Novel first-principles methods for studying thermoelastic properties of materials

研究材料热弹性特性的新第一性原理方法

基本信息

  • 批准号:
    2036176
  • 负责人:
  • 金额:
    $ 30.11万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    2021
  • 资助国家:
    美国
  • 起止时间:
    2021-09-01 至 2025-08-31
  • 项目状态:
    未结题

项目摘要

NONTECHNICAL SUMMARYThis award supports computational research activities aimed at developing novel methods to calculate thermoelastic parameters of materials, such as the coefficient of thermal expansion, and linear and non-linear elastic constants at different temperatures and pressures. Materials expand or contract when subjected to changes of temperature and/or pressure. The changes in the material's volume upon heating or induced by external mechanical forces have an atomistic origin, as they emerge from the quantum motion of atoms, their spatial arrangement, and the nature of the chemical bonds between the atoms forming the material. Calculating the material coefficients related to changes in volume as a function of temperature and pressure is of both fundamental and technological importance. For example, calculating the coefficient of thermal expansion of materials is crucial for designing reliable technological devices operating at variable temperatures, and predicting the values of elastic constants of minerals over extended intervals of temperature and pressure is essential to interpret seismic data. In this project, the PI will develop novel, general, and computationally efficient methods to calculate thermoelastic parameters by using accurate and parameter-free atomistic descriptions of a material. The PI will apply the new methods to study the thermoelastic properties of minerals of geological relevance and metal alloys for structural applications. This award also supports the training and education of graduate and undergraduate students. The PI will develop a simulation-based physical-chemistry course for undergraduate students. Innovative strategies will be adopted to attract minority students to attend the course and conduct undergraduate research in the PI's lab. In addition, the PI will offer two-week long summer programs for high school students aimed at showcasing computer simulations as means to learn, explore, and do science.TECHNICAL SUMMARYThis award supports computational research activities aimed at developing and applying methods to calculate thermoelastic parameters of materials from first principles. Coefficients of thermal expansion and elastic constants are important materials parameters. Novel and efficient first-principles methods for routine calculations of these thermoelastic parameters are needed to compensate the lack of experimental data, to study thermoelastic behaviors of materials under extreme conditions that are unattainable experimentally, and to enable the high-throughput screening of useful mechanical parameters at relevant environmental conditions, such as the ideal strength of metal alloys for structural applications. In this project, the PI will develop novel, general, and computationally efficient methods relying on the quasi-harmonic approximation. These methods will allow calculation of the coefficient of thermal expansion, and both second- and, most notably, third-order elastic constants of a material at finite temperature and constant volume. Furthermore, thanks to the use of numerical extrapolation techniques, the novel methods will allow the obtainment, at virtually no extra computational cost, a full thermoelastic characterization of a material in the neighborhood of an arbitrary reference state. In this project, these methods will be used to predict the equation of state and elastic constants at high pressures and temperatures of low-symmetry minerals of geological relevance, and to study the thermal expansion properties and ideal strength at finite temperature of selected high-entropy metallic alloys.This award also supports the training and education of graduate and undergraduate students. The PI will develop a simulation-based physical-chemistry course for undergraduate students. Innovative strategies will be adopted to attract minority students to attend the course and conduct undergraduate research in the PI's lab. In addition, the PI will offer two-week long summer programs for high school students aimed at showcasing computer simulations as a means to learn, explore, and do science.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.
非技术摘要这一奖项支持旨在开发新方法来计算材料热弹性参数的新方法,例如热膨胀系数,以及在不同温度和压力下的线性和非线性弹性常数。材料在温度和/或压力变化时扩展或收缩。材料在加热或由外部机械力引起的材料体积的变化具有原子来源,因为它们从原子的量子运动,它们的空间排列以及形成材料的原子之间的化学键的性质中出现。计算与体积随温度和压力变化相关的材料系数既具有基本和技术重要性。例如,计算材料热膨胀系数对于设计在可变温度下运行的可靠技术设备以及预测矿物质弹性常数在温度和压力的扩展间隔内对于解释地震数据至关重要。在该项目中,PI将通过使用材料的准确和无参数的原子描述来开发新颖,一般和计算有效的方法来计算热弹性参数。 PI将应用新方法来研究地质相关性和金属合金矿物质的热弹性特性。该奖项还支持研究生和本科生的培训和教育。 PI将为本科生开发基于模拟的物理化学课程。将采用创新策略来吸引少数民族学生参加该课程并在PI实验室中进行本科研究。此外,PI还将为旨在展示计算机模拟的高中生提供两周的长期夏季课程。第一原则的材料。热膨胀和弹性常数的系数是重要的材料参数。需要新的,高效的第一原理方法,以进行这些热弹性参数的常规计算,以补偿缺乏实验数据,以在实验上无法实现的极端条件下研究材料的热弹性行为,并启用对有用的机械参数的高直发筛选在相关的环境条件下,例如用于结构应用的金属合金的理想强度。在这个项目中,PI将开发依靠准谐波近似的新颖,一般和计算有效的方法。这些方法将允许计算热膨胀系数,以及在有限温度和恒定体积下的材料的第二阶弹性常数。此外,由于使用了数值外推技术,这种新方法将允许在任意参考状态附近的材料的完整热弹性表征获得,这几乎没有额外的计算成本。在该项目中,这些方法将用于预测高压力和低对称矿物质矿物质的状态和弹性常数的方程,并研究在选定的高注射层的有限温度下的热膨胀特性和理想强度金属合金。该奖项还支持研究生和本科生的培训和教育。 PI将为本科生开发基于模拟的物理化学课程。将采用创新策略来吸引少数民族学生参加该课程并在PI实验室中进行本科研究。此外,PI将为旨在展示计算机模拟的高中生提供为期两周的夏季课程,以作为学习,探索和进行科学的手段。该奖项反映了NSF的法定任务,并被认为是值得通过使用的支持。基金会的智力优点和更广泛的影响审查标准。

项目成果

期刊论文数量(2)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
A first-principles method to calculate fourth-order elastic constants of solid materials
  • DOI:
    10.1016/j.cpc.2023.108751
  • 发表时间:
    2023-02
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Abhiyan Pandit;A. Bongiorno
  • 通讯作者:
    Abhiyan Pandit;A. Bongiorno
Enhancing efficiency and scope of first-principles quasiharmonic approximation methods through the calculation of third-order elastic constants
通过计算三阶弹性常数提高第一原理准调和近似方法的效率和范围
  • DOI:
    10.1103/physrevmaterials.6.043803
  • 发表时间:
    2022
  • 期刊:
  • 影响因子:
    3.4
  • 作者:
    Bakare, Adewumi;Bongiorno, Angelo
  • 通讯作者:
    Bongiorno, Angelo
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Angelo Bongiorno其他文献

Angelo Bongiorno的其他文献

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{{ truncateString('Angelo Bongiorno', 18)}}的其他基金

MRI: Acquisition of a high-performance computing resource to enhance research and undergraduate education at the College of Staten Island
MRI:收购高性能计算资源以加强史坦顿岛学院的研究和本科教育
  • 批准号:
    2215760
  • 财政年份:
    2022
  • 资助金额:
    $ 30.11万
  • 项目类别:
    Standard Grant

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