innovation (Engineering Research Initiation) (PFI (ERI)) project is the enabling of versatile, low-cost thermal energy storage technologies that will result from the materials development work. Direct resistance-heated thermal energy storage (DRH-ETS) technology stores electricity from the grid, which can either be directly utilized for high-temperature industrial heat or efficiently converted back to electricity. This directly addresses the global decarbonization challenges of (1) balancing supply and demand on an electrical grid with a high penetration of renewables, and (2) reducing industrial dependence of fossil fuels for producing high-temperature industrial heat. In 2021, combustion of fossil fuels for the production of heat in heavy industrial applications such as cement and steel-making accounted for 10% of all global emissions. Yet, the options for decarbonizing industrial heat inputs remain very limited, with most being cost-prohibitive at large scale. Traditional thermal energy storage technologies utilizing indirect metallic heating elements have been recognized as among the most cost-effective heating options but cannot achieve high enough temperatures to suit most carbon-intensive processes. DRH-ETS will overcome these limitations by using electricity to directly heat conductive thermal storage materials.The proposed project will screen and develop materials that optimize the performance of DRH-ETS systems. While refractory oxide materials have good oxidation resistance and can be doped for electrical conductivity, most simple binary oxides are unable to satisfy the combination of required chemical, thermal, and electrical properties. As such, the number of known bulk-dopant material combinations that would be feasible for DRH-ETS applications is extremely limited. Here, mixed metal oxides are promising, but the relevant properties of most higher order mixtures are not readily known. To address this challenge, this project will perform computational screening of materials for single-phase stability over a large temperature range, small resistivity temperature derivative, and dopability. The screening will employ a combination of thermochemical modeling, electronic band structure calculations, and ab initio defect analysis to downselect from large multicomponent compositional spaces. This will result in improved understanding of composition-structure-property relationships in doped multinary metal oxides, which will inform system design and operation. This screening will be combined with fabrication and testing to identify and develop new candidate materials for achieving low cost and optimal performance in a DRH-ETS system.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

这种创新合作伙伴关系（工程研究启动）（PFI（ERI））项目的更广泛的影响/商业潜力是启用由材料开发工作产生的多功能，低成本的热量储能技术。直接电阻加热的热能储存（DRH-ETS）技术可从网格中存储电力，该电网可以直接用于高温工业热量，或者有效地转换回电力。这直接解决了（1）在电网上平衡供求的全球脱碳挑战与可再生能源的渗透率很高，以及（2）减少化石燃料的工业依赖性，以产生高温工业热量。 2021年，化石燃料在重工厂（例如水泥和钢制造）中生产热量的燃烧占所有全球排放量的10％。然而，脱碳工业热输入的选择仍然非常有限，大多数是大规模成本过高的。利用间接金属加热元件的传统热能储能技术已被认为是最具成本效益的加热选择之一，但无法达到足够高的温度来适应大多数碳密集型过程。 DRH-ET将通过使用电力直接加热导电储存材料来克服这些局限性。拟议的项目将筛选和开发优化DRH-ETS系统性能的材料。虽然难治性氧化物材料具有良好的氧化耐药性，并且可以用于电导率，但大多数简单的二元氧化物无法满足所需的化学，热和电性能的组合。因此，对于DRH-ETS应用来说是可行的，已知的散装材料组合的数量极为有限。在这里，混合的金属氧化物是有希望的，但是大多数高阶混合物的相关特性却不容易知道。为了应对这一挑战，该项目将对材料进行计算筛查，以在较大温度范围内，电阻率温度导数和吸毒性较小的单相稳定性。该筛选将采用热化学建模，电子带结构计算和从头算缺陷分析的组合，以降低大型多组分组成空间的选择。这将提高人们对掺杂的多元金属氧化物中组成结构 - 特制关系的了解，这将为系统设计和操作提供信息。该筛查将与制造和测试相结合，以识别和开发新的候选材料，以实现DRH-ETS系统中的低成本和最佳性能。该奖项反映了NSF的法定任务，并且认为值得通过基金会的知识分子优点和更广泛的影响来通过评估来获得支持。

项目成果

High-Throughput Prediction of Molten Salt Mixture Density with Supervised Machine Learning

利用监督机器学习高通量预测熔盐混合物密度

• 发表时间: 2023
• 期刊: Transactions of the American Nuclear Society
• 作者: Julián Barra Otondo, Shayan Shahbazi