RUI: Image-Based Strong-Field Adaptive Control of Molecular Dynamics

RUI：基于图像的分子动力学强场自适应控制

• 批准号: 1404185
• 负责人: Eric Wells
• 金额: $ 12.94万
• 依托单位: Augustana University Association
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-01 至 2017-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1404185&HistoricalAwards=false
• 关键词: RUI; Image; Based; Strong; Field

Non-technical description:Traditional chemical synthesis methods resemble cooking in the sense that the ingredients, mixing methods, temperature, and pressure all may be varied to produce a desired result. Despite control over all of these macroscopic variables there are some chemical processes that remain elusive. Since the invention of the laser in the 1960s, the field of coherent control has sought to use the laser to manipulate chemical dynamics by applying energy of suitable color and duration directly to individual molecules. In this sense, the laser can be thought of as a new type of reagent that drives a chemical reaction. While easily stated, this task has proved challenging. Molecules are complicated and dynamic, making it difficult to determine the correct laser characteristics to drive a particular process. A proven method for approaching this problem is to use experimental feedback to guide an adaptive search of the possible laser pulses. In a physics version of natural selection, laser pulses that provide a better outcome are given an increased chance to survive and have their characteristics contribute to the tailored pulse that ultimately produces the desired outcome. Such a method, however, is only as good as the feedback that drives it. The goal of these studies is to develop enhanced image-based feedback techniques that enable this adaptive approach to coherent control of chemical dynamics. Technical description:The PI has recently developed the ability to use three-dimensional momentum imaging of the laser-molecule reaction products to define the control objective described in the non-technical description above. Using three-dimensional imaging to target a specific final state has led to better understanding of the mechanisms that undergird the laser-based control, especially in situations in which obtaining precise optical spectroscopic feedback is impractical. Increased mechanistic understanding can subsequently lead to better search parameterization, enhancing the adaptive control process. Current efforts are focused on applying image-based adaptive control to study and influence photoisomerization processes in small molecules such as ethylene. By studying photoionization, it is possible to probe how electronic excitation is rapidly converted to nuclear motion, an essential step in many ultrafast chemical processes. Ethylene is particularly interesting as a benchmark molecule for examining the role of conical intersections in these electronic to nuclear energy conversions. These studies will be advanced by using two-pulse experiments, which allow the separation of the ionization step from the subsequent evolution of the molecular ion, which the group hopes to control. Strong-field tunneling ionization of polyatomic molecules often involves multiple molecular orbitals, and studies of these relationships help link the image-based feedback to more specific target states, again with the objective of refining adaptive control methods. A goal of this project will be extending this work to explore the control of laser driven electron rescattering via feedback derived from angle resolved photoelectron distributions. Electron rescattering is an essential part of many ultrasfast laser-based processes, such as high-harmonic generation and the production of attosecond pulses, and therefore control of this sort has a number of potential applications. Finally, as an undergraduate institution, this project helps identify and develop talented students by immersing them in forefront research.

非技术描述：传统的化学合成方法与烹饪相似，因为原料、混合方法、温度和压力都可以改变，以产生所需的结果。尽管控制了所有这些宏观变量，但仍有一些化学过程仍然难以捉摸。自20世纪60年代激光发明以来，相干控制领域一直试图通过将合适的颜色和持续时间的能量直接施加到单个分子上来使用激光来操纵化学动力学。从这个意义上说，激光可以被认为是一种驱动化学反应的新型试剂。虽然这项任务很容易说，但事实证明，它具有挑战性。分子是复杂和动态的，很难确定正确的激光特性来驱动特定的过程。解决这个问题的一种行之有效的方法是使用实验反馈来指导对可能的激光脉冲的自适应搜索。在自然选择的物理版本中，提供更好结果的激光脉冲被给予更多的生存机会，并使其特征有助于定制最终产生预期结果的脉冲。然而，这种方法的效果取决于推动它的反馈。这些研究的目标是开发增强的基于图像的反馈技术，使这种自适应方法能够对化学动力学进行相干控制。技术描述：PI最近开发了使用激光-分子反应产物的三维动量成像来定义上述非技术描述中描述的控制目标的能力。使用三维成像来瞄准特定的最终状态，使人们更好地理解了支撑基于激光的控制的机制，特别是在无法获得精确的光学光谱反馈的情况下。增加对机理的理解可以随后导致更好的搜索参数化，从而增强自适应控制过程。目前的工作集中在应用基于图像的自适应控制来研究和影响乙烯等小分子的光异构化过程。通过研究光致电离，可以探索电子激发是如何迅速转化为核运动的，这是许多超快化学过程中的一个重要步骤。作为检测锥形交叉点在这些电子到核能转换中的作用的基准分子，乙烯尤其令人感兴趣。这些研究将通过使用双脉冲实验来推进，该实验允许将电离步骤与随后分子离子的演化分离，该小组希望控制分子离子的演化。多原子分子的强场隧道电离通常涉及多个分子轨道，对这些关系的研究有助于将基于图像的反馈与更具体的目标状态联系起来，这也是改进自适应控制方法的目标。这个项目的一个目标是扩展这项工作，探索通过角度分辨光电子分布的反馈来控制激光驱动的电子再散射。电子再散射是许多基于超快激光的过程的重要组成部分，例如高次谐波的产生和阿秒脉冲的产生，因此这类控制具有许多潜在的应用。最后，作为一所本科院校，该项目通过让学生沉浸在前沿研究中来帮助他们识别和发展有才华的学生。