(58b) Highlights of Collaboration between the U.S.DOE Carbon Capture Simulation for Industry Impact Program and the Discovery of Carbon Capture Substances and Systems Initiative

The Department of Energy’s (DOE) Fossil Energy (FE) Carbon Capture Program recently launched the Discovery of Carbon Capture Substances and Systems (DOCCSS) Initiative with the objective of commercializing transformational carbon capture technologies. This initiative integrates fundamental contributions from national laboratories with the practical perspective of industrial stakeholders to streamline the commercialization process of transformational carbon capture materials. To efficiently inform the design and operation of processes that fully leverage the unique benefits of the transformational CO₂ capture technology supported by the DOCCSS initiative, rigorous multi-scale modeling that links performance projections from the materials level through the device scale is critical.

The U.S. DOE’s Carbon Capture Simulation for Industry Impact (CCSI²) project is designed to utilize the open source computational tools and models developed under the Carbon Capture Simulation Initiative (CCSI) in partnership with industry to scale-up new and innovative carbon capture technology. Led by the National Energy Technology Laboratory (NETL), CCSI² operates in conjunction with and in support of the Department of Energy’s (DOE) Fossil Energy (FE) Carbon Capture Program to focus on accelerating and reducing the risk of advancing promising technologies. The CCSI² technical team includes researchers from Lawrence Berkeley National Laboratory (LBNL), Lawrence Livermore National Laboratory (LLNL), Los Alamos National Laboratory (LANL) and Pacific Northwest National Laboratory (PNNL), West Virginia University, and the University of Texas at Austin.

CCSI² provides fundamental analysis, modeling, and optimization of carbon capture technologies by working closely with industry partners. In addition, CCSI² efficiently identifies data collection needs, characterizes carbon capture materials, designs and optimizes devices and processes, and propagates uncertainty in model predictions to provide a detailed perspective on the accuracy of results. CCSI² assists carbon capture technology developers by providing the following:

• More detailed understanding of capture materials through system performance under parametric uncertainty
• Designs for high performance and intensified unit operations
• Synthesis of processes optimized for novel materials
• Characterization of dynamic system behavior
• More informed design, operating & control decisions
• Optimized processes under uncertainty
• A framework for improved design of experiments at all levels of maturity to maximize learning to reduce risk.

The CCSI² framework for materials analysis through system optimization supports the DOCCSS Initiative recently launched by DOE/NETL. DOCCSS requires a multi-hierarchical characterization which embodies materials through systems level performance. The major contribution of CCSI² is to provide specific guidance on systems and device scale optimization to accommodate the unique characteristics of transformational carbon capture materials. Where necessary, through implementation of optimal design of experiments (DoE), CCSI² will also provide insight on additional data requirements that can maximize the information content in the data. Ultimately, a significant reduction is expected in development time and cost of materials and processes as compared with conventional approaches. Furthermore, an estimate of the uncertainty of all the key economic measures will be developed.

The collaboration between CCSI² and DOCCSS will enable more rapidly identification of optimal system/material pairing that can be commercialized with lower risk. We will present the most recent computational results developed from collaboration with the three recently awarded DOCCSS concepts:

1) Lawrence Berkeley National Laboratory (LBNL) Metal-Organic Framework (MOF) Sorbent Materials

2) Pacific Northwest National Laboratory (PNNL) CO₂ Binding Organic Liquids (CO₂BOL)

3) Lawrence Livermore National Laboratory (LLNL) Additively Manufactured Reactors

LBNL discovered a class of diamine-functionalized MOF materials that exhibit cooperative adsorption of CO₂, generating step-like CO₂ adsorption isotherms. While this breakthrough results in a much higher working capacity for CO₂, the rapid adsorption also results in a rapid liberation of adsorption heat. The unique characteristics of the LBNL MOF require a system that is capable of rapid heat removal if the material’s benefits are to be fully realized; otherwise, the steep isotherm cannot be effectively utilized in practice, reducing overall performance. CCSI² is characterizing MOF performance and evaluating cost-optimal system designs.

PNNL has developed a low-viscosity, water lean solvent with a polarity swing regeneration process that is anticipated to have favorable CO₂ capture costs. CCSI² is developing a validated CO₂BOL solvent models to derive an optimal system using conventional equipment that accommodates the solvent/antisolvent pairing unique to the PNNL CO₂BOL technology.

LLNL is developing advanced reactor designs with customized geometries made realizable through advances in 3D printing, such as gyroid surfaces and hierarchical flow paths. This new capability creates the potential for high performance, multi-functional, intensified devices that can consolidate processes and result in lower capital cost. CCSI² is analyzing the potential to integrate the proposed PNNL CO₂BOL solvent and liquid anti-solvent system unconstrained by conventional equipment assumptions. The resulting optimal device design will be constructed by LLNL leveraging advanced manufacturing techniques. A computationally-efficient framework for exploration of novel geometry options will be developed.

Results of predictive LBNL MOF isotherm modeling of the “step-change” isotherm behavior, PNNL CO₂BOL systems level optimization, and development of the LLNL computational device design framework will be presented.