SAJID FAROOQ

SAJID FAROOQ

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Recognition of breast cancer subtypes using FTIR hyperspectral data
2024 - FAROOQ, SAJID; DEL-VALLE, MATHEUS; SANTOS, SOFIA N. dos; BERNARDES, EMERSON S.; ZEZELL, DENISE M.
Fourier -transform infrared spectroscopy (FTIR) is a powerful, non-destructive, highly sensitive and a promising analytical technique to provide spectrochemical signatures of biological samples, where markers like carbohydrates, proteins, and phosphate groups of DNA can be recognized in biological micro -environment. However, method of measurements of large cells need an excessive time to achieve high quality images, making its clinical use difficult due to speed of data -acquisition and lack of optimized computational procedures. To address such challenges, Machine Learning (ML) based technologies can assist to assess an accurate prognostication of breast cancer (BC) subtypes with high performance. Here, we applied FTIR spectroscopy to identify breast cancer subtypes in order to differentiate between luminal (BT474) and nonluminal (SKBR3) molecular subtypes. For this reason, we tested multivariate classification technique to extract feature information employing three -dimension (3D) -discriminant analysis approach based on 3D -principle component analysis -linear discriminant analysis (3D-PCA-LDA) and 3D -principal component analysis -quadratic discriminant analysis (3D-PCA-QDA), showing an improvement in sensitivity (98%), specificity (94%) and accuracy (98%) parameters compared to conventional unfolded methods. Our results evidence that 3D-PCALDA and 3D-PCA-QDA are potential tools for discriminant analysis of hyperspectral dataset to obtain superior classification assessment.
Bridging the gap
2024 - HABIB, MUHAMMAD; MUHAMMAD, ZAHIR; HALEEM, YASIR A.; FAROOQ, SAJID; NAWAZ, RAZIQ; KHALIL, ADNAN; SHAHEEN, FOZIA; NAEEM, HAMZA; ULLAH, SAMI; KHAN, RASHID
Layered transition metal dichalcogenides (TMDCs) have garnered immense interest in supercapacitor energy storage applications. Despite the growing reports on TMDCs in the context of electrochemical supercapacitor studies, the prevailing use of carbon-based additives often obscures their correct analysis and overshadows their intrinsic behavior. In this work, we meticulously analyzed supercapacitor characteristics of distinct TMDC materials without using carbon or any other conductive, revealing their pure intrinsic behavior, specifically focusing on highly crystalline 2H phase tantalum (Ta), tungsten (W) and zirconium (Zr)-based TMDCs, grown using the chemical vapor transport (CVT) technique. The grown materials were characterized using cutting-edge techniques like X-ray diffraction (XRD), Raman spectroscopy, and high-resolution transmission electron microscopy (HRTEM), ensuring a comprehensive perspective of the synthesized TMDCs. To delve into the electrochemical properties of the prepared electrodes, extensive analysis using cyclic voltammetry (CV), galvanostatic charge-discharge (GCD) and electrochemical impedance spectroscopy (EIS) was performed. The obtained results were further supported with density functional theory (DFT) calculations to get insights regarding the charge transfer mechanism and electronic density distribution proximate to the Fermi levels. The synergy between the experimental results and theoretical calculations significantly improved the validity of our findings, thus probing the comprehension and optimization avenues of TMDCs for superior supercapacitor performance.
Quantitative analysis of high performance plasmonic metamolecules for targeted deep tissues applications
2023 - FAROOQ, SAJID; RATIVA, DIEGO; ARAUJO, RENATO E. de
Rationally designed gold nanoparticles (Au NPs) show a great potential for biomedical applications. Specifically, for optically induced heating of deep tissues facilitated by plasmonic-assisted lasers, nanostructures with high optical absorption coefficient in biological window are required. Plasmonic metamolecules, such as gold nanodimers (NDs), exhibit a robust localized field enhancement with strong infrared optical absorption. However, an exclusive investigation of the optical/ thermal features of high-performance Au NDs for optical infrared heating remains a challenge. Here, we focus on Au NDs for optothermal characteristics in deep tissues heating procedures. Our analysis encompasses parameters such as absorption cross-sections, field enhancement, and temperature rise with a systematic methodology selecting optimal NDs. Our findings reveal a non-uniform spatial distribution of temperature at the nano-scale and show that short-pulsed laser excitation enhances the temperature near the dimer’s junction. Remarkably, when compared to monomeric gold nanorods under the same excitation resonance mode, optically generated heating of Au NDs leads a threefold higher temperature increase. These results evidence valuable insights for using Au NDs as efficient plasmonic nanoheaters in photothermal-assisted applications.
Diabetes monitoring through urine analysis using ATR-FTIR spectroscopy and machine learning
2023 - FAROOQ, SAJID; ZEZELL, DENISE M.
Diabetes mellitus (DM) is a widespread and rapidly growing disease, and it is estimated that it will impact up to 693 million adults by 2045. To cope this challenge, the innovative advances in non-destructive progressive urine glucose-monitoring platforms are important for improving diabetes surveillance technologies. In this study, we aim to better evaluate DM by analyzing 149 urine spectral samples (86 diabetes and 63 healthy control male Wistar rats) utilizing attenuated total reflection–Fourier transform infrared (ATR-FTIR) spectroscopy combined with machine learning (ML) methods, including a 3D discriminant analysis approach—3D–Principal Component Analysis–Linear Discriminant Analysis (3D-PCA-LDA)—in the ‘bio-fingerprint’ region of 1800–900 cm−1 . The 3D discriminant analysis technique demonstrated superior performance compared to the conventional PCA-LDA approach with the 3D-PCA-LDA method achieving 100% accuracy, sensitivity, and specificity. Our results show that this study contributes to the existing methodologies on non-destructive diagnostic methods for DM and also highlights the promising potential of ATR-FTIR spectroscopy with an ML-driven 3D-discriminant analysis approach in disease classification and monitoring.
Rapid identification of breast cancer subtypes using micro-FTIR and machine learning methods
2023 - FAROOQ, SAJID; DEL-VALLE, MATHEUS; SANTOS, MOISES O. dos; SANTOS, SOFIA N. dos; BERNARDES, EMERSON S.
Breast cancer (BC) molecular subtypes diagnosis involves improving clinical uptake by Fourier transform infrared (FTIR) spectroscopic imaging, which is a non-destructive and powerful technique, enabling label free extraction of biochemical information towards prognostic stratification and evaluation of cell functionality. However, methods of measurements of samples demand a long time to achieve high quality images, making its clinical use impractical because of the data acquisition speed, poor signal to noise ratio, and deficiency of optimized computational framework procedures. To address those challenges, machine learning (ML) tools can facilitate obtaining an accurate classification of BC subtypes with high actionability and accuracy. Here, we propose a ML-algorithmbased method to distinguish computationally BC cell lines. The method is developed by coupling the K-neighbors classifier (KNN) with neighborhood components analysis (NCA), and hence, the NCA-KNN method enables to identify BC subtypes without increasing model size as well as adding additional computational parameters. By incorporating FTIR imaging data, we show that classification accuracy, specificity, and sensitivity improve, respectively, 97.5%, 96.3%, and 98.2%, even at very low co-added scans and short acquisition times. Moreover, a clear distinctive accuracy (up to 9 %) difference of our proposed method (NCA-KNN) was obtained in comparison with the second best supervised support vector machine model. Our results suggest a key diagnostic NCA-KNN method for BC subtypes classification that may translate to advancement of its consolidation in subtype-associated therapeutics.
Thermo-optical performance of bare laser-synthesized TiN nanofluids for direct absorption solar collector applications
2023 - FAROOQ, SAJID; VITAL, CAIO V.P.; TIKHONOWSKI, GLEB; POPOV, ANTON A.; KLIMENTOV, SERGEY M.; MALAGON, LUIS A.G.; ARAUJO, RENATO E. de; KABASHIN, ANDREI V.; RATIVA, DIEGO
Titanium nitride (TiN) nanoparticles (NPs) look very promising for solar energy harvesting owing to a strong plasmonic absorption with the maximum in the near-infrared range. However, the synthesis of TiN nanofluids is very challenging as one has to combine the plasmonic feature and long-term colloidal stability to withstand harsh conditions of direct absorption solar collectors (DASC). Here, we explore solutions of bare (ligand free) TiN NPs synthesized by pulsed laser ablation in acetone as the nanofluid. We show that such NPs are low size-dispersed (mean size 25 nm) and exhibit a broad absorption peak around 700 nm, while their negative charge ensures a prolonged electrostatic stabilization of solutions. Solar weighted absorption coefficient of such TiN nanofluids reaches 95.7% at very low volume fractions (1.0 × 10−5), while nanofluid temperature can be increased up to 29 °C under 1.25-sun illumination. Our data evidence that the thermal efficiency of a DASC using TiN nanofluid is 80% higher compared to Au-based counterparts. The recorded high photothermal efficiency and excellent colloidal stability of TiN nanofluids promises a major advancement of DASC technology, while laser-ablative synthesis can offer easy scalability and relative cost-efficiency required for the implementation of systems for solar energy harvesting.
Selecting plasmonic nanoshells for colorimetric sensors
2023 - BALTAR, RAPHAEL M.S.M.; FAROOQ, SAJID; ARAUJO, RENATO E. de
In this work, the use of gold and silver nanoshells was evaluated as a starting point for the establishment of colorimetric sensor platforms. The sensitivity and linearity of the nanoplatforms (SiO2 core–metallic shell nanoparticles) were assessed under the influence of the nanoshell configuration, color space, and light source illuminant. A computational procedure for selecting high-performance plasmonic colorimetric sensor platforms is described. The evaluation methodology involves considering five different color spaces and 15 different color components. By exploring crucial figures of merit for sensing, the performance of the plasmonic nanoplatforms was evaluated, exploring Mie theory. We determined that gold nanoshells are highly efficient on colorimetric sensing, while silver nanoshells are a better choice for spectroscopic sensors. Plasmonic nanoplatforms based on nanoshells with 10 nm SiO2 core radii and 5 nm thick Au shells presented sensitivity values up to 4.70 RIU−1 , considering the hue angle of the HSV color space. Color variation of up to 40% was observed, due to the adsorption of a 10 nm thick molecular layer on the gold nanoshell surface. In the search for advances in colorimetric biosensors, the optimization approach used in this work can be extended to different nanostructures.
Selecting high-performance gold nanorods for photothermal conversion
2022 - PEDROSA, TULIO de L.; FAROOQ, SAJID; ARAUJO, RENATO E. de
In this work, we establish a new paradigm on identifying optimal arbitrarily shaped metallic nanostructures for photothermal applications. Crucial thermo-optical parameters that rule plasmonic heating are appraised, exploring a nanoparticle size-dependence approach. Our results indicate two distinct figures of merit for the optimization of metallic nanoheaters, under both non-cumulative femtosecond and continuum laser excitation. As a case study, gold nanorods are evaluated for infrared photothermal conversion in water, and the influence of the particle length and diameter are depicted. For non-cumulative femtosecond pulses, efficient photothermal conversion is observed for gold nanorods of small volumes. For continuous wave (CW) excitation at 800 nm and 1064 nm, the optimal gold nanorod dimensions (in water) are, respectively, 90 × 25nm and 150 × 30 nm. Figure of Merit (FoM) variations up to 700% were found considering structures with the same peak wavelength. The effect of collective heating is also appraised. The designing of high-performance plasmonic nanoparticles, based on quantifying FoM, allows a rational use of nanoheaters for localized photothermal applications.
Tailoring the scattering response of optical nanocircuits using modular assembly
2022 - FAROOQ, SAJID; SHAFIQUE, SHAREEN; AHSAN, ZISHAN; CARDOZO, OLAVO; WALI, FAIZ
Owing to the localized plasmon resonance of an ensemble of interacting plasmonic nanoparticles (NPs), there has been a tremendous drive to conceptualize complex optical nanocircuits with versatile functionalities. In comparison to modern research, there is still not a sufficient level of sophistication to treat the nanostructures as lumped circuits that can be adjusted into complex systems on the basis of a metatronic touchstone. Here, we present the design, assembly, and characterization of single relatively complex photonic nanocircuits by accurately positioning several metallic and dielectric nanoparticles acting as modular lumped elements. In this research, Au NPs along with silica NPs were used to compare the proficiency and precision of our lumped circuit model analytically. On increasing the size of an individual Au NP, the spectral peak resonance not only modifies but also causes more scattering efficiency which increases the fringe capacitance linearly and decreases the nanoinductance of lumped circuit element. The NPs-based assembly induced the required spectral resonance ascribed by simple circuit methods and are depicted to be actively reconfigurable by tuning the direction or polarization of input signals. Our work demonstrates a vital step toward developing the modern modular designing tools of complex electronic circuits into nanophotonic-related applications.
High performance blended nanofluid based on gold nanorods chain for harvesting solar radiation
2023 - FAROOQ, SAJID; RATIVA, DIEGO; SAID, ZAFAR; ARAUJO, RENATO E. de
Colloids composed of metallic nanoparticles are promising working fluids for solar radiation harvesting using Direct Absorption Solar Collectors (DASC), due to a high thermal conductivity characteristic and a broad optical absorption that can be tuned to match the solar spectrum. Recently, different studies report gold nanorod (Au-NR) chains for biosensing and photothermal applications, which have broadband and high absorption cross-section and potential possibilities to orientate the nanoparticle using electromagnetic fields. Moreover, colloids with nanoparticles blended configuration show an efficient solar radiation absorption characteristics. Here, working fluids for DASC based on gold nanorod chains in an unblended and blended configuration are evaluated using numerical simulations. The results indicate that the solar absorption increases proportional to the size of the Au-NR assembly, and the best configuration is obtained for a tetramer structure. By using different blended arrangements such as single Au monomers, dimers, trimmers, and tetramers nanorods, it is possible to obtain solar weighted absorption coefficients close to an ideal solar thermal collector, even obtained at low volume fraction (1×10(−5)). Moreover, the results show an enhancement of the temperature of 58.45 °C for tetramer compared with a monomer structure, both under one sun excitation. Therefore, the Au-NR assembly shows a high potentiality to be explored as a high-performance working fluid for solar thermal collectors.

SAJID FAROOQ

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