Ph.D. Candidate in Petroleum Engineering at Soran University 2024 to now.
M.Sc. in Petroleum Engineering at University of Kurdistan Hewler 2021.
B.Sc. in Petroleum Engineering at Knowledge University 2018.
RESEARCH, TEACHING, or OTHER INTERESTS
Engineering, Civil and Structural Engineering, Materials Science, Artificial Intelligence
9
Scopus Publications
27
Scholar Citations
3
Scholar h-index
Scopus Publications
Chemical Composition–Driven Modeling of Rheological Properties in Sustainable Oil Well Cement Using Individual Oxides and Indices With Micro- and Nano-Silica Additives Mohammed Ariwan Jamal, Ahmed Salih Mohammed, Jagar A. Ali Journal of Petroleum Geology, 2026 Yield stress and plastic viscosity (PV) are key rheological parameters controlling the flow behavior, placement efficiency, and zonal isolation of oil well cement slurries. Maintaining these properties within API standards is essential for well integrity. This study investigates the effect of the chemical composition of cement, particularly silicon dioxide (SiO 2 ), on yield stress across three systems: base cement, nano‐silica (NS)‐modified cement, and silica fume (SF)‐modified cement. In modified systems, total SiO 2 includes contributions from both cement and additives. A dataset of 224 entries was analyzed alongside 358 entries from the literature to examine the relationship between yield stress and PV. Four quartic regression models were developed using different chemical descriptors: individual oxides (IOs), alumina‐ferric ratio (AFR), silicate–metallic ratio (SMR), and lime modulus (LM). Results show that in base cement, the IO model achieved the highest accuracy ( R 2 = 0.98, RMSE = 2.49), whereas the LM model performed worst ( R 2 = 0.80, RMSE = 8.88). For NS cement, IO, and AFR models showed strong performance ( R 2 = 0.96), whereas all models performed similarly well for SF systems ( R 2 ≈ 0.97). Overall, models based on IOs outperformed combined indices. These findings highlight the critical role of oxide composition, particularly SiO 2 , in controlling cement rheology and support incorporating detailed chemical parameters into predictive models of oil well cement performance.
Memory Effect of Bacteria-Killing Properties of Piezo-Catalysts Nanomaterials through Defect Engineering Omid Amiri, Karzan A. Qurbani, Karukh A. Babakr, Peshang Kh. Omer, L. Jay Guo, Hastyar Hama Rashid Najmuldeen, Martin Bertau, Peshawa H. Mahmood, Sangar S. Ahmed, Mohammed A. Jamal Advanced Nanobiomed Research, 2025 This study investigates the effects of piezo‐catalysts on sterilizing surfaces. The memory effects in three piezo‐catalysts, ZnO, CuO, and SiO2 are discovered, which are produced by a calcination process. After applying mechanical force to these materials, they retain an antibacterial effect for a period of days. With this discovery, it is possible to combat antibiotic‐resistant bacteria by using piezo materials on hospital floors or operating rooms that can kill bacteria just by walking on them. The results show that ZnO, CuO, and SiO2 are capable of killing bacteria even after being subjected to mechanical force for 9 days. The memory effect duration can be influenced by a variety of factors, including the calcination temperature, the storage condition after ultrasonication, the drying temperature after ultrasonication, and the solvent in which the piezo‐catalyst is ultrasonicated. When ZnO, CuO, and SiO2 are kept under a vacuum in a dark environment, the piezo effect remains almost constant for 11 days after sonication.
Predicting Compressive Strength of Oil Well Cement Slurries: Novel Moduli-Based Analysis of Chemical Composition at Different Temperature Condition Mohammed Ariwan Jamal, Ahmed Salih Mohammed, Jagar A. Ali Structural Design of Tall and Special Buildings, 2025 This study evaluates the impact of cement chemical composition on the compressive strength (CS) of cement slurries, utilizing silica fume (SF) and fly ash (FA) as additional materials. A comprehensive analysis was conducted on 317 datasets from the literature, focusing on factors including silicon dioxide (SiO₂), aluminum oxide (Al₂O₃), calcium oxide (CaO), iron oxide (Fe₂O₃), water‐to‐binder (w/b) ratio, and SF and FA content, as well as curing time and temperature. The research presents three geochemical moduli, namely, silicate modulus (SM), aluminate modulus (AM), and hydraulic modulus (HM), to assess and forecast CS. The investigation utilizing full quadratic (FQ) and cubic (CUB) models underscores the precision of prediction models corroborated by statistical metrics, such as scatter index (SI), root mean squared error (RMSE), and correlation coefficient (R2). Univariate, bivariate, and multivariate evaluations indicate that SM, AM, and HM significantly decrease input parameters while preserving or enhancing model accuracy. The ideal replacement percentages for SF and FA to maximize strength were determined to be 14.6% and 11.6%, respectively. The optimal values for SM, AM, and HM were 2.62, 1.38, and 2.21, respectively. The results establish a solid framework for optimizing cement formulations, presenting sustainable alternatives for improved mechanical performance and decreased material consumption in oil well cementing and building applications.
Simulation and Modeling of Data Transmission Process in Boreholes Using Intelligent Drill Pipe for a Laboratory Experiment Mohammed A. Namuq, Ezideen A. Hasso, Mohammed A. Jamal, Koran A. Namuq, Yibing Yu Modelling, 2024 Currently, most oil and gas wells are drilled by continuously transmitting downhole measured information (directional and geological information) in real-time to the surface to monitor and steer the well along a pre-defined path. The intelligent drill pipe method can transmit data over longer distances and at a higher rate than other methods, such as mud pulse telemetry, acoustic telemetry, and electromagnetic telemetry. Nevertheless, it is expensive and requires boosters along the drill string. In the available literature, academic research rarely addresses the data transmission process in boreholes using intelligent drill pipes. Furthermore, there is a need for an effective and validated model to study various controllable parameters to enhance the efficiency of the intelligent drill pipe telemetry without the need to develop several physical lab or field prototypes. This paper presents the development of a model based on MATLAB Simulink to simulate the process of data transmission in boreholes utilizing intelligent drill pipes. Laboratory experimental prototype measurements have been used to test the model’s effectiveness. A good correlation is found between the measured lab data and the model’s predictions for the signals transmitted contactless through intelligent drill pipes with a correlation coefficient (R2) above 0.9. This model can enhance data transmission efficiency via intelligent drill pipes, study different concepts, and eliminate the need to develop several unnecessarily expensive and time-consuming physical lab prototypes.
Mechanism and kinetic of piezo-catalytic desulfurization of model and actual fuel samples over CexOy/SrO nanocomposite at room temperature Karwan M. Rahman, Omid Amiri, Sangar S. Ahmed, Savana J. Ismael, Noor S. Rasul, Karukh A. Babakrb, Mahnaz Dadkhah, Mohammed A. Jamal Heliyon, 2024 SOx emissions are primarily caused by compounds containing sulfur in petroleum and fuels, which lead to severe air pollution. For this reason, it is necessary to develop a fast and simple desulfurization method in order to comply with ever-increasing environmental regulations. The newly discovered piezo-catalyst nanocomposite CexOy/SrO can convert mechanical energy directly into chemical energy, thereby enabling mechanically oxidative sulfur desulfurization. 320 W of bath sonication were used to polarize and activate the prepared piezo-catalyst nanocomposite CexOy/SrO for sulfur removal from thiophene and dibenzothiophene as model fuels and kerosene as a real fuel. Using uniform and spherical CeO2/SrO nanocomposites resulted in the highest desulfurization rates of 95.4 %, 97.3 %, and 59.7 %, respectively, for thiophene and dibenzothiophene. This study examined the effect of several parameters, such as sulfur concentration, pH of fuel, dosage of CexOy/SrO nanocomposite, power and time of ultrasonic, and shaking time, on the piezo-desulfurization of thiophene (TP) and dibenzothiophene (DBTP). To identify the major active species in piezo desulfurization, radical trapping experiments were conducted. This study investigated the possibility of reusing the catalyst, and the piezo-desulfurization activity that was demonstrated in the removal of TP and DBTP after 11 cycles as well as the ability of the catalyst to remove real fuel even after 14 cycles was promising. As the kinetic results show, the reaction follows the second order with K = 0.0050. Also, thermodynamic results showed the oxidation of sulfide to sulfoxide and sulfoxide is endothermic. Activation energy for second order rate constant is (3.824 Kj/mole). 0.0236 mol-1. Sec−1 was calculated for Arrhenius Constant.
Memory Effect of Bacteria‐Killing Properties of Piezo‐Catalysts Nanomaterials through Defect Engineering O Amiri, KA Qurbani, KA Babakr, PK Omer, LJ Guo, HHR Najmuldeen, ... Advanced NanoBiomed Research, 2300144 , 2025 2025 Citations: 2
Modeling the impact of SiO2, Al2O3, CaO, and Fe2O3 on the compressive strength of cement modified with nano-silica and silica fume MA Jamal, AS Mohammed, JA Ali Multiscale and Multidisciplinary Modeling, Experiments and Design 8 (2), 156 , 2025 2025 Citations: 8
Predicting Compressive Strength of Oil Well Cement Slurries: Novel Moduli‐Based Analysis of Chemical Composition at Different Temperature Condition MA Jamal, AS Mohammed, JA Ali The Structural Design of Tall and Special Buildings 34 (2), e2214 , 2025 2025 Citations: 1
Innovative assessment of cement chemistry and the impact of additives on compressive strength across various specimen sizes and extended curing conditions MA Jamal, AS Mohammed, JA Ali Multiscale and Multidisciplinary Modeling, Experiments and Design 8 (1), 106 , 2024 2024 Citations: 3
Simulation and modeling of data transmission process in boreholes using intelligent drill pipe for a laboratory experiment MA Namuq, EA Hasso, MA Jamal, KA Namuq, Y Yu Modelling 5 (4), 1961-1979 , 2024 2024 Citations: 4
Advanced modeling of compressive strength in silica-modified oil well cement: impact of silicate, aluminate, and hydraulic moduli M Ariwan Jamal, AS Mohammed, JA Ali Nondestructive Testing and Evaluation 40 (10), 5022-5057 , 2024 2024 Citations: 1
Mechanism and kinetic of piezo-catalytic desulfurization of model and actual fuel samples over CexOy/SrO nanocomposite at room temperature KM Rahman, O Amiri, SS Ahmed, SJ Ismael, NS Rasul, KA Babakrb, ... Heliyon 10 (2) , 2024 2024 Citations: 5
Stable perovskite solar cells resist to water without encapsulation by p-type Si NWs as hole collection layers KM Rahman, O Amiri, KA Younis, MH Khalil, AM Azhdarpour, M Saadat, ... Journal of Nanostructures 13 (2), 341-352 , 2023 2023 Citations: 1
Leading Academic Lab Experimental Trial Demonstrating the Intelligent Drill Pipe Technology Functionality MA Namuq, EA Hasso, MA Jamal Journal of China University of Petroleum 47 (4), 1159-1173 , 2023 2023 Citations: 2
Artificial Neural Network Application for Prediction of ROP of Directional Wells for an Oil Field in Kurdistan MA Jamal University of Kurdistan Hewler , 2021 2021
MOST CITED SCHOLAR PUBLICATIONS
Modeling the impact of SiO2, Al2O3, CaO, and Fe2O3 on the compressive strength of cement modified with nano-silica and silica fume MA Jamal, AS Mohammed, JA Ali Multiscale and Multidisciplinary Modeling, Experiments and Design 8 (2), 156 , 2025 2025 Citations: 8
Mechanism and kinetic of piezo-catalytic desulfurization of model and actual fuel samples over CexOy/SrO nanocomposite at room temperature KM Rahman, O Amiri, SS Ahmed, SJ Ismael, NS Rasul, KA Babakrb, ... Heliyon 10 (2) , 2024 2024 Citations: 5
Simulation and modeling of data transmission process in boreholes using intelligent drill pipe for a laboratory experiment MA Namuq, EA Hasso, MA Jamal, KA Namuq, Y Yu Modelling 5 (4), 1961-1979 , 2024 2024 Citations: 4
Innovative assessment of cement chemistry and the impact of additives on compressive strength across various specimen sizes and extended curing conditions MA Jamal, AS Mohammed, JA Ali Multiscale and Multidisciplinary Modeling, Experiments and Design 8 (1), 106 , 2024 2024 Citations: 3
Memory Effect of Bacteria‐Killing Properties of Piezo‐Catalysts Nanomaterials through Defect Engineering O Amiri, KA Qurbani, KA Babakr, PK Omer, LJ Guo, HHR Najmuldeen, ... Advanced NanoBiomed Research, 2300144 , 2025 2025 Citations: 2
Leading Academic Lab Experimental Trial Demonstrating the Intelligent Drill Pipe Technology Functionality MA Namuq, EA Hasso, MA Jamal Journal of China University of Petroleum 47 (4), 1159-1173 , 2023 2023 Citations: 2
Predicting Compressive Strength of Oil Well Cement Slurries: Novel Moduli‐Based Analysis of Chemical Composition at Different Temperature Condition MA Jamal, AS Mohammed, JA Ali The Structural Design of Tall and Special Buildings 34 (2), e2214 , 2025 2025 Citations: 1
Advanced modeling of compressive strength in silica-modified oil well cement: impact of silicate, aluminate, and hydraulic moduli M Ariwan Jamal, AS Mohammed, JA Ali Nondestructive Testing and Evaluation 40 (10), 5022-5057 , 2024 2024 Citations: 1
Stable perovskite solar cells resist to water without encapsulation by p-type Si NWs as hole collection layers KM Rahman, O Amiri, KA Younis, MH Khalil, AM Azhdarpour, M Saadat, ... Journal of Nanostructures 13 (2), 341-352 , 2023 2023 Citations: 1
Artificial Neural Network Application for Prediction of ROP of Directional Wells for an Oil Field in Kurdistan MA Jamal University of Kurdistan Hewler , 2021 2021
