Kinetic Pathways to Phase Separation

该奖项支持理论凝聚态物理学的综合研究，教育和推广活动。 该研究调查了流体分层成两个或多个流体或固体相时的动态变化。各种体系相分离动力学的理论和计算机模拟是蛋白质和胶体溶液研究的基础，因为它们具有技术和生物医学意义。相分离的结果的多样性，例如致密液滴、凝胶、无定形沉淀物、聚合物纤维和晶核，敏感地取决于相图中的初始位置。 预测分离过程的结果需要了解在起始点可用的动力学途径以及实验条件如何影响经历这种变化的系统的演变。该项目特别强调蛋白质晶体成核的问题，因为能够生长高质量的晶体以确定蛋白质结构的重要性。 晶体成核是生长高质量蛋白质晶体的瓶颈。此外，还有无数的工业过程，涉及胶体悬浮液和相分离，这是重要的和良好的实验表征，但在很大程度上没有详细的预测理论models.To进一步的理论基础上了解的动力学途径相分离过程中的研究人员将研究几个主题。第一个主题是中间动力学途径，如致密液滴，晶体成核和生长的影响。第二个主题是各向异性分子相互作用的影响，以表征高度定向的，有吸引力的相互作用的临界核的几何形状和成核的成核障碍的影响。第三个主题解决了相平衡和成核速率的浓度和类型的代理通常用于沉淀溶质分子的依赖性。该项目采用理论方法研究与这些主题相关的平衡和非平衡性质。 沿着统计物理学中的理论，以及蒙特卡罗模拟、有限尺寸标度理论、过渡路径和伞形抽样模拟以及密度泛函理论。该项目雇用了参与科学本科和研究生学习的学生研究人员。 这项研究有助于他们学习理论技术和理解材料的性质，以及使用计算建模将理论与材料性质预测联系起来的经验。此外，对于所涉及的研究生，研究形成了论文工作的基础，导致博士非技术摘要：该奖项支持理论凝聚态物理学的综合研究，教育和推广活动。 该研究调查了流体分层成两个或多个流体或固体相时的动态变化。各种体系相分离动力学的理论和计算机模拟是研究的基础， 蛋白质和胶体溶液，因为它们的技术和生物医学意义。分层或沉淀的结果的多样性，例如致密液滴、凝胶、无定形沉淀物、聚合物纤维和晶核，敏感地取决于过程的初始条件和组成分子。 预测分离过程的结果需要了解分离过程的动态过程，以及实验条件如何影响经历这种变化的系统的演变。该项目特别强调蛋白质晶体成核的问题，因为能够生长高质量的晶体以确定蛋白质结构的重要性。 晶体成核是生长高质量蛋白质晶体的瓶颈。此外，还有无数涉及胶体悬浮和相分离的工业过程，这些过程在实验上很重要，也很好地表征，但需要预测性的理论模型。为了进一步从理论上理解相分离过程中的动力学途径，研究人员采用了多种理论工具。 沿着统计物理学中的理论，以及蒙特卡罗模拟、有限尺寸标度理论、过渡路径和伞形抽样模拟以及密度泛函理论。该项目雇用了参与科学本科和研究生学习的学生研究人员。 这项研究有助于他们学习理论技术和理解材料的性质，以及使用计算建模将理论与材料性质预测联系起来的经验。此外，对于研究生参与，研究形成了论文工作的基础，导致博士学位。

TECHNICAL SUMMARY:This award supports integrated research, education and outreach activities in theoretical condensed matter physics. The research investigates the dynamical changes in fluids when demixing into two or more fluid or solid phases. The theory and computer simulation of kinetics of phase separation for a variety of systems is the foundation of the research which emphasizes protein and colloidal solutions because of their technological and biomedical significance. The multiplicity of outcomes of phase separation, for example dense liquid droplets, gels, amorphous precipitates, polymer fibers and crystal nuclei, depends sensitively on the initial position in the phase diagram. Predicting the result of the separation process requires understanding the kinetic pathways available at the starting point and how the experimental conditions influence the evolution of a system undergoing this change. The project particularly emphasizes problems involved in protein crystal nucleation because of the importance of being able to grow high quality crystals in order to determine protein structure. Crystal nucleation is the bottleneck in growing high quality protein crystals. There are, in addition, innumerable industrial processes that involve colloidal suspensions and phase separation which are important and well characterized experimentally but largely without detailed predictive theoretical models.To further the theoretical basic understanding of kinetic pathways in phase separation processes the researcher will study several topics. The first topic is the effect of intermediate kinetic pathways, such as dense liquid droplets, on crystal nucleation and growth. A second topic is the effect of anisotropic molecular interactions in order to characterize the impact of highly directional, attractive interactions on the geometry of the critical nuclei and the nucleation barrier to nucleation. A third topic addresses the dependence of phase equilibria and nucleation rates on the concentration and type of agent commonly used to precipitate the solute molecules. The project employs theoretical methods to study the equilibrium and non-equilibrium properties associated with these subjects. Theories founded in statistical physics are employed along with Monte Carlo simulations, finite size scaling theory, transition path and umbrella sampling simulations and density functional theory.The project employs student researchers who are involved in undergraduate and graduate study in the sciences. The research contributes to their education in learning the theoretical techniques and understanding the properties of the materials and experience in the use of computational modeling to connect theory to prediction of materials properties. In addition, for the graduate students involved, the research forms the basis for dissertation work leading to the Ph.D.NON-TECHNICAL SUMMARY:This award supports integrated research, education and outreach activities in theoretical condensed matter physics. The research investigates the dynamical changes in fluids when demixing into two or more fluid or solid phases. The theory and computer simulation of kinetics of phase separation for a variety of systems is the foundation of the research which emphasizes protein and colloidal solutions because of their technological and biomedical significance. The multiplicity of outcomes of demixing or precipitation, for example dense liquid droplets, gels, amorphous precipitates, polymer fibers and crystal nuclei, depends sensitively on the initial conditions of the process and the constituent molecules. Predicting the result of the separation process requires understanding the dynamic processes available for the separation process and how the experimental conditions influence the evolution of a system undergoing this change. The project particularly emphasizes problems involved in protein crystal nucleation because of the importance of being able to grow high quality crystals in order to determine protein structure. Crystal nucleation is the bottleneck in growing high quality protein crystals. There are, in addition, innumerable industrial processes that involve colloidal suspensions and phase separation which are important and well characterized experimentally but in need of predictive theoretical models.To further the theoretical basic understanding of kinetic pathways in phase separation processes the researchers employ multiple theoretical tools. Theories founded in statistical physics are employed along with Monte Carlo simulations, finite size scaling theory, transition path and umbrella sampling simulations and density functional theory.The project employs student researchers who are involved in undergraduate and graduate study in the sciences. The research contributes to their education in learning the theoretical techniques and understanding the properties of the materials and experience in the use of computational modeling to connect theory to prediction of materials properties. In addition, for the graduate students involved, the research forms the basis for dissertation work leading to the Ph.D.