REU Site: Computational Methods with applications in Materials Science

该项目由材料研究部和刺激竞争力研究的既定计划（EPSCoR）共同资助。非技术描述：计算方法和数据分析现在被广泛用于预测材料的性能，并从材料实验和模拟中了解数据。虽然这些计算技术通常在科学，数学和工程的研究生课程中教授，但很少有本科生有机会了解它们或参与这个快速发展的研究领域。本研究经验为本科生（REU）网站解决了这一缺点，并提供了一个独特的机会，本科生参加有意义的研究与一组研究人员从中心计算科学（CCS），跨学科的计算研究中心在密西西比州立大学（MSU）。这个REU计划的参与者中有很大一部分是从历史上的黑人学院和大学，主要是来自美国各地的本科院校招募的。 每年为高中教师举办一次为期一天的讲习班，为教师提供他们可以与自己的学生一起进行的研究指导。这个REU网站的毕业生在科学，工程或数学的研究生学习做好了充分的准备。技术专长：为这个REU招募的学生参与者花了10个星期的多学科研究与八个教师导师在数学，统计学，物理学，和化学从CCS。学生首先接受基础科学和计算技术的培训，这些技术是他们研究项目所必需的。额外的培训活动提高了参与者的计算技能以及书面和口头陈述技能。这八个研究项目分别是：（1）电子-电子关联物理;（2）相场模型的数值方法;（3）高性能复合材料中的界面性质;（4）无稀土永磁材料研究;（5）材料分析的图像去噪和分割方法;（6）贝叶斯参数估计和模型比较;（7）材料分析的图像去噪和分割方法。（7）新型多环芳烃及其配合物的物理化学性质;（8）高维材料数据分析。REU参与者可以访问MSU高性能计算合作实验室的超级计算资源。学生参加每周小组会议，研讨会和科学和计算主题的培训课程，以及研究生入学考试研讨会。在夏季结束时，他们将项目的最终结果提交给REU小组和MSU夏季本科生研究研讨会。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估来支持。

This project is jointly funded by the Division of Materials Research and the Established Program to Stimulate Competitive Research (EPSCoR).NON-TECHNICAL DESCRIPTION: Computational methods and data analysis are now widely used to predict the properties of materials and to understand data from materials experiments and simulations. While these computational techniques are commonly taught in graduate programs in science, math, and engineering, few undergraduate students have an opportunity to learn about them or participate in this rapidly expanding research field. This Research Experiences for Undergraduates (REU) Site addresses this shortcoming and provides a unique opportunity for undergraduate students to participate in meaningful research with a group of researchers from the Center for Computational Sciences (CCS), an interdisciplinary computational research center at Mississippi State University (MSU). A significant portion of participants for this REU program are recruited from historically black colleges and universities and primarily undergraduate institutions from across the United States. An annual one-day workshop for high school teachers offers the teachers guidance on research that they can perform with their own students. Graduates of this REU site are well prepared for graduate study in science, engineering, or mathematics.TECHNICAL DETAILS: The student participants recruited for this REU spend 10 weeks over the summer in multidisciplinary research with eight faculty mentors in Mathematics, Statistics, Physics, and Chemistry from CCS. The students are first trained in the basic science and computational techniques necessary for their research projects. Additional training activities improve the participants’ computational skills as well as written and oral presentation skills. The eight research projects are: (1) electron-electron correlation physics; (2) numerical Methods for Phase Field Models; (3) interfacial properties in high-performance composite materials; (4) materials research for rare earth-free permanent magnets; (5) image denoising and segmentation methods for material analysis; (6) Bayesian parameter estimation and model comparison; (7) photophysical properties of novel polycyclic aromatic hydrocarbons and their complexes; and (8) high-dimensional material data analysis. REU participants are given access to supercomputing resources at the MSU High Performance Computing Collaboratory. The students participate in weekly group meetings, seminars and training sessions on scientific and computational topics, and a Graduate Record Exam workshop. At the end of the summer they present the final results of their project to the REU group and at the MSU Summer Undergraduate Research Symposium.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.