Multiscale Modeling and Computation Core

Overall Scientific Challenge

The overall challenge in this area is the development of multiscale theories and computational tools capable of handling several orders of magnitude in length scales (Ångstrom to mm) with required fidelity to fully integrate with and be informed by experimental studies. The national vision of materials design has prioritized the use of modeling and computation, integrated with physical experimentation and cyberinfrastructure. Since the properties of a material are determined by its structure at different length and time scales, our goals are the development of advanced multiscale theoretical foundations, fast algorithms to handle high throughput computations, high resolution/fidelity imaging and visualization, andbig data analytics including uncertainty quantification. These models and tools must not only bridge the physics across multiple scales, but also be fully integrated with experimental observations and materials genome databases via an iterative design loop (Figure 2). A lasting legacy will be the availability of the developed computational tools and the database (e.g., Materials Data Bank, MDB, discussed below) to the broad materials research community.

While the value of multiscale modeling and computation in materials science is receiving increasing recognition, most current efforts are focused on theories with well-separated and limited scale ranges. We will integrate proven theories at local scales to develop a theoretical and computational framework enabling the exploration of material design, synthesis, structure and properties at an unprecedented range of scales, applicable to the model systems explored in the thrusts and a broader set of materials. The research goals are organized into two broad areas: first, we will develop multiscale theories and computational tools to guide and assist the three thrusts in the screening of materials’ composition, assembly and processing. New model reduction, novel learning methodologies and multi-level image analysis strategies will be incorporated to accelerate the modeling-experiment iterative development cycle. In addition, we will develop new courses and curricula for training students in multiscale theories and simulations. Especially, a new MS degree program in computational science will be launched at USCB. Second, we will implement our multiscale models and image analysis algorithms in an open source computational infrastructure designed to meet infrastructure needs for the material systems in this proposal. This framework will combine data analytics, experimental observations, visualization, and machine learning using the interactive, iterative design loop illustrated in Figure 2. The models and computational tools that we develop will be shared with the broader materials science community.


Year 1

Year 2

Year 3


Year 1

  • Dey, Bijoy, Presentation, 2017, Hamilton-Jacobi equation, reaction action surface and the emergence of the force concept in chemical reaction dynamics, 2017 Southeastern Meeting of the American Chemical Society, Charlotte, NC
  • Tu, Sidong, Presentation, 2018, Engineering Highly Stable Enzyme-Polymer Conjugates: Molecular Dynamics Simulation Study Engineering Highly Stable Enzyme-Polymer Conjugates: Molecular Dynamics Simulation Study, Society For Biomaterials 2018 Annual Meeting and Exposition, Atlanta, GA
  • Wang, Fang; Schiller, Ulf, Presentation, 2018, Mesoscopic simulation of transport phenomena in fibrous porous media, International Conference for Mesoscopic Methods in Engineering in Science, Newark, DE
  • Kuksenok, Olga, Meeting, 2018, Pattern Formation in Hydrogels – Controlling Functionality via Feedback Mechanism, 2018 Spring Materials Research Society Meeting, Phoenix, AZ
  • Schiller, Ulf, Presentation, 2018, Simulation-driven optimization of stents for treatment of brain aneurysms, International Conference on Discrete Simulation of Fluid Dynamics, Worcester, MA

Year 2

  • Schiller, Ulf, Presentation (invited), 2018, Application-Driven Multiscale Modeling in Materials Science and Biomedicine, Amsterdam
  • Schiller, Ulf, Presentation (invited), 2018, Coupling of Molecular Dynamics and Lattice Boltzmann, Stuttgart
  • Schiller, Ulf, Presentation (invited), 2018, Mesoscopic Simulation of Transport Phenomena in Fibrous Porous Media, Fargo, ND

Year 3

  • Ahmed, Kishwar and Liu, J. Simulation of Energy-Efficient Demand Response for High Performance Computing Systems. Winter Simulation Conference (WSC), National Harbor, MD, 2019.
  • Ahmed, Kishwar, Yoshii, K. and Tasnim, S. Thermal-Aware Power Capping Allocation Model for High Performance Computing Systems. International Conference on Computational Science and Computational Intelligence (CSCI), Las Vegas, NV, 2019.
  • Kuksenok, Olga and Palkar , Vaibhav. (Keynote) Active reconfiguration of hydrogels-based systems: from hydrogel membranes to assemblies of nanogels at soft interfaces. 97th Colloid Surface Science Symposium of the American Chemical Society, Atlanta, GA, 2019. (Invited Presentation)
  • Kuksenok, Olga and Vaibhav Palkar. Development of a DPD framework for simulating tetra-PEG gels with degradable crosslinks. Sixth LAMMPS Workshop and Symposium, , Sandia Labs, Albuquerque, NM, 2019.
  • Kuksenok, Olga and Vaibhav Palkar. Poster: Designing nanostructured soft interfaces: focus on shape changes and spreading of hydrogels. Materials Research Society Fall Meeting, Boston, MA, 2019.
  • Kuksenok, Olga and Vaibhav Palkar. Presentation: Modeling polymer networks with degradable crosslinks. Materials Research Society Fall Meeting, Boston, MA, 2019.
  • Kuksenok, Olga. Modeling dynamic reconfiguration of hydrogels-based systems: focus on feedback mechanisms. NERM 2019 ACS, Saratoga Springs, NY, 2019. (Invited Presentation)
  • Kuksenok, Olga. Multi-scale Modeling of Hydrogels: Focus on Feedback Mechanisms and Controlled Degradation. International Symposium on Stimuli-Responsive Materials, Winsor, CA, 2019. (Invited Presentation)
  • Kuksenok, Olga; Tu, Sidong and Luzinov, Igor. Conference Presentation: Tu, S. Choudhury, C.K. Giltner,M, Wei, L., Luzinov, I, Kuksenok, O. (talk) Phase Separation of Multi-Component System Incorporating Bottlebrushes: A Dissipative Particle Dynamics Approach. 92nd Colloid Surface Science Symposium of the American Chemical Society, Atlanta, GA, 2019.
  • Schiller, Ulf and Wang, Fang. Computational Modeling of Droplet Spreading and Coalescence on Fiber Rails. American Physical Society, Denver, CO, 2019.
  • Schiller, Ulf and Wang, Fang. Lattice Boltzmann simulation of coalescence filtration through non-woven fibrous media. CECAM, Prato, , 2019.
  • Schiller, Ulf and Wang, Fang. Mesoscopic Simulation of Droplet Coalescence in Fibrous Porous Media. International Conference on Computational Science, Faro, , 2019.
  • Schiller, Ulf and Wang, Fang. Mesoscopic Simulation of Droplet Spreading in Fibrous Porous Media. International Conference on Mesoscopic Methods in Engineeringand Science, Edinburgh, 2019.

Core Co-leaders:

Rachel Getman (ChemE, Clemson)
Qi Wang (Math, USC)

Contributing Faculty:

Allen Clabo (Chem, Francis Marion)
Wolfgang Dahmen (Math, USC)
Bijoy Dey (Chem, Claflin)
Sophya Garashchuk (Chem, USC)
Dieter Haemmerich (Pediatrics, MUSC)
Andreas Heyden (ChemE, USC)
Jianjun Hu (CSE, USC)
Ming Hu (ME, USC)
Olga Kuksenok (MSE, Clemson)
Vitaly Rassolov (Chem, USC)
Sapna Sarupria (ChemE, Clemson)
Ulf Schiller (MSE, Clemson)
Victor Zordan (SoC, Clemson)

Affiliated Faculty:

Paul Anderson (CS, CofC)
Yiming Ji (CS/Math, USCB)
Xuwei Liang (CS/Math, USCB)
George Shields (Chem, Furman)

MADE in SC Research Clusters

Modeling and Computation Core
Thrust 1: Optical, Electrochemical and Magnetic Materials
Thrust 2: Stimuli-Responsive Polymeric Materials
Thrust 3: Biomaterials

MGI Approach adopted by MADE in SC
Materials Databases