Plasmonics & Interferometry

PRINCIPAL RESEARCHER

Prof Ir Dr Ahmad Ashrif A BAKAR

B.EEE (UNITEN), M.Sc (UPM), Ph.D (UQ), SM.IEEE, SM.OSA,

Optical sensor design & systems.

ashrif [at] ukm.edu.my

Scopus ID: 56926940300

Linkedin.com/ashrif

Surface Plasmon Resonance

Surface Plasmon Resonance (SPR) is a label-free optical technique for real-time analysis of molecular and quantum interactions. It measures binding kinetics, affinities, and concentrations, making it widely applicable in biochemistry, quantum research, drug discovery, and materials science. Surface plasmons are electron oscillations at the metal-dielectric interface, excited by polarized light at a specific angle. Their resonance, highly sensitive to refractive index changes, enables precise molecular detection on sensor platforms.

Sensing Materials

The performance of Surface Plasmon Resonance sensors is enhanced by utilising functional sensing materials to the surface of metal thin films. These materials are carefully selected for their ability to interact selectively with target analytes and translate those interactions into measurable shifts in the SPR signal.

By modifying the sensing surface, sensitivity is significantly improved as changes in the optical properties, induced by analyte binding and alter the resonance angle. The choice of sensing material plays a vital role in determining overall sensor performance, contributing to higher specificity, enhanced sensitivity, improved stability against degradation, and better reusability.

Daniyal, W.M.E.M.M. et al. (2024). Sensitive and selective Cu2+ detection via surface plasmon resonance using ionophore decorated nanocrystalline cellulose-graphene oxide thin film. Sensors and Actuators A: Physical, 366.

We explore several categories of sensing materials, organic polymers, carbon-based materials, and inorganic compounds. Each selected for their unique properties and suitability in surface plasmon resonance-based applications. Polysaccharides such as cellulose, starch, carrageenan, and chitosan are chosen for their natural origin, biodegradability, biocompatibility, and ease of functionalization. Carbon-based materials include graphene oxide, valued for its high surface area, tunable optical and electrical properties, and mechanical strength, as well as carbon dots, which offer fluorescence, size versatility, and surface functionalization potential. Inorganic materials under study include zinc oxide, known for its wide bandgap, photoluminescence, and chemical stability, and ZIF-8, a metal-organic framework that provides high porosity, selective adsorption, and compatibility for integration with other materials. These materials hold great potential for application in chemical and biological sensing, environmental monitoring, food safety, and medical diagnostics.

Our research focuses on optimizing SPR sensor performance through the use of diverse sensing materials. We study their interactions with analytes—particularly electrostatic forces and hydrogen bonding—and evaluate both unmodified and modified polymers. Physical and chemical modifications are applied to enhance sensitivity and selectivity, forming a structured approach to tailor sensor response for various applications.

Azeman, N. H. et al. (2022). Carboxymethyl chitosan/graphene oxide/silver nanotriangles nanohybrid as the sensing materials for the enhancement of ammonia localized surface plasmon resonance sensor. Opt. Laser Technol., 148.

This figure highlights two approaches to modifying chitosan for sensing applications: physical and chemical. In the physical modification, graphene oxide (GO) is incorporated into the chitosan matrix to form a Chitosan/GO composite, where hydrogen bonding enhances interaction with analytes. In the chemical modification, chitosan is structurally altered by introducing carboxymethyl groups, producing carboxymethyl chitosan with improved solubility and functional properties. Both strategies aim to enhance the material’s sensing performance for use in SPR-based sensors.

Laser Feedback Interferometry

Laser Feedback Interferometry (LFI) is a promising interferometric sensing method that operates based on the self-mixing effect, where a laser beam emitted from the Vertical-Cavity Surface-Emitting Laser (VCSEL) is directed toward a target, and a portion of the reflected light re-enters the laser cavity. This optical feedback alters the laser’s output, which can be used to measure displacement, vibration, or velocity with high precision.

Known for its high sensitivity, compactness, and cost-effectiveness, LFI is used in real-time, non-contact measurements such as displacement, vibration, and velocity. At Photonics, research in LFI focuses on improving sensitivity, exploring advanced modulation schemes, and integrating the method with fiber-optic and smart sensing platforms for diverse applications.

This section illustrates the Laser Feedback Interferometry technique utilizing a VCSEL in a standard TO-46 package. In this configuration, the reflected signal can be detected in two ways: via a built-in photodiode (PD) within the TO-46 package, or without any external photodetector—by directly monitoring variations in the junction voltage of the laser. This dual detection capability enhances the versatility of the system, offering a simplified, compact, and cost-effective approach to high-resolution optical sensing. The TO-46 package serves as a robust and stable platform, providing precise alignment between components while maintaining a small footprint. Its integration of the VCSEL and PD in a single enclosure minimizes optical misalignment, reduces assembly complexity, and supports scalable manufacturing—making it especially suitable for real-time, embedded, or portable sensing applications.

LFI operates under different optical feedback regimes, determined by the amount of light reflected back into the laser cavity. These regimes—classified from weak to strong feedback—directly influence the amplitude, frequency, and waveform of the self-mixing signal. The figures illustrate how the signal evolves across feedback regimes, highlighting the distinct waveform characteristics associated with each regime. Furthermore, model fitting techniques applied to these signals allow for accurate estimation of system parameters, aiding in both sensor calibration and laser behavior analysis.

This work presents a proof-of-concept application of the Laser Feedback Interferometry technique for detecting electrocardiographic (ECG) signals using a customized electro-optic phase modulator. The feasibility of capturing surface biopotentials through the LFI approach was successfully demonstrated.

Given LFI’s capability to measure vibration and displacement at nanometer-scale resolution, the detection of myocardial signals—essentially subtle surface displacements—can be achieved through similar sensing principles. This highlights the potential of LFI as a non-contact, high-sensitivity method for biomedical diagnostics, particularly in cardiovascular monitoring applications.

Bakar, A.A.A., et al. (2013). On the feasibility of self-mixing interferometer sensing for detection of the surface electrocardiographic signal using a customized electro-optic phase modulator. Physiological Measurement, 34(2), 281–289.

Selected Published References | SPR*

[1] Hishamuddin, A. H., Zoolfakar, A. S., Azeman, N. H., Abu Bakar, M. H., Abdullah, F., Mohd Daniyal, W. M. E. M., A. Bakar, A. A., & Zolkapli, M. (2024). Integrative approach to fluorescence-based oxygen sensing in polymer optical fibers with surface plasmon resonance. Sensors and Actuators A: Physical, 379. https://doi.org/10.1016/j.sna.2024.115979

[2] Bakar, M. H. A., Azeman, N. H., Mobarak, N. N., Nazri, N. A. A., Mohd Daniyal, W. M. E. M., Zan, M. S. D., Mahdi, M. A., Zain, A. R. M., Gupta, R., Abdullah, F., Abdullah, F., & Bakar, A. A. A. (2024). Real-time cationic sensing using plasmonic fiber optic sensor based phosphoryl-carrageenan. Sensors and Actuators A: Physical, 377. https://doi.org/10.1016/j.sna.2024.115725

[3] Azeman, N. H., Zain, A. R. M., Daniyal, W. M. E. M. M., Jamil, M. S. M., Bakar, M. H. A., Nazri, N. A. A., Khushaini, M. A. A., Mokhtar, M. H. H., & Bakar, A. A. A. (2024). Zeolitic-Imidazolate Frameworks Enhanced Surface Plasmon Resonance Sensor for Organic Dyes Sensing. IEEE Sensors Journal, 24(16), 25617–25626. https://doi.org/10.1109/JSEN.2024.3421640

[4] Abu Bakar, M. H., Azeman, N. H., Mobarak, N. N., Nazri, N. A. A., Daniyal, W. M. E. M. M., Othman, M. Q., Abdullah, F., & Bakar, A. A. A. (2024). Uv–vis spectroscopy for simple chloride content analysis in edible oil using charged amino-functionalized carbon quantum dots fluorophore reagent. Spectrochimica Acta - Part A: Molecular and Biomolecular Spectroscopy, 317. https://doi.org/10.1016/j.saa.2024.124419

[5] Daniyal, W. M. E. M. M., Fen, Y. W., Abdullah, J., Bakar, A. A. A., & Mahdi, M. A. (2024). Sensitive and selective Cu2+ detection via surface plasmon resonance using ionophore decorated nanocrystalline cellulose-graphene oxide thin film. Sensors and Actuators A: Physical, 366.

https://doi.org/10.1016/j.sna.2023.114847

[6] Nazri, N. A. A., Azeman, N. H., Bakar, M. H. A., Mobarak, N. N., Masran, A. S., Zain, A. R. M., Mahdi, M. A., Saputro, A. G., Wung, T. D. K., Luo, Y., Luo, Y., & A. Bakar, A. A. (2024). Polymeric carbon quantum dots as efficient chlorophyll sensor-analysis based on experimental and computational investigation. Optics and Laser Technology, 170. https://doi.org/10.1016/j.optlastec.2023.110259

[7] Sulaiman, R., Azeman, N. H., Mokhtar, M. H. H., Mobarak, N. N., Abu Bakar, M. H., & Bakar, A. A. A. (2024). Hybrid ensemble-based machine learning model for predicting phosphorus concentrations in hydroponic solution. Spectrochimica Acta - Part A: Molecular and Biomolecular Spectroscopy, 304. https://doi.org/10.1016/j.saa.2023.123327

[8] Sulaiman, R., Azeman, N. H., Abu Bakar, M. H., Ahmad Nazri, N. A., Masran, A. S., & Ashrif A Bakar, A. (2023). Nitrate Classification Based on Optical Absorbance Data Using Machine Learning Algorithms for a Hydroponics System. Applied Spectroscopy, 77(2), 210–219. https://doi.org/10.1177/00037028221140924

[9] Ahmad Khushaini, M. A., Azeman, N. H., Tg Abdul Aziz, T. H., Bakar, A. A. A., De La Rue, R. M., Md Zain, A. R., Majlis, B. Y., & TH Tee, C. A. (2023). Third-order nonlinearity with subradiance dark-state in ultra-strong excitons and surface plasmon coupling using self-antiaggregation organic dye. Physica Scripta, 98(5). https://doi.org/10.1088/1402-4896/acc69b

[10] Abu Bakar, M. H., Azeman, N. H., Mobarak, N. N., Nazri, N. A. A., Sulaiman, R., Arsad, N., Mahdi, M. A., & A Bakar, A. A. (2022). Succinyl-carrageenan on a localised surface plasmon resonance fiber sensor for ammonium ion assays. Journal of Materials Chemistry C, 10(45), 17258–17265. https://doi.org/10.1039/d2tc02106d

*Full publication records are available on Scopus under Author ID (56926940300)

Selected Published References | LFI*

[1] Kashif, M., Bakar, A. A. A., & Hashim, F. H. (2016). Analysing surface plasmon resonance phase sensor based on Mach-Zehnder interferometer technique using glycerin. Optics Communications, 380, 419–424. https://doi.org/10.1016/j.optcom.2016.06.033

[2] Kliese, R., Taimre, T., Bakar, A. A. A., Lim, Y. L., Bertling, K., Nikolić, M., Perchoux, J., Bosch, T., & Rakić, A. D. (2014). Solving self-mixing equations for arbitrary feedback levels: A concise algorithm. Applied Optics, 17, 3723–3736. https://doi.org/10.1364/AO.53.003723

[3] Kashif, M., Bakar, A. A. A., Arsad, N., & Shaari, S. (2014). Development of phase detection schemes based on surface plasmon resonance using interferometry. Sensors (Switzerland), 14(9), 15914–15938. https://doi.org/10.3390/s140915914

[4] Bakar, A. A. A., Lim, Y. L., Wilson, S. J., Fuentes, M., Bertling, K., Taimre, T., Bosch, T., & Rakić, A. D. (2013). On the feasibility of self-mixing interferometer sensing for detection of the surface electrocardiographic signal using a customized electro-optic phase modulator. Physiological Measurement, 34(2), 281–289. https://doi.org/10.1088/0967-3334/34/2/281

*Full publication records are available on Scopus under Author ID (56926940300)

Team Members

This research theme brings together a multidisciplinary team of experts from the fields of chemistry, physics, and engineering. Each discipline plays a critical role in advancing Surface Plasmon Resonance technologies and Interferometry —whether through material design, optical modeling, or system integration. The collaboration across these domains fosters innovative approaches and comprehensive solutions in the development of high-performance sensing platforms and systems.

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