In this talk, I present our recent activities and efforts responding to Chips/Science Acts especially related to Semiconductor Advanced Packaging (AP) and Heterogeneous Integration (HI). Efforts include the initiation of Florida Semiconductor Institute (FSI) and launching Southeast Consortium for Assured and Leading-Edge Semiconductors (SCALES). Further, synergistic efforts and programs for collaborative R&D and education include NSF convergence accelerator program on metaconductor; NSF Regional Engine in partnership with BRIDG and 7 other FL public and private sectors; and DARPA Next Generation Microelectronics Manufacturing (NGMM) in partnership with BRIDG and 8 other nationwide partners. Next, I highlight a few leading-edge technologies related to AP/HI research and development such as high efficiency meta-interconnects and meta-antennas, and its extension to translation based on public and private partnership. 

Autonomous unmanned vehicles (AUVs), including unmanned aerial vehicles (UAVs, e.g., drones), unmanned ground vehicles (UGVs, e.g., ground robots), and unmanned surface vehicles (USVs, e.g., drone boat) are new driving forces for economic development over the next decades. These technologies are not military-centric business any more in the sense that their broad applications are prevalent in many civil operations, including but not limited to emergency response, hazard monitoring, delivery service, and public safety. Thanks to technological improvement on smartphones and various sensor devices, the autonomous unmanned vehicles market in 2024 will increase rapidly. Thus, the number of civil operations of autonomous unmanned vehicles will soon be larger than that of military operations. During the presentation, Dr. Jae Ryu will share his experiences on various AUVs platforms, potentially contributing to STEM education and research in K-16 environment as well as KSEA UAV/UGV/USV (U3V) ecosystems in years to come. 

As populations age, the need for targeted healthcare solutions such as precision rehabilitation becomes increasingly urgent. Wearable robotic technology, augmented with advanced biosensors, offers a highly promising avenue for addressing this challenge. These smart devices can not only mitigate the economic impact of work-related injuries—costing over $13 billion in 2019—but also improve the mobility and overall well-being for millions facing ambulatory limitations. My research is committed to advancing wearable robotics that provide personalized, sensor-guided mechanical assistance to users. These robots utilize biosensors that monitor real-time physiological and biomechanical data, making the assistance highly individualized. This is not just about the robot adapting to the user; we emphasize a co-adaptation model, where both the human and the robot make mutual adjustments for optimal performance and user outcomes. To facilitate this interactive and dynamic process, we employ Human-in-the-Loop (HIL) Bayesian optimization—a machine-learning technique that uses biofeedback for real-time adaptation. This method has effectively reduced the physical exertion required for walking and squatting with wearable devices such as ankle and hip exoskeletons. Additionally, to enhance user experience and outcomes, we have developed visual and verbal instruction methods, making the technology more accessible even under initially challenging conditions. Our future research aims to refine co-adaptation algorithms, enhance the capabilities of biosensors for more nuanced feedback, and optimize HIL controllers and user guidance systems. The overarching goal is to deliver the most personalized and effective precision rehabilitation solutions, directly responding to the unique healthcare needs of our aging society.

In this talk, I will introduce the field of mechanobiology, i.e., how mechanical forces influence cellular behavior. My laboratory is dedicated to understanding the interplay between cells and the extracellular matrix (ECM) in response to various mechanical cues, including bulk stiffness, nanoscale ECM architecture, and fluid shear stress. We employ innovative physical assays and computational techniques to quantify cellular traction forces and leverage imaging data analysis to observe the dynamic cell-ECM adhesion process from inception to disassembly. We have developed and shared a suite of computational tools to advance the field: (1) a traction force microscopy (TFM) software that enhances the precision and interpretation of cellular traction fields, and (2) a focal adhesion analysis package to monitor and categorize the diverse cell-ECM adhesions. Additionally, we integrate time series analysis to correlate adhesion dynamics with traction forces. Using these computational tools and live-cell imaging of key structural and signaling molecules, my lab seeks to identify the fundamental mechanism underlying the transduction process, i.e., from force transmission, structural sensing to signaling, within integrin-based adhesions for sensing the bulk and local ECM stiffness. I will focus on delivering a summary of our recent publication elucidating the myosin-independent stiffness-dependent traction transmission. Our work reveal that cells can generate differential tension in response to substrate stiffness without necessitating myosin contractility. This suggests that such differential tension is not contingent on a signaling response yet can initiate varied signaling pathways for other cellular processes, such as proliferation or survival. I will also briefly introduce a mathematical model that can explain the stiffness-dependent force transmission in myosin independent manner. 

Heterogeneous integration and 3D integrated electronics/optoelectronics can lead to disruptive improvement in IoT devices. Conventionally, wireless electronic skins rely on rigid integrated circuit chips that compromise the overall flexibility and consume considerable power. I will talk about a chip-less wireless e-skin based on surface acoustic wave sensors made of freestanding ultrathin single-crystalline piezoelectric gallium nitride membranes. Surface acoustic wave–based e-skin offers highly sensitive, low-power, and long-term sensing of strain, ultraviolet light, and ion concentrations in sweat. Also, hemispherical image sensors based on organic semiconductors and photolithography processes are introduced. Our organic hemispherical image sensor array shows the best responsivity for similar dark currents among all the reported hemispherical image sensor arrays to date.z

Although we always use tap-water, the anxiety about tap-water still remains. In the presentation, we will find out where this anxiety comes from and whether there is actually a problem with the tap-water we use. Based on the tap-water quality test data from the Indianapolis, we verify how clean and safe the tap-water quality is in our area. 

Zeolites, with their unique pore and channel systems, are essential in industrial applications such as acid catalysis and molecular separations. Designing these intricate structures is challenging due to the competition among multiple metastable polymorphs during crystallization, complicating the development of new synthesis routes. The rational design of zeolite synthesis and predicting crystallization outcomes have traditionally been difficult due to the process being sensitive to a range of synthetic variables, including temperature, pH, and precursor gel compositions. Among these factors, organic structure-directing agents (OSDAs) are crucial, guiding the pre-nucleation and organic-inorganic complex formation, essential for crystallizing targeted structures with desired properties. Despite efforts to design new OSDAs by predicting binding energies, practical challenges still remain, with many OSDAs failing to produce the targeted structures or proving difficult to synthesize. To address these challenges, we have employed a novel approach that utilizes natural language processing to extract insights from the existing literature, identifying OSDAs historically effective in the selective crystallization of desired zeolite frameworks. We then combined high-throughput computational simulations to calculate the stabilization energies of each OSDA molecule within the corresponding zeolite structures. This method facilitates accurate predictions of OSDA-zeolite interactions, providing a roadmap through the intricate energetic landscape of organic templating molecules. Our integrated pipeline assists in identifying viable structures and the selecting OSDAs that are easy to synthesize and cost-effective. These are essential for synthesizing targeted zeolite frameworks, including intricate intergrown structures. Our methodology enables the discovery of new, viable organic molecules for efficient zeolite synthesis, achieving enhanced phase selectivity and reduced complexity.

This presentation will explore the energy impact of connected and automated vehicles (CAVs), with a focus on their energy efficiency. The methodology for assessing CAVs' energy efficiency, both in simulation and experimentation, will be thoroughly discussed. Additionally, we will explain key factors influencing energy consumption in CAVs and introduce strategies for enhancing their energy efficiency.