Multi-scale engineering toolbox for systematic assessment of porous materials in the context of adsorption and membrane separations

Lead Research Organisation: University of Edinburgh
Department Name: Sch of Engineering

Abstract

We will integrate structure characterization, molecular simulation and process modelling methods into a single computational toolbox and apply this toolbox to explore the scope and accuracy of multi-scale approaches in the assessment of performance of porous materials in adsorption and membrane separation processes. Separation processes consume about 10-15% of global energy, while high energy cost of carbon capture still presents a major hurdle in the implementation of this technology. Recent discovery of new families of porous materials opens unprecedented opportunities to advance energy efficient adsorption and membrane separations; however the large number of new materials demands a transition from traditional trial-and-error process design to rational selection of materials based on computational screening. In this project, we develop computational tools required for this transition, test them against bench scale experiments, and explore their robustness in screening materials for realistic process configurations. In the latter case, we use portable oxygen concentration technologies as a source of extensive reference data to test computational predictions. At the same time, we use this case as an opportunity to apply multi-scale approaches to explore further optimization of portable oxygen concentrators (POC) to make these medical devices even lighter with longer battery life.

Planned Impact

In this project we will develop a multi-scale software toolbox, aimed at the systematized and streamlined design of energy efficient adsorption and membrane separation processes, capitalizing on the recent developments in material engineering, molecular simulations and process optimization.

1) This toolbox will probe whether accurate ranking of porous materials for adsorption and membrane separations can be obtained within a fully self-contained computational framework.
2) It will open opportunities for design of adsorption and membrane separation processes based on simultaneous material and process optimization, shifting from the traditional trial-and-error paradigm.
3) Within the toolbox novel combinations of adsorption and membrane separations can be explored.
4) It will be applied to optimize Portable Oxygen Concentration (POC) devices for health, sports and military applications.

No simulation suite of this type exists at the moment. Currently available software, commercial or public, specializes in either the molecular simulation level of description (Accelrys, Materials Design) or process design and optimization (AdSim from Aspen Tech, gPROMS from PSE). Industrial companies working in the field of adsorption and membrane technologies are identified as the immediate beneficiaries of the project. The proposed toolbox alleviates the need for the companies to develop their own software, which would be time consuming and unaffordable for smaller companies. This will have a direct impact on the competitiveness of the UK in large scale industrial separations and other technologies. Specifically, research in carbon capture (within a larger theme of energy efficiency) and materials science have been a UK strength, however process optimization through material engineering and technology commercialization have been lagging behind in the UK compared to other countries such as the USA, where the "Materials Genome" project has become a frontline multi-agency initiative, championed by the White House. Having a technology developed based on PIMs would be particularly symbolic and impactful for the UK competitiveness in this area, as these materials have been discovered in the UK.

On the academic side, the most immediate beneficiaries of this project will be eight academic groups within the School of Engineering (UoE), including those of applicants, working in the fields of adsorption, membranes, molecular simulation and process optimization. These groups will receive at their disposal a powerful tool which will expand the type of problems and analysis they can tackle, leading to new research outcomes, ideas and collaborations. In addition to the group of Prof. Kaskel at TUD, several other academic groups expressed their interest in using the software, including Profs. Russell Morris (St. Andrews), Andy Copper (Liverpool), Neil McKeown (Edinburgh) and six of the current users of the Poreblazer software. The groups mentioned above specialise in material synthesis and characterization; for these groups it is important to explore properties of newly discovered materials in real applications and the proposed toolbox will allow them to do that, without developing their own codes.

Another group of beneficiaries of this project will be companies working on the development of the POC devices, medical and health services, companies and services associated with sports medicine and health, various sectors within the defence industry, and patients with different types of health conditions, such as the Chronic Obstructive Pulmonary Disease. They will benefit from this project if it produces new, optimized processes for portable oxygen concentration, based on novel materials.

Publications

10 25 50
 
Description Since the last report, the project has made several substantial advances. Firstly, it is important to briefly summarize the original remit of the project. Imagine, a new porous material (for example, a new metal-organic framework) is discovered either experimentally, or via some virtual method. The structure is then subjected to an automated computational analysis that produces not only equilibrium adsorption data, but also the performance of the material in the actual dynamic process. Availability of such a computational framework would revolutionize the way we approach design of chemical separation processes and other operations. In this project we set to develop such a framework by combining molecular and process simulation tools and to apply this framework to several key separations, such as carbon capture and oxygen generation. So far:

1) We have systematically identified the most efficient code to perform molecular simulations ("Automated analysis and benchmarking of GCMC simulation programs in application to gas adsorption" RJ Gowers, AH Farmahini, D Friedrich, L Sarkisov Molecular Simulation 44 (4), 309-321). This step is vital as the in silico screening of materials as described above will be computationally demanding. Along with systematic benchmarking of the codes, we advanced molecular simulation science in several other fundamental aspects: we proposed some new ideas on how to systematically compare performance of the codes to each other and to obtain statistically comparable sets of data. We produced several utilities and scripts to set up and analyze molecular simulation data.

2) We explored in a systematic way how molecular simulation and process simulation levels should be connected to each other, what information is required and passed between the different levels of description. This has been published recently in "From crystal to adsorption column: challenges in multiscale computational screening of materials for adsorption separation processes" AH Farmahini, S Krishnamurthy, D Friedrich, S Brandani, L Sarkisov Industrial & Engineering Chemistry Research 57 (45), 15491-15511. One of the discoveries of the article is the sensitivity of process performance predictions to the parameters of the process simulations that are not available from molecular simulations and hence this presents an additional challenge. We also identified significant gasp in the current molecular simulation practices that prevent seamless connection of molecular and process simulations.

Currently, we extend the concepts developing in the articles above to the actual screening of materials for carbon capture. The results will be formulated as a set of case studies and scripts, thus delivering on the original objective of the proposal.
Exploitation Route We will be delivering a set of codes and tools to connect molecular and process simulations; so to some extent the original objectives of the project will be achieved. This tools will be of a significant interest to a wide community of scientists working at the interface of molecular and process simulations; on carbon capture and other problems.
Sectors Chemicals,Energy,Environment

 
Title Case studies for computational performance of the Monte Carlo codes 
Description As a first step of the project we develop a database of case studies to probe the computational performance of five publicly available Monte Carlo codes. Specifically, we concentrated on the case of carbon dioxide adsorption in a metal organic framework, IRMOF-1. Five codes have been obtained (RASPA, MuSiC, Towhee, Cassandra, DL_MONTE) and their performance and accuracy compared in application system above. Firstly it was important to establish that all codes are consistent with each other and under what conditions. Secondly, it was important to compare their performance. Currently we are working on associated publication and the database will be released to the general public along with the publicationm 
Type Of Material Computer model/algorithm 
Provided To Others? No  
Impact Material screening for adsorption applications is becoming a very important area of research particularly in application to carbon capture and to methane storage. This requires in general computationally efficient and accurate tools, specifically Monte Carlo methods traditionally used for adsorption problems. In molecular dynamics community, the scale of the community and the interest in large biological system, has been driving the development of benchmarks and case studies which would test the performance and accuracy of the md codes. This is not the case for Monte Carlo community, where systematic comparison of the codes in terms of accuracy and performance is lacking. This database of case studies is the first example of benchmarking the Monte Carlo codes. It will allow the researchers to identify the best code for their applications, to build their own case studies and simulations set up, and it will help to validate the newly developed codes, by providing accurate reference data.