课题基金 / 基金详情

RII Track-2 FEC:Cost-effective Conversion of Natural Gas and Biomass to Hydrogen and Performance Carbons

RII Track-2 FEC:Cost-effective Conversion of Natural Gas and Biomass to Hydrogen and Performance Carbons
RII Track-2 FEC:将天然气和生物质经济高效地转化为氢气和高性能碳
批准号:
2218070
负责人:
Steven Crossley
金额:
$400.0万
依托单位国家:
美国
项目类别:
Cooperative Agreement
财政年份:
2022
资助国家:
美国
项目状态:
未结题
起止时间:
2022-08-01 至 2026-07-31

项目摘要

项目成果

Steven Crossley的其他基金

相似基金

相关文献

中文摘要
翻译
在这个多学科和双机构合作项目中,来自俄克拉荷马大学和爱荷华州立大学的研究人员将研究基本原则,这些基本原则将加速开发可持续和具有成本效益的无碳或负碳氢气和增值先进材料的生产工艺,包括碳纳米管和碳纳米纤维。在过去,获得这些先进材料的过程都是基于利基的高价值固体产品开发的,而没有关注气态副产品的价值或大规模利用。这里的重点是大规模、低成本地生产无二氧化碳的氢气。也就是说,该项目将侧重于提高丰富的天然气资源的氢气产量,使用富含地球的金属作为催化材料,出于环境和技术经济原因,需要从固体产品中回收氢气。因此,该项目的一个核心部分是氢产率和催化剂回收能力的优化。从技术经济角度来看,次要但同样重要的部分是可用于大规模应用的高性能碳材料的性能优化。在该项目的后半部分,还将探索其他新兴的高影响技术,如无碳合成氨和利用废塑料生产环境友好的能源。该项目包括具有互补专业知识的研究人员,从催化过程的实验和理论建模和技术经济建模,到活性催化表面的材料合成和表征,以及生产的碳纳米材料的表征。该研究计划设想基于具有特定基本步骤序列的现实模型的实验动力学,纳米尺度的材料和过程的表征,以及从第一原理密度泛函理论(DFT)和从头算分子动力学(AIMD)计算的计算分析。机器学习和人工智能方法将被纳入该项目,以连接各种建模尺度并预测有前景的表面结构。该项目还将开展重要的社区推广活动,包括为人数不足的本科生提供研究机会,以及举办针对高中生的实践活动的讲习班,以更好地教育学生在避免或尽量减少温室气体排放的同时,技术在能源生产中的重要性。该团队将与地区MSI和部落学院合作,为代表不足的群体创造研究机会,如美洲原住民学生,以鼓励和授权他们攻读工程学研究生学位。这一奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
In this multidisciplinary and bi-institutional collaborative project, researchers from the University of Oklahoma and Iowa State University will investigate fundamental principles that will accelerate the development of sustainable and cost-effective processes for production of carbon-free or carbon-negative hydrogen and value-added advanced materials, including carbon nanotubes and carbon nanofibers. In the past, processes to obtain these advanced materials have been developed based on niche high-value solid products, without focusing on the value or utilization of the gaseous by-product at a large scale. Here, the emphasis is in the large-scale and low-cost production of CO2-free hydrogen. Namely, the project will focus on enhancing hydrogen yields from abundant natural gas resources using earth-abundant metals as catalytic materials, which need to be reclaimed from the solid product for environmental and technoeconomic reasons. Therefore, a central part of the project is the optimization of hydrogen yield and catalyst recyclability. A secondary but equally important part from a technoeconomic standpoint is the property optimization of the resulting performance carbon materials that could be employed in large-scale applications. In the latter half of the project, other emerging high-impact technologies, such as carbon-free ammonia production and environmentally benign energy from waste plastics will also be explored.This project includes researchers with complementary expertise ranging from experimental and theoretical modeling and technoeconomic modeling of the catalytic processes to materials synthesis and characterization of reactive catalytic surfaces as well as characterization of the produced carbon nanomaterials. The research plan contemplates experimental kinetics based on realistic models with specified sequences of elementary steps, characterization of the materials and processes at the nanoscale, and computational analysis ranging from first-principles density functional theory (DFT) and ab-initio molecular dynamics (AIMD) calculations. Machine learning and artificial intelligence methods will be incorporated in the project to connect the various modeling scales and predict promising surface structures. This project will also carry a significant community outreach component, including research opportunities for underrepresented undergraduate students, as well as workshops with hands-on activities aimed at high school students to better educate students on the importance of technology in energy generation while avoiding or minimizing greenhouse gas emissions. The team will pair with regional MSI’s and tribal colleges to create research opportunities for underrepresented groups, such as Native American students, to encourage and empower them to pursue graduate degrees in engineering.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.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
CAS: Collaborative Research: Tailoring the Distribution of Transient vs. Dynamic Active Sites in Solid-Acid Catalysts and Their Impacts on Chemical Conversions
  • 批准号:
    2154399
  • 项目类别:
    Standard Grant
  • 资助金额:
    $56.56万
  • 财政年份:
    2022
  • 负责人:
    Steven Crossley
  • 依托单位:
EFRI E3P: Tuning Catalyst Design to Recycle Mixed Polymer Streams
  • 批准号:
    2029394
  • 项目类别:
    Standard Grant
  • 资助金额:
    $200.0万
  • 财政年份:
    2021
  • 负责人:
    Steven Crossley
  • 依托单位:
Collaborative Research: Understanding an Active and Beneficial Role for Water in Solid-Acid Catalyzed Hydrocarbon Chemistry
  • 批准号:
    1764130
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $59.82万
  • 财政年份:
    2018
  • 负责人:
    Steven Crossley
  • 依托单位:
SusChEM:CAREER:Using unique synthesis techniques and reaction kinetics to quantify and manipulate catalytically active sites in metal-reducible oxide systems
  • 批准号:
    1653935
  • 项目类别:
    Standard Grant
  • 资助金额:
    $54.88万
  • 财政年份:
    2017
  • 负责人:
    Steven Crossley
  • 依托单位:
海外基金