A Versatile Synthesis of Self-Healing Polymers
Mentor: Jenny Vu
Flexible, self-healing polymers are of great interest to the materials community. With applications in soft robotics, sensors, medical devices, and coatings for space vehicles and structures there is a need for these polymers with tunable mechanistic properties. For example, soft robotics require stretchable materials with shape memory while some medical devices require more rigidity, but the utility of both are greatly enhanced by self-healing properties. The goal of this project is to create a versatile, green one-pot synthesis of a self-healing PDMS-urea based polymer that can be easily modified to fit multiple applications. This PDMS-urea based polymer can be “tuned” by quenching the reaction with various commercially available alcohols and thiols to provide covalently bound linkages to the ends of the polymer that will change the mechanical properties of the material. Our research efforts will focus on exploring the relationship between the alcohol or thiol and the self-healing and mechanical properties of the material.
Additive Manufacturing of Shape-Stabilized Phase-Change Materials (PCMs)
Mentor: Prof. Sandra Boetcher
The goal of the proposed research is to manufacture shape-stabilized PCMs via additive manufacturing. PCM will be combined with high-density polyethylene (HDPE), which is compatible with hydrocarbons found in PCM, and carbon fiber by utilizing the melt-mixing method. This new material will then be extruded into a usable 1.75 mm filament using a 3Devo Extruder. The filament will then be printed into custom shapes for experiments. The team has already successfully extruded PCM/HDPE composite filament using PureTemp PCM 42, an organic-based PCM that changes phase around 42°C. The shapestabilized PCM will be tested for composition using a differential scanning calorimeter (DSC) to measure the effective latent heats and compare them to the value for the pure substances. Mechanical properties and thermal conductivity will be measured using a transient plane-source thermal conductivity apparatus.
Space Radiation: Study of Intracellular Reactive Oxygen Species
Mentor: Prof. Hugo Castillo
Bacteria exposed to sub-lethal doses of ionizing radiation generate increasing amounts of reactive oxygen species (ROS), leading to oxidative stress. ROS propagate rapidly through Fenton reaction and have the potential to cause significant degrees of DNA and protein damage, ultimately reducing bacterial survival. Dyes such as SYBR green, 2′,7′-Dichlorofluorescin diacetate, and dihydrorhodamine are extensively used to quantify intracellular levels of ROS using fluorescence microscopy. In bacteria, these methods must be adapted to overcome the membrane permeability and high metabolic rates. The goal of this project is to produce a standardized technique to measure the intracellular concentration of ROS in different species of bacteria and yeast, in relation to chronic exposure to sub-lethal doses of ionizing radiation using a low-dose gamma irradiator allowing to quantify the oxidative stress status of the cell concerning DNA damage. The uniqueness of this technique could prove useful to study the oxidation-reduction state of bacteria exposed to different types of space stresses and including exposure to antibiotics.
Investigation of Space Biomechanics and Additive Manufacturing of the Orthopedics
Mentor: Prof. Victor Huayamave
Long-term exposure of microgravity in space imposes biomechanical structural changes such as weakening of the structural integrity of the hip joint. Experimental methods have been developed to investigate these pathophysiological adaptive changes; the microgravity environment cannot be recreated accurately. Contrastingly, the predictive power of the finite element method (FEM) is able to look at internal structures of the human body to investigate biomechanical changes due to microgravity. Anatomical models using patient-specific images (C.T., MR) have been successfully developed to investigate the biomechanics of the hip joint and muscle performance. The participants will learn about (1) current state of space biomechanics research, (2) segmenting anatomical images to develop finite element models, and (3) 3D printed components using additive manufacturing. The computational pipeline will be introduced to the predictive power of the FEM to assess the structural integrity of the hip joint under microgravity conditions.
Fabrication of a Flexible, Stretchable, and Self-Healable Platform for Aerospace Applications
Mentors: Prof. Foram Madiyar, Prof. Daewon Kim
The goal of this project is to investigate the use of polymers not only having tunable electrical and thermal properties, but also reversible bond chemistry that imparts materials high stretchability, exceptional toughness, and self-healability. The fabrication of the polymer follows the principle of the formation of the mixture of both strong and weak crosslinking hydrogen bonds. The strong crosslinking bonds confer robustness and elasticity, while the weak bonds can dissipate strain energy through efficient reversible bond breakage and reformation, in a one-pot condensation method. The applications of such a platform will be explored on the grounds of sensor substrates or additive manufacturing of aerospace structures using self-healable materials, matrix self-healing of composite structures, smart polymer actuators, and sensors.
On-Site Biomarker Sensing using Flexible Transistors on Skin
Mentor: Prof. Foram Madiyar
The goal of the project is to design a wearable technology for the real-time screening, diagnosis and multiplex detection of different biomarkers. This involves the fabrication of thin, flexible, non-invasive, sensitive health monitoring and clinical diagnosis system using bio-fluids on the skin. The substrate under study will be flexible plastic and electrodes fabricated by photolithography and screen-printing and microfluidic channels. The materials for electrodes will be organic conductive polymers, metal oxides, metal nanoparticles, and carbon nanomaterials. Biofluids such as sweat, and tears have been researched for glucose as an indicator to diagnose and treat diabetes, lactic acid to track an individual's performance and examine the tissue oxygenation, measuring levels of Ca2+, Na+, K+, Cl- that aid in tracking metabolism, monitoring peptides, inflammatory biomarkers hormones, proteins, and DNAs/RNAs in in these body fluids has been lacking. These sensors will be integrated with performance circuits that will have source, drain, and gate system with mobile devices for data recording and integration.
Biofidelic Piezoresistive Nanocomposite Multiscale Analysis
Mentor: Prof. Sirish Namilae
Biofidelic materials can mimic the mechanical response of a biological tissue like human brain tissues. These surrogate materials can overcome several problems involved in using biological tissues such as inadequate availability, biodegradation, and ethical considerations. Besides, biofidelity, electrical conductivity, and deformation sensing capability will enable the accurate capturing of the in-situ deformation response during static and impact loading, which cannot be adequately addressed using external sensors. The objective of this research is to design and fabricate a complex prototype of biological structure like a human brain, which exhibits biofidelic mechanical response coupled with a high gauge factor deformation sensing capability. In our preliminary research, silicone-nanocarbon sheet sandwich fibers were fabricated and exhibited electrical conductivity, deformation sensing, and a mechanical response corresponding to the white matter of human brain tissue. In the proposed research, we will further engineer the electro-mechanical response of the structure through (a) varying the constituents in the silicone matrix and (b) engineering the interface mechanical properties in the core layer. We will use 3-D printed molds to create the substrates with curvatures and shapes that can be integrated into the human brain prototype model.
Investigating Methods to Minimize the Gap between Pre and Post-Space Flight Syndrome
Mentor: Prof. Christine Walck
Space physiology aims at mitigating microgravity deconditioning syndrome using resistive exercise as a countermeasure. The hostile environment of space has adverse short- and long-term effects on the human body, specifically causing muscle atrophy, bone decalcification, and poor cardiovascular endurance. Therefore, this research aims explicitly to effectively reducing the gap between precondition and postcondition syndrome. We propose to design an optimized lower extremity force acquisition system (LEFAS) that integrates with a lower-body negative pressure (LBNP) box and subject-specific protocols for improved fitness results by taking a computationally simulated optimization approach. Such an approach uses a multidimensional response surface and musculoskeletal (MSK) modeling within a simulated microgravity environment. The combination of LEFAS, LBNP, and personalized controls will combat microgravity deconditioning syndrome minimizing the gap between pre- and post-flight syndrome, allowing astronauts to respond to emergencies, and remain healthy during and after extended space travel.
High-Throughput Additive Manufacturing of Thermosetting Additive Polymer Materials
Mentor: Prof. Jiang Yizhou
Thermosetting polymer materials, such as polyurethanes and polydimethylsiloxanes (PDMS), are widely used in a myriad of industrial applications, including machine parts, protective coatings, and medical devices. They possess high thermal and mechanical stability and the attractive features of being lightweight, and ease of manufacturing relative to other high-strength materials (e.g., metals/alloys). Highly desirable, however, is additive manufacturing (AM) methodologies amenable to processing these materials, as this would enable on-demand and energy-efficient means of their production. Although AM has been demonstrated as a platform for rapidly fabricating customizable parts, the difficulty in AM of thermosetting polymer materials largely remains in the perspective of slow fabrication speed and limited building dimensions. There is an essential need to develop AM techniques that enable the more efficient processing of thermosetting polymer materials. The objective of this study is to develop novel AM processes to further offer potential access to 3D-printed large-scale parts with tailored properties for aerospace applications.
System Diagnostics through Frequency-Domain Analysis of Acoustic Data and Spectral Descriptors
Mentor: Prof. David Canales Garcia
The objective is to diagnose and predict the behavior according to unique relationships between mathematical descriptors obtained from doing Fast-Fourier Transform to the signal, advancing the accuracy and reliability from machine-learning- based prediction, and allowing for anomalies to be identified before they cause failure. This has been observed by predicting a failure of an additive manufacturing platform. This project will tackle the problem of diagnostics from its fundamental roots, leveraging the physics of sound and the relationship between mathematical descriptors that are inherent to acoustic signals. The resulting research will be universally applicable and not application restricted. This project will provide knowledge related to machine learning, applied mathematics and systems diagnostics.
Immersive Spacecraft Trajectory Design Via Augmented Reality
Mentor: Prof. David Canales Garcia
Immersive technology may offer novel user interaction modalities to manipulate and design spacecraft trajectories within complex dynamical environments. The objective of this project is to use the VR/AR technology within the Space Trajectories and Applications Research (STAR group) to set up a framework to be able to design space missions between the Earth and the Moon in an immersive way. Baseline results will have to be demonstrated and should be displayed in multiple HoloLens 2 at the same time. This project will provide knowledge in astrodynamics and immersive design through VR/AR.