Search results for: Carbon trading price

Authors: Zane Turner, Kevin Labille, Susan Gauch

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Sentiment analysis is a broad and expanding field that aims to extract and classify opinions from textual data. Lexicon-based approaches are based on the use of a sentiment lexicon, i.e., a list of words each mapped to a sentiment score, to rate the sentiment of a text chunk. Our work focuses on predicting stock price change using a sentiment lexicon built from financial conference call logs. We introduce a method to generate a sentiment lexicon based upon an existing probabilistic approach. By using a domain-specific lexicon, we outperform traditional techniques and demonstrate that domain-specific sentiment lexicons provide higher accuracy than generic sentiment lexicons when predicting stock price change.

Keywords: computational finance, sentiment analysis, sentiment lexicon, stock movement prediction

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Authors: Amir Bahrami

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In the fields of chemical graph theory, molecular topology, and mathematical chemistry, a topological index or a descriptor index also known as a connectivity index is a type of a molecular descriptor that is calculated based on the molecular graph of a chemical compound. Topological indices are numerical parameters of a graph which characterize its topology and are usually graph invariant. Topological indices are used for example in the development of quantitative structure-activity relationships (QSARs) in which the biological activity or other properties of molecules are correlated with their chemical structure. In this paper some descriptor index (descriptor index) of single-walled carbon nanotubes, is determined.

Keywords: chemical graph theory, molecular topology, molecular descriptor, single-walled carbon nanotubes

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Authors: Carlos Tapia Cortez, Serkan Saydam, Jeff Coulton, Claude Sammut

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Strategic mineral commodities (SMC) both energetic and metals have long been fundamental for human beings. There is a strong and long-run relation between the mineral resources industry and society's evolution, with the provision of primary raw materials, becoming one of the most significant drivers of economic growth. Due to mineral resources’ relevance for the entire economy and society, an understanding of the SMC market behaviour to simulate price fluctuations has become crucial for governments and firms. For any human activity, SMC price fluctuations are affected by economic, geopolitical, environmental, technological and psychological issues, where cognition has a major role. Cognition is defined as the capacity to store information in memory, processing and decision making for problem-solving or human adaptation. Thus, it has a significant role in those systems that exhibit dynamic equilibrium through time, such as economic growth. Cognition allows not only understanding past behaviours and trends in SCM markets but also supports future expectations of demand/supply levels and prices, although speculations are unavoidable. Technological developments may also be defined as a cognitive system. Since the Industrial Revolution, technological developments have had a significant influence on SMC production costs and prices, likewise allowing co-integration between commodities and market locations. It suggests a close relation between structural breaks, technology and prices evolution. SCM prices forecasting have been commonly addressed by econometrics and Gaussian-probabilistic models. Econometrics models may incorporate the relationship between variables; however, they are statics that leads to an incomplete approach of prices evolution through time. Gaussian-probabilistic models may evolve through time; however, price fluctuations are addressed by the assumption of random behaviour and normal distribution which seems to be far from the real behaviour of both market and prices. Random fluctuation ignores the evolution of market events and the technical and temporal relation between variables, giving the illusion of controlled future events. Normal distribution underestimates price fluctuations by using restricted ranges, curtailing decisions making into a pre-established space. A proper understanding of SMC's price dynamics taking into account the historical-cognitive relation between economic, technological and psychological factors over time is fundamental in attempting to simulate prices. The aim of this paper is to discuss the SMC market cognition hypothesis and empirically demonstrate its dynamic-cognitive capacity. Three of the largest and traded SMC's: oil, copper and gold, will be assessed to examine the economic, technological and psychological cognition respectively.

Keywords: commodity price simulation, commodity price uncertainties, dynamic-cognition, dynamic systems

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Authors: Papali Maqalika

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Lesotho farmers produce significant quantities of Merino wool of a quality competitive on the global market and make a substantial impact on the economy of Lesotho. However, even with the economic contribution, the production and quality information and trends of this fibre has been recognised nor documented. This is a sombre shortcoming as Lesotho wool is unknown on international markets. The situation is worsened by the fact that Lesotho wool is auction together with South African wool, trading and benchmarking Lesotho wool are difficult not to mention attempts to advance its production and quality. Based on the information above, available data on Lesotho wool for 10 years were collected and analysed for trends to used in benchmarking where applicable. The fibre properties analysed include fibre diameter (fineness), vegetable matter and yield, application and price. These were selected because they are fundamental in determining fibre quality and price. Production of wool in Lesotho has increased slightly over the ten years covered by this study. It also became apparent that production and quality trends of Lesotho wool are greatly influenced by the farming practices, breed of sheep and climatic conditions. Greater adoption of the merino sheep breed, sheds/barns and sheep coats are suggested as ways to reduce mortality rate (due to extremely cold temperatures), to reduce the vegetable matter on the fibre thus improving the quality and increase yield per sheep and production as a whole. Some farming practices such as the lack of barns, supplementary feeding and veterinary care present constraints in wool production. The districts in the Highlands region were found to have the highest production of mostly wool, this being ascribed to better pastures, climatic, social and other conditions conducive to wool production. The production of Lesotho wool and its quality can be improved further, possibly because of the interventions the Ministry of Agriculture introduced through the Small Agricultural and Development Project (SADP) and other appropriate initiatives by the National Wool and Mohair Growers Association (NWMGA). The challenge however, remains the lack of direct involvement of the wool growers (farmers) in decisions making and policy development, this potentially influences and may lead to the reluctance to adopt the strategies. In some cases, the wool growers do not receive the benefits associated with the interventions immediately. Based on these discoveries; it is recommended that the relevant educators and researchers in wool and textile science, as well as the local wool farmers in Lesotho, be represented in policy and other decision making forums relating to these interventions. In this way, educational campaigns and training workshops will be demand driven with a better chance of adoption and success. This is because the direct beneficiaries will have been involved at inception and they will have a sense of ownership as well as intent to see them through successfully.

Keywords: lesotho wool, wool quality, wool production, lesotho economy, global market, apparel wool, database, textile science, exports, animal farming practices, intimate apparel, interventions

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Authors: Victoria Masi Haruna Karatu, Nik Kamariah Nikmat

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In recent times awareness about the environment and green purchase has been on the increase across nations due to global warming. Previous researchers have attempted to determine what actually influences the purchase intention of consumers in this environmentally conscious epoch. The consumers too have become conscious of what to buy and who to buy from in their purchasing decisions as this action will reflect their concern about the environment and their personal well-being. This trend is a widespread phenomenon in most developed countries of the world. On the contrary evidence revealed that only 5% of the populations of Nigeria involve in green purchase activities thus making the country lag behind its counterparts in green practices. This is not a surprise as Nigeria is facing problems of inadequate green knowledge, non-enforcement of environmental regulations, sensitivity to the price of green products when compared with the conventional ones and distrust towards green products which has been deduced from prior studies of other regions. The main objectives of this study is to examine the direct antecedents of green purchase intention (green availability, government regulations, perceived green knowledge, perceived value and green price sensitivity) in Nigeria and secondly to establish the mediating role of perceived behavioral control on the relationship between these antecedents and green purchase intention. The study adopts quantitative method whereby 700 questionnaires were administered to lecturers in three Nigerian universities. 502 datasets were collected which represents 72 percent response rate. After screening the data only 440 were usable and analyzed using structural equation modeling (SEM) and bootstrapping. From the findings, three antecedents have significant direct relationships with green purchase intention (perceived green knowledge, perceived behavioral control, and green availability) while two antecedents have positive and significant direct relationship with perceived behavioral control (perceived value and green price sensitivity). On the other hand, PBC does not mediate any of the paths from the predictors to criterion variable. This result is discussed in the Nigerian context.

Keywords: Green Availability, Green Price Sensitivity, Green Purchase Intention, Perceived Green Knowledge, Perceived Value

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Authors: M. Deyab, A. Al-Sabagh, S. Keera

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The effects of flow velocity, sand concentration, sand size and temperature on erosion-corrosion of carbon steel in oil sands slurry were studied by electrochemical polarization measurements. It was found that the anodic excursion spans of carbon steel in oil sands slurry are characterized by the occurrence of a well-defined anodic peak, followed by a passive region. The data reveal that increasing flow velocity, sand concentration and temperature enhances the anodic peak current density (jAP) and shifts pitting potential (Epit) towards more negative values. The variation of sand particle size does not have apparent effect on polarization behavior of carbon steel. The ratios of the erosion rate to corrosion rate (E/C) were calculated and discussed. The ratio of erosion to corrosion rates E/C increased with increasing the flow velocity, sand concentration, sand size and temperature indicating that an increasing slurry flow velocity, sand concentration, sand size and temperature resulted in an enhancement of the erosion effect.

Keywords: erosion-corrosion, steel, oil sands slurry, polarization

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Authors: Nuray Uçar, Mervin Ölmez, Özge Alptoğa, Nilgün K. Yavuz, Ayşen Önen

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In recent years, research on continuous graphene oxide fibers has been intensified. Therefore, many factors of production stages are being studied. In this study, the effect of exfoliation time and presence of activated carbon particle (ACP) on graphene oxide fiber’s properties has been analyzed. It has been seen that cross-sectional appearance of sample with ACP is harsh and porous because of ACP. The addition of ACP did not change the electrical conductivity. However, ACP results in an enormous decrease of mechanical properties. Longer exfoliation time results to higher crystallinity degree, C/O ratio and less d space between layers. The breaking strength and electrical conductivity of sample with less exfoliation time is some higher than sample with high exfoliation time.

Keywords: activated carbon, coagulation by wet spinning, exfoliation, graphene oxide fiber

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Authors: Marlen Acosta Alamo, Lisa Manne, Richard Veit

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Habitat loss due to land use change is one of the leading causes of biodiversity loss worldwide. This form of habitat loss is a non-random phenomenon since the same environmental factors that make an area suitable for supporting high local biodiversity overlap with those that make it attractive for urban development. We aimed to compare the effect of two non-random habitat loss predictors on the richness, abundance, and rarity of nature-affiliated and human-affiliated North American breeding birds. For each group of birds, we simulated the non-random habitat loss using two predictors: the House Price Index as a measure of the attractiveness of an area for humans and the Normalized Difference Vegetation Index as a proxy for primary productivity. We compared the results of the two non-random simulation sets and one set of random habitat loss simulations using an analysis of variance and followed up with a Tukey-Kramer test when appropriate. The attractiveness of an area for humans predicted estimates of richness loss and increase of rarity higher than primary productivity and random habitat loss for nature-affiliated and human-affiliated birds. For example, at 50% of habitat loss, the attractiveness of an area for humans produced estimates of richness at least 5% lower and of a rarity at least 40% higher than primary productivity and random habitat loss for both groups of birds. Only for the species abundance of nature-affiliated birds, the attractiveness of an area for humans did not outperform primary productivity as a predictor of biodiversity following habitat loss. We demonstrated the value of the House Price Index, which can be used in conservation assessments as an index of the risks of habitat loss for natural communities. Thus, our results have relevant implications for sustainable urban land-use planning practices and can guide stakeholders and developers in their efforts to conserve local biodiversity.

Keywords: biodiversity loss, bird biodiversity, house price index, non-random habitat loss

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Authors: Princess Stephanie P. Llanos, Rinlee Butch M. Cervera

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Lithium iron phosphate (LiFePO4) is a potential cathode material for lithium-ion batteries due to its promising characteristics. In this study, carbon-coated nanograined LiFePO4 is synthesized via wet chemistry method at a low temperature of 400 °C and investigated its performance as a cathode in Lithium battery. The X-ray diffraction pattern of the synthesized samples can be indexed to an orthorhombic LiFePO4 structure. Agglomerated particles that range from 200 nm to 300 nm are observed from scanning electron microscopy images. Transmission electron microscopy images confirm the crystalline structure of LiFePO4 and coating of amorphous carbon layer. Elemental mapping using Energy dispersive spectroscopy analysis revealed the homogeneous dispersion of Fe, P, O, and C elements. On the other hand, the electrochemical performances of the synthesized cathodes were investigated using cyclic voltammetry, galvanostatic charge/discharge tests with different C-rates, and cycling performances. Galvanostatic charge and discharge measurements revealed that the sample sintered at 400 °C for 3 hours with carbon coating demonstrated the highest capacity among the samples which reaches up to 160 mAhg⁻¹ at 0.1C rate.

Keywords: cathode, charge-discharge, electrochemical, lithium batteries

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Authors: Carlson Murray, Ali Lazrak

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Robust experimental evidence of systematic violations of expected utility (EU) establishes that individuals facing risk overweight utility from low probability gains and losses when making choices. These findings motivated development of models of preferences with probability weighting functions, such as rank dependent utility (RDU). We solve for the optimal investing strategy of an RDU investor in a dynamic binomial setting from which we derive implications for investing behavior. We show that relative to EU investors with constant relative risk aversion, commonly measured probability weighting functions produce optimal RDU terminal wealth with significant downside protection and upside exposure. We additionally find that in contrast to EU investors, RDU investors optimally choose a portfolio that contains fair bets that provide payo↵s that can be interpreted as lottery outcomes or exposure to idiosyncratic returns. In a calibrated version of the model, we calculate that RDU investors would be willing to pay 5% of their initial wealth for the freedom to trade away from an optimal EU wealth allocation. The dynamic trading strategy that supports the optimal wealth allocation implies portfolio weights that are independent of initial wealth but requires higher risky share after good stock return histories. Optimal trading also implies the possibility of non-participation when historical returns are poor. Our model fills a gap in the literature by providing new quantitative and qualitative predictions that can be tested experimentally or using data on household wealth and portfolio choice.

Keywords: behavioral finance, probability weighting, portfolio choice

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Authors: F. Ahwide, Y. Aldali

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This article presents a current and future energy situation in Libya. The electric power efficiency and operating hours in power plants are evaluated from 2005 to 2010. Carbon dioxide emissions in most of power plants are estimated. In 2005, the efficiency of steam power plants achieved a range of 20% to 28%. While, the gas turbine power plants efficiency ranged between 9% and 25%, this can be considered as low efficiency. However, the efficiency improvement has clearly observed in some power plants from 2008 to 2010, especially in the power plant of North Benghazi and west Tripoli. In fact, these power plants have modified to combine cycle. The efficiency of North Benghazi power plant has increased from 25% to 46.6%, while in Tripoli it is increased from 22% to 34%. On the other hand, the efficiency improvement is not observed in the gas turbine power plants. When compared to the quantity of fuel used, the carbon dioxide emissions resulting from electricity generation plants were very high. Finally, an estimation of the energy demand has been done to the maximum load and the annual load factor (i.e., the ratio between the output power and installed power).

Keywords: power plant, efficiency improvement, carbon dioxide emissions, energy situation in Libya

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Authors: Maria Fonseca, Ana Branco, Joao Graca, Rui Mendes, Pedro Mimoso

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The present work is focused on the production of a carbon composite element for cycling through different techniques, namely, blow-molding and high-pressure resin transfer injection (HP-RTM). The main objective of this work is to compare both processes to produce carbon composite elements for the cycling industry. It is well known that the carbon composite components for cycling are produced mainly through blow-molding; however, this technique depends strongly on manual labour, resulting in a time-consuming production process. Comparatively, HP-RTM offers a more automated process which should lead to higher production rates. Nevertheless, a comparison of the elements produced through both techniques must be done, in order to assess if the final products comply with the required standards of the industry. The main difference between said techniques lies in the used material. Blow-moulding uses carbon prepreg (carbon fibres pre-impregnated with a resin system), and the material is laid up by hand, piece by piece, on a mould or on a hard male. After that, the material is cured at a high temperature. On the other hand, in the HP-RTM technique, dry carbon fibres are placed on a mould, and then resin is injected at high pressure. After some research regarding the best material systems (prepregs and braids) and suppliers, an element was designed (similar to a handlebar) to be constructed. The next step was to perform FEM simulations in order to determine what the best layup of the composite material was. The simulations were done for the prepreg material, and the obtained layup was transposed to the braids. The selected material was a prepreg with T700 carbon fibre (24K) and an epoxy resin system, for the blow-molding technique. For HP-RTM, carbon fibre elastic UD tubes and ± 45º braids were used, with both 3K and 6K filaments per tow, and the resin system was an epoxy as well. After the simulations for the prepreg material, the optimized layup was: [45°, -45°,45°, -45°,0°,0°]. For HP-RTM, the transposed layup was [ ± 45° (6k); 0° (6k); partial ± 45° (6k); partial ± 45° (6k); ± 45° (3k); ± 45° (3k)]. The mechanical tests showed that both elements can withstand the maximum load (in this case, 1000 N); however, the one produced through blow-molding can support higher loads (≈1300N against 1100N from HP-RTM). In what concerns to the fibre volume fraction (FVF), the HP-RTM element has a slightly higher value ( > 61% compared to 59% of the blow-molding technique). The optical microscopy has shown that both elements have a low void content. In conclusion, the elements produced using HP-RTM can compare to the ones produced through blow-molding, both in mechanical testing and in the visual aspect. Nevertheless, there is still space for improvement in the HP-RTM elements since the layup of the braids, and UD tubes could be optimized.

Keywords: HP-RTM, carbon composites, cycling, FEM

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Authors: Charmaine Lamiel, Van Hoa Nguyen, Marjorie Baynosa, Jae-Jin Shim

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Electrochemical supercapacitors have attracted considerable attention because of their high potential as an efficient energy storage system. The combination of carbon-based material and transition metal oxides/sulfides are studied because they have long and improved cycle life as well as high energy and power densities. In this study, a hierarchical mesoporous carbon sphere/nickel cobalt sulfide (CS/Ni-Co-S) core/shell structure was synthesized using a facile hydrothermal method without any further sulfurization or post-heat treatment. The CS/Ni-Co-S core/shell microstructures exhibited a high capacitance of 724 F g−1 at 2 A g−1 in a 6 M KOH electrolyte. After 2000 charge-discharge cycles, it retained 86.1% of its original capacitance, with high Coulombic efficiency of 97.9%. The electrode exhibited a high energy density of 58.0 Wh kg−1 at an energy density of 1440 W kg−1, and high power density of 7200 W kg−1 at an energy density of 34.2 Wh kg−1. The successful synthesis was considered to be simple and cost-effective which supports the viability of this composite as an alternative activated material for high performance supercapacitors.

Keywords: carbon sphere, electrochemical, hydrothermal, nickel cobalt sulfide, supercapacitor

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Authors: K. Domagala, D. Kata, T. Graule

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Diseases caused by contaminated drinking water are the worldwide problem, which leads to the death and severe illnesses for hundreds of millions million people each year. There is an urgent need for efficient water treatment techniques for virus pathogens removal. The aim of the research was to develop safe and economic solution, which help with the water treatment. In this study, the synthesis of copper-based multi-walled carbon nanotube composites is described. Proposed solution utilize combination of a low-cost material with a high active surface area and copper antiviral properties. Removal of viruses from water was possible by adsorption based on electrostatic interactions of negatively charged virus with a positively charged filter material.

Keywords: multi walled carbon nanotubes, water purification, virus removal, water treatment

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Authors: ChoLiang Chung, YuMin Chen

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C-doped TiO2 nanofibers were prepared by electrospinning successfully. Different amounts of carbon were added into the nanofibers by using chitosan, aiming to shift the wave length that is required to excite the photocatalyst from ultraviolet light to visible light. Different amounts of carbon and different atmosphere fibers were calcined at 500oC, and the optical characteristic of C-doped TiO2 nanofibers had been changed. characterizes of nanofibers were identified by X-Ray Diffraction (XRD), Field Emission Scanning Electron Microscope (FE-SEM), UV-vis, Atomic Force Microscope (AFM), and Fourier Transform Infrared Spectroscopy (FTIR). The XRD is used to identify the phase composition of nanofibers. The morphology of nanofibers were explored by FE-SEM and AFM. Optical characteristics of absorption were measured by UV-Vis. Three dimension surface images of C-doped TiO2 nanofibers revealed different effects of processing. The results of XRD showed that the phase of C-doped TiO2 nanofibers transformed to rutile phase and anatase phase successfully. The results of AFM showed that the surface morphology of nanofibers became smooth after high temperature treatment. Images from FE-SEM revealed the average size of nanofibers. UV-vis results showed that the band-gap of TiO2 were reduced. Finally, we found out C-doped TiO2 nanofibers can change countenance of nanofiber and make it smoother.

Keywords: carbon, TiO2, chitosan, electrospinning

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Authors: Illyas Md Isa, Sharifah Norain Mohd Sharif, Norhayati Hashima

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A mercury(II) sensor was developed by using multi-walled carbon nanotubes (MWCNTs) paste electrode modified with Zn/Al layered double hydroxide-3(4-methoxyphenyl)propionate nanocomposite (Zn/Al-HMPP). The optimum conditions by cyclic voltammetry were observed at electrode composition 2.5% (w/w) of Zn/Al-HMPP/MWCNTs, 0.4 M potassium chloride, pH 4.0, and scan rate of 100 mVs-1. The sensor exhibited wide linear range from 1x10-3 M to 1x10-7 M Hg2+ and 1x10-7 M to 1x10-9 M Hg2+, with a detection limit of 1x10-10 M Hg2+. The high sensitivity of the proposed electrode towards Hg(II) was confirmed by double potential-step chronocoulometry which indicated these values; diffusion coefficient 1.5445 x 10-9 cm2 s-1, surface charge 524.5 µC s-½ and surface coverage 4.41 x 10-2 mol cm-2. The presence of 25-fold concentration of most metal ions had no influence on the anodic peak current. With characteristics such as high sensitivity, selectivity and repeatability the electrode was then proposed as the appropriate alternative for the determination of mercury(II).

Keywords: cyclic voltammetry, mercury(II), modified carbon paste electrode, nanocomposite

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Authors: Robert Kwame Kpaliba, Dennis Kpakpor Adotey, Yaw Serfor-Armah

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Increase in the oceanic carbon dioxide absorbance from the atmosphere due to climate change has led to appreciable change in the chemistry of the oceans. The change in oceanic pH referred to as ocean acidification poses multiple threats and stresses on marine species, biodiversity, goods and services, and livelihoods. Marine ecosystems are continuously threatened by plethora of natural and anthropogenic stressors including carbon dioxide (CO₂) emissions causing a lot of changes which has not been experienced for approximately 60 years. Little has been done in Africa as a whole and Ghana in particular to improve the understanding of the variations of the carbonate chemistry of seawater and the biophysical impacts of ocean acidification on security of seafood, nutrition, climate and environmental change. There is, therefore, the need for regular monitoring of carbonate chemistry of seawater along Ghana’s coastline to generate reliable data to aid marine policy formulation. Samples of seawater were collected thrice every month for a one-year period from five study sites for the various parameters to be analyzed. Analysis of the measured physico-chemical and the carbonate chemistry parameters was done using simple statistics. Correlation test and ANOVA were run on both of the physico-chemical and carbonate chemistry parameters. The carbonate chemistry parameters were measured using computer software programme (CO₂cal v4.0.9) except total alkalinity and pH. The study assessed the variability of seawater carbonate chemistry in selected portions of the Central Atlantic Coastline of Ghana (Tsokomey/Bortianor, Kokrobitey, Gomoa Nyanyanor, Gomoa Fetteh, and Senya Breku landing beaches) over a 1-year period (June 2016–May 2017). For physico-chemical parameters, there was insignificant variation in nitrate (NO₃⁻) (1.62 - 2.3 mg/L), ammonia (NH₃) (1.52 - 2.05 mg/L), and salinity (sal) (34.50 - 34.74 ppt). Carbonate chemistry parameters for all the five study sites showed significant variation: partial pressure of carbon dioxide (pCO₂) (414.08-715.5 µmol/kg), carbonate ion (CO₃²⁻) (115-157.92 µmol/kg), pH (7.9-8.12), total alkalinity (TA) (1711.8-1986 µmol/kg), total carbon dioxide (TCO₂) (1512.1 - 1792 µmol/kg), dissolved carbon dioxide (CO₂aq) (10.97-18.92 µmol/kg), Revelle Factor (RF) (9.62-11.84), aragonite (ΩAr) (0.75-1.48) and calcite (ΩCa) (1.08-2.14). The study revealed that the partial pressure of carbon dioxide and temperature did not have a significant effect on each other (r² = 0.31) (p-value = 0.0717). There was an appreciable effect of pH on dissolved carbon dioxide (r² = 0.921) (p-value = 0.0000). The variation between total alkalinity and dissolved carbon dioxide was appreciable (r² = 0.731) (p-value = 0.0008). There was a significant correlation between total carbon dioxide and dissolved carbon dioxide (r² = 0.852) (p-value = 0.0000). Revelle factor correlated strongly with dissolved carbon dioxide (r² = 0.982) (p-value = 0.0000). Partial pressure of carbon dioxide corresponds strongly with atmospheric carbon dioxide (r² = 0.9999) (p-value = 0.00000).

Keywords: carbonate chemistry, seawater, central atlantic coastline, Ghana, ocean acidification

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Authors: Dang HuynhMinhTam, Kuang-Cong Lu, Yi-Hung Chen, Zhung-Yu Lin, Cheng-Siang Cheng

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Carbon capture, utilization, and storage (CCUS) technology become a predominant technique to mitigate carbon dioxide and achieve net-zero emissions goals. This research targets to continuously capture the low concentration CO₂ from the tail gas of the regenerative thermal oxidizer (RTO) in the high technology industry. A rotating packed bed (RPB) reactor is investigated to capture the efficiency of CO₂ using a mixture of NaOH/Na₂CO₃ solutions to simulate the real absorbed solution. On a lab scale, semi-batch experiments of continuous gas flow and circulating absorbent solution are conducted to find the optimal parameters and are then examined in a continuous operation. In the semi-batch tests, the carbon capture efficiency and pH variation in the conditions of a low concentration CO₂ (about 1.13 vol%), the NaOH concentration of 1 wt% or 2 wt% mixed with 14 wt% Na₂CO₃, the rotating speed (600, 900, 1200 rpm), the gas-liquid ratio (100, 200, and 400), and the temperature of absorbent solution of 40 ºC are studied. The CO₂ capture efficiency significantly increases with higher rotating speed and smaller gas-liquid ratio, respectively, while the difference between the NaOH concentration of 1 wt% and 2 wt% is relatively small. The maximum capture efficiency is close to 80% in the conditions of the NaOH concentration of 1 wt%, the G/L ratio of 100, and the rotating speed of 1200 rpm within the first 5 minutes. Furthermore, the continuous operation based on similar conditions also demonstrates the steady efficiency of the carbon capture of around 80%.

Keywords: carbon dioxide capture, regenerative thermal oxidizer, rotating packed bed, sodium hydroxide

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Authors: Alexander Rodríguez-Hernández, Arnulfo Rojas-Perez, Liz Diaz-Vazquez

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The rise in consumerism over the past century has resulted in the creation of higher amounts of plasticizers, personal care products and other chemical substances, which enter and accumulate in water systems. Other sources of pollutants in Neotropical regions experience large inputs of nutrients with these pollutants resulting in eutrophication of water which consume large quantities of oxygen, resulting in high fish mortality. This dilemma has created a need for the development of targeted detection in complex matrices and remediation of emerging contaminants. We have synthesized carbon nanoparticles from macro algae (Ulva fasciata) by oxidizing the graphitic carbon network under extreme acidic conditions. The resulting material was characterized by STEM, yielding a spherical 12 nm average diameter nanoparticles, which can be fixed into a polysaccharide aerogel synthesized from the same macro algae. Spectrophotometer analyses show a pH dependent fluorescent behavior varying from 450-620 nm in aqueous media. Heavily oxidized edges provide for easy functionalization with enzymes for a more targeted analysis and remediation technique. Given the optical properties of the carbon base nanoparticles and the numerous possibilities of functionalization, we have developed a selective and robust targeted bio-detection and bioremediation technique for the treatment of emerging contaminants in complex matrices like estuarine embayment.

Keywords: aerogels, carbon nanoparticles, fluorescent, targeted analysis

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Authors: A. González-Caro, A. M. Merino-Lechuga, D. Suescum-Morales, E. Fernández-Ledesma, J. R. Jiménez, J. M. Fernández-Rodríguez

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Climate change is one of the most significant issues today. Since the 19th century, the rise in temperature has not only been due to natural change, but also to human activities, which have been the main cause of climate change, mainly due to the burning of fossil fuels such as coal, oil and gas. The boom in the construction sector in recent years is also one of the main contributors to CO₂ emissions into the atmosphere; for example, for every tonne of cement produced, 1 tonne of CO₂ is emitted into the atmosphere. Most of the research being carried out in this sector is focused on reducing the large environmental impact generated during the manufacturing process of building materials. In detail, this research focuses on the recovery of waste from olive oil mills. Spain is the world's largest producer of olive oil, and this sector generates a large amount of waste and by-products such as olive pits, “alpechín” or “alpeorujo”. This olive stone by means of a pyrosilisis process gives rise to the production of active carbon. The process causes the carbon to develop many internal spaces. This study is based on the manufacture of porous mortars with Portland cement and natural limestone sand, with an addition of 5% and 10% of activated carbon. Two curing environments were used: i) dry chamber, with a humidity of 65 ± 10% and temperature of 21 ± 2 ºC and an atmospheric CO₂ concentration (approximately 0.04%); ii) accelerated carbonation chamber, with a humidity of 65 ± 10% and temperature of 21 ± 2 ºC and an atmospheric CO₂ concentration of 5%. In addition to eliminating waste from an industry, the aim of this study is to reduce atmospheric CO₂. For this purpose, first, a physicochemical and mineralogical characterisation of all raw materials was carried out, using techniques such as fluorescence and X-ray diffraction. The particle size and specific surface area of the activated carbon were determined. Subsequently, tests were carried out on the hardened mortar, such as thermogravimetric analysis (to determine the percentage of CO₂ capture), as well as mechanical properties, density, porosity, and water absorption. It was concluded that the activated carbon acts as a sink for CO₂, causing it to be trapped inside the voids. This increases CO₂ capture by 300% with the addition of 10% activated carbon at 7 days of curing. There was an increase in compressive strength of 17.5% with the CO₂ chamber after 7 days of curing using 10% activated carbon compared to the dry chamber.

Keywords: olive stone, activated carbon, porous mortar, CO₂ capture, economy circular

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Authors: Illyas Md Isa, Sharifah Norain Mohd Sharif, Norhayati Hashim

Abstract:

A mercury(II) sensor was developed by using multi-walled carbon nano tubes (MWCNTs) paste electrode modified with Zn/Al layered double hydroxide-3(4-methoxyphenyl) propionate nano composite (Zn/Al-HMPP). The optimum conditions by cyclic voltammetry were observed at electrode composition 2.5% (w/w) of Zn/Al-HMPP/MWCNTs, 0.4 M potassium chloride, pH 4.0, and scan rate of 100 mVs-1. The sensor exhibited wide linear range from 1x10-3 M to 1x10-7 M Hg2+ and 1x10-7 M to 1x10-9 M Hg2+, with a detection limit of 1 x 10-10 M Hg2+. The high sensitivity of the proposed electrode towards Hg(II) was confirmed by double potential-step chronocoulometry which indicated these values; diffusion coefficient 1.5445 x 10-9 cm2 s-1, surface charge 524.5 µC s-½ and surface coverage 4.41 x 10-2 mol cm-2. The presence of 25-fold concentration of most metal ions had no influence on the anodic peak current. With characteristics such as high sensitivity, selectivity and repeatability the electrode was then proposed as the appropriate alternative for the determination of mercury.

Keywords: Cyclic voltammetry, Mercury(II), Modified carbon paste electrode, Nanocomposite

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Authors: Fahim Ullah, Muhammad Usman

Abstract:

Energy consumption and environmental sustainability are hard challenges of 21st century. Energy richness increases environmental pollution while energy poverty hinders economic growth. Considering these two aspects, present study calculates energy deficiency and examines the role of renewable energy to overcome rising energy deficiency and carbon emission for selected countries from 1990 to 2021. For empirical analysis, this study uses methods of moments panel quantile regression analysis and to check the robustness, study used panel quantile robust analysis. Graphical analysis indicated rising global energy deficiency since last three decades where energy consumption is higher than energy production. Empirical results showed that renewable energy is a significant factor for reducing energy deficiency. Secondly, the energy deficiency increases carbon emission level and again renewable energy decreases emissions level. This study recommends that global energy deficiency and rising carbon emissions can be controlled through structural change in the form of energy transition to replace non-renewable resources with renewable resources.

Keywords: energy deficiency, renewable energy, carbon emission, energy trade, PQL analysis

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Authors: Sh. Minapoor, S. Ajeli, M. Javadi Toghchi

Abstract:

Non-crimp 3D orthogonal fabric composite is one of the textile-based composite materials that are rapidly developing light-weight engineering materials. The present paper focuses on geometric and micro mechanical modeling of non-crimp 3D orthogonal carbon fabric and composites reinforced with it for aerospace applications. In this research meso-finite element (FE) modeling employs for stress analysis in different load conditions. Since mechanical testing of expensive textile carbon composites with specific application isn't affordable, simulation composite in a virtual environment is a helpful way to investigate its mechanical properties in different conditions.

Keywords: woven composite, aerospace applications, finite element method, mechanical properties

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Authors: Yiying Xiao, Chia Wei Lim, Jinquan Chang, Qixin Yuan, Lei Wang, Ning Yan

Abstract:

Electrocatalytic reductive amination (ERA) offers an attractive way to make organonitrogen chemicals from renewable feedstock. Here, we report carbon nanotube (CNT) as an effective catalyst for the ERA of biomass-derivable α-keto acids into amino acids using NH₃ as the nitrogen source. Through a facile ball milling (BM) treatment, the intrinsic defects in the CNTs were increased while the electrocatalytic activity of CNTs converting 2-ketoglutaric acid into glutamic acid was enhanced by approximately seven times. A high Faradaic efficiency (FE) of ~90% with a corresponding glutamic acid formation rate up to 180.9 mmol•g⁻¹𝒸ₐₜt•h⁻¹ was achieved, and ~60% molar yield of glutamic acid was obtained after 8 h of electrolysis. Electrokinetic analyses indicate that the BM-CNTs catalysed ERA exhibits first-order dependences on the substrate and NH₃, with a rate-determining step (RDS) involving the first electron transfer. Following this protocol, a number of amino acids were prepared with moderate to high FEs and formation rates. Significantly, we synthesised long carbon chain amino acids, which typically face lower yields using the existing methods.

Keywords: amino acids, carbon nanotubes, electrocatalysis, reductive amination, α-keto acids

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Authors: Motonori Tamura

Abstract:

The hydrogen barrier properties of the coatings of diamond-like carbon (DLC) were evaluated. Using plasma chemical vapor deposition and sputtering, DLC coatings were deposited on Type 316L stainless steels. The hydrogen permeation rate was reduced to 1/1000 or lower by the DLC coatings. The DLC coatings with high hydrogen content had high hydrogen barrier function. For hydrogen diffusion in coatings, the movement of atoms through hydrogen trap sites such as pores in coatings, and crystal defects such as dislocations, is important. The DLC coatings are amorphous, and there are both sp3 and sp2 bonds, and excess hydrogen could be found in the interstitial space and the hydrogen trap sites. In the DLC coatings with high hydrogen content, these hydrogen trap sites are likely already filled with hydrogen atoms, and the movement of new hydrogen atoms could be limited.

Keywords: hydrogen permeation, stainless steels, diamond-like carbon, hydrogen trap sites

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Authors: Yongseok Hong, Kurt Louis Solis

Abstract:

In the present study, a hybrid sorbent using the metal organic framework (MOF), UiO-66, and powdered activated carbon (pAC) is synthesized to remove cationic and anionic metals simultaneously. UiO-66 is an octahedron-shaped MOF with a Zr₆O₄(OH)₄ metal node and 1,4-benzene dicarboxylic acid (BDC) organic linker. Zr-based MOFs are attractive for trace element remediation in wastewaters, because Zr is relatively non-toxic as compared to other classes of MOF and, therefore, it will not cause secondary pollution. Most remediation studies with UiO-66 target anions such as fluoride, but trace element oxyanions such as arsenic, selenium, and antimony have also been investigated. There have also been studies involving mercury removal by UiO-66 derivatives, however these require post-synthetic modifications or have lower effective surface areas. Activated carbon is known for being a readily available, well-studied, effective adsorbent for metal contaminants. Solvothermal method was employed to prepare hybrid sorbent from UiO66 and activated carbon, which could be used to remove mercury and selenium simultaneously. The hybrid sorbent was characterized using FSEM-EDS, FT-IR, XRD, and TGA. The results showed that UiO66 and activated carbon are successfully composited. From BET studies, the hybrid sorbent has a SBET of 1051 m² g⁻¹. Adsorption studies were performed, where the hybrid showed maximum adsorption of 204.63 mg g⁻¹ and 168 mg g⁻¹ for Hg (II) and selenite, respectively, and follows the Langmuir model for both species. Kinetics studies have revealed that the Hg uptake of the hybrid is pseudo-2nd order and has rate constant of 5.6E-05 g mg⁻¹ min⁻¹ and the selenite uptake follows the simplified Elovich model with α = 2.99 mg g⁻¹ min⁻¹, β = 0.032 g mg⁻¹.

Keywords: adsorption, flue gas wastewater, mercury, selenite, metal organic framework

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Authors: Sofia Stoica

Abstract:

In this paper, we use historical data to predict the stock price of a tech company. To this end, we use a dataset consisting of the stock prices in the past five years of ten major tech companies – Adobe, Amazon, Apple, Facebook, Google, Microsoft, Netflix, Oracle, Salesforce, and Tesla. We experimented with a variety of models– a linear regressor model, K nearest Neighbors (KNN), a sequential neural network – and algorithms - Multiplicative Weight Update, and AdaBoost. We found that the sequential neural network performed the best, with a testing error of 0.18%. Interestingly, the linear model performed the second best with a testing error of 0.73%. These results show that using historical data is enough to obtain high accuracies, and a simple algorithm like linear regression has a performance similar to more sophisticated models while taking less time and resources to implement.

Keywords: finance, machine learning, opening price, stock market

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Authors: Vahid Ramezankhani, Keith J. Stevenson, Stanislav. S. Fedotov

Abstract:

Lithium-ion batteries (LIBs) play a pivotal role in achieving the key objective “zero-carbon emission” as countries agreed to reach a 1.5ᵒC global warming target according to the Paris agreement. Nowadays, due to the tremendous mobile and stationary consumption of small/large-format LIBs, the demand and consequently the price for such energy storage devices have been raised. The aforementioned challenges originate from the shrinkage of the major applied critical materials in these batteries, such as cobalt (Co), nickel (Ni), Lithium (Li), graphite (G), and manganese (Mn). Therefore, it is imperative to consider alternative elements to address issues corresponding to the limitation of resources around the globe. Potassium (K) is considered an effective alternative to Li since K is a more abundant element, has a higher operating potential, a faster diffusion rate, and the lowest stokes radius in comparison to the closest neighbors in the periodic table (Li and Na). Among all reported materials for metal-ion batteries, some of them possess the general formula AMXO4L [A = Li, Na, K; M = Fe, Ti, V; X = P, S, Si; L= O, F, OH] is of potential to be applied both as anode and cathode and enable researchers to investigate them in the full symmetric battery format. KTiPO4F (KTP structural material) has been previously reported by our group as a promising cathode with decent electronic properties. Herein, we report a synthesis, crystal structure characterization, morphology, as well as K-ion storage properties of KTiPO4F. Our investigation reveals that KTiPO4F delivers discharge capacity > 150 mAh/g at 26.6 mA/g (C/5 current rate) in the potential window of 0.001-3 V. Surprisingly, the cycling performance of C-KTiPO4F//K cell is stable for 1000 cycles at 130 mA/g (C current rate), presenting capacity > 130 mAh/g. More interestingly, we achieved to assemble full symmetric batteries where carbon-coated KTiPO4F serves as both negative and positive electrodes, delivering >70 mAh/g in the potential range of 0.001-4.2V.

Keywords: anode material, potassium battery, chemical characterization, electrochemical properties

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Authors: Melody Wong

Abstract:

Taikoo Green Ribbon is the winning scheme of International Advancing Net Zero ANZ Ideas Competition 2021 and shortlisted as a finalist of top Architectural Award “AJ100 Sustainability Initiative of the Year, 2022, demonstrating city's aspirations to reach carbon neutrality by 2050. The project showcases total design solutions to blend technology and nature to create a futuristic workplace achieving net zero within a decade. The net zero building design featured with extremely low embodied carbon emission (<250 kgCO2/sqm), significant surplus in renewable energy generation (130% of energy consumption) and various carbon capture technology. The project leverages aesthetics, user-experience, sustainability, and technology to develop over 40 design features. Utilizing AI-controlled Smart Envelope system, the possibility of naturally ventilation was maximized to adjust the microclimate to foster behavourial change. The design principle – healthy and collaborative working environment is realized with a landscaped sky-track with kinetic energy pads, natural ventilated open space with edible plants across floors, and 500-seat open-space rooftop theatre to reshape and redefine the new generation of workplaces.

Keywords: NetZero, zero carbon, green, sustainability

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Authors: Krishang Surapaneni

Abstract:

The goal of this project is to determine how to predict important aspects of options, including the ask price. We want to compare different machine learning models to learn the best model and the best hyperparameters for that model for this purpose and data set. Option pricing is a relatively new field, and it can be very complicated and intimidating, especially to inexperienced people, so we want to create a machine learning model that can predict important aspects of an option stock, which can aid in future research. We tested multiple different models and experimented with hyperparameter tuning, trying to find some of the best parameters for a machine-learning model. We tested three different models: a Random Forest Regressor, a linear regressor, and an MLP (multi-layer perceptron) regressor. The most important feature in this experiment is the ask price; this is what we were trying to predict. In the field of stock pricing prediction, there is a large potential for error, so we are unable to determine the accuracy of the models based on if they predict the pricing perfectly. Due to this factor, we determined the accuracy of the model by finding the average percentage difference between the predicted and actual values. We tested the accuracy of the machine learning models by comparing the actual results in the testing data and the predictions made by the models. The linear regression model performed worst, with an average percentage error of 17.46%. The MLP regressor had an average percentage error of 11.45%, and the random forest regressor had an average percentage error of 7.42%

Keywords: finance, linear regression model, machine learning model, neural network, stock price

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