CERES :: Browsing by Author "Clough, Peter T."

Browsing by Author "Clough, Peter T."

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Open Access
Activated carbon derived from biomass combustion bottom ash as solid sorbent for CO2 adsorption
(Elsevier, 2023-05-05) Gorbounov, Mikhail; Petrovic, Ben; Ozmen, Serap; Clough, Peter T.
Climate change and global warming, caused mainly by the anthropogenic CO2 emissions, has been recognised to be the biggest threat to global ecosystems. Replacing fossil fuels with sustainable biomass for heat and power generation is a key tool in our fight against climate change. Such combustion, however, generates large quantities of ash which, unlike the coal counterparts, are yet to find major applications in industry. This leads to challenging waste management and thus, necessitating urgent measures to valorise this increasing waste stream. However, producing activated carbon from biomass combustion ash allows for not only effective waste valorisation into value-added products, but also to prepare a sorbent for post-combustion carbon capture from an abundant and cheap source that is readily available for in-situ application (hence, minimising overall costs). This work has focused on preparation and activation of industrial-grade biomass ash-derived porous carbon via an economical direct method, followed by an extensive characterisation of its textural properties as well as an evaluation of the CO2 uptake of both the virgin and the activated carbonaceous sorbents. The final sample was selected based on an extensive optimisation campaign aiming towards maximisation of yield and CO2 uptake. The optimum activated sample adsorbed 0.69 mmol/g, thus, nearly doubling the adsorption capacity of the virgin biomass combustion bottom ash-derived carbon.
Embargo
An investigation of a novel monolithic nickel-based catalyst for clean hydrogen production
(Cranfield University, 2024-05) Shen, Ziqi; Clough, Peter T.; Nabavi, Seyed A.; Wagland, Stuart T.
The decarbonisation of the energy sector can anticipate the future of net zero, and hydrogen is currently one of the most promising energy carriers to contribute to this goal. As for hydrogen production, steam methane reforming (SMR) occupies the predominant status and will remain in its position in the short term. The SMR process requires high-performance catalysts such as nickel-based catalysts, and carbon capture technology is of interest to decarbonise the SMR to produce clean hydrogen. The overall aim of the PhD project is to develop a novel monolithic nickel-based catalyst and evaluate its performance under SMR and sorbent-enhanced SMR (SE-SMR) conditions. The literature review looked back on the ceramic materials used in the SMR and SE-SMR processes, and also the method to prepare nickel-based catalysts. Silicon carbide was chosen as the support material due to its excellent thermal and mechanical properties. The monolithic nickel-based catalysts were designed, synthesised, characterised and tested in a fixed-bed reactor, in which the main reactor pipe and the steam generator were designed and constructed for this project. In addition, a pulse injection system was designed and installed on the reactor, and the SMR kinetics were studied using the monolithic catalysts. After the integration of the solid sorbents, a further study was conducted on the effect of structure within the SE-SMR process using the monolithic catalysts. The monolithic catalysts exhibited excellent activity at low SMR temperatures and pressures with a realistic gas space velocity. A kinetic model was established to describe the reaction rates using a novel and time-saving approach. The mass transfer limitations led to a low activation energy in kinetics and a reduction in activity when sorbents were applied. The monolithic catalysts will be a strong candidate for the decarbonisation of the energy sectors, with further improvement of its long-term stability and coordination with appropriate sorbents.
Open Access
Application of machine learning in hydrogen production via the process of sorbent enhanced steam methane reforming.
(Cranfield University, 2023-06) Nkulikiyinka, Paula; Clough, Peter T.; Manovic, Vasilije; Wagland, Stuart
This thesis is focused on the exploration of the use of machine learning and computational methods for modelling process conditions and for materials screening within the process of sorbent enhanced steam methane reforming (SE- SMR) for carbon-abated hydrogen production. Hydrogen is a clean, abundant and versatile energy carrier that can be used for a wide range of applications. However, the production of hydrogen is still largely dependent on fossil fuels, which presents a significant challenge for achieving a truly sustainable energy system. The purpose of this study is to address this challenge by exploring novel approaches to hydrogen production, namely using machine learning, thermodynamic simulations, theoretical modelling, and the proposal of new methodologies and materials for low-carbon hydrogen production. Three main areas of work were conducted within this thesis, which include 1) two surrogate models have been developed and used to predict and estimate variables that would otherwise be difficult direct measured.; 2) applying machine learning, namely quantitative structure–property relationship analysis (QSPR) has been employed in the exploration of combined sorbent catalyst material (CSCM) for SE-SMR; and 3) applying machine learning to screen suitable metal organic frameworks (MOFs) for the storage of the produced blue hydrogen. Firstly, a surrogate model, was developed which was done by firstly simulating the model in Aspen Plus, applying a sensitivity analysis to gather a large dataset, then applying two multiple linear regression model, to observe the accuracy of predicting the gas concentration outputs. Two models were successfully developed with both models were accurate with high R² values, all above 98%. Secondly, the novel approach of QSPR with inductive transfer learning and datamining, was applied to develop two large databases of sorbent and catalyst properties, respectively. Then the developed machine learning models from these databases were applied, to predict the optimal conditions and precursor materials for the highest performing CSCM, in terms of last cycle capacity and methane conversion. Lastly, a similar approach was applied for the screening of MOFs for the storage of hydrogen by using multiple linear regression, simple geometric descriptors, and patterns in data to identify a better performing MOF than the currently reported experimental MOFs in literature.
Open Access
Applying machine learning algorithms in estimating the performance of heterogeneous, multi-component materials as oxygen carriers for chemical-looping processes
(Elsevier, 2020-01-09) Yan, Yongliang; Mattisson, Tobias; Moldenhauer, Patrick; Anthony, Edward J.; Clough, Peter T.
Heterogeneous, multi-component materials such as industrial tailings or by-products, along with naturally occurring materials, such as ores, have been intensively investigated as candidate oxygen carriers for chemical-looping processes. However, these materials have highly variable compositions, and this strongly influences their chemical-looping performance. Here, using machine learning techniques, we estimate the performance of heterogeneous, multi-component materials as oxygen carriers for chemical-looping. Experimental data for 19 manganese ores chosen as potential chemical-looping oxygen carriers were used to create a so-called training database. This database has been used to train several supervised artificial neural network models (ANN), which were used to predict the reactivity of the oxygen carriers with different fuels and the oxygen transfer capacity with only the knowledge of reactor bed temperature, elemental composition, and mechanical properties of the manganese ores. This novel approach explores ways of dealing with the training dataset, learning algorithms and topology of ANN models to achieve enhanced prediction precision. Stacked neural networks with a bootstrap resampling technique have been applied to achieve high precision and robustness on new input data, and the confidence intervals were used to assess the precision of these predictions. The current results indicate that the best trained ANNs can produce highly accurate predictions for both the training database and the unseen data with the high coefficient of determination (R2 = 0.94) and low mean absolute error (MAE = 0.057). We envision that the application of these ANNs and other machine learning algorithms will accelerate the development of oxygen carrying materials for a range of chemical-looping applications and offer a rapid screening tool for new potential oxygen carriers.
Open Access
Assessment of optimal conditions for the performance of greenhouse gas removal methods
(Elsevier, 2021-06-18) Asibor, Jude Odianosen; Clough, Peter T.; Nabavi, Seyed Ali; Manovic, Vasilije
In this study, a comparative literature-based assessment of the impact of operational factors such as climatic condition, vegetation type, availability of land, water, energy and biomass, management practices, cost and soil characteristics was carried out on six greenhouse gas removal (GGR) methods. These methods which include forestation, enhanced weathering (EW), soil carbon sequestration (SCS), biochar, direct air capture with carbon storage (DACCS) and bioenergy with carbon capture and storage (BECCS) were accessed with the aim of identifying the conditions and requirements necessary for their optimum performance. The extent of influence of these factors on the performance of the various GGR methods was discussed and quantified on a scale of 0–5. The key conditions necessary for optimum performance were identified with forestation, EW, SCS and biochar found to be best deployed within the tropical and temperate climatic zones. The CCS technologies (BECCS and DACCS) which have been largely projected as major contributors to the attainment of the emission mitigation targets were found to have a larger locational flexibility. However, the need for cost optimal siting of the CCS plant is necessary and dependent on the presence of appropriate storage facilities, preferably geological. The need for global and regional cooperation as well as some current efforts at accelerating the development and deployment of these GGR methods were also highlighted.
Open Access
CO2 capture performance of gluconic acid-modified limestone-dolomite mixtures under realistic conditions
(ACS, 2019-07-10) Wang, Ke; Gu, Feng; Clough, Peter T.; Zhao, Pengfei; Anthony, Edward J.
Calcium Looping (CaL) technology has become one of the most attractive ways to capture CO2 from fossil fuel power plants. However, with increasing numbers of cyclic reactions, the CO2 capture capacity rapidly decreases. To address this shortcoming, limestone-dolomite mixtures modified by gluconic acid were explored to prepare highly effective, MgO-stabilized, CaO sorbents that exhibited a high and stable CO2 capture capacity over multiple cycles. The sorbents were all tested over 10 carbonation-calcination cycles and were performed under realistic CaL conditions (calcination in a high CO2 concentration). The results of this research have demonstrated that the inhomogeneous composition that occurs between CaO and MgO - caused by the small CaO crystallite size, porous texture, nanosheet (~100 nm thick) morphology - provides sufficient void space for the volume expansion during carbonation to mitigate the effects of repeated cycle sintering and retain structural stability. A MgO content as low as 10 mol% was able to ensure a superior CO2 capture performance with a fast carbonation rate, high CO2 carrying capacities and remarkable stability. Furthermore, these sorbents retained a conversion (above 90%) over multiple cycles following a recarbonation step
Open Access
A country-level assessment of the deployment potential of greenhouse gas removal technologies
(Elsevier, 2022-09-13) Asibor, Jude Odianosen; Clough, Peter T.; Nabavi, Seyed Ali; Manovic, Vasilije
The deployment of greenhouse gas removal (GGR) technologies has been identified as an indispensable option in limiting global warming to 1.5 °C by the end of the century. Despite this, many countries are yet to include and promote this option in their long-term plans owing to factors such as uncertainty in technical potential, deployment feasibility and economic impact. This work presents a country-level assessment of the deployment potential of five GGR technologies, including forestation, enhanced weathering (EW), direct air carbon capture and storage (DACCS), bioenergy with carbon capture and storage (BECCS) and biochar. Using a multi criteria decision analysis (MCDA) approach consisting of bio-geophysical and techno-economic factors, priority regions for the deployment of these GGR technologies were identified. The extent of carbon dioxide removable by 2100 via these technologies was also estimated for each of the 182 countries considered. While the obtained results indicate the need for regional cooperation among countries, it also provides useful evidence on the need for countries to include and prioritise GGR technologies in their revised nationally determined contributions (NDCs).
Open Access
Country-level assessment of the deployment potential of greenhouse gas removal technologies.
(Cranfield University, 2023-07) Asibor, Jude Odianosen; Clough, Peter T.; Nabavi, Sayed Ali; Manovic, Vasilije
The deployment of greenhouse gas removal (GGR) technologies has been identified as an indispensable option in meeting the warming target of 1.5 °C by the end of the century. Despite the importance of this pathway, the Nationally Determined Contributions (NDCs) of countries indicates a low intent to deploy these technologies. Among the major factors responsible for this low level of inclusion is the lack of robust country-level bio-geophysical and techno-economic feasibility assessments to ascertain national GGR deployment potential. Herein lies the challenge that this thesis aimed to address. This study investigated the potential of 182 countries to deploy five of the most promising GGR technologies, including forestation, enhanced weathering, direct air carbon capture and storage, bioenergy with carbon capture and storage, and biochar. A comparative literature-based assessment was carried out to identify and rank the major factors required for optimum performance of these GGR methods. Based on the bio-geophysical and techno-economic characteristics, Machine Learning (ML) was applied to identify the range of GGR technologies that respective countries can suitably and effectively deploy. ML models were also developed for predictive locational resource mapping of these technologies. Furthermore, the extent of carbon dioxide removable by 2100 via these technologies for each country (national potential) was evaluated using a Multi Criteria Decision Analysis approach. An assessment of domestic and regional sufficiency was also carried out to provide an evidence base for international collaboration. Priority regions for the deployment of these GGR technologies were identified, with Latin America and Sub-Saharan Africa regions found to have surplus potentials, and thus, expected to serve as a major hub to support other regions of the world. While the obtained results indicate the need for regional cooperation among countries, it also provides useful evidence on the need for countries to include and prioritise GGR technologies in their revised NDCs.
Open Access
Design and performance testing of a monolithic nickel-based SiC catalyst for steam methane reforming
(Elsevier, 2023-12-13) Shen, Ziqi; Nabavi, Seyed Ali; Clough, Peter T.
Hydrogen is a highly promoted carbon-free energy carrier that has drawn significant attention recently due to its potential to decarbonise energy sector. More than three-quarters of hydrogen is currently produced via steam methane reforming (SMR), and nickel-based catalysts are used in most applications. Structured catalysts have been reported to be able to further improve catalyst performance as they can optimise heat and mass transfer, as well as prevent coke formation with its structural and textural proprieties. Silicon carbide (SiC) has excellent hardness, thermal conductivity, and chemical inertness, therefore is a promising material to develop structured nickel-based monolithic SiC catalysts for SMR. In this work, a structured monolithic catalyst support has been formed by a modified freeze-gelation method, initially starting from SiC powder, and nickel has been distributed to form a monolithic nickel-based catalyst by wet impregnation. The results showed that the catalysts can achieve thermodynamic equilibrium at 600 °C with a gas hourly space velocity (GHSV) of 10,000 h−1, while reaching a high methane conversion of 86% at 800 °C and GHSV value of 20,000 h−1 during the performance tests using low feeding concentration and low pressure. This is the first time SiC catalytic materials have had their performance demonstrated for SMR under realistic operating conditions.
Open Access
Desulfurization using limestone during sludge incineration in a fluidized bed furnace: Increased risk of particulate matter and heavy metal emissions
(Elsevier, 2020-04-03) Zha, Jianrui; Huang, Yaji; Clough, Peter T.; Dong, Lu; Xu, Ligang; Zhu, Zhicheng; Yu, Mengzhu
Incineration of sludge can be an effective method to minimise waste whilst producing useful heat. However, incineration can cause secondary pollution issues due to the emission of SO2, therefore a set of experiments of sludge incineration in a bubble bed furnace were conducted with limestone addition to study desulfurization of sludge incineration flue gas. As expected, over 93% emission of SO2 was reduced with limestone addition, and that of CO and NOx were increased and decreased respectively when the fuel feeding rate raised. The distribution of fly ash was also increased by raising the fuel feeding rate due to increasing fragmentation of the ash. However, distributions of PM2.5 and heavy metals in submicron particles have dramatically increased with limestone desulfurization. The mechanism was revealed by SEM and EDS statistical analysis, indicating that the reaction between aluminosilicate and calcium made particles agglomerate and eutectic mixtures form, these larger ash particles were found to divide between collection as cyclone ash and fragmentation into finer particles that bypassed the cyclone. Those fine particles provided more surface area for heavy metal condensation. Furthermore, it was found that the reaction mechanism for semi-volatile metals involved them being released from the sludge and forming PM1 particles due to the vaporization-condensation mechanism, leading to higher emission of PM1 and distribution of heavy metals in PM1. Thus, it should be considered that there may actually be higher emission risks of PM and heavy metal emissions when aiming to desulfurize a flue gas using Ca-based minerals in certain circumstances
Embargo
Development of bimetallic catalysts for (sorption-enhanced) steam methane reforming
(Cranfield University, 2023-12) Wang, Siqi; Clough, Peter T.; Nabavi, Seyed Ali
Hydrogen has gained increasing attention in recent years as one of the most promising solutions to decarbonize the energy sector, as it emits zero carbon when combusted. The demand for clean hydrogen continues to rise as government, industry, and academia endeavour to meet the net zero goal by the year 2050. Steam methane reforming is currently the predominant hydrogen production pathway and is predicted to remain so for the years to come. Many techniques exist for the optimization and decarbonization of the steam methane reforming process. Two of the most widely employed methods include using more efficient and stable catalysts and adding in an in-situ carbon capture step using solid CO₂ sorbents. The overall aim of this PhD study is to develop and evaluate the performance of novel bimetallic catalysts for the (sorption-enhanced) steam methane reforming process. Starting from a comprehensive literature review, recent advances in the field of bimetallic SMR catalysts were summarized and reviewed, based on their catalytic activity, stability, and physical-chemical properties. Based on the review, three bimetallic catalysts (Ni₃M ₁ /Al₂ O₃, M = Cu, Fe, and Ge) were synthesized, characterized using different techniques, and tested in a laboratory-scale fixed bed reactor under typical steam methane reforming conditions. CaO particles were then added to the system and the performance of the catalysts under sorption-enhanced steam methane reforming conditions was evaluated. A study on the influence of Cu loading on the bimetallic Ni-Cu catalysts was also carried out. The experimental studies were also accompanied by Density Functional Theory calculations of the carbon and oxygen adsorption energies on the bimetallic surfaces, and microkinetic modelling of the SMR reaction based on previous literature on its reaction mechanism. Finally, machine learning models were developed for the prediction of atomic adsorption energies using readily available elemental properties. Together with the previously developed microkinetic model, a fast high throughput screening of bimetallic alloys was carried out and catalysts with high sulphur resistance were successfully identified. Overall, the addition of Cu was found to be highly beneficial for promoting the catalytic activity of the conventional Ni catalysts, and the addition of Ge promotes the activity and can potentially improve the sulphur resistance of the catalysts. The wide application of these cost-effective and highly active bimetallic catalysts will contribute significantly to the decarbonisation of the energy sector by enabling the efficient production of hydrogen.
Open Access
Development of nanoporosity on a biomass combustion ash-derived carbon for CO2 adsorption
(IEEE, 2022-11-08) Gorbounov, Mikhail; Petrovic, Ben; Özmen, Seran; Clough, Peter T.; Bekmuratova, Dilyara; Masoudi Soltani, Salman
Carbonaceous adsorbents are one of the most widely-used materials used for the removal of chemical species in gaseous and aqueous media. However, the route from precursor to activated carbon is riddled with myriad techniques and steps, that entail additional costs. Such expenses could be minimized via waste valorization e.g. biomass combustion bottom ash which has been used in this work. In order to develop surface nanoporosity, the waste-derived carbon was thermally treated, increasing the CO 2 adsorption capacity by nearly twofold and thus, producing a cost-effective sorbent for post-combustion CO 2 capture. The effectiveness of such “unconventional” activation route has been verified using Scanning Electron Microscopy, Fourier-Transform Infrared Spectroscopy as well as Proximate Analysis and the CO 2 adsorption data obtained via Thermogravimetric Analysis (TGA). The proposed material and method could serve as a viable alternative to the current methods for decarbonization of the UK power sector through in-situ waste valorization.
Open Access
Developments in calcium/chemical looping and metal oxide redox cycles for high-temperature thermochemical energy storage: A review
(Elsevier, 2019-11-27) Yan, Yongliang; Wang, Ke; Clough, Peter T.; Anthony, Edward J.
Energy storage is one of the most critical factors for maximising the availability of renewable energy systems while delivering firm capacity on an as- and when-required basis, thus improving the balance of grid energy. Chemical and calcium looping are two technologies, which are promising from both the point of view of minimising greenhouse gas emissions and because of their suitability for integrating with energy storage. A particularly promising route is to combine these technologies with solar heating, thus minimising the use of fossil fuels during the materials regeneration steps. For chemical looping, the development of mixed oxide carrier systems remains the highest impact research and development goal, and for calcium looping, minimising the decay in CO2 carrying capacity with natural sorbents appears to be the most economical option. In particular, sorbent stabilisers such as those based on Mg are particularly promising. In both cases, energy can be stored thermally as hot solids or chemically as unreacted materials, but there is a need to build suitable pilot plant demonstration units if the technology is to advance.
Open Access
Dynamic transformations of metals in the burning solid matter during combustion of heavy metal-contaminated biomass
(American Chemical Society, 2021-05-10) Zha, Jianrui; Huang, Yaji; Zhu, Zhicheng; Yu, Mengzhu; Clough, Peter T.; Yan, Yongliang; Dong, Lu; Cheng, Haoqiang
Combustion as an efficient and reliable method is widely used for metal-enriched biomass to achieve energy and metal recoveries, but there are emission risks of heavy metals in the flue gas and bottom ash that can give rise to secondary pollutions. To optimize such combustion processes, this work investigated the combustion characteristics of a kind of hyperaccumulator biomass and focused on the intermediate states and dynamic transformations of metals for the first time. A pseudo-in situ sampling method was used to collect the burning solid residues at different time intervals before further analysis. The conversions between elemental forms were revealed, and their conversion rates were also calculated. It was found that the transformation of metals was determined by their elemental natures, species distributions, and combustion progress where there was not a consecutive process but separated by several stages, which were related to (1) the release of volatile matters, (2) the formation and consumption of the char, and (3) the fixation by silicates. Based on the information of dynamic metal characteristics, a new strategy was proposed to optimize metal distribution by adjusting the combustion time of operations. The methodology introduced in this work will also help emission control and metal recovery for other metal-rich fuels.
Open Access
Enhanced hydrogen production from thermochemical processes
(Royal Society of Chemistry, 2018-07-24) Ji, Guozhao; Yao, Joseph G.; Clough, Peter T.; Diniz da Costa, João C.; Anthony, Edward J.; Fennell, Paul S.; Wang, Wei; Zhao, Ming
To alleviate the pressing problem of greenhouse gas emissions, the development and deployment of sustainable energy technologies is necessary. One potentially viable approach for replacing fossil fuels is the development of a H2 economy. Not only can H2 be used to produce heat and electricity, it is also utilised in ammonia synthesis and hydrocracking. H2 is traditionally generated from thermochemical processes such as steam reforming of hydrocarbons and the water-gas-shift (WGS) reaction. However, these processes suffer from low H2 yields owing to their reversible nature. Removing H2 with membranes and/or extracting CO2 with solid sorbents in situ can overcome these issues by shifting the component equilibrium towards enhanced H2 production via Le Chatelier's principle. This can potentially result in reduced energy consumption, smaller reactor sizes and, therefore, lower capital costs. In light of this, a significant amount of work has been conducted over the past few decades to refine these processes through the development of novel materials and complex models. Here, we critically review the most recent developments in these studies, identify possible research gaps, and offer recommendations for future research.
Open Access
The extent of sorbent attrition and degradation of ethanol-treated CaO sorbents for CO2 capture within a fluidised bed reactor
(Elsevier, 2017-12-01) Clough, Peter T.; Greco, Gianluca; Erans, María; Coppola, Antonio; Montagnaro, Fabio; Anthony, Edward J.
The application of an ethanol pre-treatment step on biomass-templated calcium looping sorbents resulting in an improved pore structure for cyclic CO2 capture was investigated. Three ethanol solutions of varying concentrations were used with an improved pore and particle structure, and thermogravimetric analyser CO2 carrying capacity arising with the 70 vol% ethanol solution. The extent of attrition of these sorbents was tested within a fluidised bed reactor and compared against an untreated sorbent and a limestone base case. It found that despite the ethanol-treated sorbents displaying an admirable CO2 carrying capacity within the thermogravimetric analyser even under realistic post-combustion conditions, this was not translated equivalently in the fluidised bed. Attrition and elutriation of the biomass-templated sorbents was a significant issue and the ethanol pre-treatment step appeared to worsen the situation due to the roughened surface and mechanically weaker structure.
Open Access
Gaseous CdCl2 and PbCl2 adsorption by limestone at high temperature: Mechanistic study through experiments and theoretical calculation
(Elsevier, 2021-03-28) Zha, Jianrui; Zhu, Zhicheng; Huang, Yaji; Clough, Peter T.; Xia, Zhipeng
There is a risk of heavy metal emission during solid waste incineration, and the capture of gaseous semi-volatile metal by mineral sorbents is an effective method for its pollution control. As a cheap and common additive for combustion industry, limestone is an effective sorbent for controlling various gaseous pollutants, but its high-temperature sorption mechanism for gaseous metal chlorides has not been systematically studied yet. In this study, an experimental study in a fixed bed furnace and density functional theoretical study were conducted to investigate the adsorption mechanism of gaseous CdCl2 and PbCl2 by limestone at high temperature. The capture performance was greater at a higher temperature due to the formation of an enhanced pore structure through limestone decomposition, while the efficiency decreased at temperatures higher than 700 °C because of the negative movement of the reaction equilibrium. Additionally, the higher equilibrium constant of CdCl2 caused more effective adsorption than PbCl2. According to theoretical calculations, both limestone and lime can adsorb molecular metal chlorides while lime has higher adsorption energies due to its more active surface. For a commercial application, it is recommended to inject limestone into the furnace at a high temperature to capture heavy metal more effectively.
Open Access
Green production of a novel sorbent from kaolin for capturing gaseous PbCl2 in a furnace
(Elsevier, 2020-09-22) Zha, Jianrui; Huang, Yaji; Clough, Peter T.; Xia, Zhipeng; Zhu, Zhicheng; Fan, Conghui; Yu, Mengzhu; Yan, Yongliang; Cheng, Haoqiang
The pollution of semi-volatile heavy metals is one of the key environmental risks for municipal solid waste incineration, and in-situ adsorption of metals within the furnace by mineral sorbents such as kaolin has been demonstrated as a promising emission control method. To lessen the consumption of sorbent, a novel material of amorphous silicate was produced from kaolin through pressurised hydrothermal treatment. Its performance of gaseous PbCl2 capture was tested in a fixed bed furnace and compared with unmodified kaolin and metakaolin. With increasing temperature, the adsorption rates for all sorbents declined due to higher saturated vapour pressure, while the partitions of residual form lead increased which indicated higher stability of heavy metals in the sorbent because of melting effect. The new sorbent with a larger surface area and reformed structure presented 26% more adsorption efficiency than raw kaolin at 900 °C, and increasing the modification pressure improved these properties. Additionally, the production of this high-temperature sorbent was relatively inexpensive, required little thermal energy and no chemicals to produce and no waste effluent was generated, thus being much cleaner than other modification methods.
Open Access
Harnessing the power of machine learning for carbon capture, utilisation, and storage (CCUS) – A state-of-the-art review
(Royal Society of Chemistry, 2021-11-01) Yan, Yongliang; Borhani, Tohid N.; Subraveti, Sai Gokul; Pai, Kasturi Nagesh; Prasad, Vinay; Rajendran, Arvind; Nkulikiyinka, Paula; Asibor, Jude Odianosen; Zhang, Zhien; Shao, Ding; Wang, Lijuan; Zhang, Wenbiao; Yan, Yong; Ampomah, William; You, Junyu; Wang, Meihong; Anthony, Edward J.; Manovic, Vasilije; Clough, Peter T.
Carbon capture, utilisation and storage (CCUS) will play a critical role in future decarbonisation efforts to meet the Paris Agreement targets and mitigate the worst effects of climate change. Whilst there are many well developed CCUS technologies there is the potential for improvement that can encourage CCUS deployment. A time and cost-efficient way of advancing CCUS is through the application of machine learning (ML). ML is a collective term for high-level statistical tools and algorithms that can be used to classify, predict, optimise, and cluster data. Within this review we address the main steps of the CCUS value chain (CO2 capture, transport, utilisation, storage) and explore how ML is playing a leading role in expanding the knowledge across all fields of CCUS. We finish with a set of recommendations for further work and research that will develop the role that ML plays in CCUS and enable greater deployment of the technologies.
Open Access
High CO2 absorption in new amine based-transition-temperature mixtures (deep eutectic analogues) and reporting thermal stability, viscosity and surface tension: Response surface methodology (RSM)
(Elsevier, 2020-07-23) Ghaedi, Hosein; Zhao, Ming; Clough, Peter T.; Anthony, Ben; Fennell, Paul S.
To study CO2 capture potential, three types of transition-temperature mixtures (TTMs) were prepared by mixing ethyltriphenylphosphonium bromide (MTPPB) as a hydrogen bond acceptor (HBA) and n-methyl diethanolamine (MDEA) as a hydrogen bond donor (HBD) in different molar ratios (1:7, 1:10 and 1:16). Fourier transform infrared spectroscopy (FT-IR) results showed that TTMs have almost similar spectra to their HBD (MDEA) with different levels of transmittance and exhibit similar behavior. From the experimental results, it was found that the thermal stability, viscosity and surface tension of TTMs decreased as the concentration of MDEA in the mixture increased. According to response surface methodology (RSM) models and analysis of variance (ANOVA), temperature and molar ratio had a great effect on the viscosity and surface tension of TTMs. Finally, it was found that CO2 solubility in TTMs (at 303.15 K at pressure up to 1.35 MPa) was enhanced as the MDEA quantity increased in the mixture up to 1:10 mol ratio. However, by increasing MDEA concentration to 16:1 mol ratio, there was a decreasing trend in the CO2 solubility data. Also, all TTMs, particularly TTM containing 10:1 mol MDEA (MTPPB-MDEA 1:10) exhibited an equilibrium loading capacity approaching 1 mol CO2 per mole solvent at high pressure, revealing their high potential for CO2 capture. A comparison showed that the CO2 solubility in the studied solvents was higher than that of existing deep eutectic solvents (DESs) and other TTMs as well as several ionic liquids (ILs) to date. To the best of our knowledge, this is the first study to report the CO2 solubility in phosphonium-base TTMs containing MDEA

Browsing by Author "Clough, Peter T."

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