Collaborative Research: Guided Discovery of Sustainable Superhard Materials via Bond Optimization
合作研究:通过键优化引导可持续超硬材料的发现
基本信息
- 批准号:1562226
- 负责人:
- 金额:$ 25万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2016
- 资助国家:美国
- 起止时间:2016-06-01 至 2020-05-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Superhard, wear resistant materials are widely used by the automotive, aerospace, oil and gas, and any manufacturing industry that relies on drilling, cutting, and grinding. Yet, the synthesis of most materials employed for these applications, such as polycrystalline diamond, require high temperatures and extreme pressures, which escalates their cost. A class of materials known as transition metal borides are more easily processed making them viable alternatives; however, they contain expensive and exceedingly scarce metals. This award supports the fundamental research necessary to discover new, low-cost synthetic processes for novel superhard, wear resistant materials that incorporate earth-abundant elements. Achieving these research goals will require the integration of materials engineering, chemistry, computational physics, and data mining. This coordinated approach will not only lead to higher performance materials but it also has the potential to transform many manufacturing processes by replacing current systems with sustainable, cost-effective alternatives. Further, this award will be used to teach undergraduate and graduate students how to address materials design problems through a multi-disciplinary, holistic picture that includes both performance and resource considerations. Teaching the next generation of STEM students how fundamental chemical research can lead to applied materials engineering is essential for global competitiveness. The development of earth-abundant, superhard materials will employ informatics and computation to screen ternary intermetallic boride and carbide phase space. In combination, this approach will guide the experimental identification of novel crystal structures with outstanding mechanical properties. The research team will develop energy efficient microwave heating, induction heating, and solution-based synthesis to overcome the conventional high temperatures and pressures required to prepare these materials. Additionally, novel mechanochemical experiments using in-situ nanoindentation coupled with IR spectroscopy, in conjunction with first principles electronic structure theory, will establish the fundamental mechanisms of mechanical deformation. These experiments will serve to validate the computationally screened compounds as well as reveal opportunities to optimize chemical bonding interactions further enhancing the mechanical response. The result will inform the future advancement of engineering materials by producing a methodological framework to understand the mechanics of disparate classes of complex inorganic solids.
超硬耐磨材料广泛应用于汽车、航空航天、石油和天然气以及任何依赖钻孔、切割和磨削的制造业。然而,用于这些应用的大多数材料(例如多晶金刚石)的合成需要高温和极压,这会增加其成本。一类被称为过渡金属硼化物的材料更容易加工,使其成为可行的替代品;然而,它们含有昂贵且极其稀有的金属。该奖项支持必要的基础研究,以发现新的低成本合成工艺,以生产包含地球丰富元素的新型超硬耐磨材料。实现这些研究目标需要整合材料工程、化学、计算物理和数据挖掘。这种协调的方法不仅会带来更高性能的材料,而且还有可能通过用可持续、具有成本效益的替代品取代当前系统来改变许多制造工艺。此外,该奖项将用于教授本科生和研究生如何通过包括性能和资源考虑在内的多学科、整体图景来解决材料设计问题。教导下一代 STEM 学生如何将基础化学研究引向应用材料工程对于全球竞争力至关重要。 地球储量丰富的超硬材料的开发将利用信息学和计算来筛选三元金属间硼化物和碳化物相空间。结合起来,这种方法将指导具有出色机械性能的新型晶体结构的实验鉴定。研究团队将开发节能的微波加热、感应加热和基于溶液的合成,以克服制备这些材料所需的传统高温和高压。此外,使用原位纳米压痕与红外光谱结合的新型机械化学实验,结合第一原理电子结构理论,将建立机械变形的基本机制。这些实验将用于验证计算筛选的化合物,并揭示优化化学键相互作用的机会,进一步增强机械响应。该结果将通过产生一个方法框架来了解不同类别的复杂无机固体的力学,从而为工程材料的未来进步提供信息。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Taylor Sparks其他文献
Taylor Sparks的其他文献
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{{ truncateString('Taylor Sparks', 18)}}的其他基金
EAGER: SSMCDAT2023: Natural Language Processing and Large Language Models for Automated Extraction of Materials Chemistry Data from Scientific Literature
EAGER:SSMCDAT2023:用于从科学文献中自动提取材料化学数据的自然语言处理和大型语言模型
- 批准号:
2334411 - 财政年份:2023
- 资助金额:
$ 25万 - 项目类别:
Standard Grant
REU Site: Research Experience in Utah for Sustainable Materials Engineering (ReUSE)
REU 网站:犹他州可持续材料工程(再利用)的研究经验
- 批准号:
1950589 - 财政年份:2020
- 资助金额:
$ 25万 - 项目类别:
Standard Grant
Collaborative Research: SSMCDAT2020: Solid-State and Materials Chemistry Data Science Hackathon
合作研究:SSMCDAT2020:固态和材料化学数据科学黑客马拉松
- 批准号:
1938734 - 财政年份:2019
- 资助金额:
$ 25万 - 项目类别:
Standard Grant
CAREER: SusChEM: Data Mining to Reduce the Risk in Discovering New Sustainable Thermoelectric Materials
职业:SusChEM:通过数据挖掘降低发现新型可持续热电材料的风险
- 批准号:
1651668 - 财政年份:2017
- 资助金额:
$ 25万 - 项目类别:
Continuing Grant
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