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.

这个创新伙伴关系（工程研究启动）（PFI (ERI)）项目的更广泛的影响/商业潜力是实现多功能，低成本的热能储存技术，这将从材料开发工作中产生。直接电阻加热热能储存（DRH-ETS）技术储存来自电网的电力，这些电力既可以直接用于高温工业供热，也可以有效地转换回电力。这直接解决了全球脱碳的挑战：(1)在可再生能源高渗透率的电网上平衡供需，以及(2)减少工业对生产高温工业热的化石燃料的依赖。2021年，水泥和炼钢等重工业应用中燃烧化石燃料产生的热量占全球总排放量的10%。然而，工业热输入脱碳的选择仍然非常有限，大多数在大规模上成本过高。利用间接金属加热元件的传统热能储存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，以适应大多数碳密集型工艺。DRH-ETS将通过直接使用电来导热储热材料来克服这些限制。拟议的项目将筛选和开发优化DRH-ETS系统性能的材料。虽然耐火氧化物材料具有良好的抗氧化性，并且可以掺杂电导率，但大多数简单的二元氧化物无法满足所需的化学，热学和电学性能的组合。因此，可用于DRH-ETS应用的已知块状掺杂材料组合的数量非常有限。在这里，混合金属氧化物很有前途，但大多数高阶混合物的相关性质尚不清楚。为了应对这一挑战，该项目将对材料在大温度范围内的单相稳定性、小电阻率温度导数和可掺杂性进行计算筛选。筛选将采用热化学建模、电子能带结构计算和从头算缺陷分析相结合的方法，从大型多组分组成空间中进行筛选。这将提高对掺杂多金属氧化物的组成-结构-性质关系的理解，这将为系统设计和操作提供信息。这种筛选将与制造和测试相结合，以确定和开发新的候选材料，从而在DRH-ETS系统中实现低成本和最佳性能。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

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