Digital Commons Network^™

Synergistic V2ctₓ Mxene–Pani Hybrid With Expanded Interlayers For Ultrastable And High-Rate Pseudocapacitive Energy Storage, Amideddin Nouralishahi, Maryam Sharifi Paroushi, Mansour Razavi, Amarachi Clare Nnachor, Harish Singh, Manashi Nath

Chemistry Faculty Research & Creative Works

Recently, MXene-conducting polymer hybrids have emerged as promising electrode materials for sustainable energy storage applications, owing to their impressive electrochemical properties. Herein, we report the synthesis of vanadium carbide MXene nanoparticles (V2CT_x-MXene) using innovative Spark Plasma Sintering (SPS) technology followed by exfoliation steps. The V2CT_x nanoparticles were incorporated with PANI (MXene-PANI) by electrochemical polymerization of aniline monomers in the presence of V2CT_x nanolayers, to be used as a highly efficient material for charge storage application. PANI nanofibers form a conductive and porous architecture, which intercalates the V2CT_x nanoflakes. The resulting structure increases the interlayer spacing …

Rogue Waves In Extended Gross-Pitaevskii Models With A Lee-Huang-Yang Correction, Sathyanarayanan Chandramouli, S. I. Mistakidis, G. C. Katsimiga, D. J. Ratliff, D. J. Frantzeskakis, P. G. Kevrekidis

Physics Faculty Research & Creative Works

We explore the existence and dynamical generation of rogue waves (RWs) within a one-dimensional quantum droplet-bearing environment. RWs are computed by deploying a space-time fixed point scheme to the relevant extended Gross-Pitaevskii equation (eGPE). Parametric regions where the ensuing RWs are different from their counterparts in the nonlinear Schrödinger equation are identified. To corroborate the controllable generation—relevant to ultracold atom experiments—of these rogue patterns, we exploit two different protocols. The first is based on interfering dam break flows emanating from Riemann initial conditions, and the second refers to the gradient catastrophe of a spatially localized waveform. A multitude of possible …

Datamut: Deterministic Algorithms For Time-Delay Attack Detection In Multi-Hop Uav Networks, Keiwan Soltani, Federico Corò, Punyasha Chatterjee, Sajal K. Das

Computer Science Faculty Research & Creative Works

Unmanned Aerial Vehicles (UAVs), also known as drones, have gained popularity in various fields such as agriculture, emergency response, and search and rescue operations. UAV networks are susceptible to potential security threats, such as wormhole attacks, jamming, spoofing, and false data injection. Time-Delay Attack (TDA) is a unique attack in which malicious UAVs intentionally delay packet forwarding, posing significant threats, especially in time-sensitive applications. It is challenging to distinguish malicious delay from benign network delay due to the dynamic nature of UAV networks, intermittent wireless connectivity, or the Store-Carry-Forward (SCF) mechanism during multi-hop communication. Some existing works propose machine learning-based …

Pciafl: Personalized And Class Imbalance-Aware Federated Learning For Driver Behavior Classification, Osho Osho, Shubh Garg, Suchetana Chakraborty, Sajal K. Das

Computer Science Faculty Research & Creative Works

Automated understanding of driver behavior from vehicular kinematics is vital for safety-aware intelligent transportation systems. However, centralized cloud processing suffers from latency, scalability, and privacy issues. Federated Learning (FL) provides a decentralized alternative but faces two major challenges: (i) non-IID client data due to heterogeneous driving styles and sensors, and (ii) severe class imbalance, as risky behaviors are inherently rare. In this work, we propose a personalized FL framework that uses a shared CNN-LSTM backbone with client-adaptive classifiers and incorporates a cost-sensitive loss to address behavior skew. Evaluated on the UAH-DriveSet dataset, our method achieves 92.60% accuracy and 91.68% macro-F1, …

Rescue: Routing Under Evolving Stochastic Congestion And Uncertain Spread In Wildfire Emergencies, Sowjanya Tammali, Arindam Khanda, Anurag Satpathy, S. M. Shovan, Sajal K. Das

Computer Science Faculty Research & Creative Works

Wildfires cause unpredictable spread and panic-driven congestion, posing severe challenges to evacuation planning. We present RESCUE (Routing under Evolving Stochastic Congestion and Uncertain Spread in Wildfire Emergencies), a dynamic, risk-aware framework that models the road network as a time-varying weighted graph. RESCUE operates in two stages: (i) a preprocessing phase integrating fire forecasts, traffic density, and distance to assign edge weights, and (ii) a real-time routing phase that adaptively updates paths using a multi-granular strategy distinguishing macro-level disruptions (e.g., rapid spread) from micro-level changes (e.g., local congestion). Two stochastic edge-cost functions are introduced: the Edge-Fire Risk Function (EFRF), estimating road …

Enhanced Superconductivity And Vortex Dynamics In Quasi-1d Tas2 Nanowires, Mathew Pollard, Visakha Ho, Clarissa Wisner, Eric W. Bohannan, Yew San Hor

Chemistry Faculty Research & Creative Works

We report the synthesis of high-quality 2H-TaS₂ nanowires via a controlled two-step conversion process from TaS₃ precursors, achieving robust superconductivity with a transition temperature T c ≈ 3.6K, which is significantly higher than bulk 2H-TaS₂ (T c ≈ 0.8K). Structural and compositional analyses confirm phase purity and preserved one-dimensional morphology, while magneto transport measurements reveal an enhanced upper critical field μ 0 H c2 (2K)≈5 T, far exceeding the bulk value (_μ0H_c2 (0)≈1.17T), attributed to dimensional confinement and suppression of charge-density wave order. Magnetic characterization demonstrates complex vortex dynamics, including flux jumps and a …

Meshless Collocation Methods For Time-Dependent Nonlocal Problems Based On Radial Basis Functions, Qiao Zhuang, Yanzhi Zhang, Zhongqiang Zhang

Mathematics and Statistics Faculty Research & Creative Works

We present radial basis function (RBF) collocation methods for time-dependent space fractional problems on general bounded domains. Building on a recently developed approach for accurately computing the integral fractional Laplacian of any RBF, we design collocation schemes for fractional heat and Stokes equations using extended-domain techniques. In particular, we propose a numerical Leray projection method for fractional Stokes problems, where both the discrete projection operator and the collocation scheme are formulated on extended domains to handle complex domains. Numerical results demonstrate the effectiveness of the proposed methods in solving time-dependent nonlocal problems on complex domains.

January 2026 Cafe Newsletter - Special Events Edition, Missouri University Of Science And Technology

CAFE Faculty Newsletters

No abstract provided.

A Coupled Thermo-Hydraulic Transfer Model For Soil Freezing, Antai Dong, Xiong Zhang

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Frost heave is a common challenge in cold regions, threatening infrastructure stability. Despite decades of research, numerical simulation remains difficult due to the complex nature of coupled processes. This study presents a coupled thermo-hydraulic model for soil freezing, developed within the framework of unsaturated soil mechanics. The model uses suction and temperature as primary variables and incorporates a method to estimate ice content. It employs a soil freezing characteristic surface (SFCS), previously developed in related work, to calculate unfrozen water content as a function of both suction and temperature in partially frozen soils. The model is implemented in COMSOL for …

Soil Freezing Characteristic Surface For Partially Frozen Soils, Antai Dong, Xiong Zhang, Ming Xiao

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

The soil freezing characteristic curve (SFCC), which relates unfrozen water content to temperature, is a fundamental constitutive relationship in frost heave simulations. However, the influence of soil suction, another critical state variable, is often neglected. This study highlights how the SFCC is significantly affected by suction conditions, with unfrozen water content varying markedly between saturated (suction = 0) and completely dried (suction = ∞) conditions at the same subfreezing temperature. Recognizing this limitation, the concept of the soil freezing characteristic surface (SFCS) is proposed to incorporate the impacts of both temperature and suction on unfrozen water content. After that a …

Managing And Accelerating The Circular Economy Transitions Within The Construction Value Chain Using Network Governance And Game Theory Systems Perspectives, Radwa Eissa, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

The fragmented nature of the construction industry has hindered its transition toward circular economy (CE) practices. While game theory (GT) has been successfully applied to support the strategic decisions of CE transitions in other sectors, CE-GT models in the construction domain remain extremely limited. This paper addresses two research questions: (1) how are CE network governance activities currently modeled using GT across domains? (2) How can such models be transferred and adapted to solve strategic interactions within the construction value chain in a manner that enables CE practices to emerge as equilibrium outcomes? These questions are driven by the need …

Optimal Error Estimates For A Semi-Discrete Finite Element Scheme Of Cahn-Hilliard-Navier-Stokes-Darcy Model, Yanyun Wu, Yali Gao, Xiaoming He, Yanping Lin

Mathematics and Statistics Faculty Research & Creative Works

In this paper, we present a rigorous optimal error analysis for a semi-discrete finite element method of the coupled Cahn-Hilliard-Navier-Stokes-Darcy model. The optimal convergence order for the phase variable in the L^∞(0,T;H¹) norm and the velocity in the L^∞(0,T;L²) norm are proved with two key techniques. One key technique is establishing the discrete L²(0,T;H²)∩L²(0,T;L^∞) boundedness of the numerical solution for the phase variable to handle the nonlinear regional coupling terms. Another key technique adopts the inverse inequality and Ritz projection to bound the L …

Fourier Pseudospectral Methods For The Variable-Order Space Fractional Wave Equations, Yanzhi Zhang, Xiaofei Zhao, Shiping Zhou

Mathematics and Statistics Faculty Research & Creative Works

In this paper, we propose Fourier pseudospectral methods to solve the variable-order space fractional wave equation and develop an accelerated matrix-free approach for its effective implementation. In constant-order cases, fast algorithms can be designed via the fast Fourier transforms (FFTs), and the computational cost at each time step is O(Nlog⁡N) with N the total number of spatial points. In variable-order cases, however, the spatial dependence in the power s(x) leads to the failure of inverse FFTs. While the direct matrix-vector multiplication approach becomes impractical due to excessive memory requirements. Hence, we propose an accelerated matrix-free approach for effective implementation in …

Geometric Effects Of Warfighters On Body Armor Fit And Protective Capabilities Against Shock Wave Energy, Melissa Lynn Sutter

Doctoral Dissertations

Body armor is a vital piece of protective equipment for warfighters to defend against threats, necessitating continued development to improve comfort, weight, and protection. However, female warfighters often wear unisex body armor, designed primarily for the male torso. Current research has evaluated the short- and long-term detriments of female warfighters wearing these armors, focusing on comfort and performance. However, these studies do not comprehensively consider how a non-form-fitting armor compromises warfighter safety from battlefield threats. This research examines the geometric effects of female warfighters on armor protection level when defending against shock threats by evaluating the energy distribution on a …

Scalable Transfer Of Dna Origami–Directed Nanoparticle Arrays Onto Functional Surfaces Using Thermal Release Tape, Yuwei Zhang, Chikadibia Genevieve Edward, Ethan Keuhn, Shelley D. Minteer, Risheng Wang

Chemistry Faculty Research & Creative Works

Precise integration of DNA origami nanostructures onto functional substrates is essential for advancing electronics, photonics, and biosensing. However, most surface-assembly methods are highly sensitive to substrate type, limiting their broader applications. Here, we introduce a thermal release tape (TRT)-assisted transfer method that enables efficient, large-area printing of DNA origami-guided gold nanoparticle (AuNP-DNA origami) arrays from mica onto diverse surfaces. The method relies on differential adhesion: AuNP-DNA origami arrays form strong electrostatic and hydrogen-bonding interactions with 3-aminopropyltriethoxysilane (APTES)-functionalized receiver substrates, while the TRT adhesive weakens upon heating to 120°C, allowing release from the tape. Using this approach, well-ordered AuNP-DNA origami arrays …

Evaluation Of A Novel Re-Crosslinkable Preformed Particle Gel For Conformance Control In Ultra-High Temperature Reservoirs, Yanbo Liu, Tao Song, Caleb Kwasi Darko, Thomas P. Schuman, Mingzhen Wei, Baojun Bai

Chemistry Faculty Research & Creative Works

Preferential fluid flow remains a major challenge in subsurface energy production and gas storage operations, resulting in excessive water production in mature oil fields, reduced heat extraction in geothermal reservoirs, and low sweep and storage efficiency in CO₂-EOR projects. Polymer gels are widely used to mitigate high-permeability channels; however, conventional systems exhibit limited plugging efficiency and short lifetimes in ultra-high-temperature reservoirs due to poor thermal stability. This study presents a novel ultra-high-temperature-resistant preformed particle gel (UHT-PPG) developed for conformance control in reservoirs with temperatures of 150–275 °C and severe super-K or channeling problems. The material was evaluated in …

Progression Toward Terminal Oxidation Of Starch Via Hybrid Organic–Enzymatic Bioanode For Renewable Carbohydrate Conversion, Adam Milam, Jose Intano, Shelley D. Minteer

Chemistry Faculty Research & Creative Works

The performance of starch-based biofuel cells is fundamentally limited by inefficient utilization of the fuel's inherent energy density. Sequential oxidation of carbohydrate fuels, such as glucose, the monomeric unit of starch, using minimal catalyst systems has therefore emerged as a promising strategy to improve biofuel cell efficiency. Here, we extend a previously reported three-catalyst, organic–enzymatic glucose oxidation cascade to polymeric carbohydrate fuels by integrating enzymatic starch depolymerization with downstream electrochemical oxidation. To our knowledge, this represents the first demonstration of a defined hybrid organic–enzymatic cascade designed to drive progression of starch-derived glucose equivalents toward terminal oxidation using a minimal catalyst …

Closing The Nitrogen Loop In Groundwater With Biohybrid Technologies, Linjie Zhou, Biao Li, Jianhua Guo, Shelley D. Minteer, Yifeng Zhang

Chemistry Faculty Research & Creative Works

Nitrate in groundwater should be treated as a nitrogen source rather than a contaminant. Biohybrid technologies coupling microbial selectivity with renewable electro(photo)chemical energy offer opportunities to convert nitrate to value-added ammonium, although challenges remain in scalability, microbial stability, material–microbe integration, process engineering, regulatory compliance, and economic feasibility.

Partially Penalized Anisotropic Trilinear Ife-Pic Methods For Dc Plasma Transport Problems, Jiahui Li, Guangqing Xia, Yajie Han, Ziping Wang, Chang Lu, Xiaoming He

Mathematics and Statistics Faculty Research & Creative Works

Implicit and hybrid particle-in-cell methods are widely used for efficient simulation of DC discharge plasma transport. However, their computations require solving anisotropic elliptic equations and face challenges related to mesh geometry, non-axisymmetry, and complex interfaces. Moreover, the accuracy of particle trajectories is critical for plasma etching and erosion studies, where errors near interfaces can significantly impact simulation results. To address these challenges, this paper proposes a three-dimensional anisotropic trilinear partially penalized immersed finite element (ATPPIFE) method, which captures interfaces on Cartesian meshes and effectively reduces discontinuities at interface element faces, ensuring that particle trajectories better align with real-world behavior. Building …

Serum Biomarker Trajectory Clusters Predict Functional Outcome And Quality Of Life For Traumatic Brain Injury, Thanh Son Do, Chantal Carnes, Zhihui Yang, Firas Kobeissy, Hamad Yadikar, Gayla R. Olbricht, Olli Tenovuo, Jussi P. Posti, Ewout W. Steyerberg, Lindsay Wilson, Nicole Von Steinbüchel, Endre Czeiter, Andras Buki, David K. Menon

Mathematics and Statistics Faculty Research & Creative Works

Serum brain-enriched biomarkers are increasingly employed in the clinical evaluation of traumatic brain injury (TBI) to assist with triage, neuroimaging decisions, and prognostication. However, the potential of temporal biomarker trajectories to inform disease monitoring and long-term outcomes remains underexplored. We aim to identify distinct biomarker trajectory (TRAJ) profiles in traumatic brain injury patients and to examine their associations with long-term clinical outcomes. The study included 373, CT-positive Intensive Care Unit (ICU) traumatic brain injury patients (256 with initial Glasgow Coma Scale 3–12) from the Collaborative European Neurotrauma Effectiveness Research in TBI (CENTER-TBI) core study who had at least two serum …

Triangulating Primary Sources, Professional Judgement, And Llm-Generated Summaries: Educating Nurses In An Ai-First World, Sarah Oerther, Daniel B. Oerther

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

No abstract provided.

Evaluation Of Two-Group Iate Coupling With Pbe For Beyond Bubbly Flows In A Large Diameter Pipe, Sungje Hong, Joshua P. Schlegel, Subash L. Sharma

Nuclear Engineering and Radiation Science Faculty Research & Creative Works

This study evaluates the two-group interfacial area transport equation (2G IATE) coupled with the S-Gamma (Sγ) population balance equation (PBE) model for beyond bubbly flow regimes in a vertical large-diameter pipe. The 2G IATE framework incorporates intergroup mass transfer mechanisms and is implemented within the Sγ model, which assumes a log-normal bubble size distribution. The numerical approach is validated against experimental data from Schlegel et al. (2012), with a focus on the void fraction and interfacial area concentration (IAC) distributions. The results show that 2G IATE improves the predictions of the void fraction and IAC, although its accuracy varies with …

Sapphire Optical Fiber Bragg Grating Sensors Based On Dispersive Microwave-Photonic Frequency-Time Domain Analysis, Ruimin Jie, Chen Zhu, Farhan Mumtaz, Koustav Dey, Bohong Zhang, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

Sapphire fiber Bragg gratings (SFBGs) have attracted growing interest for high temperature sensing in harsh environments, yet their interrogation typically relies on optical spectrum measurements, demanding a high-resolution optical spectrum analyzer (OSA) that is bulky, expensive, and constrained in acquisition speed. Moreover, the inherently multimode nature of sapphire fiber further complicates spectrum-based demodulation, thereby limiting the achievable sensing resolution. In this paper, we propose and experimentally demonstrate a microwave-photonic interrogation approach for SFBG sensors. Instead of measuring the optical reflection spectrum, the complex frequency response in the microwave domain of an SFBG is acquired using a vector network analyzer (VNA) …

Fully Differential Studies On Dissociative Capture In P + D2 Collisions And On Ionization In P + He Collisions, Shruti Majumdar

Doctoral Dissertations

Advancing our understanding of few-body dynamics in simple atomic systems is a fundamental objective in atomic scattering research. The underlying problem is that the Schrödinger equation is not analytically solvable for more than two mutually interacting particles. This involves a comprehensive exploration of various channels, such as ionization, capture, and excitation. A common theoretical approach to describe ion-atom collisions is based on perturbation theory, where the scattering amplitude is expanded in powers of the interaction potential. Here, understanding the few-body problem means accurately describing the relative importance of the higher- vs the first order terms.

In the case of ionization, …

Stall Detection In Hydraulic Excavator Operations Using Heuristics And Machine Learning: A Case Study, Mateo Fernando Montenegro Defaz, Kwame Awuah-Offei, Yixiang Gao

Mining Engineering Faculty Research & Creative Works

This work aims to develop a reliable algorithm for stall detection during excavator digging by analyzing key operational variables such as velocity and angular displacements from machine monitoring data. The work develops and validates a heuristic algorithm to detect stalling events and trains a support vector machine classification algorithm to distinguish between "normal" digging cycles and cycles with stalling. This work is a novel attempt at using a classification algorithm to categorize digging cycles into normal and those with stalling events based on machine monitoring data alone. The developed classification algorithm achieved a sensitivity of 100%, indicating it correctly identified …

Relativistic And Recoil Corrections To Light-Fermion Vacuum Polarization For Bound Systems Of Spin-0, Spin-1=2, And Spin-1 Particles, Gregory S. Adkins, Ulrich D. Jentschura

Physics Faculty Research & Creative Works

In bound systems whose constituent particles are heavier than the electron, the dominant radiative correction to energy levels is given by light-fermion (electronic) vacuum polarization. In consequence, relativistic and recoil corrections to the one-loop vacuum-polarization correction are phenomenologically relevant. Here, we generalize the treatment, previously accomplished for systems with orbiting muons, to bound systems of constituents with more general spins: spin-0, spin-1=2, and spin-1. We discuss the application of our more general expressions to various systems of interest, including spinless systems (pionium), muonic hydrogen and deuterium, and devote special attention to the excited non-S states of deuteronium, the bound system …

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 …

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 …

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 …

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 …