ITR - (ASE) - (sim+dmc): Parallel Data Mining for Nanoscale Kinetic Monte Carlo Simulation Models

知识价值：计算科学和技术的进步使材料过程和特性的理论建模可行，可取，并且是实验工作的有力补充。由于对材料宏观性质的理解和操作依赖于在微观层面上获得的信息，因此ASE面临的挑战之一是为材料性质和相关现象的无缝、多尺度研究开发框架。动力学蒙特卡罗方法就是这样一种技术，它适用于大范围的长度和时间尺度的模拟，并具有将原子细节与宏观观察联系起来的潜力。然而，标准方法由于需要对潜在的原子机制及其能量学的先验知识而受到限制。通常，只有少数涉及单原子运动的过程被提供作为动力学蒙特卡罗模拟的输入，从而忽略了集体原子运动，空位产生和复杂原子过程的作用，以及系统的时间演化。在以sim和dmc为技术重点的ASE研究中，我们计划通过包含独特和创新的模式识别方案以及用于动态计算系统能量的自动化程序来克服这些限制。这个程序将允许开发一个广泛的可能原子事件的数据库。收集的数据库将作为使用机器学习和数据挖掘进行进一步分析和处理的输入，以开发高效，稳健和准确的映射功能，这些功能将通过模拟外延生长中的各种现象进行广泛测试，并通过与相关实验数据的比较进行验证。由此产生的映射功能将极大地提高模拟的准确性和速度。更广泛的影响：我们的目标是为薄膜生长等现象的模拟创造准确有效的计算算法，这将是sim和dmc技术重点领域的重大成就，因为跨学科方法产生了创新的方法。然而，材料计算机设计算法的成功实施将是ASE的突破，因为它将使技术上重要的材料的开发成本大大降低，控制能力大大提高。这项工作还将使我们有机会开展具有广泛国家、国际和社会影响的教育和外联活动。除了对ITR的研究生和本科生进行教育和培训外，我们还将建议与K-12社区一起努力。我们打算通过研究和教育的结合来做到这一点。我们的团队将把研究成果整合到物理计算方法、数据挖掘、机器学习和自适应并行化技术等课程中。还将为教学和外联目的制定一个模块。此外，还将招聘两名高中教师，在韩国国立大学进行暑期授课。与K-12教师和学生的定期外展活动将有助于扩大信息技术和纳米级科学素养个人的人才库。PI与芬兰Alatalo教授、俄罗斯Trushin博士和土耳其Durukanoglu博士的现有国际合作将有助于在国际上推广拟议工作的成果。

Intellectual Merit:Advances in computational science and technology have made the theoreticalmodeling of materials processes and properties viable, desirable, and a strong supplement to experimental work. Since the understanding and manipulation of the macroscopic properties of materials relies on information obtained at the microscopic level, one of the challenges in ASE is in developing the framework for a seamless, multiscale study of materials properties and related phenomena. The kinetic Monte Carlo method is one such technique which is suitable for simulations over a large range of length and time scales and which has the potential to connect atomistic details with macroscopic observations.The standard method is, however, handicapped because of the requirement of prior knowledge of theunderlying atomic mechanisms and their energetics. Typically only a few processes involving singleatom motion are provided as input to kinetic Monte Carlo simulations, thereby neglecting the role ofcollective atomic motion, vacancy creation, and complex atomic processes, as well as biasing the timeevolution of the system. In the proposed research in ASE with technical focus in sim and dmc, we planto overcome these limitations through the inclusion of unique and innovative pattern recognition schemesalong with automated procedures for the calculation of system energetics on the fly. This procedure willallow the development of an extensive database of possible atomic events. The database so collected willserve as input for further analysis and processing using machine learning and data mining for thedevelopment of efficient, robust, and accurate mapping functions which will be extensively tested throughsimulations of a variety of phenomena in epitaxial growth and validated through comparison with relevantexperimental data. The resulting mapping functions will serve to vastly increase the accuracy and speedof simulations.Broader Impact:Our goal of creating accurate and efficient computational algorithms for the simulationof phenomena such as thin-film growth will be a significant achievement in the technical focus areas ofsim and dmc, because of the innovative methodologies resulting from cross-disciplinary approaches. Thesuccessful implementation of the algorithms for computer design of materials, however, will be abreakthrough in ASE, as it will enable the development of technologically important materials with muchreduced cost and much greater control.The work will also provide us opportunities for educational and outreach activities with broad national, international and societal impact. Apart from the education and training of our graduate and undergraduate students in ITR, we will propose to work with the K-12 community in this endeavor. We intend to do so through the integration of research and education. Our team will collectively incorporate products of the research into courses on computational methods in physics, on data mining, on machine learning, and on adaptive parallelization techniques. A module for instructional and outreach purposes will also be developed. Two high school teachers will be recruited to spend summer sessions at KSU. Regular outreach activities with K-12 teachers and students will help broaden the pool of individuals in IT and nanoscale science literate individuals. Existing international collaborations of the PI with Prof. Alatalo, Finland, Dr. Trushin, Russia, and Dr. Durukanoglu, Turkey will help extend the outcomes of the proposed work internationally.