Digital Commons Network^™

Design, Construction, And Initial Testing Of A Oxy-Acetylene Testing Facility, Blake Bowman, Davide Viganò

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Thermal Protection Systems (TPS) are critical for atmospheric re-entry and hypersonic flight vehicles, yet ground-based evaluation of TPS materials remains challenging due to the cost, complexity, and limited availability of large arc-jet and inductively coupled plasma (ICP) facilities. Oxy-acetylene testing provides a low-cost and accessible alternative for preliminary material screening, sensor development, and fundamental studies of material response under high heat-flux conditions. This paper presents the design, construction, and initial validation of the High-Enthalpy Acetylene Testing (HEAT) facility at Missouri University of Science and Technology. The facility incorporates a modular experimental architecture, independently controlled oxygen and acetylene mass-flow systems, and …

Supersonic Wind Tunnel Free Stream Turbulence Characterization Using 2-Point Focused Laser Differential Interferometry, Joseph Villarreal, Joshua Gary, Davide Vigano

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Non-intrusive laser-based diagnostics, such as Two-Point Focused Laser Differential Interfer-ometry (2-FLDI), play a crucial role in modern aerodynamic research by enabling simultaneous measurements of density and velocity in compressible flows. A 2-FLDI system has been developed and implemented for the Missouri S&T Supersonic Wind Tunnel to characterize free stream turbulence fluctuations and free stream convective velocity. Design choices that enabled the 2-FLDI to overcome low turbulence to measure free stream velocity are detailed. The free stream velocity measurements are validated against previous particle image velocimetry data, showing good agreement. Analysis of normalized velocities and density-based turbulence intensities found that the …

Corrigendum To “3d Semi-Analytical Thermo-Elasto-Plastic Model For Additive Manufacturing”(Additive Manufacturing, (2026), 127, C, (105308), (S2214860426002344), 10.1016/J.Addma.2026.105308), Tao Liu, Ming C. Leu, Edward C. Kinzel, Chinedum Okwudire

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The author regret about the correction in the Equation B(1) in original article. The corrected version of the Equation B(1) is given below,(1.1)∂uxxx,ξ∂x=116πμ1−ν4ν−1x−ξxR3−3x−ξx3R5−8ν−5x−ξxR13+34ν−3x−ξx3R15−18x−ξxzξzR15+30x−ξx3zξzR17−12ν−12ν−1x−ξxR1R1+z+ξz2+4ν−12ν−1x−ξx3R13R1+z+ξz2+8ν−12ν−1x−ξx3R12R1+z+ξz3 The authors would like to apologise for any inconvenience caused. DOI of original article: < 10.1016/j.addma.2026.105308>

Multi-Period Coordinated Planning Of Xfcs In Coupled Tn-Pdn Networks: Integrating Demand Charge Reduction And Pre-Existing Infrastructure, Waqas Ur Rehman, Siyuan Wang, Liheng Lv, Jonathan W. Kimball, Rui Bo

Electrical and Computer Engineering Faculty Research & Creative Works

The widespread adoption of electric vehicles (EVs) and transportation electrification is encumbered by two chief barriers: i) the limited driving range of EVs in the market today and ii) inadequate charging infrastructure support. This paper aims to address the latter bottleneck and proposes a strategic multi-period coordinated planning model to optimally site and size battery energy storage system (BESS) assisted extreme fast charging stations in a highway transportation network and solar systems in a power distribution network. The proposed approach accounts for pre-existing charging stations, the increasing EV penetration levels, decreasing technology costs, and technological advancements in the future and …

Mitigating Hysteresis In Metal-Coated Fibers Via Optimized Thermal Treatment For Advanced Distributed High-Temperature Sensing Applications, Koustav Dey, Rony Kumer Saha, Bohong Zhang, S. Narasimman, Farhan Mumtaz, Jeffrey D. Smith, Rex E. Gerald, Ronald J. O'Malley, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

Metal-coated optical fibers are widely employed in sensing applications owing to their superior mechanical strength and corrosion resistance. However, their calibration at elevated temperatures is hindered by hysteresis, manifested as discrepancies between heating and cooling cycles, primarily caused by residual strain from mismatched thermal expansion coefficients (TECs) between the metal coating and silica cladding. This research introduces an optimal heat treatment procedure aimed at minimizing the impact of the mismatch in TECs between the cladding and the coating materials that causes the residual strain in gold (Au) and copper (Cu) coated fibers for achieving reliable distributed high temperature sensing up …

Multi-Parameter Optimization And Adaptive Temperature Compensation For Fbg Strain Sensors In Wide-Temperature-Range Aerospace Applications, Ruling Zhou, Jiacheng Yu, Yutang Dai, Jianguan Tang, Minghong Yang, Farhan Mumtaz

Electrical and Computer Engineering Faculty Research & Creative Works

Accurate strain measurement in cryogenic fuel pipelines is crucial for ensuring the structural integrity and reliability of rocket engine systems operating under extreme thermal conditions. Fiber Bragg grating (FBG) sensors show significant potential for such applications; however, their inherent temperature-strain cross-sensitivity limits performance over wide temperature ranges. This research presents an enhanced compensation strategy combining multi-parameter optimization with temperature-zone-specific adaptation to improve the accuracy and stability of FBG-based strain sensing in harsh aerospace environments. Four special steel substrate materials including S03, S06, S07, and 1Cr18Ni9Ti, were evaluated using strain transfer theory and thermo-mechanical coupling simulations. Genetic algorithms optimized key design …

Waveguide-Assisted Single-Mode Fiber Bragg Gratings In A Highly Multimode Coreless Fiber Via Femtosecond Laser Inscription For Extreme Temperature Quasi-Distributed Thermal Sensing, Farhan Mumtaz, Koustav Dey, Bohong Zhang, Jeffrey D. Smith, Ronald J. O'Malley, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

This research reports a potential quasi-distributed thermal mapping optical sensing system for extreme temperatures, leveraging femtosecond (fs) laser inscribed single-mode fiber Bragg gratings (FBGs) and a waveguide within coreless, highly multimode optical fiber, resulting in a single-mode structure. Unlike doped single-mode fibers, coreless fibers composed of silica rods prevent issues associated with dopant migration and ensure data accuracy. The strategic placement of point-by-point FBGs in a cascaded formation on the fs-laser inscribed waveguide facilitates localized multipoint sensing. The long-term stability of the proposed waveguide-assisted FBG system was assessed over 24 hours at elevated temperatures (1000°C), showing no hysteresis during heating …

Embeddable Optical Fiber Sensor For Simultaneous Strain And Temperature Monitoring, Amardeep Kaur, Sudharshan Anandan, Steve Eugene Watkins, Yinan Zhang, Kumbla Chandrashekhara, Hai Xiao

Electrical and Computer Engineering Faculty Research & Creative Works

We present an embeddable hybrid optical fiber sensor based on a cascaded extrinsic Fabry–Pérot interferometer (EFPI) and intrinsic Fabry–Pérot interferometer (IFPI) for simultaneous strain and temperature monitoring in high-performance composite materials. The sensor is fabricated using femtosecond laser micromachining and is embedded within bismaleimide composite laminates manufactured via an out-of-autoclave process. Experimental results demonstrate linear and decoupled responses to strain and temperature, with the EFPI showing minimal temperature sensitivity (1.7 pm/°C) and the IFPI exhibiting high temperature sensitivity (16.1 pm/°C). Strain sensitivities for both components were consistent at 0.6pm/με in embedded conditions. The sensor maintained structural integrity and stable spectral …

Performance Analysis And Optimization Of Fructose Memristor-Based Neuromorphic Systems, Harshvardhan Uppaluru, Shakil Mahmud Jiban, Shah Zayed Riam, Feng Zhao, Jinhui Wang

Electrical and Computer Engineering Faculty Research & Creative Works

Natural organic memristors have demonstrated promising synaptic behavior, positioning them as strong candidates for synaptic devices in neuromorphic systems. This paper presents the fabrication and evaluation of a neuromorphic system based on natural organic 16-level and 32-level fructose memristors. First, the manufacturing process of fructose memristors is described in detail. Second, the nonlinear property associated with fructose memristors is investigated, and an optimization method is applied to address the nonlinear effects. The performance of the fructose memristor-based neuromorphic system on MNIST with a multi-layer perceptron and on CIFAR-10 with VGG-8 is evaluated and reported under various conditions -with/without nonlinearity optimization …

Integrating Optical And Radiofrequency Interferometry For Enhanced Phase Sensing, Ruimin Jie, Zhaopeng Zhang, Chen Zhu, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

Interferometry is a crucial investigative technique used across diverse fields to achieve high-precision measurements. It works by analyzing the phase difference between two interfering waves, which results from variations in optical path lengths within an interferometer. We introduce a novel method for directly measuring changes in the phase difference within an optical interferometer, importantly, with the added advantage of a controllable enhancement factor. This approach is achieved through a two-step process: first, the optical phase difference is encoded into a sub-GHz radiofrequency (RF) signal using microwave-photonic manipulation; then, RF interferometry-assisted phase amplification is implemented at the destructive interference point. In …

New Metrics For Disambiguating Feature Overlap And Catastrophic Forgetting In Incremental Learning Contexts, Niklas M. Melton, Leonardo Enzo Brito Da Silva, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

Catastrophic forgetting remains a central challenge in lifelong learning, where newly acquired knowledge interferes with previously learned tasks, degrading performance over time. Mitigation strategies such as rehearsal and regularization have been proposed, but both introduce limitations, either by retaining old data or by constraining model updates in ways that may impair learning. Complicating matters, recent findings show that feature-space overlap between tasks can produce similar performance drops even in models that memorize data, making it difficult to distinguish true forgetting from representational interference. Current accuracy-based metrics fail to disentangle these effects, undermining diagnostic clarity. In this work, we introduce the …

Enhancing Measurement Accuracy: The Impact Of Missing Data On Parameter Estimation In Mass-Spring-Damper Systems, Michkath Omanda Bouraima, Steven Thompson, Maciej J. Zawodniok

Electrical and Computer Engineering Faculty Research & Creative Works

In sensor-driven dynamic systems, missing data can severely degrade parameter estimation accuracy. This article investigates the impact of missing data on phase estimation in a mass-spring-damper system using an information-theoretic framework based on the Cramér-Rao Lower Bound (CRLB). Closed-form CRLB expressions are derived for four scenarios: complete data, missing completely at random (MCAR) deletion, MCAR-based imputation, and missing at random (MAR) missingness via a selection-weighted formulation. These bounds are used as theoretical benchmarks to evaluate classical imputation methods (last observation carried forward (LOCF), linear interpolation) and advanced approaches (Kalman filtering, Rauch-Tung-Striebel (RTS) smoothing, Bayesian inference, and transformer-based imputation) through Monte …

Honey-Cnt Memristive Artificial Synaptic Device For Sustainable Neuromorphic Computing System, Md Mehedi Hasan Tanim, Zoe Templin, Harshvardhan Uppaluru, Jinhui Wang, Kuan Yew Cheong, Feng Zhao

Electrical and Computer Engineering Faculty Research & Creative Works

Brain-inspired neuromorphic computing systems require hardware components analogous to biological neurons and synapses. Honey based natural organic memristor has demonstrated promising nonvolatile memristive behaviors, with the advantages of sustainability, environmentally friendliness, and low-cost manufacturing. In this study, carbon nanotubes (CNTs) are added in honey to fabricate honey-CNT memristive artificial synaptic devices. Honey-CNT film is characterized by micro-Raman spectroscopy and the distribution of CNT bundles embedded in the honey-CNT composite layer by cross-sectional scanning electron microscopy for the first time. Critical synaptic functions of the honey-CNT memristor, including spike-rate-dependent plasticity, spike voltage dependent plasticity, learn-forget-relearn, and supralinear spatial summation are revealed, …

Resolving Stiffness Trade-Offs In Simultaneous Pressure And Vibration Sensing Using A Corrugated-Tube Fiber-Optic Sensor, Yizheng Chen, Yan Tang, Jie Huang, Qi Zhang, Biyao Shi, Zewei Wu

Electrical and Computer Engineering Faculty Research & Creative Works

This article proposes and experimentally demonstrates a corrugated-tube-based fiber-optic sensor capable of measuring pressure, vibration, or both simultaneously. To address the limited sensitivity of conventional diaphragm-based designs, the sensor incorporates an optimized corrugated tube that balances the conflicting stiffness requirements for pressure and vibration measurements. The corrugated tube, acting as a mechanical transducer, is integrated with an extrinsic fiber-optic Fabry–Perot interferometer (EFPI). The EFPI cavity is formed between a reflective surface at the sealed end of the corrugated tube and the cleaved end face of an optical fiber fixed within a mounting assembly. In this configuration, displacement of the corrugated …

Nash Equilibrium Strategies For Multicluster Pursuit–Evasion Game With Disturbances: A Prescribed-Time Convergence Approach, Lei Xue, Xian Yu, Yongbao Wu, Jian Liu, Changyin Sun, D. C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

This article investigates the problem of prescribed-time Nash equilibrium (NE) seeking for a multicluster pursuit–evasion game (PEG) subject to external disturbances. To mitigate the impact of disturbances and reach the NE within a user-defined prescribed time, a prescribed-time disturbance observer (PTDO) is devised to estimate and compensate for them. Based on this observation, a novel control algorithm is developed, which facilitates collaboration among multiple pursuers to capture multiple evaders within the prescribed time. It is theoretically demonstrated that the designed algorithm ensures prescribed-time convergence to the NE of the multicluster PEG with disturbances. Finally, numerical simulations are conducted to verify …

Transformer-Customer Relationship Identification Based On Load-Switching Fluctuation Characteristics Considering Same-Feeder-Adjacent-Transformer Condition, Yanan Zhang, Gan Zhou, Yuyuan Liu, Wei Gu, Yanjun Feng, Yujue Wang, Rui Bo

Electrical and Computer Engineering Faculty Research & Creative Works

Accurately identifying the connectivity between transformers and downstream three-phase customers in low-voltage distribution networks is challenging, because voltage curves of different phases and nearby nodes can be weakly distinguishable, especially when adjacent transformers on the same feeder serve geographically close customers with highly similar voltage curves. This paper proposes a novel method based on load-switching fluctuation characteristics recorded by smart meters. By extracting localized current and voltage fluctuations and establishing correlation matching, the method overcomes the limited discriminability using steady-state measurements. The method operates in two stages: first, switching-induced fluctuation characteristics are extracted and matched to cluster customers by the …

Deep Learning Based High-Resolution Electromagnetic Inversion Imaging Using Deep Convolutional Double-Module Structure, He Ming Yao, Shiji Song, Lijun Jiang, Michael Ng

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, a novel deep learning (DL) approach has been proposed to realize high-resolution electromagnetic (EM) inversion imaging. The newly proposed approach is based on the deep convolutional double-module structure (DCDMS), consisting of the pixel-interpolating module and the corresponding quality-improving module. While the pixel-interpolating module roughly increases the 'resolution' of the initial input, the following quality-improving module realizes quantitative EM imaging in high resolution. The input of the proposed DCDMS adopts the mixed input scheme, consisting of the received EM scattered field and the initial reconstruction in much low resolution computed from Gauss-Newton method. The output of the proposed …

Lidar-Based Framework For Detecting Suspicious Human Activities, Ahd Aljumah, Charalampos Antoniadis, Hakim Ghazzai, Nawfal Guefrachi, Ahmad Alsharoa, Gianluca Setti

Electrical and Computer Engineering Faculty Research & Creative Works

This study explores the development of Human Activity Recognition (HAR) systems capable of identifying suspicious activities to enhance security in public spaces. We propose an innovative solution that integrates LiDAR sensors with deep learning technologies. Our method employs advanced models operating on LiDAR point cloud, PV-RCNN for human detection, and LidarGait++ for classifying activities into categories such as standing or walking (non-suspicious) and sneaking or fighting (suspicious). Due to the scarcity of suitable real-world datasets for training such systems, we utilize a 3D simulation tool, Blender, to create realistic environments and generate labeled point cloud data. This synthetic dataset allows …

Effect Of Sample Properties On Short-Circuited Waveguide Measurements For Materials Characterization, Alexander Hook, Jared Sinkey, Kristen M. Donnell

Electrical and Computer Engineering Faculty Research & Creative Works

Microwave materials characterization measurements can be performed using a number of well-established approaches. One such approach, the filled transmission line approach featuring a short-circuited rectangular waveguide (SC-RWG) sample holder, is known to have sample placement restrictions related to measurement viability. This work focuses on this approach and addresses the measurement restrictions within the context of sample length and dielectric properties. The complex reflection properties, S11, of a sample placed in a SC-RWG sample holder are studied to quantitively define when a sample must be offset from the SC-end. The impact of the sample holder is also studied from a measurement …

Deep Learning Approach For Microwave Imaging Based On Deep Convolutional Asymmetric Encoder-Decoder Structure And Physics-Induced Loss, He Ming Yao, Shiji Song, Michael Kwok Po Ng, Lijun Jiang

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, we introduce an innovative deep learning (DL) methodology designed for real-time quantitative microwave imaging (MWI). Our approach is centered around the utilization of a deep convolutional asymmetric encoder-decoder structure (DCAEDS), which requires only a single-frequency far-field measurement of the electromagnetic (EM) scattered field as input and subsequently predicts the contrasts (permittivities) of the target materials. During the offline training process, we incorporate an EM forward solver specifically crafted to compute the EM scattered field generated by the predicted target contrasts (permittivities) produced by the DCAEDS. The DCAEDS is seamlessly integrated with this EM forward solver to optimize …

Dynamic Modeling Of The Earth's Trapped Proton Environment, Xiaojing Xu, Steve R. Blattnig, Francis F. Badavi, Martha S. Clowdsley, Edward J. Semones

Physics Faculty Publications

Context: Reliable prediction of space radiation exposure is critical for safeguarding spacecraft systems and ensuring astronaut health during missions. Accurate radiation risk assessment for space mission requires advanced models of the Earth’s trapped proton environment. These models must reflect temporal variations driven by geomagnetic field evolution and solar cycle modulation. Existing static models, such as AP8 and IRENE-AP9, are not designed to fully capture these evolving conditions. Aims: This paper presents a dynamic modeling method for the prediction of trapped proton fluxes, which incorporate time-dependent variations due to geomagnetic field evolution and solar cycle fluctuations. Methods: The …

Forcing A Molecule To Switch: Quantifying Mechanical Control At The Atomic Scale, A. M. Shashika D. Wijerathna, Markus Zirnheld, Michael L. Hildebrand, Myles Perry, Marjorie Cenese, Yuan Zhang

Physics Faculty Publications

Mechanically induced conformational switching at the single-molecule level represents a fundamental mechanism for molecular functionality, yet quantitative characterization of the underlying force and energy landscape remains limited. Here, we study individual TBrPP-Co(II) molecules on Au(111) using qPlus atomic force microscopy. By reconstructing interaction potentials from 3D Δf(x,y,z) data, we determine a threshold force of ∼96 ± 8 pN and a tip-induced switching interaction energy of ∼38 ± 4 meV associate with the conformational transition. The isolated tip-molecule force follows a power law (exponent ∼6), indicating dominance of long-range van der Waals interactions. …

Evaluating The Impact Of Cognitive Distraction On Spaceflight-Relevant Task Performance Using Surface Electromyography And Motion Capture, Allyson K. Mitchell

UNF Graduate Theses and Dissertations

Cognitive distraction poses a risk to astronaut performance during complex, multitasking operations in spaceflight environments. This study examined the effects of cognitive load on neuromuscular coordination and task execution using surface electromyography (sEMG) and motion capture. Thirteen participants performed spaceflight-relevant tasks under undistracted and distracted conditions, with distraction induced through verbal questioning. EMG signals from eight upper-extremity muscles were processed using envelope filtering, peak normalization, and time normalization to enable inter-subject comparison, and group-level mean activation with standard deviation was analyzed. While overall muscle activation was similar between conditions, phase-dependent differences were observed, with undistracted trials showing higher activation during …

Multi-Objective Optimization Strategy For Component Sizing In Solar-Hydrogen Microgrids Using An Advanced Hybrid Genetic Algorithm, Dylan Jones

UNF Graduate Theses and Dissertations

This thesis presents the development of a genetic algorithm (GA) optimization framework for the design and component sizing of hybrid solar-hydrogen microgrids. The framework addresses a critical gap in research and existing commercial tools by unifying performance maximization and cost minimization objectives across both grid-tied and islanded configurations. Integrating solar photovoltaics, electrolyzers, hydrogen storage, fuel cells, and batteries, the GA employs adaptive weighting and dynamic boundary constraints to balance technical feasibility with economic efficiency. To ensure real-world viability, the algorithm relies on a novel Daylight Sun Factor (DSF) for localized solar assessment and was rigorously validated against multi-year, high-fidelity irradiance …

Mechanical Behavior Of Additively Manufactured Ti-6al-4v Eli Parts: Effects Of Laser Parameter Selection, Samuel Lopez

UNF Graduate Theses and Dissertations

Additive manufacturing (AM) of TI-6AL‑4V Extra‑Low Interstitial (ELI) enables complex geometries for fatigue‑critical medical device applications, yet fatigue performance remains sensitive to process‑induced defects. This work investigates the effect of laser process parameter selection on the microstructure, mechanical properties, and fatigue behavior of TI- 6AL‑4V ELI fabricated via laser powder bed fusion (L‑PBF) using a Renishaw RenAM system. The influence of laser parameters was isolated by holding powder chemistry, build orientation, scan strategy, sub‑transus annealing, and post‑processing constant between a non‑optimized baseline and an optimized parameter set selected based on tensile performance.

Optical microscopy showed the optimized condition exhibited improved …

Experimental Validation Of Optical Wireless Communication And Power Transfer For Uav Applications, Fnu Dhruv

UNF Graduate Theses and Dissertations

Unmanned Aerial Vehicles (UAVs) have revolutionized emergency response, disaster assessment, and search-and-rescue operations. However, their operational efficacy is fundamentally constrained by limited battery endurance and the susceptibility of traditional radio-frequency communication to disruption in adverse weather. To address these limitations, this thesis proposes and experimentally validates a novel architecture integrating Free-Space Optical (FSO) communication with Simultaneous Lightweight Information and Power Transfer (SLIPT). This system utilizes a split-beam configuration to concurrently enable high-bandwidth data transmission and optical energy harvesting to replenish the UAV's battery pack. The research was conducted in three progressive phases. Initially, system feasibility was established through rigorous optical …

Evaluating Species At Risk In Data-Limited Fisheries: A Productivity-Susceptibility Analysis For Marine Aquarium Fish, Gabrielle A. Baillargeon, Alice A. Wynn, Jemelyn Grace P. Baldisimo, Michael F. Tlusty, Andrew L. Rhyne

Biological Sciences Faculty Publications

The marine aquarium trade (MAT) is a significant global industry harvesting millions of wild-caught, live coral reef fishes for public and private aquaria markets in the United States and Europe annually, while supporting fisher livelihoods in the Indo-Pacific. This diverse and species-rich trade is considered data-limited, creating barriers to quantifying the current and future socio-ecological sustainability of the fishery. We present a revised and expanded productivity–susceptibility analysis (PSA) that serves as a holistic risk assessment to estimate the vulnerability of marine aquarium fish to overfishing. Our global analysis includes 306 species that are actively in trade. Improvements to the PSA …

Quantitative Grain Structure And Texture Analysis Of Hot-Pressed Zrb2 Via 3d Ebsd, Randi Swanson, Michael Chapman, Yue Zhou, Ashley Hilmas, Lisa Rueschhoff, Michael Uchic, William Fahrenholtz, Scott J. Mccormack

Materials Science and Engineering Faculty Research & Creative Works

Understanding and controlling the grain structure of ZrB₂ is critical for optimizing its mechanical and thermal performance in high-temperature applications. Fully dense ZrB₂, densified by hot pressing at 2150˚C and 32 MPa, was analyzed in three dimensions using electron backscattered diffraction, electron and optical microscopy, and mechanical polishing serial sectioning. Grain size followed a gamma distribution, with extreme deviations observed only in the largest 0.1% of grains. Large grains exhibited plate-like morphologies, with the shortest-to-longest axis ratio converging to ∼0.4 as grain volume increased. This work revealed a crystallographically controlled growth mechanism orthogonal to [0001] that is …

High Temperature Diffraction From Aerodynamically Levitated Materials, Chris J. Benmore, Stephen K. Wilke, David Lipke, Richard Weber

Materials Science and Engineering Faculty Research & Creative Works

Aerodynamic levitation combined with laser beam heating has become an established technique for studying the structure of materials at ultra-high temperatures and under non-equilibrium conditions. This article briefly highlights some recent technical and scientific advancements in understanding the relationships between a material's behavior and its structure, investigated using diffraction methods. It focuses on three evolving frontiers: sophisticated sample environments for accessing metastable states and reactive chemistries, high-flux photon and neutron probes to reveal atomic structure, and advanced computational modeling frameworks. Free from contamination, containerless processing (levitation) can minimize heterogeneous nucleation at the interface, enabling access to deeply supercooled melts or …

Investigating The Effects Of Pressure On Fe And Co Intercalated 2h-Tas2 Through First-Principle Calculations, Ronald E. Putnam Jr.

UNF Graduate Theses and Dissertations

Using first-principles methods, we investigate the effects of applied isotropic pressure on the electronic and magnetic properties of intercalated Fe1/3TaS2 and Co1/3TaS2. Fe1/3TaS2 has been shown to be a ferromagnet that undergoes structural and magnetic phase transitions under applied pressure. The magnetic phase transitions are observed to be linked to the structural shift, and a mixture of magnetic phase states is present between 3 GPa and 6 GPa. Co1/3TaS2 was found to be antiferromagnetic, as confirmed by experimental work. One- and two-unit-cell systems of Co1/3TaS2 are analyzed, both showing band splitting that disappears under pressure. The application of pressure forces …