Tijjani Adam
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Preferred name
Tijjani Adam
Official Name
Tijjani, Adam
Alternative Name
Adam, T.
Adama, Tijjani
Adam, Tijjani
Adam, Tijjan
Tijjani, A.
Main Affiliation
Scopus Author ID
55074964600
Researcher ID
AAH-5534-2019

Research Output
Now showing 1 - 8 of 8
  • Publication
    Thermal diffussion: a simulation based study on shallow junction formation
    ( 2012-07)
    Uda Hashim
    ;
    N. Hamat N. H,
    ;
    Siti Fatimah
    ;
    Tijjani Adam
    Ultra shallow junction fabrication in future ultra large scaled integrated (ULSI) technology is one of the difficult challenges in device manufacturing. Low energy ion implantation is hte most widely used technique at present to form ultra shallow junction but research has been to overcome its limitations such as crystal damage. In this research paper, thermal diffusion from spin-on dopant (SOD) into silicon has been studied in order to form shallow junction. This study was done by simulation using TSUPREM-4 from Synopsys Inc to determine the junction depth and the sheet resistance in order to fulfill the ITRS requirements. Ultra shallow junction which is defined to be less than 30 nm in depth has been obtained through this simulation using this easy and simple spin-on dopant technique. This economical spon-on dopant (SOD) technique has been proven as one promising method for shallow junction formation in future generations.
  • Publication
    Development of silicon nanowire lab-on-chip microfluidics integrated biosensor for low concentration bio-molecules detection
    ( 2015)
    Tijjani Adam
    Lab-on-chip fabricated with one-dimensional nanowires offer excellent electrical properties where bio molecular analysis at very low concentrations is becoming increasingly relevant for medical and research communities. Good number of techniques and promising results has been established for detecting small concentrations; however, for high-throughput measurements and label-free detection are still area of fresh investigation. Many research groups have reported high level of bio recognition by using semiconductor nanowire. The semiconductors silicon nanowire biosensor utilizes a Nano wire between two conducting materials. The nanowire has its atoms concentrated on its surface. Thus, any small changes in the charges present on the nanowire will cause a change in the flow of current. In this thesis, a simulation study coupled with experimental approach to explain the change in wire surface behavior as function of the surface charge. The linear behavior of the conductivity to increase the sensitivity of a semiconducting nanowire biosensor is ascertained. The silicon wire should be between 5 to 20nm to allow mean distance between atoms, the oxide should be as thin as possible for optimum surface integrity, and the functional layer should be thin and have a high dielectric constant. The ionic concentration of the electrolyte should be kept low in order to have a large Debye screening length. To confirm these theoretical results, Silicon nanowire of ≈ 15nm was fabricated using conventional photolithography coupled with dry etching process. To determine the capability of the device, it subjected to various pH values and to achieve this, the device is being operated based on the principle of Field Effect Transistor (FET). The surface of the device is hole dominated (p-type material).
  • Publication
    Silica and graphene mediate arsenic detection in mature rice grain by a newly patterned current–volt aptasensor
    ( 2021)
    M. N. A. Uda
    ;
    Subash Chandra Bose Gopinath
    ;
    Uda Hashim
    ;
    N. H. Halim
    ;
    N. A. Parmin
    ;
    M. N. Afnan Uda
    ;
    Tijjani Adam
    ;
    Periasamy Anbu
    Arsenic is a major global threat to the ecosystem. Here we describe a highly accurate sensing platform using silica nanoparticles/graphene at the surface of aluminum interdigitated electrodes (Al IDE), able to detect trace amounts of arsenic(III) in rice grain samples. The morphology and electrical properties of fabricated Al IDEs were characterized and standardized using AFM, and SEM with EDX analyses. Micrometer scale Al IDEs were fabricated with silicon, aluminum, and oxygen as primary elements. Validation of the bare Al IDE with electrolyte fouling was performed at different pH levels. The sensing surface was stable with no electrolyte fouling at pH 7. Each chemical modification step was monitored with current–volt measurement. The surface chemical bonds were characterized by fourier transform infrared spectroscopy (FTIR) and revealed different peaks when interacting with arsenic (1600–1000 cm−1). Both silica nanoparticles and graphene presented a sensitive limit of detection as measured by slope calibration curves at 0.0000001 pg/ml, respectively. Further, linear regression was established using ΔI (A) = 3.86 E−09 log (Arsenic concentration) [g/ml] + 8.67 E−08 [A] for silica nanoparticles, whereas for graphene Y = 3.73 E−09 (Arsenic concentration) [g/ml] + 8.52 E−08 on the linear range of 0.0000001 pg/ml to 0.01 pg/ml. The R2 for silica (0.96) and that of graphene (0.94) was close to the maximum (1). Modification with silica nanoparticles was highly stable. The potential use of silica nanoparticles in the detection of arsenic in rice grain extract can be attributed to their size and stability.
  • Publication
    Conductometric immunosensor for specific Escherichia coli O157:H7 detection on chemically funcationalizaed interdigitated aptasensor
    ( 2024)
    Muhammad Nur Afnan Uda
    ;
    Alaa Kamal Yousif Dafhalla
    ;
    Thikra S. Dhahi
    ;
    Tijjani Adam
    ;
    Subash Chandra Bose Gopinath
    ;
    Asral Bahari ambek
    ;
    Muhammad Nur Aiman Uda
    ;
    Nor Azizah Parmin
    ;
    Nur Hulwani Ibrahim
    ;
    Uda Hashim
    Escherichia coli O157:H7 is a strain of Escherichia coli known for causing foodborne illness through the consumption of contaminated or raw food. To detect this pathogen, a conductometric immunosensor was developed using a conductometric sensing approach. The sensor was con-structed on an interdigitated electrode and modified with a monoclonal anti-Escherichia coli O157: H7 aptamer. A total of 200 electrode pairs were fabricated and modified to bind to the target molecule replica. The binding replica, acting as the bio-recognizer, was linked to the electrode surface using 3-Aminopropyl triethoxysilane. The sensor exhibited excellent performance, detecting Escherichia coli O157:H7 in a short time frame and demonstrating a wide detection range of 1 fM to 1 nM. Concentrations of Escherichia coli O157:H7 were detected within this range, with a minimum detection limit of 1 fM. This innovative sensor offers simplicity, speed, high sensitivity, selectivity, and the potential for rapid sample processing. The potential of this pro-posed biosensor is particularly beneficial in applications such as drug screening, environmental monitoring, and disease diagnosis, where real-time information on biomolecular interactions is crucial for timely decision-making and where cross-reactivity or interference may compromise the accuracy of the analysis.
  • Publication
    Modular architecture of a non-contact pinch actuation micropump
    ( 2012)
    Pei Song Chee
    ;
    Rashidah Arsat
    ;
    Tijjani Adam
    ;
    Uda Hashim
    ;
    Ruzairi Abdul Rahim
    ;
    Pei Ling Leow
    This paper demonstrates a modular architecture of a non-contact actuation micropump setup. Rapid hot embossing prototyping was employed in micropump fabrication by using printed circuit board (PCB) as a mold material in polymer casting. Actuator-membrane gap separation was studied, with experimental investigation of three separation distances: 2.0 mm, 2.5 mm and 3.5 mm. To enhance the micropump performance, interaction surface area between plunger and membrane was modeled via finite element analysis (FEA). The micropump was evaluated against two frequency ranges, which comprised a low driving frequency range (0–5 Hz, with 0.5 Hz step increments) and a nominal frequency range (0–80 Hz, with 10 Hz per step increments). The low range frequency features a linear relationship of flow rate with the operating frequency function, while two magnitude peaks were captured in the flow rate and back pressure characteristic in the nominal frequency range. Repeatability and reliability tests conducted suggest the pump performed at a maximum flow rate of 5.78 mL/min at 65 Hz and a backpressure of 1.35 kPa at 60 Hz.
  • Publication
    Insight on the structural aspect of ENR-50/TiO2 hybrid in KOH/C3H8O medium revealed by NMR spectroscopy
    ( 2020)
    Omar S. Dahham
    ;
    Rosniza Hamzah
    ;
    Mohamad Abu Bakar
    ;
    Nik Noriman Zulkepli
    ;
    Abdulkader M. Alakrach
    ;
    Sam Sung Ting
    ;
    Mohd Firdaus Omar
    ;
    Tijjani Adam
    ;
    Awad A. Al-rashdi
    The ring-opening reactions (ROR) of epoxide groups in epoxidized natural rubber/titania (ENR-50/TiO2) hybrid in potassium hydroxide/isopropanol medium were examined using NMR spectroscopy and supported by the FTIR technique. The thermal behaviour of the hybrid was also studied using TG/DTG and DSC analyses. The 1H NMR results suggested that 16.82% of ROR occurred in the hybrid, while the 13C NMR results exhibited five new peaks at δ 19.5, 71.0, 73.7, 91.7 and 94.4 ppm in the hybrid. 2D NMR, such as HMQC, HMBC and COSY techniques, further scrutinized these assignments. The FTIR spectrum exhibited Ti-O-C characteristics via the peak at 1028 cm−1. The TG/DTG results showed four steps of thermal degradation at 44–148, 219–309, 331–489 and 629–810 °C due to the existence of Ti moieties along with a polymer chain mixture (intact and ring-opened epoxide groups) of ENR-50, which in turn led to an increase in the Tg value of the hybrid to 27 °C compared to that of purified ENR-50 at −17.72 °C.
  • Publication
    Recent advances in density functional theory approach for optoelectronics properties of graphene
    ( 2023)
    A.L. Olatomiwa
    ;
    Tijjani Adam
    ;
    C.O. Edet
    ;
    A.A. Adewale
    ;
    Abdullah Chik
    ;
    Mohammed Mohammed
    ;
    Subash Chandra Bose Gopinath
    ;
    Uda Hashim
    Graphene has received tremendous attention among diverse 2D materials because of its remarkable properties. Its emergence over the last two decades gave a new and distinct dynamic to the study of materials, with several research projects focusing on exploiting its intrinsic properties for optoelectronic devices. This review provides a comprehensive overview of several published articles based on density functional theory and recently introduced machine learning approaches applied to study the electronic and optical properties of graphene. A comprehensive catalogue of the bond lengths, band gaps, and formation energies of various doped graphene systems that determine thermodynamic stability was reported in the literature. In these studies, the peculiarity of the obtained results reported is consequent on the nature and type of the dopants, the choice of the XC functionals, the basis set, and the wrong input parameters. The different density functional theory models, as well as the strengths and uncertainties of the ML potentials employed in the machine learning approach to enhance the prediction models for graphene, were elucidated. Lastly, the thermal properties, modelling of graphene heterostructures, the superconducting behaviour of graphene, and optimization of the DFT models are grey areas that future studies should explore in enhancing its unique potential. Therefore, the identified future trends and knowledge gaps have a prospect in both academia and industry to design future and reliable optoelectronic devices.
  • Publication
    Magnetic induction tomography for brain tissue imaging based on conductivity distribution for parkinson’s disease diagnosis
    ( 2023-10)
    Hussaini Adam
    ;
    Subash Chandra Bose Gopinath
    ;
    Mohd Khairuddin Md Arshad
    ;
    Uda Hashim
    ;
    Tijjani Adam
    Parkinson's disease is a prevalent neurodegenerative complication defined by the accumulation of alpha synuclein lewy bodies in the brain. Misdiagnosis results widespread of Parkinson’s disease because clinical diagnosis is challenging, underlining a need of a better detection technique, such as non-invasive magnetic induction tomography (MIT) technique. Non-invasive techniques for biological tissues imaging are becoming popular in biomedical engineering field. Therefore, MIT technology as a non-invasive technique has been encouraged in a medical field due to its advancement of technology in diagnosing diseases. The measurement parameters in MIT are passive electromagnetic properties (conductivity, permittivity, permeability) for biological tissue and the most dominant parameter in MIT is conductivity properties. It is uses a phase shift between a primary magnetic field and an induced field caused by a target object's conductivity. As a function of conductivity, the phase shift between the applied and secondary fields is expressed. Thus, the phase shift can be used to characterize the conductivity of a target object. The phase shift between the excitation and induced magnetic fields (EMF and IMF) reflects the change in conductivity in biological tissues. This paper focuses on the virtual simulation by using COMSOL Multi-physics for the design and development of MIT system that emphasizes on single channel magnetic induction tomography for biological tissue (bran tissue) imaging based on conductivity distribution for Parkinson’s disease diagnosis. The develop system employs the use of excitation coils to induce an electromagnetic field (e.m.f) in the brain tissue, which is then measured at the receiving side by sensors. The proposed system is capable of indicating Parkinson’s disease based on conductivity distribution. This method provides the valuable information of the brain abnormality based on differences of conductivities of normal brain and Parkinson’s disease brain tissues.