Department of Mechanical Engineering

Permanent URI for this collectionhttps://hdl.handle.net/10315/37650

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Access status: Open Access ,
Hardware-in-the-loop emulation for 6-DOF free-floating spacecraft using active gravity compensation with a collaborative robot
(Elsevier, 2026-05-28) Jahanshahi, Hadi
This technical note presents a hardware-in-the-loop testbed that uses a UR10e collaborative robot to emulate 6-DOF free-floating spacecraft motion through active gravity compensation. Experimental validations across all three Cartesian axes demonstrated high translational fidelity with a mean speed correlation of 0.9992 between the measured robot trajectory and an independently initialized rigid-body simulation, low residual forces below the controller deadband, and minor rotational errors of 2° to 6° attributed to kinematic coupling through the robot joint structure. The platform provides a cost-effective testbed for ground-based emulation of free-floating spacecraft dynamics.
Access status: Open Access ,
A comprehensive review of tactile sensing technologies in space robotics
(Elsevier, 2025-01-23) Jahanshahi, Hadi; Zhu, Zheng Hong
This review explores the current state and future prospects of tactile sensing technologies in space robotics, addressing the unique challenges posed by harsh space environments such as extreme temperatures, radiation, microgravity, and vacuum conditions, which necessitate specialized sensor designs. We provide a detailed analysis of four primary types of tactile sensors: resistive, capacitive, piezoelectric, and optical, evaluating their operating principles, advantages, limitations, and specific applications in space exploration. Recent advancements in materials science, including the development of radiation-hardened components and flexible sensor materials, are discussed alongside innovations in sensor design and integration techniques that enhance performance and durability under space conditions. Through case studies of various space robotic systems, such as Mars rovers, robotic arms like Canadarm, humanoid robots like Robonaut, and specialized robots like Astrobee and LEMUR 3, this review highlights the crucial role of tactile sensing in enabling precise manipulation, environmental interaction, and autonomous operations in space. Moreover, it synthesizes current research and applications to underscore the transformative impact of tactile sensing technologies on space robotics and highlights their pivotal role in expanding human presence and scientific understanding in space, offering strategic insights and recommendations to guide future research and development in this critical field.
Access status: Open Access ,
Comprehensive review of swarm intelligence for space robotics
(Elsevier, 2026-06-26) Zhang, Zixuan; Zhu, Zhang Hong
Swarm intelligence has emerged as a transformative paradigm for autonomous space robotics, enabling scalable, robust, and adaptive behaviors through decentralized coordination of multiple agents. Inspired by collective phenomena in nature, swarm intelligence provides solutions to the challenges of extreme space environments, where resilience, autonomy, and fault tolerance are crucial. This review explores recent advances in the modeling, control, and validation of swarm-based space robotic systems. Mathematical frameworks ranging from single- and double-integrator dynamics to orbital swarm dynamics are examined, alongside formation control strategies such as consensus-based, leader–follower, virtual structure, and behavior-based approaches. The review covers swarm controllability, scalability, and performance metrics, highlighting trade-offs between efficiency, robustness, and computational complexity. Emerging optimization paradigms, including bio-inspired algorithms, hybrid global-local strategies, and multi-objective optimization, are surveyed for their applicability to mission-critical tasks such as debris removal, and distributed satellite constellations. The review also investigates numerical simulation platforms and experimental testbeds associated with swarm intelligence, highlighting their role in bridging the gap between theory and deployment. Case studies of current and proposed space missions illustrate the transition of swarm intelligence from conceptual design to operational reality, while trends in reinforcement learning, blockchain integration, and large language model-guided swarms signal future research directions. By consolidating theoretical foundations, experimental progress, and mission applications, this paper outlines the opportunities and challenges of harnessing swarm intelligence for future space exploration and infrastructure.
Access status: Open Access ,
Review of machine learning in robotic grasping control in space application
(Elsevier, 2024-04-15) Jahanshahi, Hadi; Zhu, Zheng Hong
This article presents a comprehensive survey of the integration of machine learning techniques into robotic grasping, with a special emphasis on the challenges and advancements for space applications. The incorporation of artificial intelligence, particularly through deep learning, reinforcement learning, transfer learning, convolutional neural networks and recurrent neural networks, has significantly revolutionized robotic grasping. These advancements facilitate autonomous, efficient, and sophisticated manipulation in the challenging environment of outer space, transitioning from traditional mechanical grippers to sophisticated systems powered by advanced algorithms. This transition highlights the critical integration of sensory perception, grasp planning, and execution mechanisms, enhancing robots' capabilities to perceive, interact with, and manipulate objects with unprecedented precision and adaptability. The article meticulously outlines significant advancements achieved through the deployment of convolutional neural networks for visual information processing, RNNs for sequential decision-making, RL for autonomous strategy refinement, and transfer learning for leveraging pre-learned knowledge in novel tasks. These technologies address the unique challenges of space environments, such as varied textures, occlusions, microgravity conditions, and the sim-to-real gap, by enhancing sample efficiency, improving sim-to-real transfer capabilities, and integrating multimodal data for better object localization and pose estimation. Furthermore, the review explores the specific challenges faced in space robotic grasping, including handling varied textures and occlusions, adapting to unpredictable conditions, achieving real-time processing, and ensuring safety and reliability. It proposes future research directions focused on overcoming these hurdles, such as enhanced generalization through multimodal learning, robust sim-to-real transfer techniques, and the development of collaborative robotics and swarm intelligence. Critical to the development of ML models for robotic grasping are the roles of specialized datasets and simulation environments. Datasets like the Cornell Grasping Dataset and the Yale-CMU-Berkeley Object, along with simulation platforms such as Gazebo and PyBullet, provide essential resources for training, testing, and refining ML models. These tools enable researchers to simulate complex robotic systems and interactions within realistic environments, fostering rapid iterations on design and control strategies. In summary, this article offers in-depth insights into the progress, current challenges, and future prospects of machine learning techniques in robotic grasping for space exploration. It showcases significant strides made in the field and charts a path forward, emphasizing the need for innovative solutions to navigate the complexities of robotic manipulation in outer space. Through the strategic integration of advanced ML techniques, the development of adaptable and efficient robotic systems for space applications continues to advance, promising to unlock new possibilities in space exploration and beyond.
Access status: Open Access ,
Uncertainty propagation networks for neural ordinary differential equations
(Elsevier, 2026-02-23) Jahanshahi, Hadi; Zhu, Zheng Hong
This paper introduces Uncertainty Propagation Network (UPN), a novel family of neural differential equations that naturally incorporate uncertainty quantification into continuous-time modeling. Unlike existing neural ordinary differential equations (neural ODEs) that predict only state trajectories, UPN simultaneously models both state evolution and its associated uncertainty by parameterizing coupled differential equations for mean and covariance dynamics. The architecture is grounded in Gaussian moment closure approximation, which enables efficient analytical uncertainty propagation through nonlinear dynamics without requiring stochastic sampling or ensemble methods. UPN supports two operational modes: pure prediction from initial conditions, and adaptive filtering with sparse measurement updates when observations become available during the prediction horizon. The continuous-depth formulation provides principled uncertainty quantification in a single forward pass, handles irregularly-sampled observations naturally, and adapts evaluation strategy to each input’s complexity. Experimental results demonstrate UPN’s effectiveness across multiple domains: (1) four canonical non-chaotic dynamical systems achieve near-perfect 96.7 % confidence interval coverage with single-point Markovian initialization; (2) chaotic Lorenz attractor modeling maintains 94.5 % calibration while correctly capturing exponential uncertainty growth in a fully Markovian framework; (3) real-world CubeSat trajectory prediction achieves 89.6 % error reduction through integrated measurement updates; and (4) time-series forecasting on the ETTh1 benchmark dataset demonstrates 14 % improved accuracy and 6.6 × faster inference compared to Neural Stochastic Differential Equations (Neural SDEs). These gains stem from UPN’s analytical distribution evolution, which provides superior computational efficiency and calibration compared to sampling-based approaches.
Access status: Open Access ,
A comprehensive survey of space robotic manipulators for on-orbit servicing
(Frontiers Media, 2024-10-09) Alizadeh, Mohammad; Zhu, Zheng Hong
On-Orbit Servicing (OOS) robots are transforming space exploration by enabling vital maintenance and repair of spacecraft directly in space. However, achieving precise and safe manipulation in microgravity necessitates overcoming significant challenges. This survey delves into four crucial areas essential for successful OOS manipulation: object state estimation, motion planning, and feedback control. Techniques from traditional vision to advanced X-ray and neural network methods are explored for object state estimation. Strategies for fuel-optimized trajectories, docking maneuvers, and collision avoidance are examined in motion planning. The survey also explores control methods for various scenarios, including cooperative manipulation and handling uncertainties, in feedback control. Additionally, this survey examines how Machine learning techniques can further propel OOS robots towards more complex and delicate tasks in space.
Access status: Open Access ,
Fatigue behavior and electromechanical properties of additively manufactured continuous wire polymer composites for structural health monitoring
(Wiley, 2022-06-29) Saleh, MA; Kempers, R; Melenka, GW
The fatigue behaviour of continuous wire polymer composite (CWPC) fabricated by fused filament fabrication was investigated. Four compositions were examined: polylactic acid (PLA), PLA with copper wire (Cu), thermoplastic polyurethane (TPU), and TPU with Cu wire. Residual properties were measured after different sets of number of cycles (102, 104, 105). CWPC electromechanical properties under fatigue test demonstrated reverse piezoresistivity behavior. A strain-controlled fatigue life analytical model was compared to the experimental results showing good agreement. This study demonstrates the applicability of FFF technique to print sensors with continuous integrated wire with tunable properties.
Access status: Open Access ,
Investigation of Secondary (Dean) Flows in Curved Microchannels and Application to Microparticle Manipulation in Various Fluids
(2023-08-04) Nikdoost, Arsalan; Rezai, Pouya
Separation, solution exchange, and detection of microparticles and microorganisms, such as DNA, bacteria, and cancer cells are essential steps in a wide range of biomedical applications. Conventional methods such as centrifugation and mechanical filtration rely on laborious processes and deal with the possibility of damaging particles and cells. Microfluidic methods such as inertial manipulation of particles in microchannels, on the other hand, offer low cost and fast sample processing down to the single cell manipulation and detection level. The Dean flow-coupled inertial and elasto-inertial systems, taking advantage of secondary vortices lateral to the direction of the flow in curved microchannels, have provided an improved level of precision over particle separation throughput compared to straight channels. However, the dynamics of fluid flow and particle focusing in fluids with various rheological characteristics like blood and milk still requires a thorough fundamental investigation. In this thesis, we attempt to fully investigate the control parameters of both fluids and particles in a curvilinear microchannel, with an aim to provide fundamental understanding of the fluid dynamics and particle focusing in various aqueous microenvironments, with a focus on non-Newtonian fluids. In objective 1 of the thesis, we focused on understanding the physics of the secondary Dean flow of viscoelastic fluids and shear-thickening nanofluids in curved microchannels. Various parameters such as channel dimensions and fluid properties were investigated to obtain a comprehensive knowledge of the secondary vortices. Two empirical correlations were developed for the average Dean velocity (VDe) of viscoelastic PEO solutions and SiO2 nanofluids, which significantly reduced the prediction error compared to the existing water-based VDe correlations in the literature. In objective 2, the particle dynamics in Dean-coupled elasto-inertial systems were experimentally investigated to understand the effects of different channel geometries and fluid viscosity on particle focusing behavior in curved microchannels. In objective 3, we demonstrated a proof-of-concept duplex particle washing process in viscoelastic PEO solutions. The developed knowledge of particle and fluid interactions in Dean-coupled elasto-inertial systems could be vital in various biomedical applications that require a target particle washing process. In objective 4, for the first time, we presented the particle behavior analysis in SiO2 nanofluids and investigated the effects of channel curvature, fluid axial velocity, and viscosity on particles focusing at the channel outlet. Our investigations could be utilized to enhance the throughput and efficiency of microdevices to address real life challenges in microparticle purification and detection in fluids with various rheological properties.
Access status: Open Access ,
Fiber identification of braided composites using micro-computed tomography
(Elsevier, 2021-06-02) Melenka, Garrett W.; Gholami, Ali
Braided composites contain interwoven fibers that are embedded in a matrix material. Advanced measurement methods are required to accurately measure and characterize braided composites due to their interwoven composition. Micro-computed tomography (μCT) is an X-ray based measurement method that allows for the internal structure of objects to be examined. High-resolution μCT of braided composites allows for their internal geometry to be accurately measured. Braid samples were measured with a voxel size of 1.0 μm3, which resulted in a field of view of 4.904 x 4.904 x 3.064 mm3. With this field of view, individual fibers within the braid yarns could be identified and measured. The scientific visualization software package Avizo and the XFiber extension was used to identify and measure braid yarn fibers from the collected μCT measurements. Fiber properties such as orientation angles (ϕ and θ), curved fiber length, tortuosity, and fiber diameter were obtained. Additionally, finite element mesh geometries of the braid yarns within a braided structure were created. The presented methodology provides a roadmap for the accurate modeling of braided composite unit cell geometries using high-resolution μCT data.
Access status: Open Access ,
Experimental evaluation of carbon fibre, fibreglass and aramid tubular braided composites under combined tension-torsion loading
(Elsevier, 2021-08-01) Armanfard, Abbas; Melenka, Garrett W.
Braided composites are a class of composite materials that feature an inter-woven structure that improves structural stability and damage tolerance. Presently, braided composites under tension and torsion loading have been studied individually. Mechanical behaviour of braided composites under combined tension–torsion loading is common and therefore requires investigation. In this study, mechanical properties of carbon fibre, fibreglass and aramid 2D tubular braided composites (TBCs) were assessed and compared under coupled tension–torsion loading. The plane stress theory investigated the failure mechanism of braids. A contact-free three-dimensional digital image correlation (3D DIC) technique was used to derive detailed and continuous strain maps and understand the buckling behaviour of TBCs.
Access status: Open Access ,
Finite element analysis of 2-D tubular braided composite based on geometrical models to study mechanical performances
(Taylor & Francis, 2021-11-21) Gholami, Ali; Melenka, Garrett W.
Tubular Braided Composites (TBC) have a higher strength to weight ratio than conventional materials and better mechanical properties compared to laminated composite materials. The optimization of the TBC and the introduction of new applications requires a comprehensive understanding of TBC’s behavior. One efficient way to study the behavior of TBC is using Finite Element Modeling (FEM). This paper will introduce a method for generating geometrical models with different patterns and variables. Micro Computed-Tomography (μCT) is also used for generating an actual 3-D model of a TBC. The geometrical model and the μCT models are visually compared. The geometrical model is inputted into the FEM software package and is studied in different conditions. Finally, the result of FEM is compared against experimental and analytical results.
Access status: Open Access ,
A Comparative Study on the Electromechanical Properties of 3D-Printed Rigid and Flexible Continuous Wire Polymer Composites for Structural Health Monitoring
(Elsevier, 2021-09-01) Saleh, M.A.; Kempers, R.; Melenka, GW
In this study, the electromechanical properties of two different three-dimensional (3D) printed continuous wire polymer composites (CWPC) were characterized and compared. The two composite materials were copper wire polylactic acid (PLA) composite (rigid material) and copper wire polyurethane (PU) composite (flexible material). The electromechanical measurements were based on piezoresistive properties of the sensor at which the mechanical strain and the electrical resistance were correlated under a uniaxial loading condition. Both types of materials exhibited a direct linear relationship between the two quantities, indicating the ability of CWPC to be used for strain sensing applications. The gauge factor (GF) sensitivity was compared for the two types of materials. It was found that there is no statistical significance difference between the GF of PLA CWPC (1.36 ± 0.14) and PU CWPC (1.29 ± 0.07)); therefore, the sensing property depends mainly on the wire integrated into the 3D-printed structure rather than the matrix. Thus, different matrices can be used to fit different applications. An analytical model for GF showed agreement with the experimental results for both materials. PU CWPC showed significant improvement in both Young’s modulus (E) and ultimate tensile strength (UTS) (210.5 % and 31.86 %, respectively), compared with pure PU, while the change in Poisson’s ratio (ν) was insignificant. Young’s modulus of PLA CWPC was significantly increased by 80.3 % compared with PLA, while UTS and ν did not significantly change. The experimental mechanical properties showed good agreement with data from the analytical models. The outcome of this study focused on the manufacturing of 3D-printed functionalized structure for strain sensing applications with improved mechanical properties. The wide range of attained strain allowed their use in different applications based on the range of strain needed, such as rigid sports equipment and flexible wearable sensors.
Access status: Open Access ,
Micro-computed tomography analysis of tubular braided composites
(Elsevier, 2015-06-22) Melenka, Garrett W; Lepp, Eric; Cheung, Benjamin KO; Carey, Jason
Two dimensional (2D) tubular braided composites consist of textile fibers imbedded in a resin matrix. Braid geometry and void content will affect the mechanical behavior of the tubular braided composite samples. In this study, tubular braid samples were assessed using micro X-ray computed tomography (μCT) to evaluate sample porosity/void content and to identify the strand geometry of the reinforcing fibers. The process described in this manuscript can be used to assess the quality and consistency of the tubular braided composite manufacturing process.
Access status: Open Access ,
Characterization of open-cellular polymeric foams using micro-computed tomography
(Elsevier, 2022-08-12) Timpano, Cristofaro; Abdoli, Hossein; Leung, Siu Ning; Melenka, Garrett W.
Utilization of Polyvinylidene fluoride (PVDF) open-cellular foam allows for the creation of high-efficiency Triboelectric nanogenerators (TENG). The micro-structure of TENG devices can be problematic to characterize accurately using conventional methods like scanning electron microscope (SEM). This work aims to provide a methodology in which representative 3D measurements can be made on open-cellular PVDF foams. Open-cell PVDF foams were produced through a salt-leeching procedure. Analysis of the PVDF foams was done by imaging the sample through a desktop micro-computed tomography (μ-CT) machine to allow for a full 3D dataset to be obtained. Foams were produced with salt sizes of 250–500 μm, 106–250 μm, 53–106 μm, and <53 μm to explore the capabilities of the segmentation procedure at identifying the microstructure of the foam. Images were segmented and analyzed to calculate the porosity, sample volume, pore volume and surface area. Results from μ-CT analysis were compared to that from a SEM, which is currently the most widely used method for assessing open foam PVDF structures. Results from the μ-CT when quantifying pore dimensions proved to be much more representative than SEM due to its ability to capture the entire volume of the foam rather than a single plane. These techniques can be used as the baseline for further verification and improvement the manufacturing of PVDF foam structures.
Access status: Open Access ,
Flexural testing of cellulose fiber braided composites using three dimensional digital image correlation
(Elsevier, 2019-10-15) Unlusoy, Can; Melenka, Garrett W.
Braided composites consist of woven fibers embedded within a matrix material. Braided structures are commonly produced using conventional materials such as carbon, glass and aramid fibers. However, natural fibers and bio-based resins may also be utilized with this manufacturing process. In this work, the flexural properties of tubular braid structures produced using bio-based materials was investigated. Braid samples were assessed using a contact free three dimensional digital image correlation (3D DIC) technique to assess the strain fields that occur in the samples due to applied flexural loads. Additionally, the bio-based structures were evaluated using micro-computed tomography (µCT) to assess the cross-sectional geometry and void content of the produced samples.
Access status: Open Access ,
Advanced Measurement Techniques for Braided Composite Structures: A Review of Current and Upcoming Trends
(Sage, 2020-04-15) Melenka, Garrett
Braiding is an advanced textile manufacturing method that is used to produce two dimensional (2D) and three dimensional (3D) components. Unlike a laminated structures braids have interlaced yarns that forms a continuity between layers. This structure allows for improved impact resistance, damage tolerance and improved through-thickness reinforcement. Despite the numerous advantages of braided composites, braids also have shortcomings. Their highly complex fiber architecture presents challenges in the availability and choice of the strain measuring and characterization techniques. Advanced measurement methods such as optical strain measurement, micro-computed tomography, and in-situ strain measurement are required. Optical strain measurement methods such as digital image correlation and high speed imaging are necessary to accurately measure the complex deformation and failure that braided composites exhibit. X-ray based micro-computed tomography measurements can provide detailed geometric and morphologic information for braided structures which is necessary for accurately predicting the mechanical properties of braided structures. Finally, in-situ strain measurement methods will provide detailed information on the internal deformation and strain that exists within braided structures. In-situ sensors will also allow for in-service health monitoring of braided structures. This paper provides a detailed review of the aforementioned sensing technologies and their relation to the measurement of braided composite structures.
Access status: Open Access ,
Stability and control of radial deployment of electric solar wind sail
(Springer Nature, 2021-01-05) Li, Gangqiang; Zhu, Zheng H.; Du, Chonggang
The paper studies the stability and control of radial deployment of an electric solar wind sail with the consideration of high-order modes of elastic tethers. The electric solar wind sail is modeled by combining the flexible tether dynamics, the rigid-body dynamics of central spacecraft, and the flexible-rigid kinematic coupling. The tether deployment process is modeled by the nodal position finite element method in the arbitrary Lagrangian–Eulerian framework. A symplectic-type implicit Runge–Kutta integration is proposed to solve the resulting differential–algebraic equation. A proportional–derivative control strategy is applied to stabilize the central spacecraft’s attitudes to ensure tethers’ stable deployment with a constant spinning rate. The results show the electric solar wind sail requires thrust at remote units in the tangential direction to counterbalance the Coriolis forces acting on the tethers and remote units to deploy tethers radially successfully. The parametric analysis shows the tether deployment speed and the thrust magnitude significantly impacts deployment stability and tether libration, which opens the possibility of successful deployment of tethers by using optimal control. Finally, the analysis results show that radial deployment is advantageous due to the isolated deployment mechanism, and a jammed tether can be isolated from affecting the deployment of rest tethers.
Access status: Open Access ,
Three-Dimensional High-Fidelity Dynamic Modeling of Tether Transportation System with Multiple Climbers
(American Institute of Aeronautics and Astronautics, 2019-03-04) Zhu, Zheng H.; Li, Gangqiang; Shi, Gefei
This paper studies the dynamics of a tether transportation system by the nodal position finite element method in the framework of an arbitrary Lagrangian–Eulerian description. Material coordinate is introduced as a state variable that is decoupled with the position coordinate. The movement of climbers is represented by moving nodes associated with the material coordinates. It is integrated into the finite element method by a variable-length tether together with a process of dividing and merging elements. The dynamic behavior of the tether transportation system with multiple climbers is studied. The results show that the elastic-flexible tether model is able to capture the high-frequency oscillation of the tether transportation system. The oscillation could have an adverse effect on the safe operation of the tether transportation system, especially in causing fatigue failure of the tether, and must be considered.
Access status: Open Access ,
Flight Dynamics and Control Strategy of Electric Solar Wind Sails
(American Institute of Aeronautics and Astronautics, 2019-11-27) Zhu, Zheng H.; Li, Gangqiang; Du, Chonggang
This paper studies the flight dynamics and control strategy for electric solar wind sails based on the nodal position finite element method, where the coupling effects between tether dynamics and the electrical field are considered. A modified throttling control strategy is proposed to control the attitude of electric sails by modulating individual tether voltage synchronously with the spinning motion of the sails. The effects of four critical physical parameters (tether numbers, tether length, sail spin rate, and mass of remote units) are investigated. The results show that the effect of the relative velocity of the solar wind has a significant effect on the spin rate of the sail in attitude maneuvering, which in turn affects the attitude dynamics and orbit motion of the sail. Numerical results show that the proposed control strategy work successfully stabilizes the spin rate of sail when the new type sail is adopted.
Access status: Open Access ,
Comparative study on the detection of early dental caries using thermo-photonic lock-in imaging and optical coherence tomography
(The Optical Society of America, OSA, 2018-09-01) Shokouhi, Elnaz B.; Razani, Marjan; Gupta, Ashish; Tabatabaei, Nima
Early detection of dental caries is known to be the key to the effectiveness of therapeutic and preventive approaches in dentistry. However, existing clinical detection techniques, such as radiographs, are not sufficiently sensitive to detect and monitor the progression of caries at early stages. As such, in recent years, several optics-based imaging modalities have been proposed for the early detection of caries. The majority of these techniques rely on the enhancement of light scattering in early carious lesions, while a few of them are based on the enhancement of light absorption at early caries sites. In this paper, we report on a systemic comparative study on the detection performances of optical coherence tomography (OCT) and thermophotonic lock-in imaging (TPLI) as representative early caries detection modalities based on light scattering and absorption, respectively. Through controlled demineralization studies on extracted human teeth and µCT validation experiments, several detection performance parameters of the two modalities such as detection threshold, sensitivity and specificity have been qualitatively analyzed and discussed. Our experiment results suggests that both modalities have sufficient sensitivity for the detection of well-developed early caries on occlusal and smooth surfaces; however, TPLI provides better sensitivity and detection threshold for detecting very early stages of caries formation, which is deemed to be critical for the effectiveness of therapeutic and preventive approaches in dentistry. Moreover, due to the more specific nature of the light absorption contrast mechanism over light scattering, TPLI exhibits better detection specificity, which results in less false positive readings and thus allows for the proper differentiation of early caries regions from the surrounding intact areas. The major shortcoming of TPLI is its inherent depth-integrated nature, prohibiting the production of depth-resolved/B-mode like images. The outcomes of this research justify the need for a light-absorption based imaging modality with the ability to produce tomographic and depth-resolved images, combining the key advantages of OCT and TPLI.

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