Functional Nanomaterials: Functional Low-Dimensional (0D, 1D, 2D) Materials 2022: Functional Bio-Nanomaterials & Biosensors II
Sponsored by: TMS Functional Materials Division, TMS: Nanomaterials Committee
Program Organizers: Michael Cai Wang, University of South Florida; Yong Lin Kong, University of Utah; Sarah Ying Zhong, University of South Florida; Surojit Gupta, University of North Dakota; Nasrin Hooshmand, Georgia Institute of Technology; Woochul Lee, University of Hawaii at Manoa; Min-Kyu Song, Washington State University; Simona Hunyadi Murph, Savannah River National Laboratory; Hagar Labouta, University of Manitoba; Max Anikovskiy, University of Calgary; Patrick Ward, Savannah River National Laboratory

Wednesday 2:00 PM
March 2, 2022
Room: 260B
Location: Anaheim Convention Center

Session Chair: Michael Cai Wang, University of South Florida; Yong Lin Kong, University of Utah

2:00 PM  
Spatial Control of Laser Induced Graphene Morphology on Flexible Substrates: Moataz Abdulhafez1; Golnaz Tomaraei1; Ki-Ho Nam1; Mostafa Bedewy1; 1University of Pittsburgh
    Laser induced graphene (LIG) is an emerging technique that enables directly patterning conductive carbon electrodes for a plethora of flexible devices, including supercapacitors and sensors. Here, we present a new method for creating functionally graded LIG based on utilizing controlled gradients of optical energy flux to create spatial gradients of LIG morphologies having different electrical conductivities. Importantly, we demonstrate the seamless transition between neighboring regions having different porosity and conductivity. We developed a method to continuously sweep laser fluence = values by controlling the defocus level of the sample surface. This sweeping method enabled identifying the precise fluence thresholds that correspond to morphological transitions. Hence, our results provide new insights into the fluence-dependence of the physicochemical processes underlying LIG formation. Our approach enables generating a morphology diagram for LIG, which facilitates precise tunability of both the morphology, electrical and electrochemical properties of LIG patterns, based on easy-to-control processing parameters.

2:20 PM  
Joining Graphene-modified Textile Fiber Sensors via Nanosolder Melting and Interconnection: Edward Fratto1; Ramaswamy Nagarajan1; Xuejun Lu1; Zhiyong Gu1; 1University of Massachusetts Lowell
    Electronic device miniaturization has driven component study to the nanoscale, sparking interest in nontraditional packaging substrates for targeted device fabrication and design. The emerging field of ‘e-textiles’ examines the translation of traditional manufacturing strategies onto flexible textiles to establish functional garment devices. We investigated the modification of textiles with nanosolder-inks, establishing conductive communication channels and joining resistive sensing elements through non-destructive soldered interconnection. Low melting temperature tin/indium nanosolder particles were synthesized and formulated into conductive inks at various loadings. These nanoinks were applied to threads of differing fabric blends by dip-dry coating, alongside thermal/electrical processing to improve adhesion. Exposure to infrared heating enabled targeted nanosolder melting without harming the fiber structure. Following melting, threads modified by nanoinks with incorporated graphene oxide demonstrated sensing capability (e.g., temperature, humidity, liquid phase salinity, or chemical vapors). Generated signal was transmitted via thread-to-thread soldered joining, demonstrating robust, non-destructive interconnection within a conductive textile platform.

2:40 PM  Keynote
Skin-interfaced Wearable Biosensors: Wei Gao1; 1California Institute of Technology
    The rising research interest in personalized medicine promises to revolutionize traditional medical practices. This presents a tremendous opportunity for developing wearable devices toward predictive analytics and treatment. In this talk, I will introduce our efforts in developing fully-integrated skin-interfaced biosensors for non-invasive molecular analysis. Such wearable biosensors can continuously, selectively, and accurately measure a broad spectrum of sweat analytes including metabolites, electrolytes, hormones, drugs, and other small molecules. The clinical value of our wearable sensing platforms is evaluated through multiple human studies involving both healthy and patient populations toward physiological monitoring, nutritional monitoring, disease diagnosis, mental health assessment, and drug personalization. This talk will feature our recent works on self-powered battery-free electronic skins and mHealth-based biosensors for multiplexed COVID-19 diagnosis and management. These wearable and flexible devices could open the door to a wide range of personalized monitoring, diagnostic, and therapeutic applications.

3:25 PM Break

3:45 PM  
Multi-scale Numerical Modelling of Nanoparticle Transport across the Placental Barrier on Placenta-on-a-chip Physical Model: Hongwei Liu1; Anisa Khan1; Moustafa Ali1; Hagar Labouta1; Pooneh Maghoul1; 1University of Manitoba
    The rapid development of nanotechnologies offers unique advantages in nanomedical therapies during pregnancy. The ability to control the beneficial effects of nanoparticle and to avoid toxicity during treatment requires in-depth understanding of the mechanism of nanoparticle transport across the placental barrier. In this paper, a novel placenta-on-a-chip model is designed to mimic the structure of placental barrier with an upper channel representing maternal side and a lower channel representing fetal side. A multi-scale finite element model is developed to study the effect of nanoparticle size, nanoparticle concentration, flow rate, and diffusion of placental barrier on the transport of nanoparticle across the placental barrier. The proposed multi-scale model can be used to study the transport of nanoparticle under various conditions so that preliminary recommendations can be given to reduce the risk of nanoparticle-related toxicity during pregnancy treatment.

4:05 PM  
Machine Learning Analysis of Spectral Data Using Bacteria for Signal Amplification: Hong Wei1; Yixin Huang1; Peter Santiago1; Allon Hochbaum1; Regina Ragan1; 1University of California Irvine
    Bacterial metabolism is sensitive to chemistry in the local environment and this stress response can serve as amplifiers of solution chemistry, including measuring nutrient deprivation, which is useful for feedback on growth conditions for the pharmaceutical industry, and detection of toxic heavy metal contaminants in water. Surface enhanced Raman scattering (SERS) sensors with controlled surface chemistry and gold nanogap spacing are used to detect changes in bacterial metabolism. When spectral data is analyzed with machine learning (ML) algorithms, nutrition source deprivation of E.Coli MG1655 strain. For example, changes in metabolism due to changing glucose and sucrose sources as well as the diauxic shift between glucose and xylose are observable. Detection of arsenic (Ⅲ) ions (As3+) and chromium (Ⅵ) ions (Cr6+) is possible at ultralow concentrations. As3+ is detectable at concentrations as low as 0.65 ng/L.

4:25 PM  
Optically Active Nanoparticles in Protein Corona Studies: Max Anikovskiy1; 1University of Calgary
    Nanoparticles continue conquering the fields of drug delivery and diagnostics. However, their engineered properties become altered the moment they enter the biological milieu due to protein deposition on their surface. This process has become known as protein corona formation and has been investigated for individual proteins. However, these studies do not consider possible competition between different proteins in the body. For instance, questions remain as to what happens to nanoparticles when they transition from blood into an extracellular matrix and vice versa. This talk will focus on how optically active nanoparticles can be used to investigate the dynamic nature of protein corona formation. Furthermore, approaches to spectroscopic data analysis in order to characterize the protein corona quantitatively will be discussed.