Digital Commons Network^™

Enhancing Mucus Flow And Clearance By Grafting Zwitterionic Hydrogel Films To Luminal Surfaces, Ryan Horne, Caleb Escudero, Morgan Ellerman, C. Allan Guymon, Marlan Hansen

Faculty Publications

Objective

To determine the effects of zwitterionic hydrogel films on mucus contact angles, flow, and stasis with respect to medical polymer surfaces, both flat and tubular.

Methods

A zwitterionic hydrogel thin film was photografted onto medical rubber surfaces and compared against non-zwitterionic hydrogel thin films and untreated surfaces to determine its impact on mucus contact angles, mucus flow on sheets and tubes, and mucus plugging.

Results

Zwitterionic and conventional hydrogel films significantly reduce the mucus contact angles and the tilt required to initiate mucus flow on sheets and in tubular systems. Preliminary experiments show that these films may also shorten …

Trans-Arg: Predicting Antibiotic Resistance Genes With A Transformer-Based Model And Pretrained Protein Language Model, Mohd Manzar Abbas, Amit Ranjan, Aixin Hou, Supratik Mukhopadhyay

Faculty Publications

Antibiotic resistance presents an emerging challenge to global health by reducing the efficacy of antibiotics administered to treat bacterial infections. Traditional approaches for detecting antibiotic resistance genes (ARGs) involve alignment-based sequence similarity techniques, which are time-consuming and resource-intensive. This signifies the necessity for developing advanced computational methods to detect ARGs early. To address this challenge, we introduce Trans-ARG, a novel multi-head attention transformer-based model designed to predict potential ARGs. Our approach leverages the pretrained ESMFold model to extract embeddings from protein sequences, capturing intricate structural and functional information. Protein sequences labelled as ARG or non-ARG were used as the dataset. …

Kg-Dta: A Knowledge Graph-Based Meta-Path Learning Framework To Predict Drug-Target Binding Affinity, Amit Ranjan, Adam Bess, Md Saiful Islam Sajol, Magesh Rajasekaran, Chris Alvin, Supratik Mukhopadhyay

Faculty Publications

Drug target affinity (DTA) prediction is essential at different phases of drug discovery and virtual drug screening. However, traditional wet lab experiments are time and resource-intensive owing to the complex interactions within the vast biological and chemical spaces. Computational methods have proven their potential to predict DTA, but none have considered the association of drugs and proteins to capture the complex interactions in the biological network between drugs and proteins. To address this, we propose a novel framework leveraging knowledge graph-based meta-path learning (KG-DTA) to enhance DTA prediction. First, we construct a weighted heterogeneous network of drugs and proteins that …

Friction-Based Recycling: An Evaluation Of Friction Extrusion For Fabricating Ti-6al-4 V Wire Fabricated From Machining Chip Feedstock, Devesh Kumar Chouhan, Mageshwari Komarasamy, Scott B. Taysom, Nicole R. Overman, Nathan L. Canfield, Timothy J. Roosendaal, Anthony P. Reynolds, Scott A. Whalen

Faculty Publications

Titanium and its alloys are used in aviation and automobile industries due to their remarkable strength to weight ratio, but machining loss commonly is high with ~ 80 wt% of the material being converted to scrap. Recycling post-consumer Ti scrap directly into solid bulk products is a potential solution for repurposing valuable material. Further, eliminating fresh Ti sponge during recycling might lead to lower energy and greenhouse gas emissions. In this study, a solid-phase process known as friction extrusion was utilized to recycle Ti-6Al-4 V machining chips into solid wires which could be used as feedstock in additive manufacturing. The …

Electronic, Magnetic, And Structural Properties Of V2coal: Experimental And Computational Study, Parashu Kharel, Cole Brown, Brandon Schmidt, Caden Sadler, Salimatou Diallo, Mohd Anas, Paul M. Shand, Pavel V. Lukashev

Faculty Publications

Here, we present results of combined experimental and computations study of V2CoAl, a Heusler alloy that exhibits nearly perfect spin-polarization. Our calculations indicate that this material maintains a high degree of spin-polarization (over 90%) in the wide range of lattice parameters, except at the largest considered unit cell volume. The magnetic alignment of V2CoAl is ferrimagnetic, due to the antialignment of the magnetic moments of vanadium atoms in their two sublattices. The calculated total magnetic moment per formula unit is nearly integer at the optimal lattice parameter and at the smaller volumes of the unit cell, but it deviated from …

Byu Nano-Carbon Physics Lab, Robert Davis Dr., Richard Vanfleet Dr., Felipe Rivera Dr., David Hayes, Nick Allen, Bridget Kemper, Dan Broadbent

Faculty Publications

BYU Nano-Carbon Physics Lab

Started in 2003 by Physics Professors Robert Davis and Richard Vanfleet, who received the BYU Technology Transfer Award in 2024.

Over 81 undergraduate and 21 graduate student projects in the lab have advanced carbon nanotube (CNT) research.

Applications of research from the lab have resulted in over 30 patents, many of which have been licensed to companies for use in the world.

This display showcases highlights of work done in the lab.

Uncertainty Propagation And Sensitivity Analysis For Constrained Optimization Of Nuclear Waste Vitrification, Lagrande Gunnell, Xiaonan Lu, John D. Vienna, Dong-Sang Kim, Brian J. Riley, John Hedengren

Faculty Publications

The vitrification of high-level waste (HLW) by heating a mixture of glass-forming chemicals (GFCs) with the waste can be improved using a constrained optimization problem. This study explores how different uncertainty propagation (UP) methods implemented with the optimization process can affect the glass formulation of nuclear waste glasses. UP is the effort of propagating uncertain inputs through a system to understand and quantify output distributions. Uncertainty intervals are crafted from output distributions to inform the optimization algorithm. UP is often implemented with Monte Carlo (MC) sampling for large nonlinear systems, which can be difficult to implement within a constrained optimization …

Understanding Ionic Transport In Perovskite Lithium-Ion Conductor Li3/8Sr7/16Ta3/4Hf1/4O3: A Neutron Diffraction And Molecular Dynamics Simulation Study †, Danyi Sun, Nan Wu, Yeting Wen, Shichen Sun, Yufang He, Ke Huang, Cheng Li, Bin Ouyang, Ralph E. White, Kevin Huang

Faculty Publications

Solid-state Li-ion electrolytes (SSEs) are essential for the development of next-generation solid-state Li-metal batteries and new Li-extraction electrochemical cells. Among these, the perovskite-type SSE Li3/8Sr7/16Ta3/4Hf1/4O3 (LSTH) has garnered attention for Li-extraction applications, owing to its outstanding chemical and thermal stability and high ionic conductivity. However, its precise crystal structure and Li-ion transport mechanisms remain insufficiently understood. This study addresses these gaps by employing neutron diffraction to resolve LSTH's crystallography and machine learning force field (MLFF) based MD simulations to elucidate ionic transport mechanisms. A single-phase LSTH, synthesized via the sol–gel method, exhibits a room-temperature bulk conductivity of 0.418 mS cm−1 …

High-Resolution Model Intercomparison Project Phase 2 (Highresmip2) Towards Cmip7, Malcolm J. Roberts, Kevin A. Reed, Qing Bao, Joseph J. Barsugli, Suzana J. Camargo, Louis Philippe Caron, Ping Chang, Cheng Ta Chen, Hannah M. Christensen, Gokhan Danabasoglu, Ivy Frenger, Neven S. Fučkar, Shabeh Ul Hasson, Helene T. Hewitt, Huanping Huang, Daehyun Kim, Chihiro Kodama, Michael Lai, Lai Yung Ruby Leung, Ryo Mizuta, Paulo Nobre, Pablo Ortega, Dominique Paquin, Christopher D. Roberts, Enrico Scoccimarro, Jon Seddon, Anne Marie Treguier, Chia Ying Tu, Paul A. Ullrich, Pier Luigi Vidale, Michael F. Wehner, Colin M. Zarzycki

Faculty Publications

Robust projections and predictions of climate variability and change, particularly at regional scales, rely on the driving processes being represented with fidelity in model simulations. Consequently, the role of enhanced horizontal resolution in improved process representation in all components of the climate system continues to be of great interest. Recent simulations suggest the possibility of significant changes in both large-scale aspects of the ocean and atmospheric circulations and in the regional responses to climate change, as well as improvements in representations of small-scale processes and extremes, when resolution is enhanced. The first phase of the High-Resolution Model Intercomparison Project (HighResMIP1) …

Modelling The Effects Of Vegetation Distribution And Density On Hydrological Connectivity And Water Age In A River Delta, Madoche Jean Louis, Matthew Hiatt

Faculty Publications

Water transport timescales (WTTs) quantify how long it takes for water to travel through or remain in a system and are often cast as indicators of ecosystem function and health. Such timescales are known to be affected by vegetation in various environments. We quantify the impact of floodplain vegetation on WTTs within the Wax Lake Delta (WLD), a river delta system in Louisiana, USA, using a high-resolution Delft3D Flexible Mesh (DFM) model incorporating vegetation-induced flow resistance. We show that increased vegetation density leads to extended WTTs within vegetated sections of WLD while fostering flow localization and accelerating transport within distributary …

Increasing A-Type Co32− Substitution Decreases The Modulus Of Apatite Nanocrystals, Stephanie Wong, Abigail Eaton, Christina Krywka, Arun Nair, Christophe Drouet, Alix Deymier

Faculty Publications

Biological apatite mineral is highly substituted with carbonate (CO₃²⁻). CO₃²⁻ can exchange for either phosphate, known as B-type, or hydroxyl groups, known as A-type. Although the former has been extensively studied, A-type CO₃²⁻ substituted apatites are poorly understood. Therefore, A-type CO₃²⁻ apatites with biologically relevant levels of CO32− (1.7–5.8 wt%) were prepared and characterized. The addition of A-type CO₃²⁻ into the apatite structure caused the predicted expansion of the a-axis and contraction of the c-axis in the unit cell. This was accompanied by a significant modification in the atomic …

Multiwavelength Analysis Of At 2023sva: A Luminous Orphan Afterglow With Evidence For A Structured Jet, Gokul P. Srinivasaragavan, Daniel A. Perley, Anna Y.Q. Ho, Brendan O’Connor, Antonio De Ugarte Postigo, Nikhil Sarin, S. Bradley Cenko, Jesper Sollerman, Lauren Rhodes, David A. Green, Dmitry S. Svinkin, Varun Bhalerao, Gaurav Waratkar, A. J. Nayana, Poonam Chandra, M. Coleman Miller, Daniele B. Malesani, Geoffrey Ryan, Suryansh Srijan, Eric C. Bellm, Eric Burns, David J. Titterington, Maria B. Stone, Josiah Purdum, Tomás Ahumada, G. C. Anupama, Sudhanshu Barway, Michael W. Coughlin, Andrew Drake, Rob Fender, José F. Agüí Fernández, Dmitry D. Frederiks, Stefan Geier

Faculty Publications

We present multiwavelength analysis of ZTF23abelseb (AT 2023sva), an optically discovered fast-fading (∆mr = 2.2 mag in ∆t = 0.74 d), luminous (Mr ∼ −30.0 mag), and red (g − r = 0.50 mag) transient at z = 2.28 with accompanying luminous radio emission. AT 2023sva does not possess a γ -ray burst (GRB) counterpart to an isotropic equivalent energy limit of Eγ,iso < 1.6 × 10⁵² erg, determined through searching γ -ray satellite archives between the last non-detection and first detection, making it the sixth example of an optically discovered afterglow with a redshift measurement and no detected GRB counterpart. We analyse …

Ixpe Observation Of The Low-Synchrotron Peaked Blazar S4 0954+65 During An Optical-X-Ray Flare, Pouya M. Kouch, Ioannis Liodakis, Francesco Fenu, Haocheng Zhang, Stella Boula, Riccardo Middei, Laura Di Gesu, Georgios F. Paraschos, Iván Agudo, Svetlana G. Jorstad, Elina Lindfors, Alan P. Marscher, Henric Krawczynski, Michela Negro, Kun Hu, Dawoon E. Kim, Elisabetta Cavazzuti, Manel Errando, Dmitry Blinov, Anastasia Gourni, Sebastian Kiehlmann, Angelos Kourtidis, Nikos Mandarakas, Nikolaos Triantafyllou, Anna Vervelaki, George A. Borman, Evgenia N. Kopatskaya, Elena G. Larionova, Daria A. Morozova, Sergey S. Savchenko, Andrey A. Vasilyev, Ivan S. Troitskiy, Tatiana S. Grishina

Faculty Publications

The X-ray polarization observations, made possible with the Imaging X-ray Polarimetry Explorer (IXPE), offer new ways of probing high-energy emission processes in astrophysical jets from blazars. Here, we report the first X-ray polarization observation of the blazar S4 0954+65 in a high optical and X-ray state. During our multi-wavelength (MWL) campaign of the source, we detected an optical flare whose peak coincided with the peak of an X-ray flare. This optical-X-ray flare most likely took place in a feature moving along the parsec-scale jet, imaged at 43 GHz by the Very Long Baseline Array (VLBA). The 43 GHz polarization angle …

Structural And Magnetic Properties Of Cotemo O6, Yu Li, Jared Coles, Xin Gui, Hyowon Park, Yan Wu, Xinglong Chen, Jing Han Chen, Xiaoping Wang, Huibo Cao, Shane Stadler, Omar Chmaissem, David P. Young, Stephan Rosenkranz, John F. Ditusa

Faculty Publications

We have conducted a comprehensive investigation into the magnetic properties of the chiral multiferroic material CoTeMoO6. In contrast with the previous claim of canted antiferromagnetic order with ferromagnetic components [Y. Doi, J. Solid State Chem. 182, 3232 (2009)10.1016/j.jssc.2009.09.008], our investigation reveals an antiferromagnetic ground state with compensated moments, providing an interesting platform for exploring exotic material properties. Through careful measurements of magnetization under a series of applied fields, we demonstrate that there exist two sequential field-induced magnetic transitions in CoTeMoO6, with one occurring at Hc1=460 Oe along the a axis, and the other at Hc2=1.16 T with the field along …

Post-Wildfire Mobilization Of Organic Carbon, Travis Numan, Srinidhi Lokesh, Abrar Shahriar, Anil Timilsina, Myron L. Lard, Justin Clark, Yasaman Raeofy, Qian Zhao, Simon R. Poulson, Paul S. Verburg, Jocelyn A. Richardson, Robert L. Cook, Vera Samburova, Yu Yang

Faculty Publications

Wildfires significantly alter watershed functions, particularly the mobilization of organic carbon (OC). This study investigated OC mobility and the physicochemical characteristics of wildfire-impacted soils and ashes from the northern California and Nevada fires (Dixie, Beckworth, Caldor). Organic carbon in wildfire-derived ashes (9.2–57.3 mg/g) generally exceeded levels in the background soils (4.3–24.4 mg/g), except at the Dixie fire sites. The mobile OC fraction varied from 0.0093 to 0.029 in ashes and 0.010 to 0.065 in soils, though no consistent trend was observed between the ashes and soils. Notably, the ash samples displayed lower OC mobility compared with the soils beneath them. …

The Contemporary Distribution Of Scincine Lizards Does Not Reflect Their Biogeographic Origin, Aniruddha Datta-Roy, Matthew C. Brandley, Christopher C. Austin, Aaron M. Bauer, David James Harris, Salvador Carranza, Kanishka D.B. Ukuwela, Anslem De Silva, Krystal A. Tolley, K. Praveen Karanth, Maitreya Sil

Faculty Publications

Aim: We assess the systematic relationships and historical biogeographic patterns in the subfamily Scincinae, a group of lizards that primarily inhabits the Afro-Madagascan and Saharo-Arabian regions with isolated lineages in Europe, North America, East Asia, India and Sri Lanka. The contemporary distribution of these lineages on the historical Laurasian and Gondwanan landmasses make scincines an ideal system to study the roles of vicariance and dispersal on a geologic scale of tens of millions of years. Location: Global. Taxon: Subfamily Scincinae (Family Scincidae). Methods: We conducted biogeographic analyses on a reconstructed, time-calibrated species tree of scincine genera, including members of the …

Comparing The Restoration Effect And Stress Recovery In Real And Virtual Environments With A Green Wall, Alireza Sedghikhanshir, Yan Chen, Yimin Zhu, Melissa R. Beck, Amirhosein Jafari

Faculty Publications

Biophilic design, incorporating natural elements, is known to enhance stress recovery. Immersive virtual environments (IVEs) are increasingly utilized for biophilic design validation and research, but their efficacy in replicating the restorative effects of real environments remains uncertain. Varying responses to virtual settings suggest that specific design factors may affect their effectiveness. This study provides a novel comparison of the stress recovery and restoration effect between real and virtual green walls in a controlled climate chamber. Sixty-three participants were exposed to either a real or virtual green wall for seven minutes after a 5 min stressor task. Physiological stress responses, including …

Time-Series Data-Driven Pm2.5 Forecasting: From Theoretical Framework To Empirical Analysis, Chunlai Wu, Ruiyang Wang, Siyu Lu, Jiawei Tian, Lirong Yin, Lei Wang, Wenfeng Zheng

Faculty Publications

PM2.5 in air pollution poses a significant threat to public health and the ecological environment. There is an urgent need to develop accurate PM2.5 prediction models to support decision-making and reduce risks. This review comprehensively explores the progress of PM2.5 concentration prediction, covering bibliometric trends, time series data characteristics, deep learning applications, and future development directions. This article obtained data on 2327 journal articles published from 2014 to 2024 from the WOS database. Bibliometric analysis shows that research output is growing rapidly, with China and the United States playing a leading role, and recent research is increasingly focusing on data-driven …

Basil And Swiss Chard: Edible Crops For Use In Floating Treatment Wetlands Improving Agricultural Runoff, Clare Escamilla, David R. Tyrpak, William H.J. Stronsnider, Sarah A. White

Faculty Publications

The plant species established within floating treatment wetlands (FTWs) influence nutrient removal efficiency. To enhance adoption of FTWs by agricultural producers, both economic and ecological benefits from FTWs are needed to increase their use within irrigation retention reservoirs. Thus, we ascertained the feasibility of growing food crops in FTWs by evaluating two edible plant species to determine survivability and nutrient accumulation when grown in FTWs. We quantified plant growth (at saleable/harvestable size), nutrient uptake in root and shoot tissues, and overall nutrient removal efficiency of sweet basil (Ocimum basilicum) and Swiss chard (Beta vulgaris) over a …

Modulating The Aqueous Micellar Reorganization Of Sequence-Defined Ionic Peptoid Block Copolymers By Ionizable Monomer Position And Solution Ph, Bailee N. Barrett, Pedram Azizihariri, Vijay T. John, Donghui Zhang

Faculty Publications

The micellar aggregation of singly charged sequence-defined ionic peptoid block copolymers can be finely tuned by adjusting the position of the ionizable monomer along the chain and varying the solution pH. The pH-induced structural reorganization of these micelles was found to depend on the position of the ionizable monomer along the chain, influencing the balance of the hydrophobic interactions, excluded volume effect, and electrostatic forces (i.e., charge repulsion, solvation of the ionic monomers, counterion association) that govern the micellar structure. As the solution pH increases, positioning the ionizable monomer closer to the junction of the hydrophobic and hydrophilic blocks causes …

Processing Parameter-Performance Nexus In 3d Printing Of Nanostructured Chiral Photonics, Kyle George, Nader Taheri-Qazvini, Peter D. Olmsted, Monirosadat Sadati

Faculty Publications

Precisely crafted hierarchical architectures found in naturally derived biomaterials underpin the exceptional performance and functionality showcased by the host organism. In particular, layered helical assemblies composed of cellulose, chitin, or collagen serve as the foundation for some of the most mechanically robust and visually striking natural materials. By utilizing structured materials in additive manufacturing techniques such as extrusion-based 3D printing, the intrinsic deformation process can be used to implement bottom-up design of printed constructs, offering the potential to create intricate macroscale geometries with embedded nanoscale functionality. In this study, comprehensive rheological and rheo-optical characterization of structurally colored, photocurable liquid crystalline …

Potential Of Individual Upper-Limb Muscles To Contribute To Postural Tremor: Simulations From Neural Drive To Joint Rotation, Spencer A. Baker, Landon J. Beutler, Daniel B. Free, Dario Farina, Steven Knight Charles

Faculty Publications

Background: It is unclear which muscles contribute most to tremor and should therefore be targeted by tremor suppression methods. Previous studies used mathematical models to investigate how upper-limb biomechanics affect muscles’ potential to generate tremor. These investigations yielded principles, but the models included at most only 15 muscles. Here we expand previous models to include 50 upper-limb muscles, simulate tremor propagation, and test the validity of the previously postulated principles. Methods: Tremor propagation was characterized using the gains between tremorogenic neural drive to the 50 muscles (inputs) and tremulous joint rotations in the 7 joint degreesof- freedom (DOF) from shoulder …

Lab: Developing Explainable Multimodal Ai Models With Hands-On Lab On The Life-Cycle Of Rare Event Prediction In Manufacturing, Chathurangi Shyalika, Ruwan Wickramarachchi, Revathy Venkataramanan, Dhaval Patel, Amit Sheth

Faculty Publications

In the age of Industry 4.0 and smart automation, unplanned downtime is costing industries over $50 billion annually. Even with preventive maintenance, industries like automotive lose more than $2 million per hour due to downtime caused by unexpected or "rare'' events. The extreme rarity of these events makes their detection and prediction a significant challenge for AI practitioners. Factors such as the lack of high-quality data, methodological gaps in the literature, and limited practical experience with multimodal data exacerbate the difficulty of rare event detection and prediction. This lab will provide hands-on experience to learn how to address these challenges …

Urbanization Impacts Dissolved Organic Matter Concentration And Quality In A Southeastern United States Watershed, Gwendolyn M. Hopper, Erik M. Smith, Jade Dormoy-Boulanger, Claudia R. Benitez-Nelson

Faculty Publications

Blackwater rivers are named due to their exceptionally high concentrations of chromophoric dissolved organic matter (CDOM). They are the predominant lotic ecosystem in the United States Southeastern Coastal Plain, a region experiencing some of the nation’s highest rates of development. This study assessed variability in DOM concentration and composition across forested to urbanized blackwater systems in coastal South Carolina, U.S. Dissolved organic carbon and nutrient concentrations as well as absorbance and fluorescence optical properties reveal that urban sites have lower concentrations, elemental ratios, and less complex DOM. In contrast, forested blackwater sites have concentrations an order of magnitude higher, elevated …

A Digital Twin Based Forecasting Framework For Power Flow Management In Dc Microgrids, Kerry Sado, Jarrett Peskar, Austin Downey, Jamil A. Khan, Kristen Booth

Faculty Publications

The ability to forecast system conditions is integral to the definition and functionality of digital twins. While forecasting methods have been explored for use in digital twin systems, the integration of feedback mechanisms for real-time forecasting and in-situ decision-making in DC microgrids has not been extensively investigated. This research develops a modular forecasting framework tailored for digital twins in DC microgrids to enable real-time monitoring, online forecasting, and decision-making. DC microgrids, characterized by dynamic load variations, benefit from advanced predictive capabilities to maintain stability and operational efficiency. The proposed digital twin-based forecasting framework addresses these challenges by providing real-time predictive …

Probing Ion-Blocking Electrode Rigs For Ionic Conductivity In Hybrid Solid Polymer Electrolytes, Kyra Glassey, Gabriela Roman-Martinez, Liliana Delatte, Thomas Burns, Monirosadat Sadati, Paul T. Coman, Ralph E. White

Faculty Publications

Solid electrolytes are critical for structural batteries, combining energy storage with structural strength for applications like electric vehicles and aerospace. However, achieving high ionic conductivity remains challenging, compounded by a lack of standardized testing methodologies. This study examines the impact of experimental setups and data interpretation methods on the measured ionic conductivities of solid polymer electrolytes (SPEs). SPEs were prepared using a polymer-induced phase separation process, resulting in a bi-continuous microstructure for improved ionic transport. Eight experimental rigs were evaluated, including two- and four-electrode setups with materials like stainless steel, copper, and aluminum. Ionic conductivity was assessed using electrochemical impedance …

Toward Quantifying Interpolation Uncertainty In Set-Line Spacing Hydrographic Surveys, Elias Adediran, Christos Kastrisios, Kim Lowell, Glen Rice, Qi Zhang

Faculty Publications

The oceans remain one of Earth’s last great unknowns, with about 74% still unmapped to modern standards. Consequently, interpolation is employed to create seamless digital bathymetric models (DBMs) from incomplete hydrographic datasets, but this introduces unquantified depth uncertainties. This study aims to estimate and characterize uncertainties arising from set-line spacing hydrographic surveys, which are important for nautical charting, navigational safety, and many other applications. By sampling at different line spacings four complete coverage testbeds that vary in slope and roughness, the study interpolates across entire testbed areas using Spline, Inverse Distance Weighting, and Linear interpolation. The resulting interpolation uncertainties are …

Si-Doped Ain Using Pulsed Metalorganic Chemical Vapor Deposition And Doping, Tariq Jamil, Abdullah Al Mamun Mazumder, Mohammod Ali, Jingyu Lin, Hongxing Jiang, Grigory Simin, M. Asif Khan

Faculty Publications

In this paper we describe a pulsed metalorganic chemical vapor deposition (MOCVD) Si-doping approach for AlN epilayers over bulk AlN. The Al-rich growth/doping conditions in the pulsed MOCVD process resulted in n-AlN layers with transmission line model currents that were an order higher than for structures on layers that were grown/doped at identical temperatures using the conventional MOCVD process. Our work demonstrated that like the other reported approaches such as UV exposure during growth, the pulsed MOCVD process is also very effective in reducing point defects by the defect quasi-Fermi level-chemical potential control.

Accelerated Multiobjective Calibration Of Fused Deposition Modeling 3d Printers Using Multitask Bayesian Optimization And Computer Vision, Craig S. Ganitano, Benji Maruyama, Gilbert L. Peterson

Faculty Publications

Proper process parameter calibration is critical to the success of fused deposition modeling (FDM) three-dimensional (3D) printing, but is time-consuming and requires expertise. While existing systems for autonomous calibration have demonstrated success in calibrating for a single objective, users may need to balance multiple conflicting objectives. Herein, an easily deployable, camera-based system for autonomous calibration of FDM printers that optimizes for both part quality and completion time is presented. Autonomous calibration is achieved through a novel, multifaceted computer vision characterization and a multitask learning extension to Bayesian optimization. The system is demonstrated on four popular filament types using two distinct …

Streamlined Production, Protection, And Purification Of Enzyme Biocatalysts Using Virus-Like Particles And A Cell-Free Protein Synthesis System, Seung O. Yang, Joseph P. Talley, Gregory H. Nielsen, Kristen M. Wilding, Bradley Charles Bundy

Faculty Publications

Enzymes play an essential role in many different industries; however, their operating conditions are limited due to the loss of enzyme activity in the presence of proteases and at temperatures significantly above physiological conditions. One way to improve the stability of these enzymes against high temperatures and proteases is to encapsulate them in protective shells or virus-like particles. This work presents a streamlined, three-step, cell-free protein synthesis (CFPS) procedure that enables rapid in vitro enzyme production, targeted encapsulation in protective virus-like particles (VLPs), and facile purification using a 6× His-tag fused to the VLP coat protein. This process is performed …