Mohd Khairuddin Md Arshad
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Preferred name
Mohd Khairuddin Md Arshad
Official Name
Mohd Khairuddin , Md Arshad
Alternative Name
Md. Arshad, M. K.
Arshad, Mohd K.M.
Arshad, M. K.M.
Khairuddin Md Arshad, Mohd
Arshad, M. K.Md
Main Affiliation
Scopus Author ID
57211870224
Researcher ID
L-5830-2013

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  • Publication
    Fabrication and simulation of silicon nanowire pH sensor for Diabetes Mellitus detection
    ( 2023-04)
    C. Y. Chean
    ;
    Mohammad Nuzaihan Md Nor
    ;
    Mohamad Faris Mohamad Fathil
    ;
    M. I. Hashim
    ;
    Nur Hamidah Abdul Halim
    ;
    Zarimawaty Zailan
    ;
    Mohd Khairuddin Md Arshad
    ;
    Syamsul Syahrun Awang@Hashim
    ;
    Rozaimah A.T
    Diabetes Mellitus (DM) is a disease failed to control the balance of blood sugar level due to lack of insulin thereby it effect human health. In Malaysia, there are around 3.9 millions people aged 18 years old and above have diabetes according to National Health and Morbidity Survey 2019. Silicon Nanowire is a nanostructure which has ultra-high sensitivity and non-radioactive that has potential given good performances when applied on pH sensor and biosensor. Silicon nanowire pH sensor and biosensor is an electronic sensor that investigated to improve the sensitivity and accuracy for detecting DM. This project consists of two parts, which are fabrication of silicon nanowire pH sensor and simulation of silicon nanowire biosensor as preliminary study. In fabrication, silicon nanowire of pH sensor is fabricated by conventional lithography process, reaction ion etching (RIE) and metallization to achieved the width of 100 nm silicon nanowire. The pH6, pH7, pH10 and DI water as analytes to analysis the current-voltage (I-V) characteristics of silicon nanowire pH sensor. In second part, the silicon nanowire biosensor as preliminary study is done simulation by Silvaco ATLAS devices simulator. The silicon nanowire with 30 nm in height and 20 nm in width of biosensor is designed and simulated to analyze the performance in terms of sensitivity. I-V characteristics of silicon nanowire biosensor according to different concentration of negative interface charge is determined. The negative interface charge represent as the Retinol Binding Protein 4 (RBP4) which is used to diagnose DM. The I-V characteristic based on the change in current, resistance and conductance to determine sensitivity. Lastly, the sensitivity of silicon nanowire pH sensor obtained 23.9 pS/pH while the sensitivity of simulated silicon nanowire biosensor obtained 3.91 nS/e.cm2. The results shown the more negative charge of concentration analyte attached on surface silicon nanowire has been accumulated more current flow from drain terminal to source terminal. It leads to the resistance becomes highest and obtained good sensitivity. In summary, the silicon nanowire pH sensor exhibited good performance and high sensitivity in detection pH level. The simulated silicon nanowire biosensor is capable of detecting biomolecular interactions charges to obtained high sensitive and accuracy result.
  • 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.