Browsing by Author "MARTIN, HENRY"

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    Ab‑initio study of the transition pathways for single and double interstitial solute (H, N, O, H‑H, N‑N, and O‑O) within bcc refractory metals (Mo and Nb)
    (Springer, 2024-12) MARTIN, HENRY; Quarshie, Henry Elorm; Abavare, Eric Kwabena Kyeh; Continenza, Alessandra; 0000-0003-0173-1238
    Transition pathways of single (Hydrogen (H), Nitrogen (N), and Oxygen (O)) and double (H-H, N-N and O-O) interstitial solutes within bcc refractory metals (molybdenum (Mo) and niobium (Nb)) were investigated. This work is crucial for understanding how atmospheric gases, rich in H, O, and N, interact with metals. Ab-initio calculations for equilibrium and structural parameters, dissolution energetics, charge transfers, minimum energy path, and diffusion coefficients were performed. Single solutes exhibited preferential occupancy sites, with H favoring tetrahedral sites (t-sites), N preferring octahedral sites (o-sites), and O showing material-dependent behavior. The energy barriers for single solute diffusion ranged from 0.10 to 1.34 eV, aligning with experimental findings. Double interstitial solutes significantly reduced activation energies (Ea ), leading to faster diffusion for all configurations except for MoO. This effect is due to the second solute’s influence on repulsive/attractive forces and local lattice relaxations, altering preferred diffusion pathways.
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    Boltzmann transformation of radial two‑phase black oil model for tight oil reservoirs
    (Springer, 2022-07) MARTIN, HENRY; Prempeh, Kofi Ohemeng Kyei; Parker‑Lamptey, George; Amoako‑Yirenkyi, Peter; 0000-0003-0173-1238
    unconventional reservoirs is described by peculiar complexities such as the typical low permeability to viscosity ratio and the dissolution of some gases in the oil phase. Reservoir simulations that consider these complexities negligible stand the potential of poorly characterizing the reservoir flow dynamics. The adoption of similarity transformation effectively reduces the complexities associated with the flow equations through spatial variable (r) and temporal variable (t). The Boltzmann variable =r√t is introduced to facilitate the reformulation of transient two-phase flow phenomenon in a radial geometry. The technique converts the two-phase Black oil model (thus highly nonlinear partial differential equations (PDEs)) to ordinary differential equations (ODEs). The resulting ODEs present a reduced form on the flow model which is solved by finite difference approximations (the Implicit-Pressure-Explicit-Saturation (IMPES)) scheme. No loss of vital flow characteristics was observed between the Black oil model and the similarity transform flow model. Furthermore, the similarity approach facilitated the determination of pressure and saturation equations as unique functions of the Boltzmann variable. This derivation is applied to an infinitely acting reservoir where the Boltzmann variable tends to infinity ( → ∞ ). Finally, this case study’s analytical solution formulated critical relations for fluid flow rate and cumulative production, which are useful for single-phase flow analysis.
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    Electronic and Magnetic Properties of Transition Metal-Doped MoS2 Monolayer: First-Principles Calculations
    (PSS, 2023) MARTIN, HENRY; Boakye, Dennis; Labik, Linus K.; Britwum, Akyana; Nunoo, Oswald Ashirifi; Elloh, Van W.; Kwakye-Awuah, Bright; Yaya, Abu; Abavare, Eric K. K.; 0000-0003-0173-1238
    Density functional theory in the framework of generalized gradient approximation (GGA) of Perdew–Burke–Ernzerhof to investigate the effects of some selected transition metal (TM) and rare-earth metal (RE) dopants on the electronic and magnetic properties of a 2D molybdenum disulfide (MoS2) monolayer is reported. The results demonstrate that it is energetically stable to incorporate Ni and Cu in MoS2 structure under Mo-rich conditions. The pristine MoS2 monolayer has a calculated direct bandgap of 1.70 eV and experiences significant reduction in the gap due to the defects. There is observed induced magnetic behavior due to the tight binding effect originating from the localized dopants and the nearest-neighbor Mo atoms, with magnetic moments ranging between 0.82 and 3.00 μB. Some of the dopants result in 100% spin polarization which is useful for engineering spin filter devices on magnetic MoS2 nanostructures.
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    Molybdenum Induced Modifications in the Quantum Capacitance of Graphene-Based Supercapacitor Electrodes: First-Principle Calculations
    (PSS, 2024) MARTIN, HENRY; Ansi, David; Labik, Linus K.; Yaya, Abu; Elloh, Van W.; Abavare, Eric K. K.; 0000-0003-0173-1238
    Herein, spin-polarized calculation is performed based on density-functional theory in the frame of generalized gradient approximation to examine the quantum capacitance (CQ) and surface charge storage of graphene(G)-based supercapacitor electrodes modified with molybdenum, sulfur, nitrogen, and monovacancy. In total, 15 electrode models, including graphitic doping, monovacancy doping, and Mo adsorption on pristine and single-vacancy graphene structures are analyzed. In the results, it is demonstrated that vacancy defects and N/S/Mo doping enhances the CQ of graphene. Among all configurations, pyrrolic-S (d1S) shows the lowest CQ performance due to few states at the Fermi level. Electrodes with Mo adsorption exhibit the highest CQ, particularly when Mo is adsorbed at the top site of graphene. However, formation and adsorption energy calculations suggest that Mo is more likely to adsorb at hollow sites. Optimally, Mo can be most effectively utilized by loading it onto vacancy or N/S-decorated vacancy sites. The significant contribution of Mo’s 4dz2 and 4s states to CQ, along with the charge-redistribution around the Mo complexes, may facilitate proton-coupled electron transfer to enhance pseudocapacitance. In these findings, valuable insights into designing high quantum capacitance of 2D materials with electroactive sites for improved energy storage are offered.
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    Seemingly unrelated time series model for forecasting the peak and short-term electricity demand: Evidence from the Kalman filtered Monte Carlo method
    (Heliyon, 2023-08) MARTIN, HENRY; Owusu, Frank Kofi; Amoako-Yirenkyi, Peter; Frempong, Nana Kena; Omari-Sasu, Akoto Yaw; Mensah, Isaac Adjei; Sakyi, Adu; 0000-0003-0173-1238
    In this extant paper, a multivariate time series model using the seemingly unrelated times series equation (SUTSE) framework is proposed to forecast the peak and short-term electricity demand using time series data from February 2, 2014, to August 2, 2018. Further the Markov Chain Monte Carlo (MCMC) method, Gibbs Sampler, together with the Kalman Filter were applied to the SUTSE model to simulate the variances to predict the next day’s peak and electricity demand. Relying on the study results, the running ergodic mean showed the convergence of the MCMC process. Before forecasting the peak and short-term electricity demand, a week’s prediction from the 28th to the 2nd of August of 2018 was analyzed and it found that there is a possible decrease in the daily energy over time. Further, the forecast for the next day (August 3, 2018) was about 2187 MW and 44090 MWh for the peak and electricity demands respectively. Finally, the robustness of the SUTSE model was assessed in comparison to the SUTSE model without MCMC. Evidently, SUTSE with the MCMC method had recorded an accuracy of about 96% and 95.8% for Peak demand and daily energy respectively
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    Statistical Modeling for Prediction of CCT Diagrams of Steels Involving Interaction of Alloying Elements
    (Springer Nature, 2020-11) MARTIN, HENRY; AMOAKO-YIRENKYI, PETER; POHJONEN, AARNE; FREMPONG, NANA K.; KOMI, JUKKA; SOMANI, MAHESH; 0000-0003-0173-1238
    Steel is used in a wide variety of applications, which require specific mechanical properties. To achieve the desired properties, thermomechanical processing techniques are used, followed by continuous cooling, which results in specific microstructural evolution through phase transformation. This naturally influences the combined requisite property. During the processing, materials can be either deformed in austenitic state or as-cast from the melt and then cooled to room temperature. In the cooling stage, austenite can decompose to ferrite phase types roughly classified as (polygonal) ferrite, bainite and martensite. Since the different ferritic phases have a decisive influence on the mechanical properties, it is important to control the austenite decomposition process. The most important factor affecting the austenite decomposition is the chemical composition of the steel and the applied cooling path. The austenite decomposition is conventionally represented using time-temperature diagrams, either for holding at constant temperature (TTT, time temperature transformation diagrams) or for cooling at different rates (CCT, continuous cooling transformation diagrams). The TTT diagram can be used to calculate an estimate for the transformation start using Scheil’s additivity rule,[1,2] but since there is a considerable difference in the long-time isothermal holding and fast continuous cooling, the usage of the CCT diagram gives a better estimate of the transformation onset during rapid cooling. Since fast cooling rates are often used in steel production, predicting the decomposition of austenite using CCT diagrams was the subject of several earlier studies.[3,4,5] Earlier studies[6,7,8] focused on the usage of an additive regression model of chemical composition as well as the cooling path effect for the start of transformation of ferrite, bainite and martensite, respectively. In these earlier studies, the interaction of different alloying elements was not taken into account; instead, the applied model assumed linear dependence on the alloying elements. Unfortunately, the physical interpretation of the overall transformation kinetic of undercooled austenite in steel is determined by several factors, such as the mobility of the compositional atoms participating in the transformation. This results in solute microsegregation, formation of precipitates, etc., which signifies interaction among the alloying elements. Therefore, using an additive model does not practically represent the physical phenomenon. To address this challenge, in this article we present a model that considers the interaction and quadratic dependence of alloying elements on the transformation onset. This provides better description of the experimental data since only the most significant interaction and quadratic alloying element terms were considered. This enables all the individual alloying elements to be significant for the time-dependent growth and response temperature. The efficiency of the current model has been further examined by fitting it with the CCT behavior of several steels, represented in References 9 and 10, which focus on molybdenum-containing steels.