Journal of Smart Science and Technology

The Feasibility of Producing and Utilising Green Hydrogen as a Feedstock in Trinidad and Tobago

Mon, 31 Mar 2025 00:00:00 +0200

This study addresses Trinidad and Tobago's (T&T) heavy reliance on Grey Hydrogen from Steam Methane Reforming (SMR), contributing significantly to CO₂ emissions in the petrochemical sector. With rising hydrogen demand, especially for ammonia and methanol production, there is an imperative need to transition to green hydrogen. The study evaluates the economic feasibility of green hydrogen production in T&T, assesses the potential impact on CO₂ emissions, and analyses external factors such as subsidies, market dynamics, and the Carbon Border Adjustment Mechanism (CBAM). Findings indicate economic viability for green hydrogen under specific market conditions, significant CO₂ mitigation potential, and opportunities for T&T to establish a presence in the green hydrogen market. The impact of this transition could significantly reduce greenhouse gas (GHG) emissions, contributing to the nation's decarbonization targets under its Nationally Determined Contributions (NDCs) while enabling economic diversification.

Indoor Occupancy Detection Using Machine Learning and Environmental Sensors

Mon, 31 Mar 2025 00:00:00 +0200

Detecting the occupancy status of enclosed spaces has been immensely beneficial in the automated control of HVACs (heating, ventilation, and cooling systems), providing assistance to the elderly, healthcare provisioning, recognition of human activity, and others. As a result of these benefits, a plethora of machine learning-based solutions for occupancy detection has been developed in the literature. However, many of these solutions have poor prediction accuracies. Furthermore, it is necessary to develop models that are robust enough to achieve acceptable performance in situations where partial data from sensors are available. In this paper, we experimentally determined the Machine Learning (ML) models that are most robust for use in indoor occupancy detection. This is important because the activities of human subjects in an ML environment are capable of disrupting the data available to some deployed ML models, which might cause the performance of such models to drop. Hence, it is crucial to determine ML models that are robust against such disruptions. In this paper, three algorithms were developed: the first was for outlier removal from features, the second was for feature selection, and the third was for partial-features-availability-aware ML model selection. These algorithms were applied to data from environmental sensors such as temperature, humidity, carbon dioxide (CO₂), and light sensors, and afterward. The resulting data was used to train six different ML-based classifiers. The classifiers considered in this paper were Logistic Regression (LR), Random Forest (RF), Decision Tree (DT), K-Nearest Neighbours (KNN), Support Vector Machines (SVM), and Gradient Boosting Machines (GBM). Simulation experiments revealed that only the RF and DT models are robust against the partial features availability problem, achieving at least 90% performance scores across all the considered metrics.

Improved Palm Oil Mill Effluent Degradation by Fe²⁺/Fe³⁺ Ion Exchanger Mediator

Mon, 31 Mar 2025 00:00:00 +0200

This present study investigates the efficiency of using ion exchanger Fe²⁺/Fe³⁺ mediator for the degradation of Palm Oil Mill Effluent (POME). The ion exchanger of Fe²⁺/Fe³⁺ mediator enhanced the redox reaction in liquid POME degradation. Comprehensive analysis on POME before and after degradation by 0.005 M FeCl₃ was conducted by several characterisation techniques, including cyclic voltammetry (CV), Ultraviolet-visible (UV-Vis) spectroscopy, Attenuated Total Reflectance-Fourier Transform Infrared spectroscopy (ATR-FTIR) Analysis, X-ray diffraction (XRD), and Brunauer-Emmett-Teller (BET) analysis. The CV analysis provided a better understanding on the oxidation and reduction reaction during the degradation of liquid POME. The identification of chemical bonds and functional groups was carried out by using the ATR-FTIR analysis. The type of crystal or amorphous patterns identified by XRD and surface area measurements were done by using the BET analysis. The findings revealed that the existence of ion exchanger Fe²⁺/Fe³⁺ mediator performed redox reaction by CV and the peak current density of oxidation (Ipa) showed similar results for fresh liquid POME and liquid POME+0.005 M FeCl₃, that is 1.34 ´ 10^-1µA cm^-2. Meanwhile, the peak current density of reduction (Ipc) for both samples were -1.33 ´ 10²µA cm^-2 and -5.89 ´ 10¹µA cm^-2, respectively. The specific capacitance, C are 125.08 C and 157.71 C for both samples. Spectrometry analysis by UV-Vis spectrometry showed a significant absorbance reduction and chemical shifting when 0.005 M FeCl₃was added to liquid POME. By using the ATR-FTIR analysis, it was revealed that the chemical bonds changed on dried solid POME after degradation with the addition of 0.005 M FeCl₃. Amorphous diffractogram patterns were identified for both samples by XRD analysis. An increase in surface area from 0.94 m²g^-1 to 18.55 m²g^-1 was also revealed from the BET analysis. This research contributes to the knowledge on the role of ion exchangers Fe²⁺/Fe³⁺ mediator, providing a foundation for effective liquid POME treatment.

Volumetric and Performance-based Evaluation of Bituminous Blends

Lee Leon, Chris Maharaj, Lisa Ramoutar, Rean Maharaj — Mon, 31 Mar 2025 00:00:00 +0200

Crumb rubber (CR) and styrene-butadiene-styrene (SBS) from discarded tires and other waste materials were used as additives/replacements in asphalt mixtures. The researchers conducted Marshall and performance-based crumb rubber-modified asphalt (CRMA) testing. The dry process was employed, where CR was added to the aggregate before adding the binder. A control of 0% CR was compared to 1% CR by aggregate weight. Mix design formulations were acceptable for 5.6% and 6.3% binder contents, respectively. Marshall test results were acceptable for both formulations. For performance-based testing, the tensile strength ratio was acceptable for both formulations. However, for permanent deformation strain, the 1% CRMA was slightly higher (5.1%) than the upper acceptable range limit (4.5%), whereas the 0% CRMA control was within the acceptable range. Further investigation into the pre-treatment of CR to facilitate swelling and the phase interlocking to decrease the required binder in the mix design and increase CR addition is warranted. This study demonstrated the potential of reusing CR in road paving applications, providing an innovative, sustainable disposal option.

Soil Bearing Parameters and Settlement Prediction Using CPT Data in Southwestern Nigeria

Olumuyiwa Olusola Falowo, Abayomi Solomon Daramola, William Kunle Olabisi — Mon, 31 Mar 2025 00:00:00 +0200

The study was aimed at deriving important soil parameters relevant to civil engineering construction in schistose quartzite/quartzite dominated soil of RUGIPO, Ondo State, Nigeria, using cone penetration test (CPT). Key engineering parameters’ findings revealed a high degree of overlapping values within the two geological formations. However, both soils are very dense, stiff/hard soil, with a high dominance of coarse particles (sand) over the finer soil matrix (silt). Soil from quartzite has better bearing pressure (avg. 405 kN m^-²) than schistose quartzite (324 kN m^-²), even above the regional average of 346 kN m^-². The CPT material index with a regional average of 2.40, with schistose quartzite and quartzite showing average values of 2.39 and 2.42, and average soil permeability of 6.19×10^-7 m s^-¹ and 4.498×10^-7 m s^-¹, respectively. The soils have a mean CBR value of 38%, with the CBR of schistose quartzite (35%) less than that of quartzite (42%). The regression models between all the parameters correlated gave positive correlation coefficients, especially CBR and (0.6522), R_D and CBR (0.6536), S_u and q_c (0.9849). The practical implications of the result indicated that both soils are competent for construction (pavement, foundation, and embankment construction) in both geological formations.