School of Water, Energy and Environment (SWEE)

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Open Access
Aquatic macrophytes in morphological and physiological responses to the nanobubble technology application for water restoration
(American Chemical Society, 2020-12-04) Wang, Shuo; Liu, Yunsi; Lyu, Tao; Pan, Gang; Li, Pan
Nanobubble technology, as an emerging and sustainable approach, has been used for remediation of eutrophication. However, the influence of nanobubbles on the restoration of aquatic vegetation and the mechanisms are unclear. In this study, the effect of nanobubbles at different concentrations on the growth of Iris pseudacorus (Iris) and Echinodorus amazonicus (Echinodorus) was investigated. The results demonstrated that nanobubbles can enhance the delivery of oxygen to plants, while appropriate nanobubble levels will promote plant growth, excess nanobubbles could inhibit plant growth and photosynthesis. The nanobubble concentration thresholds for this switch from growth promotion to growth inhibition were 3.45 × 107 and 1.23 × 107 particles/mL for Iris and Echinodorus, respectively. Below the threshold, an increase in nanobubble concentration enhanced plant aerobic respiration and ROS generations in plants, resulting in superior plant growth. However, above the threshold, high nanobubble concentrations induced hyperoxia stress, particularly in submergent plants, which result in collapse of the antioxidant system and the inhibition of plant physiological activity. The expression of genes involved in modulating redox potential and the oxidative stress response, as well as the generation of relevant hormones, were also altered. Overall, this study provides an evidence-based strategy to guide the future application of nanobubble technology for sustainable management of natural waters.
Open Access
Attrition study of cement-supported biomass-activated calcium sorbents for CO2 capture
(American Chemical Society, 2016-08-19) Duan, Lunbo; Yu, Zhijian; Erans Moreno, Maria; Li, Yingjie; Manovic, Vasilije; Anthony, Edward J.
Enhanced CO2 capacity of biomass modified Ca-based sorbent has been reported recently, but undesired attrition resistance has also been observed. Cement was used as a support for biomass-activated calcium sorbent during the granulation process in this study, in order to improve the poor mechanical resistance. Attrition tests were carried out in an apparatus focused on impact breakage to evaluate how the biomass addition and cement support influence the particle strength during Ca-looping. Results showed biomass addition impaired the mechanical strength and cement support could improve it, which is reflected by the breakage probability and size change after impact of pellets experienced calcination and multiple calcination/carbonation cycles. Larger-sized particles suffered more intense attrition. The mechanical strength of sorbents declined significantly after higher temperature calcination but increased after carbonation. After multiple cycles, the mechanical strength of particles was greatly enhanced, but more cracks emerged. A semi-empirical formula for calculating average diameter after attrition based on Rittinger’s surface theory was developed. Observation on the morphology of particles indicated that particles with more porosity and cracks were more prone to breakage.
Open Access
Biochemical profile of heritage and modern apple cultivars and application of machine learning methods to predict usage, age, and harvest season
(American Chemical Society, 2017-06-02) Anastasiadi, Maria; Mohareb, Fady R.; Redfern, Sally P.; Berry, Mark; Simmonds, Monique; Terry, Leon A
The present study represents the first major attempt to characterise the biochemical profile in different tissues of a large selection of apple cultivars sourced from the UK’s National Fruit Collection comprising dessert, ornamental, cider and culinary apples. Furthermore, advanced Machine Learning methods were applied with the objective to identify whether the phenolic and sugar composition of an apple cultivar could be used as a biomarker fingerprint to differentiate between heritage and mainstream commercial cultivars as well as govern the separation among primary usage groups and harvest season. Prediction accuracy > 90% was achieved with Random Forest for all three models. The results highlighted the extraordinary phytochemical potency and unique profile of some heritage, cider and ornamental apple cultivars, especially in comparison to more mainstream apple cultivars. Therefore, these findings could guide future cultivar selection on the basis of health-promoting phytochemical content.
Open Access
Characterization of Fourier transform infrared, cavity ring-down spectroscopy, and optical feedback cavity-enhanced absorption spectroscopy instruments for the analysis of ammonia in biogas and biomethane
(American Chemical Society, 2022-10-27) Culleton, Lucy P.; di Meane, Elena Amico; Ward, Michael K. M.; Ferracci, Valerio; Persijn, Stefan; Holmqvist, Albin; Arrhenius, Karine; Murugan, Arul; Brewer, Paul J.
Novel traceable analytical methods and reference gas standards were developed for the detection of trace-level ammonia in biogas and biomethane. This work focused on an ammonia amount fraction at an upper limit level of 10 mg m–3 (corresponding to approximately 14 μmol mol–1) specified in EN 16723-1:2016. The application of spectroscopic analytical methods, such as Fourier transform infrared spectroscopy, cavity ring-down spectroscopy, and optical feedback cavity-enhanced absorption spectroscopy, was investigated. These techniques all exhibited the necessary ammonia sensitivity at the required 14 μmol mol–1 amount fraction. A 29-month stability study of reference gas mixtures of 10 μmol mol–1 ammonia in methane and synthetic biogas is also reported.
Open Access
CO2 capture performance using biomass-templated cement-supported limestone pellets
(American Chemical Society, 2016-09-09) Duan, Lunbo; Su, Chenglin; Erans Moreno, Maria; Li, Yingjie; Anthony, Edward J.; Chen, Huichao
Synthetic biomass-templated cement-supported CaO-based sorbents were produced by granulation process for high-temperature post-combustion CO2 capture. Commercial flour was used as the biomass and served as a templating agent. The investigation of porosity showed that the pellets with biomass or cement resulted in enhancement of porosity. Four types of sorbents containing varying proportions of biomass and cement were subject to 20 cycles in a TGA under different calcination conditions. After first series of tests calcined at 850 °C in 100% N2, all composite sorbents clearly exhibited higher CO2 capture activity compared to untreated limestone with exception of sorbents doped by seawater. The biomass-templated cement-supported pellets exhibited the highest CO2 capture level of 46.5% relative to 20.8% for raw limestone after 20 cycles. However, the observed enhancement in performance was substantially reduced under 950 °C calcination condition. Considering the fact that both sorbents supported by cement exhibited relatively high conversion with a maximum value of 19.5%, cement promoted sorbents appear to be better at resisting of harsh calcination conditions. Although flour as biomass-templated material generated significantly enhancement in CO2 capture capacity, further exploration must be carried out to find the way of maintaining outstanding performance for CaO-based sorbents under severe reaction conditions.
Open Access
Combustion behaviour of relatively large pulverised biomass particles at rapid heating rates
(American Chemical Society, 2016-10-28) Mock, Chinsung; Lee, Hookyung; Choi, Sangmin; Manovic, Vasilije
A pulverized solid fuel particle in a hot gas stream appears to have different characteristic behaviors at several stages, including heat-up, release of volatile matter, gas phase, and solid combustion. The characteristics of these stages may vary distinctly depending on devolatilization rate, the particle temperature history, and its chemical and physical properties. Biomass particles manifest different combustion behavior from that of burning coal particles under the same combustion conditions because they contain more volatiles (less fixed carbon), and they have a relatively lower particle density due to their fibrous structure. This paper presents an experimental study of burning behavior of different types of biomass particles (torrefied wood, coffee waste, and sewage sludge). The main experimental parameters—gas temperatures of 1090 and 1340 K, and O2 concentrations ranging from 10% to 40%—were employed to investigate the burning of biomass through a direct-observation approach using a high-speed photography technique at 7000 frames/s. In the case of firing/cofiring, biomass particles must be larger than the coal particles in order to achieve an equivalent thermal balance due to the higher energy density of coal. Therefore, the selected biomass samples were in the size range from 150–215 μm to 425–500 μm. The experimental setup has a cross-flow configuration for particle injection in order to enhance interaction between the particle and the two different streams—a cold carrier gas at 298 K, and upward-flowing postcombustion gases. It is believed that the employed experimental conditions are similar to those in a realistic furnace with a rapid heating rate of 105 K/s. The experimentally significant results, including the effective radii of the volatile flames, degrees of flame intensity, and the maximum size of a particle, are important for validation of models of single biomass particle combustion.
Open Access
Correlating asphaltene dimerization with its molecular structure by potential of mean force calculation and data mining
(American Chemical Society, 2018-04-11) Zhu, Xinzhe; Wu, Guozhong; Coulon, Frederic; Wu, Lvwen; Chen, Daoyi
Asphaltene aggregation affects the entire production chain of the petrochemical industry, which also poses environmental challenges for oil pollution remediation. The aggregation process has been investigated for decades, but it remains unclear how the free energy of asphaltene association in solvents is correlated to its molecular structure. In this study, dimerization energies of 28 types of asphaltenes in water and toluene were calculated using the umbrella sampling method. Structural parameters related to the atom types and functional groups were screened to identify the factors most influencing the dimerization energy using multiple linear regression, multilayer perceptron, and support vector regression. Results demonstrated that the influence of molecular structure on asphaltene association in water was nonlinear, while attempts to capture the relationship using linear regression had larger error. The linkage per aromatic ring, number of aromatic carbons, and number of aliphatic chains were the top three factors accounting for 52% of the dimerization energy variation in water. Asphaltene dimerization in toluene was dominated by the content of sulfur in aromatic rings and the number of aromatic carbons which contributed to 55% of the energy variation. To the best of our knowledge, this was the first study successfully predicting asphaltene dimerization using molecular structure (R > 0.9) and quantifying simultaneously the relative importance of each structural parameter. The proposed modeling approach supported the decision making on the number of structural parameters to investigate for predicting asphaltene aggregation.
Open Access
Deep eutectic solvents toward the detection and extraction of neurotransmitters: an emerging paradigm for biomedical applications
(American Chemical Society, 2023-05-17) Kaur, Harjot; Siwal, Samarjeet Singh; Kumar, Vinod; Thakur, Vijay Kumar
Neurotransmitters (NTs), the chemical messengers crucial for the proper functioning of the human brain, have some specific concentration within the human physiological system. Any fluctuations in their concentration may cause several neuronal diseases and disorders. Therefore, the requirement for fast and effective diagnosis to regulate and manage human cerebral diseases or conditions is surging swiftly. NTs can be extracted from natural products. The researchers have developed new protocols to improve the sensors’ sensing ability and eco-friendly nature. Deep eutectic solvents (DESs) have gained popularity as “green solvents” in sustainable chemistry. DESs provide a greater range of a potential window that helps in the enhanced electrocatalytic performance of the sensor and more inertness which helps in the corrosion protection of electrodes, ultimately giving better sensitivity and durability to the system. In addition, DESs provide facile electrodeposition of different materials on working electrodes, which is a prime prerequisite in electrocatalytic sensors. Here, in this review, the application of DESs as green solvents in detecting and extracting NTs is described in detail for the first time. We cover the available online articles up to December 2022 for the extraction and monitoring of NTs. Finally, we have concluded the topic with future prospects in this field.
Open Access
Development of hypertolerant strain of Yarrowia lipolytica accumulating succinic acid using high levels of acetate
(American Chemical Society, 2022-08-09) Narisetty, Vivek; Prabhu, Ashish A.; Bommareddy, Rajesh Reddy; Cox, Rylan; Agrawal, Deepti; Misra, Ashish; Ali Haider, M.; Bhatnagar, Amit; Pandey, Ashok; Kumar, Vinod
Acetate is emerging as a promising feedstock for biorefineries as it can serve as an alternate carbon source for microbial cell factories. In this study, we expressed acetyl-CoA synthase in Yarrowia lipolytica PSA02004PP, and the recombinant strain grew on acetate as the sole carbon source and accumulated succinic acid or succinate (SA). Unlike traditional feedstocks, acetate is a toxic substrate for microorganisms; therefore, the recombinant strain was further subjected to adaptive laboratory evolution to alleviate toxicity and improve tolerance against acetate. At high acetate concentrations, the adapted strain Y. lipolytica ACS 5.0 grew rapidly and accumulated lipids and SA. Bioreactor cultivation of ACS 5.0 with 22.5 g/L acetate in a batch mode resulted in a maximum cell OD600 of 9.2, with lipid and SA accumulation being 0.84 and 5.1 g/L, respectively. However, its fed-batch cultivation yielded a cell OD600 of 23.5, SA titer of 6.5 g/L, and lipid production of 1.5 g/L with an acetate uptake rate of 0.2 g/L h, about 2.86 times higher than the parent strain. Cofermentation of acetate and glucose significantly enhanced the SA titer and lipid accumulation to 12.2 and 1.8 g/L, respectively, with marginal increment in cell growth (OD600: 26.7). Furthermore, metabolic flux analysis has drawn insights into utilizing acetate for the production of metabolites that are downstream to acetyl-CoA. To the best of our knowledge, this is the first report on SA production from acetate by Y. lipolytica and demonstrates a path for direct valorization of sugar-rich biomass hydrolysates with elevated acetate levels to SA.
Open Access
Dual-emission single sensing element-assembled fluorescent sensor arrays for the rapid discrimination of multiple surfactants in environments
(American Chemical Society, 2024-03-11) Wei, Dali; Zhang, Hu; Tao, Yu; Wang, Kaixuan; Wang, Ying; Deng, Chunmeng; Xu, Rongfei; Zhu, Nuanfei; Lu, Yanyan; Zeng, Kun; Yang, Zhugen; Zhang, Zhen
Surfactants are considered as typical emerging pollutants, their extensive use of in disinfectants has hugely threatened the ecosystem and human health, particularly during the pandemic of coronavirus disease-19 (COVID-19), whereas the rapid discrimination of multiple surfactants in environments is still a great challenge. Herein, we designed a fluorescent sensor array based on luminescent metal–organic frameworks (UiO-66-NH2@Au NCs) for the specific discrimination of six surfactants (AOS, SDS, SDSO, MES, SDBS, and Tween-20). Wherein, UiO-66-NH2@Au NCs were fabricated by integrating UiO-66-NH2 (2-aminoterephthalic acid-anchored-MOFs based on zirconium ions) with gold nanoclusters (Au NCs), which exhibited a dual-emission features, showing good luminescence. Interestingly, due to the interactions of surfactants and UiO-66-NH2@Au NCs, the surfactants can differentially regulate the fluorescence property of UiO-66-NH2@Au NCs, producing diverse fluorescent “fingerprints”, which were further identified by pattern recognition methods. The proposed fluorescence sensor array achieved 100% accuracy in identifying various surfactants and multicomponent mixtures, with the detection limit in the range of 0.0032 to 0.0315 mM for six pollutants, which was successfully employed in the discrimination of surfactants in real environmental waters. More importantly, our findings provided a new avenue in rapid detection of surfactants, rendering a promising technique for environmental monitoring against trace multicontaminants.
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
Eco-friendly fabrication of highly selective amide-based polymer for CO2 capture
(American Chemical Society, 2019-09-05) Fayemiwo, Kehinde; Chiarasumran, Nutchapon; Nabavi, Seyed Ali; Loponov, Konstantin N.; Manovic, Vasilije; Benyahia, Brahim; Vladisavljevic, Goran T.
Porous polymeric adsorbents for CO2 capture (HCP-MAAMs) were fabricated by co-polymerisation of methacrylamide (MAAM) and ethylene glycol dimethacrylate (EGDMA) using acetonitrile and azobisisobutyronitrile as a porogen and initiator, respectively. The X-ray photoelectron and Fourier transform infrared spectra revealed a high density of amide groups in the polymer matrix of HCP-MAAMs, which enabled high selectivity to CO2. The polymers BET surface area and total pore volume was up to 277 m2 g-1 and 0.91 cm3 g-1, respectively. The highest CO2 uptake at 273 K and 1 bar CO2 pressure was 1.45 mmol g-1 and the heat of adsorption was 27-35 kJ mol-1. The polymer with the lowest crosslinking density exhibited unprecedented CO2/N2 selectivity of 394 at 273 K. Life cycle assessment revealed a lower environmental impact of HCP-MAAMs compared to molecularly imprinted polymers. HCP-MAAMs are eco-friendly CO2 adsorbents owing to their low regeneration energy, environmentally benign fabrication process, and high selectivity.
Open Access
Economic and environmental assessment of succinic acid production from sugarcane bagasse
(American Chemical Society, 2021-09-15) Shaji, Arun; Shastri, Yogendra; Kumar, Vinod; Ranade, Vivek V.; Hindle, Neil
This work presents technoeconomic analysis (TEA) and life cycle assessment (LCA) of a novel biorefinery producing succinic acid (SA) from sugarcane bagasse. The process consists of acid pretreatment, fermentation, followed by downstream separation and purification. Experimental data for pretreatment and fermentation are adapted for a plant processing 4 t/h of dry bagasse, producing 405 kg/h of succinic acid with the same quantity of acetic acid as a side product. Downstream separation is simulated in ASPEN PLUS. The facility is assumed to be annexed to and heat-integrated with an existing sugar mill in India. LCA is performed considering cradle-to-gate scope with 1 kg of SA as the functional unit. The TEA results show that although the process is currently not economically feasible, expected improvements in fermentation yields will make it cost-competitive. For the expected yield, the product cost of SA is INR 121/kg ($1.61/kg), and the selling price of succinic acid should be INR 178/kg ($2.37/kg) for a payback period of 4 years. Pretreatment and fermentation are the biggest contributors to the product cost. The life cycle greenhouse gas (GHG) emissions are 1.39 kg of CO2 equiv/kg succinic acid with electricity as the major contributor. Process improvement opportunities are identified to reduce the costs, as well as life cycle impacts.
Open Access
Entropy-driven three-dimensional DNA nanofireworks for simultaneous real-time imaging of telomerase and microRNA in living cells
(American Chemical Society, 2023-02-15) Wang, Jin; Wang, Kaixuan; Peng, Hanyong; Zhang, Zhen; Yang, Zhugen; Song, Maoyong; Jiang, Guibin
Real-time monitoring of different types of intracellular tumor-related biomarkers is of key importance for the identification of tumor cells. However, it is hampered by the low abundance of biomarkers, inefficient free diffusion of reactants, and complex cytoplasmic milieu. Herein, we present a stable and general method for in situ imaging of microRNA-21 and telomerase utilizing simple highly integrated dual tetrahedral DNA nanostructures (TDNs) that can naturally enter cells, which could initiate to form the three-dimensional (3D) higher-order DNA superstructures (DNA nanofireworks, DNFs) through a reliable target-triggered entropy-driven strand displacement reaction in living cells for remarkable signal amplification. Importantly, the excellent biostability, biocompatibility, and sensitivity of this approach benefited from (i) the precise multidirectional arrangement of probes with a pure DNA structure and (ii) the local target concentration enhanced by the spatially confined microdomain inside the DNFs. This strategy provides a pivotal molecular toolbox for broad applications such as biomedical imaging and early precise cancer diagnosis.
Open Access
Evaluation of moderately grafted primary, diamine, and triamine sorbents for CO2 adsorption from ambient air: balancing kinetics and capacity under humid conditions
(American Chemical Society, 2021-08-30) Wadi, Basil; Golmakani, Ayub; Manovic, Vasilije; Nabavi, Seyed Ali
Successful deployment of direct air capture (DAC) to mitigate the consequences of climate change depends on many factors, one of which is the development of kinetically efficient CO2 sorbents with a high sorption capacity, at ultralow CO2 concentrations. This work evaluated CO2 adsorption performance of primary-, diamine-, and triamine-grafted SBA-15 at pressures below 5 kPa for DAC applications, measured through volumetric sorption, followed by humid air (23% RH) adsorption by gravimetric analysis. Under humid air flow, triamines at an amine loading of 4.6 mmol/g showed the highest enhancement in adsorption, with an uptake of 26 mg/g, but the slowest average adsorption rate of 216 μg/g/min. Diamine at an amine loading of 2.78 mmol/g had an adsorption rate of 295 μg/g/min but demonstrated the lowest uptake of 13 mg/g. In comparison, primary amines at a loading of 2.6 mmol/g reached an equilibrium uptake of 22 mg/g, with a higher adsorption rate of 354 μg/g/min. Triamine grafted at 3.5 mmol/g had the fastest kinetics of all samples, reaching 525 μg/g/min. Results indicated that primary amines and moderate-to-high density triamine reagents incorporated into mesoporous media can offer a superior adsorption rate that can make up for lower adsorption capacities, by optimizing cyclic performance, and should be considered when designing for continuous DAC processes.
Open Access
Experimental determination of zinc isotope fractionation in complexes with the phytosiderophore 2′-deoxymugeneic acid (DMA) and its structural analogues, and implications for plant uptake mechanisms
(American Chemical Society, 2016-10-17) Marković, Tamara; Manzoor, Saba; Humphreys-Williams, Emma; Kirk, Guy J. D.; Vilar, Ramon; Weiss, Dominik J.
The stable isotope signatures of zinc and other metals are increasingly used to study plant and soil processes. Complexation with phytosiderophores is a key reaction and understanding the controls of isotope fractionation is central to such studies. Here, we investigated isotope fractionation during complexation of Zn2+ with the phytosiderophore 2′-deoxymugeneic acid (DMA), and with three commercially available structural analogues of DMA: EDTA, TmDTA, and CyDTA. We used ion exchange chromatography to separate free and complexed zinc, and identified appropriate cation exchange resins for the individual systems. These were Chelex-100 for EDTA and CyDTA, Amberlite CG50 for TmDTA and Amberlite IR120 for DMA. With all the ligands we found preferential partitioning of isotopically heavy zinc in the complexed form, and the extent of fractionation was independent of the Zn:ligand ratio used, indicating isotopic equilibrium and that the results were not significantly affected by artifacts during separation. The fractionations (in ‰) were +0.33 ± 0.07 (1σ, n = 3), + 0.45 ± 0.02 (1σ, n = 2), + 0.62 ± 0.05 (1σ, n = 3) and +0.30 ± 0.07 (1σ, n = 4) for EDTA, TmDTA, CyDTA, and DMA, respectively. Despite the similarity in Zn-coordinating donor groups, the fractionation factors are significantly different and extent of fractionation seems proportional to the complexation stability constant. The extent of fractionation with DMA agreed with observed fractionations in zinc uptake by paddy rice in field experiments, supporting the possible involvement of DMA in zinc uptake by rice.
Open Access
Fluorescent dissolved organic matter components as surrogates for disinfection byproduct formation in drinking water: a critical review
(American Chemical Society, 2023-06-12) Fernández-Pascual, Elena; Droz, Boris; O’Dwyer, Jean; O’Driscoll, Connie; Goslan, Emma H.; Harrison, Simon; Weatherill, John
Disinfection byproduct (DBP) formation, prediction, and minimization are critical challenges facing the drinking water treatment industry worldwide where chemical disinfection is required to inactivate pathogenic microorganisms. Fluorescence excitation–emission matrices-parallel factor analysis (EEM-PARAFAC) is used to characterize and quantify fluorescent dissolved organic matter (FDOM) components in aquatic systems and may offer considerable promise as a low-cost optical surrogate for DBP formation in treated drinking waters. However, the global utility of this approach for quantification and prediction of specific DBP classes or species has not been widely explored to date. Hence, this critical review aims to elucidate recurring empirical relationships between common environmental fluorophores (identified by PARAFAC) and DBP concentrations produced during water disinfection. From 45 selected peer-reviewed articles, 218 statistically significant linear relationships (R2 ≥ 0.5) with one or more DBP classes or species were established. Trihalomethanes (THMs) and haloacetic acids (HAAs), as key regulated classes, were extensively investigated and exhibited strong, recurrent relationships with ubiquitous humic/fulvic-like FDOM components, highlighting their potential as surrogates for carbonaceous DBP formation. Conversely, observed relationships between nitrogenous DBP classes, such as haloacetonitriles (HANs), halonitromethanes (HNMs), and N-nitrosamines (NAs), and PARAFAC fluorophores were more ambiguous, but preferential relationships with protein-like components in the case of algal/microbial FDOM sources were noted. This review highlights the challenges of transposing site-specific or FDOM source-specific empirical relationships between PARAFAC component and DBP formation potential to a global model.
Open Access
Global approximation of self-optimizing controlled variables with average loss minimization
(American Chemical Society, 2015-11-23) Ye, Lingjian; Cao, Yi; Yuan, Xiaofeng
Self-optimizing control (SOC) constitutes an important class of control strategies for real-time optimization (RTO) of chemical plants, by means of selecting appropriate controlled variables (CVs). Within the scope of SOC, this paper develops a CV selection methodology for a global solution which aims to minimise the average economic loss across the entire operation space. A major characteristic making the new scheme different from existing ones is that each uncertain scenario is independently considered in the new solution without relying on a linearised model, which was necessary in existing local SOC methods. Although global CV selection has been formulated as a nonlinear programming (NLP) problem, a tractable numerical algorithm for a rigorous solution is not available. In this work, a number of measures are introduced to ease the challenge. Firstly, we suggest to represent the economic loss as a quadratic function against the controlled variables through Taylor expansion, such that the average loss becomes an explicit function of the CV combination matrix, a direct optimizing algorithm is proposed to approximately minimize the global average loss. Furthermore, an analytic solution is derived for a suboptimal but much more simplified problem by treating the Hessian of the cost function over the entire operating space as a constant. This approach is found very similar to one of existing local methods, except that a matrix involved in the new solution is constructed from global operating data instead of using a local linear model. The proposed methodologies are applied to three simulated examples, where the effectiveness of proposed algorithms are demonstrated.
Open Access
Graphene-like dispersion and strong optical absorption in two-dimensional RP-type Sr3Ti2S7 perovskite
(American Chemical Society, 2023-11-15) Liu, Hairui; Gao, Rui; Yang, Jien; Banthia, Rohan Dinesh; Yang, Feng; Wang, Tianxing; Upadhyaya, Hari; Jain, Sagar M.
Two-dimensional (2D) Ruddlesden–Popper (RP) perovskite alloys have recently become attractive due to many desired physical properties originating from distinct van der Waals-type layered structures. In this work, a novel 2D RP-type Sr3Ti2S7 perovskite material design is proposed by using first-principles calculations. Our results reveal that the 2D Sr3Ti2S7 perovskite possesses dynamically stable structures, direct band structures with a band gap value of 0.86 eV, and a smaller effective mass (0.15/0.25 m0 for electron/hole) than MAPbI3 and phosphorene. More importantly, 2D Sr3Ti2S7 possesses wide optical spectra (from infrared-to ultraviolet-light region) and a higher absorption coefficient (105 cm–1) than MAPbI3, silicon, and MoS2 in the visible-light region. Interestingly, we also find that the ideal Dirac-like linear dispersion can appear near the Fermi level in the electronic band structures when compressive strain is applied. Especially, the Dirac-cone-like band structures can be realized when compressive strain is enhanced to −6%, indicating ultrahigh carrier mobility. These properties make the 2D Sr3Ti2S7 perovskite a promising candidate for future applications in solar cells and optoelectronic devices.
Open Access
High-throughput screening of sulfur-resistant catalysts for steam methane reforming using machine learning and microkinetic modeling
(American Chemical Society, 2024-02-28) Wang, Siqi; Saravan, Satya; Kasarapu, Kumar; Clough, Peter T.
The catalytic activity of bimetallic catalysts for the steam methane reforming (SMR) reaction was extensively studied previously. However, the performance of these materials in the presence of sulfur-containing species is yet to be investigated. In this study, we propose a novel process aided by machine learning (ML) and microkinetic modeling for the rapid screening of sulfur-resistant bimetallic catalysts. First, various ML models were developed to predict atomic adsorption energies (C, H, O, and S) on bimetallic surfaces. Easily accessible physical and chemical properties of the metals and adsorbates were used as input features. The Ensemble learning, artificial neural network, and support vector regression models achieved the best performance with R2 values of 0.74, 0.71, and 0.70, respectively. A microkinetic model was then built based on the elementary steps of the SMR reaction. Finally, the microkinetic model, together with the atomic adsorption energies predicted by the Ensemble model, were used to screen over 500 bimetallic materials. Four Ge-based alloys (Ge3Cu1, Ge3Ni1, Ge3Co1, and Ge3Fe1) and the Ni3Cu1 alloy were identified as promising and cost-effective sulfur-resistant catalysts.