This thesis explores the use of computational chemistry and machine learning techniques to aid in the design of Metal-Organic Frameworks (MOFs) for use in postcombustion carbon capture and storage (PoC-CCS). PoC-CCS is an ongoing field of research which aims to selectively remove carbon dioxide, an important greenhouse gas, from the exhaust of fossil-fuel burning powerplants. By using a suite of advanced simulation techniques, high-throughput screenings were performed on thousands of MOFs to study their behaviour in a pressure swing adsorption (PSA) system. To develop a comprehensive picture of a material’s performance, the behaviour of individual gas molecules within the pores of the crystal structures to the material’s performance in industrial scale PSA columns was evaluated. To study the behaviour of individual gas molecules within the pores of a MOF, a new algorithm which can accurately determine the locations of gas binding sites was developed. This algorithm, which relies on probability distributions generated through grand canonical Monte Carlo simulations (GCMC), was optimized for CO2 with the goal of use in high-throughput screening. By tuning the user-controlled parameters for a desired gas, this algorithm, which was named the Guest Atom Localization Algorithm (GALA), was shown to accurately reproduce experimentally determined binding sites while being run in a high-throughput manner with no user intervention. Studying MOFs at the pore or crystal scale in this manner provides valuable insights into the behaviour of gases within the materials. A major shortcoming, however, is the lack of direct insight into the material’s behaviour in industrial systems. Materials scientists and MOF chemists have historically focused on a set of performance metrics measured at this scale; however, no clear connection can be made between such metrics and the performance of that sorbent material in a PSA column. To bridge this gap between MOF chemists and the process engineers studying the PSA systems, a large-scale screening of MOFs was performed using a sophisticated PSA simulator designed to reproduce the performance of an 80 kg PSA column. By supplying isotherms obtained using GCMC simulations to be used as inputs into the PSA simulator, a multi-scale high-throughput screening of MOFs for PoC-CCS was performed for the first time under coal-fired powerplant conditions. This multi-scale screening provided the ideal conditions to study the materials science performance metrics and their relationships to industrial PSA performance. To study this relationship, a series of machine learning and artificial intelligence techniques were employed. The primary goal was to extract important relationships between the materials science and industrial PSA performance metrics, with a secondary goal of developing a predictive model which could be used to accelerate the pace of materials discovery. Through the use of machine learning, several metrics were identified which could be used to predict whether a material could meet the minimum target of 95 % purity of captured CO2, and 90 % removal (or recovery) of CO2 from the flue gas stream. Among them was the isotherm parameters for N2, the most abundant species in the flue gas. This finding was significant as to date the focus among MOF chemists studying the PoC-CCS system was placed primarily on the CO2 metrics, with N2 only implicitly considered when calculating the CO2/N2 selectivity. Although several metrics were identified which could predict the purity and recovery targets, none of the conventional metrics tested could be used to estimate the energetic cost of capture or the size of the capture plant, both important considerations in evaluating the cost of capture. The relationship between N2 binding within the pores of the MOF and its ability to meet the purity-recovery targets was explored using GALA. Using a Tanimoto similarity metric and the ratio of single component and competitive loadings, the CO2 and N2 binding environments were studied. It was determined that when the N2 binding environment was significantly altered by the presence of CO2, the material was more likely to meet the purity-recovery targets. Further analysis found that this change in binding environments was correlated to a reduced N2 uptake in the presence of CO2, implying that the competition for binding sites within the pores of the MOF is an important indicator for the material’s ability to meet the purity-recovery target. For the first time, a direct relationship between the behaviour of individual gas molecules to industrial PSA performance can be reported. Although the PSA simulator used throughout this work has proven to be a powerful tool for materials discovery, several shortcomings still exist. The first is the method used by the simulator to predict the loadings at various points within the column. This method relies on single component isotherm data despite the ability of GCMC to simulate multi-component isotherms. An alternative method to using single component isotherms was proposed which relies on multi-component isotherm data and a linear interpolation model. The existing method was compared to the new proposed interpolation method, and it was found that the loadings predicted using the interpolation method were more accurate. The second shortcoming of the PSA simulator is the computational expense associated with the optimizations. Using the PSA simulator, a single material may take up to a week to be fully optimized on a high-performance computing cluster. To increase the pace of materials discovery, a surrogate model was developed using the data accumulated over the course of the work presented in this thesis. Using artificial neural networks, a suite of models was developed which reproduces the outputs of the PSA simulator and is able to optimize a single MOF in a matter of minutes. This suite of models, known as the Fossil Fuel Combustion for Carbon Capture and Storage (FoCAS) was used to perform a screening of over 4,000 materials.

Waste-to-Energy incineration (WtE), coupled with Carbon Capture and Storage (CCS), especially Bioenergy with Carbon Capture and Storage (BECCS), suggest a way to simultaneously retrieve energy from the otherwise disposed waste and reduce CO2 emissions. Independent of one another, WtE, CCS, and BECCS are implemented in a few regions of the world, but their joint diffusion is uncommon in comparison. Regardless of how the future of their combined implementation unfolds, social acceptance is almost certainly expected to play a role in their diffusion. This thesis categorically identified overlaps and contrasts between factors that have been subjects of investigation in public acceptance research on WtE and CCS/BECCS’s social acceptance using Huijts et al’s (2012) energy technology acceptance framework. To allocate peer-reviewed international literature from the two fields for analysis, a systematic literature review was conducted. The results revealed that WtE and CCS/BECCS studies most commonly measured the public’s wide array of emotional experiences regarding the respective technologies and addressed their knowledge and experience with the technologies to the smallest degree. Energy technology projects are bound to attract emotionally charged responses, thus the commonality to address affect makes probing for emotional responses possible. Whereas knowledge can be difficult to measure due to its subjectivity. Factors that were commonly measured in one field but not in the other included public perceptions of fairness, trust, and climate change. The findings provided a comprehensive overview of factors to take into consideration when collecting public opinions on a WtE incineration facility that is coupled with CCS technology.

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Global climate change concerns help shape current environmental regulations, which increasingly seek to reduce or capture CO2 emissions. Methods for capturing CO2 emissions from energy processes have been the focus of numerous studies to provide support for those seeking to reduce the environmental impact of their processes. This research has (1) simulated a baseline case of energy-storing cryogenic carbon capture for implementation on a 550 MWe coal fired power plant, (2) presented a novel cryogenic carbon capture process for removing CO2 from natural gas down to arbitrary levels, (3) presented a natural gas liquefaction process that has the ability to be highly CO2 tolerant, and (4) developed theoretical models and their experimental validation of CO2 capture predictions for all aforementioned processes.

Weathering of silicate minerals has long been a known source of natural CO2 sequestration, that could be increased in the presence of microorganisms. Bio-enhanced weathering of silicate minerals could increase the sequestration of CO2 from the atmosphere.   The aim of this project was to evaluate the potential for a new Neutral emission technology (NET), using four different organisms, Aspergillus Niger, Knufia Petricola, Bacillus Subtilis and Cupriavidus Metallidurans and their potential to increase olivine weathering (dunite). Straw, manure and digestate was used as carbon sources. In total 9 biotic - and 9 abioitc reactors were made, containing a mixture of dunite and one of the three carbon sources. In total 250 mL of water was added to each reactor per week, for 6 weeks, and collected at the end of the week for analysis. Geochemical analyses of the leachate were performed, including pH, conductivity, alkalinity, total organic carbon (TOC), total inorganic carbon (TIC), cations, anions and three organic acids: citrate, acetate, and oxalate. Scanning emission microscope (SEM) was used to monitor potential differences pre- and post-treatment.   Straw reactors produced the most growth, both on the carbon source and the dunite grains. Likely due to the increased labile organic carbon concentrations. The total inorganic carbon and alkalinity demonstrated that inoculation of the reactors promoted weathering for all carbon sources, most significantly for the straw reactors. This observation was evidenced by etch pits in the SEM images and higher TIC, alkalinity, and magnesium values. Microbially enhanced silicate weathering has demonstrated it could be used for the development of NETs for the sequestration of atmospheric carbon. / BAM!

Post-combustion CO2 capture is a promising approach for complementing other strategies to mitigate climate change. Liquid absorption is currently used to capture CO2 from post-combustion flue gases. However, the high energy cost required to regenerate the liquid absorbents is a major drawback for this process. As a result, solid sorbents have been investigated extensively in recent years as alternative media to capture CO2 from flue gases. For example, metal organic frameworks (MOFs) are nanoporous materials that have high surface areas, large pore volumes, and flexible designs. A large number of MOFs, however, suffer from 1) low CO2 adsorption capacity at low pressure, which is the typical condition for flue gases, 2) degradation upon exposure to water present in flue gases, and 3) low selectivity of CO2 when present in a mixture of gases. Zeolitic Imidazolate Frameworks (ZIFs) are heavily investigated MOFs for CO2 sorption applications because they have better selectivity for CO2 compared to other MOFs and are resistant to degradation in water due to their hydrophobic nature. However, ZIFs (e.g., ZIF-8) investigated for CO2 sorption applications are typically produced using toxic solvents and their CO2 sorption capacity is drastically lower than other types of MOFs. Post-synthesis modifications with amine functional groups have been known to increase CO2 sorption capacity and selectivity within nanoporous materials. For ZIFs, previous research showed that sufficient loading with linear polyethyleneimine increased their CO2 sorption capacity. Therefore, the objectives of this research were to a) investigate the CO2 sorption capacity of ZIF-8 synthesized by solvothermal methods that use more eco-friendly solvents (e.g., methanol and water) and b) introduce post-synthetic modifications to ZIF-8 using branched polyethyleneimine (bPEI) to enhance its sorption capacity. A custom quartz crystal microbalance (QCM) system was assembled and used to measure the CO2 sorption capacity of unmodified and bPEI-modified ZIF-8 sorbent. The tests were conducted at 0.3 - 1 bar. The results showed that the unmodified ZIF-8 synthesized in methanol (ZIF-8-MeOH) had comparable crystal structure, thermal stability, surface area, and chemical properties to that of literature (Ta et.al 2018). ZIF-8-MeOH had a surface area of 1300 m2/g and a CO2 sorption capacity of 0.85 mmol CO2/g ZIF-8 @ 1 bar. This surface area and sorption capacity are comparable to those of ZIF-8 made in dimethylformamide (DMF). Therefore, ZIF-8-MeOH proved to be a worthy candidate MOF for replacing the ZIF-8 made in DMF for CO2 capture research. Water-based ZIF-8 was also synthesized in this study; however, its CO2 sorption capacity was not tested because it exhibited a significantly lower surface area (732 m2/g) compared to that of ZIF-8-MeOH. Modification of the ZIF-8-MeOH with bPEI resulted in a decrease in its CO2 sorption capacity. This undesired outcome is likely a result of insufficient bPEI load (mass attached), on ZIF-8-MeOH (~ 10% w/w) combined with the surface area lost (~ 770 m2/g) due to bPEI blocking some of the ZIF-8-MeOH pores. Therefore, the bPEI load attained in this study was not enough to compensate for the loss of surface area of the modified ZIF-8 and thus, the CO2 sorption capacity decreased. Future investigations should enhance the post-synthetic modification by increasing the loading of amine functional groups onto the eco-friendlier ZIF-8-MeOH used in this study.

Without a doubt, there is a consensus around the international community which suggests that our current way of life is unsustainable for a healthy planet, society and economy. One focal point that should be taken deeply into consideration is the steel industry as, globally, it accounts for 8% of global emissions. Thus, there is a dire need to incorporate drastic measures, if one wishes to reach net-zero emissions by 2050, in accordance with the Paris Agreement of 2015. Electric Arc Furnaces are seeing a rapid implementation in the steel industry. However, at 0.5 tonnes of CO2 emitted per tonne of liquid steel produced, this emissions rating is still significant considering the amount of steel being produced annually. Additionally, these furnaces emit off-gases which must be treated from the dust. This leaves operators with a conundrum as the dust content compromises the use of waste heat recovery boilers for energy recovery, due to constant breakdowns. Therefore, this study aims to analyse the feasibility of using bioenergy and carbon capture and utilisation (CCU) concepts to capitalise on the high off-gas energy and emissions content to remedy the dust issue, whilst producing higher value products. The proposed concept evaluates the effectiveness of using the off-gas as the energy carrier and feed-stock for a biogasificaiton unit. Three different cases based on different EAF off-gas compositions have been investigated. Case 1 suggested that the off-gas composition is very CO2-heavy, whichled to investigating the option of adopting a CO2 biogasification concept to directly use the CO2. Case 1 performed the best in terms of CO2 utilisation efficiency; being 0.293. The system energy utilisation also noted that 49.3% of the inlet streams energy was transferred to the desired product. On a broader picture, this means that around 11% of the total energy coming out of the EAF would be utilised in producing a value-added product in the form of syngas. This contrasts with allowing around 33% of the energy in the EAF either being completely dissipated to the environment or converting it into electricity via waste heat recovery. The following two cases, Case 2 and 3, indicate EAF off-gas composition containing 72% and 40% nitrogen respectively. For Cases 2 and 3, a steam biogasification process was integrated which did not yield positive results for CO2 utilisation, since is a more promising gasifying agent. In addition, significant energy from EAF off-gas is used in raising the temperature of steam to the design temperature of the gasifier. However, although the CO2 was not directly used in this part of the process, it allows for other opportunities of process integration, for example the reverse water-gas shift step.

Gasformig koldioxid kan absorberas i en ammoniaklösning och bilda salt. De möjliga produkterna är ammoniumvätekarbonat (NH4HCO3), ammoniumkarbamat (NH2COONH4) och ammoniumkarbonat ((NH4)2CO3). Ammoniak är gasformigt i rumstemperatur. För att förhindra avdunstning av ammoniak undersöktes det i den här rapporten om nedkylning av reaktionslösningen eller ett oljelager ovanför skulle kunna förhindra detta och därmed tillåta saltbildning i lösningen. Dessutom skulle absorptionen genomföras utan både oljelager och nedkylt förhållande för att bestämma vad som var mest effektivt för att ge ett så högt utbyte som möjligt. För bestämning av de bildade salternas sammansättning användes XRD som analysmetod.  Resultatet från experimentet visade att salterna bildades i gasfasen och inget salt erhölls från vätskefasen. Orsaken till det är inte fastslagen, men tros bero på parametrar som salternas löslighet, lösningens pH, flödeshastighet på koldioxiden som gynnar ammoniakens avdunstning samt temperaturen. Utbytet från de olika försöksuppställningarna blev lågt i samtliga experiment, som högst erhölls relativt utbyte på 1,5%. Experimentet som gav högst relativt utbyte var försök vid 15% ammoniakkoncentration och koldioxidflöde på 181 ml CO2/min. Vid detta försök gjordes inga åtgärder för att förhindra ammoniakavdunstning från lösningen. Av de proverna som analyserades med XRD erhölls endast den önskade produkten med säkerhet i ett av proverna (isbad, 15 % NH3, 181 ml CO2/min). För att bestämma optimala reaktionsbetingelser krävs vidare studier.

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