Collaborative Research: Elements: Multiparticle collision dynamics simulations of mesoscale hydrodynamic interactions in complex soft materials and environments

准确预测悬浮在溶剂(如水)中的纳米颗粒和聚合物等软材料的性质和行为，对于应对众多社会挑战至关重要，包括提高废水处理技术的效率，处理用于能源应用的先进材料，以及有效地将药物输送到人体内的特定位置。该项目将通过实施最先进的算法来表示当前可制造的多种纳米颗粒的行为，描述在许多工程应用中遇到的复杂固体表面附近的流体流动，并预测工艺设计所需的软材料和复杂流体的重要机械性能，从而显著改进用于对这些系统进行建模的公开可用的软件。该软件将为世界各地的科学家提供新的建模功能，提高预测软材料性能的能力，并加速科学发现。研究小组将通过组织关于使用该软件的讲习班、在网上免费提供培训材料以及开展各种外联活动，与其他科学家和更广泛的公众接触。该项目还将通过培训和指导来自代表性不足背景的研究生和本科生，在软件开发、高性能计算和高级建模方法方面帮助创建一支具有开发可持续科学网络基础设施所需技能的包容性劳动力队伍。该项目将为基于粒子的通用模拟软件包HOOMD-BLUE添加执行多粒子碰撞动力学(MPCD)模拟的变革性新功能。MPCD是一种最先进的中尺度方法，用于有效地模拟软材料和复杂流体中溶剂介导的流体动力学相互作用。该项目将集中于三个重要的特定领域的目标，预计将对科学应用和更广泛地采用MPCD方法产生重大影响：(1)实现与MPCD兼容的刚体积分器来模拟复杂的溶质；(2)实现一种新的算法，用于模拟受限几何中的传输的几何复杂的固体边界；以及(3)实现非平衡方法，该方法使用依赖于时间的边界条件来表征软材料的流变性。主要成果将是具有先进功能的开放源码软件，这些软件将取代目前由不同研究人员使用的私有内部代码，从而提高MPCD模拟的透明度和重复性。该项目还将通过将来自不同空间的方法和工具(例如图形处理)集成到基于物理的建模中，并通过为CPU和GPU计算架构的最新MPCD方法开发最佳并行算法和实现，来引领网络基础设施的创新。该奖项由NSF高级网络基础设施办公室颁发，由NSF工程局内的化学、生物工程、环境和运输系统部门联合支持。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Accurate prediction of the properties and behavior of soft materials, such as nanoparticles and polymers, suspended in a solvent (e.g., water) is critical for addressing numerous societal challenges, including improving the efficiency of wastewater treatment technologies, processing advanced materials for energy applications, and effectively delivering drugs to specific locations within the body. This project will significantly improve publicly available software for modeling these systems by implementing state-of-the-art algorithms to represent the behavior of many types of nanoparticles that can currently be fabricated, to describe fluid flows near the complex solid surfaces encountered in many engineering applications, and to predict important mechanical properties of soft materials and complex fluids that are needed for process design. This software will provide scientists around the world with new modeling capabilities that advance capabilities for predicting properties of soft materials and accelerate scientific discovery. The research team will engage with other scientists and the broader public by organizing workshops on using the software, making training materials freely available online, and conducting a variety of outreach activities. This project will also help create an inclusive workforce with the necessary skills for developing sustainable scientific cyberinfrastructure by training and mentoring graduate & undergraduate students from underrepresented backgrounds on software development, high-performance computing, and advanced modeling methods.This project will add transformative new features for performing multiparticle collision dynamics (MPCD) simulations to HOOMD-blue, a general-purpose particle-based simulation package. MPCD is a state-of-the-art mesoscale method for efficiently modeling solvent-mediated hydrodynamic interactions in soft materials and complex fluids. The project will focus on three important area-specific aims that are expected to have a significant impact on scientific applications and broader adoption of the MPCD method: (1) to implement MPCD-compatible rigid-body integrators for simulating complex solutes; (2) to implement a new algorithm, adapted from graphics processing, for modeling geometrically complex solid boundaries that simulate transport in confined geometries; and (3) to implement nonequilibrium methods that employ time-dependent boundary conditions to characterize the rheological properties of soft materials. The primary outcome will be open-source software with advanced features that will supplant the private, in-house codes that are currently used by different researchers, thereby enhancing the transparency and reproducibility of MPCD simulations. The project will also lead to innovation in cyberinfrastructure by integrating approaches and tools from different spaces (e.g., graphics processing) into physics-based modeling and by developing optimal parallel algorithms and implementations for state-of-the-art MPCD methods for both CPU and GPU computing architectures.This award by the NSF Office of Advanced Cyberinfrastructure is jointly supported by the Division of Chemical, Bioengineering, Environmental, and Transport Systems within the NSF Directorate for Engineering.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.