• I conduct interdisciplinary research at the intersection of in-situ mechanics and 3D computer vision, with a primary focus on computational medical images and the 3D deformation of objects subjected to diverse mechanical tests, such as mechanical failure tests, thermomechanical tests, and in-vivo pressure tests. My research aims to nondestructively measure deformation using various imaging modalities, including X-ray micro-CT (uCT), Magnetic Resonance Imaging (MRI), Optical Coherence Tomography (OCT), and 3D fluorescent confocal microscopy. The overarching objective of my work is to quantify deformation-induced degradations, damages, remodeling, and diseases, elucidating the relationship between structural changes and functional outcomes, such as the impact of lamina cribrosa deformations on neural tissue loss leading to glaucoma. In the context of my dissertation, I extensively employ the Digital Volume Correlation (DVC) technique to investigate the in-situ deformation of electronics under diverse conditions, including thermal shock and three-point bending. This involves studying phenomena such as LEDs chip deformation during operation and solder joint deformation of flip chips in mechanical bending tests. A key focus of my research is understanding the correlation between strain distribution and failure modes in electronic components.

• The three main areas of my research can be delineated as follows:

Glaucoma Prediction and Prevention from Tissue Mechanics: I delve into the mechanics of tissues to predict and prevent glaucoma, exploring how deformations in structures like the lamina cribrosa contribute to the loss of neural tissue. This work contributes to a deeper understanding of tissue degenerations and facilitates early intervention strategies.

   

Figure 1: Streth Deformation(Tensile Strain) computed between two controlled pressures on the ONH tissue.

Glaucoma, recognized as the second leading cause of global blindness by the World Health Organization (WHO), remains enigmatic in its underlying mechanisms. A pivotal factor in the onset of glaucoma is the alteration in intraocular pressure (IOP). Elevated IOP instigates structural damage to the Optic Nerve Head (ONH) through the significant deformation of the Lamina Cribrosa (LC). The LC, responsible for providing structural support to retinal ganglion cell (RGC) axons and blood vessels upon their entry into the eye, undergoes substantial deformation that can lead to neural tissue damage. Prior research has indicated that the deformed LC strains RGC axons and blood vessels, causing remote damage to retinal tissues and triggering remodeling of the connective tissue microarchitecture within the LC.

My primary objective is to quantify in-vivo LC deformations to unravel the biomechanical intricacies of glaucoma. Specifically, this research aims to achieve two key goals: first, to analyze LC deformations in response to changes in IOP, and second, to compare these deformations between individuals with glaucoma and healthy subjects. Employing OCT imaging, I will capture high-resolution, in-vivo ONH images under controlled pressure conditions. The subsequent computation of deformations will be facilitated through a sophisticated 3D image-based registration technique.

   

Figure 2: Volumetric Registration two scanned volumes are aligned and registered under the same coordinate and the view shows the slicing through coronal, sagittal and transverse plane.

Central to this research is the hypothesis that in-vivo LC deformations escalate with increasing IOP levels, and these deformations are more pronounced in glaucoma patients compared to their healthy counterparts. The quantification of differences between glaucomatous and healthy conditions is imperative for providing clinicians with a deeper understanding of the deformation mechanisms associated with varying IOP.

Looking forward, the research trajectory involves an extensive analysis of clinical data from human subjects, adapting the tools for seamless clinical translation. The potential funding avenue through NIH further underscores the commitment to advancing this research into practical applications. Furthermore, the versatility of the demonstrated technique extends beyond LC deformations; it can be seamlessly adapted to other tissues or regions within the eye, such as the trabecular meshwork, cornea, retinal fiber layer, and sclera. This adaptability enables the exploration and computation of in-vivo mechanical properties for a comprehensive understanding of ocular biomechanics.

     

Figure 3: In-vivo(Left) and Ex-vivo(Right) Various Deformation computed between paired piecewise pressures on the ONH tissue.

Computational Mechanics of Flexible Electronics: My research investigates the computational mechanics of flexible electronics, specifically addressing the deformation and reliability of electronic components under various conditions. This encompasses the study of LEDs chip deformation during operation and solder joint deformation in mechanical bending tests, shedding light on the behavior of flexible electronic systems.

In the realm of flexible electronics, the use of flexible substrates has become ubiquitous in the production of wearable and flexible electronic devices, ranging from smart watches and fitness trackers to medical devices and smart clothing. However, the substantial deformation experienced by these flexible substrates in operational settings can compromise the reliability and lead to premature failure of electronic interconnects. Despite the prevalence of flexible materials such as silicone in these applications, there is a notable gap in research regarding the deformation and strain characteristics of silicone substrates under various mechanical loads, especially at extreme temperatures. To address this critical gap, my research focuses on the development of techniques for in-situ, non-destructive measurement of deformation in flexible electronics during operational loads. While existing studies have utilized surface deformation tracking and stereoscopic methods to profile the surface of soft materials, these approaches are limited to capturing surface deformations and do not provide insights into interior deformations. In contrast, I have pioneered the application of Digital Volume Correlation (DVC) methods, enabling the computation of deformations in three dimensions within soft materials and electronics.

My novel approach involves employing the DVC method to image 3D soft materials and electronics through X-ray CT reconstruction, a groundbreaking application, particularly in the field of electronics packaging. The 3D digital model generated from X-ray reconstruction is meticulously validated against high-resolution digital camera imagery and 3D surface profiles. Subsequently, a computational model for soft materials is developed based on the measured grayscale values from the X-ray source, employing a discretization technique with tetrahedron elements. This allows for the evaluation of deformation vectors at each node of the computational model under applied loads. Significantly, the presented testing technique holds potential applicability to a broad spectrum of microelectronics and Micro-Electro-Mechanical Systems (MEMS) with encapsulation of soft materials, especially within flexible or wearable electronics. The capability to assess the reliability of electronics under diverse mechanical loading conditions positions this method as a valuable tool for research and development. As the next phase, I envision extending this technique to the assembly line of electronics, facilitating online tests and quality control in industrial engineering settings, thereby advancing the reliability and performance of flexible electronic systems.

Electronics Reliability and Prognostic Health Management(PHM): I contribute to the field of electronics reliability and Prognostic Health Management by employing the Digital Volume Correlation technique to analyze strain distribution and failure modes in electronic components. This research aids in developing strategies for predicting and managing the health of electronic systems.

Prognostic Health Management (PHM) is a critical field dedicated to predicting the failure of complex systems composed of multiple components. Central to this prediction is the estimation of Mean Time to Failure (MTTF) and Remaining Useful Life (RUL), a statistical metric quantifying the anticipated duration during which a product is expected to perform correctly before experiencing complete failure. In the context of the Solid-State Lighting (SSL) industry, PHM holds significant promise, as the reliability of SSL products is paramount for their widespread application and acceptance within the lighting community.

The SSL industry faces unique challenges during its transition from traditional lighting sources, including but not limited to wide temperature excursions, humidity variations, and vibrations. While consumer electronics are typically designed to function for only 1–3 years, SSL luminaires are expected to achieve lifetimes of 10 years and beyond for high-reliability applications. However, achieving such extended lifetimes poses challenges due to the absence of accelerated test techniques and comprehensive life prediction models.

SSL luminaires are complex systems comprising multiple material systems and interfaces, each with distinct failure modes. Interactions between optics, drive electronics, controls, and thermal design can significantly impact reliability. Moreover, the diversity of SSL components means that testing protocols effective for one sub-system might be too harsh for another. Currently, there is a notable gap in methods for predicting SSL reliability, especially concerning new and unknown failure modes. Additionally, there is a scarcity of life distribution data for LEDs and SSL devices, crucial for accurately assessing the promised lifetime of SSL products.

Addressing these challenges necessitates the development of new and advanced methodologies for predicting SSL reliability. This involves the creation of accelerated testing techniques tailored to the unique characteristics of SSL luminaires, considering the diverse materials and interfaces involved. Comprehensive life prediction models that account for interactions between different sub-systems and failure modes are essential for accurate and reliable assessments. Furthermore, efforts should be directed towards generating life distribution data for LEDs and SSL devices, facilitating a more robust understanding of their reliability and contributing to the qualification of SSL luminaires for high-stakes applications.

In summary, advancing PHM in the SSL industry requires the development of innovative testing techniques, comprehensive prediction models, and an increased understanding of life distributions for SSL components. These endeavors will not only enhance the reliability of SSL products but also accelerate their adoption in high-reliability applications, paving the way for a more sustainable and dependable lighting landscape.

In short, my research not only bridges the gap between in-situ mechanics and 3D computer vision but also addresses critical issues in medical and electronic domains. Looking ahead, my future research interests lie in expanding these investigations and exploring new avenues at the forefront of in-situ mechanics, computational imaging, and their applications in diverse fields.

• Special Topics

Finite Element Method

Real Geometry Discretization Method: Poisson-Disc Sampling and Delaunay Triangulation Algorithm: it shows the unstrained(left) vs constrained(right) geometry sampling, and the random points are placed with the minimum distance D(i,j) for each point-j in 2D coordinate.

       

Fast Volumetric Image Registration

Rigid-body 3D Volume matching: two subsets of Point Clouds from discretized 3D volumetric images are aligned and registered using ICP algorithm.

       

Deformable 3D Volume matching and Iso-surfaces alignment visualization: Two Volumetric Images are matched and aligned through the sub-volume optimization(sub-voxel accuracy) algorithm.

       

3D Volumetric Image Restoration and Enhancement

Signal Filtering and Tracking: Extended Kalman Filter and Particle Filter

• Research Showcases

X-ray Micro-CT and DVC Based Analysis of Strains in Metallization of Flexible Electronics. [LINK].

Measuring In-vivo and In-situ Ex-vivo the 3D Deformation of the Lamina Cribrosa Microstructure under Elevated Intraocular Pressure [LINK].