Digital Commons Network^™

Linker-Free Gold-Sputtered Tapered Optical Fiber Plasmonic Sensors For High-Sensitivity Refractive Index Detection In Microfluidic Platforms, Erem Ujah, Gymama Slaughter

Center for Bioelectronics Publications

Gold-sputtered tapered optical fiber (Au-TOF) sensors were developed for high-sensitivity refractive-index (RI) detection using aqueous glucose standards spanning 1.33–1.41 RIU (0–50% w/v). The sensors were fabricated using a reproducible workflow combining flame-brushing tapering, plasma surface preparation, and rotational magnetron sputtering, enabling azimuthally uniform gold coatings without the use of thiol or sulfur linker chemistries. Two sputtering durations (24 s and 30 s) were investigated to examine thickness-dependent plasmonic coupling and sensing performance. Optical measurements were conducted using a broadband supercontinuum source and compact spectrometer within a 20 µL microfluidic sensing chamber. Increasing glucose concentration produced a monotonic decrease in transmission …

Yk-4-250, A Synthetic Telmisartan-Tempol Conjugate: Crystal Structure Of A Stabilized Free Radical Containing An Angiotensin At₁ Receptor Inhibitor, Simon Friedrich, Yali Kong, Faik N. Musayev, Milton L. Brown, B. Frank Gupton

Department of Biomedical and Translational Sciences Faculty Publications

We report the first crystal structure of the telmisartan-tempol conjugate 2,2,6,6-tetramethyl-1-(λ'-oxidaneyl)piperidin-4-yl 4'-[(1,7'-dimethyl-2'-propyl-1H,3'H-[2,5'-bibenzo[d]imidazol]-3'-yl)methyl]-[1,1'-biphenyl]-2-carboxylate free radical (YK-4-250, C₄₂H₄₆N₅O₃), a dual-function inhibitor designed to target both the angiotensin II type 1 receptor (AT₁R) and reactive oxygen species (ROS). Structural analysis reveals a unique crystal architecture in which the nitroxide radical is stabilized within a sterically protected environment while preserving the telmisartan pharmacophore essential for high-affinity receptor antagonism. YK-4-250 is a novel small-molecule conjugate of telmisartan and tempol that incorporates a catalytic stabilized nitroxide radical and was rationally designed to mitigate gastrointestinal acute radiation syndrome (GI-ARS).

Crossing The Theory Threshold: The Pedagogical Potential Of Generative Artificial Intelligence In Educational Research, Amanda Burbage, Jennifer L. Styron

EVMS School of Health Professions Faculty Publications

Purpose

This paper presents findings from an educational research graduate course in which generative artificial intelligence (AI) was incorporated to strengthen learners' understanding of threshold concepts related to theoretical frameworks. Medical and health professionals often struggle with the transition from a clinical role into the educational research role.

Methods

The study posits that the use of generative AI will help learners understand and apply theoretical frameworks beyond a superficial level, furthering their understanding, constructing new knowledge, and strengthening their ability to develop sound educational research studies. Journal and AI transcripts were analyzed for 37 participants.

Results

Open-ended codes were grouped …

Proof-Of-Concept Development And Preclinical Evaluation Of A Microarray Patch Platform For Codelivery Of Multiple Broadly Neutralizing Antibodies For Hiv Prevention, M. Melissa Peet, Vivek Agrahari, Parbeen Singh, Lam Luong Hoai Nguyen, Louise A. Ouattara, Eun Sung Yang, Carolina Herrera, Amarendra Pegu, Theodore C. Pierson, Thanh D. Nguyen, Gustavo F. Doncel

CONRAD Publications

Broadly neutralizing antibodies (bnAbs) are advancing as a preventative or treatment option for HIV infection, but currently must be administered parenterally, typically as a large injection or infusion, an invasive method of delivery, especially for the pediatric population. Here, we present proof-of-concept data on a minimally invasive microneedle (MN) patch platform codelivering three bnAbs, PGT121, VRC07-523LS, and PGDM1400LS, from separate MN patch units or pixels. Each 1 cm² patch pixel, fabricated via solvent casting, contained ∼2 mg of one bnAb. In ex vivo porcine skin tests, the MNs effectively penetrated the skin. When tested in vitro in PBS buffer, MNs …

Proof-Of-Concept Development And Preclinical Evaluation Of A Microarray Patch Platform For Codelivery Of Multiple Broadly Neutralizing Antibodies For Hiv Prevention, M. Melissa Peet, Vivek Agrahari, Parbeen Singh, Lam Luong Hoai Nguyen, Louise A. Ouattara, Eun Sung Yang, Carolina Herrera, Amarendra Pegu, Theodore C. Pierson, Thanh D. Nguyen, Gustavo F. Doncel

CONRAD Publications

Broadly neutralizing antibodies (bnAbs) are advancing as a preventative or treatment option for HIV infection, but currently must be administered parenterally, typically as a large injection or infusion, an invasive method of delivery, especially for the pediatric population. Here, we present proof-of-concept data on a minimally invasive microneedle (MN) patch platform codelivering three bnAbs, PGT121, VRC07-523LS, and PGDM1400LS, from separate MN patch units or pixels. Each 1 cm² patch pixel, fabricated via solvent casting, contained similar to 2 mg of one bnAb. In ex vivo porcine skin tests, the MNs effectively penetrated the skin. When tested in vitro in PBS …

Performance Assessment And Design Improvements For An Urban Coastal Detention Basin Under Intensifying Rainfall Extremes, Imiya Mudiyanselage Chathuranika, Agyare Asante, Faeghe Borhani, Xixi Wang, Mujde Erten-Unal, Dalya Ismael

Civil & Environmental Engineering Faculty Publications

Coastal urban areas are increasingly exposed to flooding driven by more frequent and intense rainfall events, rising sea levels, and expanding impervious surfaces. Norfolk, Virginia, a low-lying coastal city with aging stormwater infrastructure, faces heightened vulnerability to these hydrologic pressures. This study evaluates the hydraulic performance of an existing urban detention basin within the Edgewater–Larchmont catchment under 10-, 50-, and 100-year, 2-h design storms using the U.S. Environmental Protection Agency’s Storm Water Management Model (SWMM). Simulations were conducted for both pre- and post-development conditions to assess changes in peak discharge, storage capacity, and water level dynamics. Results show that urbanization, …

Aura: An Ai-Powered Multimodal Prototype For Adaptive Apraxia Of Speech Therapy And Communication Support, Omotayo Omoyemi, Rachel K. Johnson

Speech-Language Pathology Faculty Publications

Apraxia of Speech (AOS) is a motor speech disorder that significantly limits communication and requires intensive, long-term therapy. Access to consistent treatment is often constrained by shortages of speech-language pathologists, high costs, and limited opportunities for continuous monitoring outside clinical settings. Recent advances in Artificial Intelligence (AI) provide new opportunities to support scalable and personalized speech therapy.

This paper presents AURA (Adaptive Understanding and Relearning Assistant for Apraxia), a multimodal AI framework designed to support speech therapy, progress monitoring, and communication for individuals with AOS. The system integrates speech analysis, machine learning–based error detection, reinforcement learning for adaptive therapy, and …

Part Ii: Industrial Information Integration Review 2020-2025, Jinzhi Li

Information Technology & Decision Sciences Faculty Publications

Industrial Information Integration Engineering (IIIE) has become increasingly essential for improving operational efficiency and harmonizing heterogeneous industrial systems through advanced digital integration approaches. Fueled by rapid advancements in Industry 4.0 technologies—including digital twins, artificial intelligence, immersive interfaces, and IoT infrastructures—IIIE is substantially transforming traditional enterprise architecture and integration frameworks. This systematic review synthesizes recent developments and emerging trends, with particular attention to the accelerating adoption of digital twins and the deepening convergence between operational technologies (OT) and information technologies (IT) across multiple sectors. While notable progress has been made, significant challenges persist, especially in developing resilient integration architectures and fully …

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. …

Utilizing Machine Learning Techniques For Computer-Aided Covid-19 Screening Based On Clinical Data, Honglun Xu, Andrews T. Anum, Michael Pokojovy, Sreenath Chalil Madathil, Yuxin Wen, Md Fashiar Rahman, Tzu-Liang (Bill) Tseng, Scott Moen, Eric Walser

Mathematics & Statistics Faculty Publications

The COVID-19 pandemic has highlighted the importance of rapid clinical decision-making to facilitate the efficient usage of healthcare resources. Over the past decade, machine learning (ML) has caused a tectonic shift in healthcare, empowering data-driven prediction and decision-making. Recent research demonstrates how ML was used to respond to the COVID-19 pandemic. This paper puts forth new computer-aided COVID-19 disease screening techniques using six classes of ML algorithms (including penalized logistic regression, random forest, artificial neural networks, and support vector machines) and evaluates their performance when applied to a real-world clinical dataset containing patients’ demographic information and vital indices (such as …

Wearable Biosensors For Continuous Monitoring Of Chronic Kidney Disease: Materials, Biofluids, And Digital Health Integration, Anupamaa Sivasubramanian, Shankara Narayanan, Gymama Slaughter

Center for Bioelectronics Publications

Chronic kidney disease (CKD) is a progressive and irreversible disorder affecting over 850 million individuals globally and is associated with significant morbidity, mortality, and healthcare burden. Conventional diagnostic approaches rely on intermittent laboratory measurements, including serum creatinine, estimated glomerular filtration rate (eGFR), and urinary albumin, which provide limited temporal resolution and fail to capture dynamic physiological changes. Recent advances in wearable biosensing technologies offer new opportunities for continuous, non-invasive monitoring of biochemical and physiological markers relevant to renal function. This review provides a comprehensive analysis of wearable biosensors for CKD monitoring, focusing on sensing mechanisms (electrochemical, optical, and field-effect transistor), …

Ai-Assisted Surface-Enhanced Raman Spectroscopy For Cardiovascular Diagnostics: From Plasmonic Materials To Clinical Translation, Anju Joshi, Gymama Slaughter

Center for Bioelectronics Publications

Raman spectroscopy (SERS) has emerged as a powerful analytical technique, offering molecular fingerprint specificity and ultrasensitive detection of cardiac biomarkers. Recent advances in plasmonic nanostructures, surface functionalization strategies, and flexible sensing platforms have significantly improved the analytical performance of SERS-based biosensors. In parallel, the integration of artificial intelligence (AI) and machine learning has enabled robust interpretation of complex spectral datasets, facilitating automated biomarker classification and improved diagnostic accuracy in heterogeneous biological environments. Despite these advances, the field remains fragmented, with limited integration between nanomaterial design, biomarker selection, and data-driven analysis, and persistent challenges related to reproducibility, standardization, and clinical validation. …

Modulation Of Prussian Blue Redox Signaling By Molecular Imprinting For Reagent-Free Electrochemical Detection Of Emtricitabine, Abdellatif Ait Lahcen, Gymama Slaughter

Center for Bioelectronics Publications

Reagent-free electrochemical sensors offer significant benefits for rapid, affordable point-of-care drug testing. In this study, we introduce a novel, reagent-free electrochemical sensor based on a molecularly imprinted polymer (MIP) specifically designed for the selective detection of Emtricitabine (FTC), a common antiretroviral used in HIV therapy. The sensor uses laser-induced graphene (LIG) electrodes, renowned for their high conductivity and porosity, ideal for electrochemical sensing. To enable reagent-free operation, the LIG surface was electrochemically coated with Prussian Blue, serving as a redox-active layer. Next, an MIP-PPy film was electropolymerized onto the Prussian Blue surface in the presence of FTC as a template, …

Ion-Imprinted Polymer-Based Sensors For Toxic Metal-Ion Detection In Water: Coordination Chemistry, Transduction Strategies, And Environmental Applications, Ghita Yammouri, Gymama Slaughter

Center for Bioelectronics Publications

Toxic metal contamination in aquatic environments remains a persistent threat to human health and ecosystems. Yet, the high cost, infrastructure demands, and centralized nature of conventional analytical methods constrain routine monitoring. Ion-imprinted polymers (IIPs), a subclass of molecularly imprinted polymers, have emerged as promising synthetic recognition materials for metal-ion sensing because they generate coordination-defined binding sites with high selectivity, chemical stability, low cost, and reusability. This review summarizes recent advances in Ion-imprinted polymer (IIP)-based sensing technologies for toxic metal-ion detection in water from 2016 to 2026. It examines the fundamental recognition chemistry of IIPs, major synthesis strategies used to generate …

A Macrocognitive Design Taxonomy For Simulation-Based Training Systems: Bridging Cognitive Theory And Human-Computer Interaction, Jessica M. Johnson

Virginia Digital Maritime Center (VDMC) Faculty Publications

Simulation-based training systems are increasingly deployed to prepare learners for complex, safety-critical, and dynamic work environments. While advances in computing have enabled immersive and data-rich simulations, many systems remain optimized for procedural accuracy and surface-level task performance rather than the macrocognitive processes that underpin adaptive expertise. Macrocognition encompasses higher-order cognitive processes that are essential for performance transfer beyond controlled training conditions. When these processes are insufficiently supported, training systems risk fostering brittle strategies and negative training effects. This paper introduces a macrocognitive design taxonomy for simulation-based training systems derived from a large-scale meta-analysis examining the transfer of macrocognitive skills from …

Advancing Food Equity Through Explainable Ai (Xai): Identifying Place-Based Factors And Conditions Of Food Security, Leslie Hoglund, Hyoshin Park

Health Behavior, Policy & Management Faculty Publications

Food behaviors, food security, and their association with socioeconomic factors constitute a critical area of study with implications for public health, economic stability, and social equity. Understanding these relationships are essential for developing effective policies and interventions that promote sustainable, healthy food systems and greater food equity. This paper employs explainable artificial intelligence (XAI) methods to identify key features influencing household food behaviors. The insights gained from the XAI analysis are further utilized in conjunction with inverse reinforcement learning (IRL) to examine expert behaviors related to eating habits satisfaction. The XAI results reveal that household health conditions, spending patterns, and …

A Hybrid Response Surface Methodology And Machine Learning Framework For Quantifying Effects Of Physicochemical Parameters On Pfas Distribution, Harsh V. Patel, Jazmin Green, Hyoshin Park, Stephanie Luster-Teasley Pass, Renzun Zhao

Engineering Management & Systems Engineering Faculty Publications

Predicting PFAS adsorption across diverse adsorbents and environmental matrices remains challenging because adsorbent physicochemical properties, PFAS molecular descriptors, and operational conditions simultaneously influence adsorption. This study develops and evaluates a unified hybrid modeling framework that integrates Response Surface Model (RSM) with machine-learning algorithms to quantify how six key variables, surface area, Log K_ow, pH_pzc, pK_a, log dose, and log-initial concentration, affect PFAS distribution coefficients (Log K_d). A data set of more than 1000 adsorption observations spanning 15 PFAS compounds, multiple adsorbent types, and a broad operational range was compiled and preprocessed using …

Metabolic Reprogramming Following Mitochondrial Transfer Between Idh2-Mutant Chondrosarcoma Cells And A Normal B-Cell Line, Caleb Wyckoff, Christopher Osgood, Ellen Jing, Michael Stacey

Bioelectrics Publications

Background/Objectives: Chondrosarcoma, glioblastoma, acute myeloid leukemia, chronic lymphocytic leukemia, and cholangiocarcinoma cancers all contain mutations in the gene isocitrate dehydrogenase 2 (IDH2). The mutant IDH2 enzyme metabolizes alpha-ketoglutarate (αKG) into the potent oncometabolite D-2-hydroxyglutarate (D2HG) in the mitochondria of these cancers, leading to altered cellular metabolism. Emerging evidence suggests that mitochondrial transfer between cancer and recipient cells represents an important form of intercellular communication that may influence cellular metabolism. The presence of intercellular TNTs between IDH2-mutant chondrosarcoma cells motivated an investigation into mitochondria-associated physiological changes occurring during an intercellular exchange with immune cells. A mitochondrial transfer is a two-way …

Determining The Electric Field In A 10 Ns Pulsed Plasma In Fuel-Air Mixtures Using Efish, Md Ziaur Rahman, Christopher J. Kliewer, Brian D. Patterson, Chunqi Jiang

Bioelectrics Publications

Transient plasma ignition (TPI) utilizes non-equilibrium plasmas, produced by nanosecond high-voltage pulses, to improve lean-fuel combustion performance and reduce emission. It is known that the relatively high reduced electric field (E/N) in TPI plays an important role in generating energetic electrons and facilitating energy-efficient radical productions, resulting in reliable ignition for lean combustion. Determining the reduced electric field in the discharge is hence important for the understanding of the TPI process and ultimately allowing for the control of the plasma chemistry. This study reports spatiotemporally resolved measurements of the electric field (E) in a 10 ns pulsed plasma that is …

Establishment And Histopathological Characterization Of A Kyse-30 Subcutaneous Xenograft Model Of Esophageal Squamous Cell Carcinoma, Pavel A. Solopov, Alayna Enos, Mantas Silkunas, Giedre Silkuniene, Eleni Zivla, Andrei G. Pakhomov, Olga N. Pakhomova

Bioelectrics Publications

Background/Objectives: Esophageal squamous cell carcinoma (ESCC) is an aggressive malignancy with poor prognosis and limited treatment options, highlighting the need for reliable preclinical models for translational research. Although xenograft models are widely used in cancer biology, systematic characterization of subcutaneous ESCC models under defined implantation conditions remains limited. The objective of this study was to systematically compare implantation conditions and define histopathological and growth-related parameters that enable reproducible tumor establishment while maintaining a practical experimental window for therapeutic studies. Methods: We established and characterized a subcutaneous ESCC xenograft model using human ESCC cell line KYSE-30 implanted into immunodeficient J:NU mice. …

Ammonia Synthesis By Nanosecond Pulsed Atmospheric Pressure Plasma Jets Impinging On Water, Zach Caudell, Lynnet Rich, Olga Pakhomova, Chunqi Jiang

Bioelectrics Publications

Developing energy-efficient technologies for carbon-neutral ammonia (NH₃) synthesis is critical for decentralized fertilizer production and global decarbonization. This study investigates generating NH₃ from water using a nanosecond pulsed atmospheric pressure plasma jet (ns‑APPJ) operating in either N₂ or dry air. The plasma jet reactor employed approximately 250 ns, up-to-22 kV pulses at 500 Hz to sustain a nonequilibrium discharge impinging directly on static liquid water. The kinetics, energy efficiency, and product selectivity of NH3 formation were quantified as functions of the pulse voltage, repetition frequency (PRF), and gas flow rate. NH₃ production increased linearly with treatment time and scaled strongly …

Combination Therapy With Hsp90 Inhibitors And Nanopulse Stimulation Synergistically Impedes Hepatocellular Carcinoma And Breast Cancer Growth In Mice, Christiana Dimitropoulou, Gagan Thangjam, Brittany P. Lassiter, Teresa Hooker, Ruben M. L. Colunga Biancatelli, John D. Catravas, Stephen J. Beebe

Bioelectrics Publications

Nanopulse Stimulation (NPS) represents a promising and innovative therapeutic approach to cancer. Heat shock protein 90 Inhibitors (HI), on the other hand, are currently under investigation in multi-drug chemotherapy trials for various types of malignancies. Here we present results of a combination therapy employing two HSP90 inhibitors (AUY-922 or 17-AAG) and NPS to ablate cancer growth. We firstly tested the inhibitors alone or in combination with NPS in vitro in N1S1 cells, and then into two models of orthotopic Hepatocellular Carcinoma (HCC) and 4T1-Luc breast cancer. NPS + HI reduced tumor growth more than the sum of HI and NPS …

Improving Expository Reading Comprehension In College Students, Danielle M. De Lucia, George Noell

Psychology Faculty Publications

This study investigated the impact of the Collaborative Strategic Reading (CSR) method on reading comprehension and psychological well-being among college students, addressing a gap in research on expository reading comprehension at the post-secondary level. A total of 47 students from Introduction to Psychology courses participated in the study. Participants initially completed pre-test assessments, including a cloze test, the Wide Range Achievement Test, and scales for self-worth, depression, anxiety, and stress. Of these, 23 students underwent CSR intervention sessions, conducted over three weeks with bi-weekly 50-minute sessions using their course textbook. Post-intervention data from 44 students were analyzed using repeated-measures ANOVA. …

Gradient-Based, Post-Optimality Sensitivity Analysis With Respect To Parameters Of State Equations, Gene Hou, Jonathan Degroff

Mechanical & Aerospace Engineering Faculty Publications

Design optimization is a computational tool that can enable a designer to investigate the effectiveness of a design concept in an organized format. However, this design process requires the design variables, constraints, and objective function to be properly defined and expressed in mathematical forms. Post-optimality analysis thus becomes a necessary step to investigate different variations in the problem formulation and parameters to ensure that optimization produces a stable and trustworthy outcome. One efficient way to achieve this aim is to compute the local derivative of the optimized objective function with respect to the optimization problem parameters, such as bounds on …

Uncertainty-Aware Estimation, Planning, And Control For Tracking Multiple Drifting Patches In Flow Fields, Daniel O. Akanji, Krishnanand N. Kaipa, Cong Wei

Mechanical & Aerospace Engineering Faculty Publications

In this study, we present a replay-based framework for uncertainty-aware persistent tracking of multiple advected surface patches using an autonomous marine vehicle operating in spatiotemporal-varying currents. The method combines three components: local flow estimation, covariance-aware patch-boundary propagation with intermittent boundary fusion, and mission-level scheduling over multiple patches. Each patch is represented by a polygonal boundary, whose vertices are propagated through the estimated flow field while carrying per-vertex covariance, thereby quantifying uncertainty growth during advection. A flow-aware gain-scheduled linear quadratic regulator (LQR) was designed to shape the desired surge speed to take advantage of favorable currents. When the vehicle services a …

Influence Of Motion Artifacts On Instantaneous Frequency Based Heart Rate Variability Of Arterial Pulse Signals Measured By A Tactile Sensor: An Analytical Study, Mamun Hasan, Zhili Hao

Mechanical & Aerospace Engineering Faculty Publications

Objective: Heart rate variability (HRV), quantified via the instantaneous frequency (IF) of arterial pulse signals, is a key indicator of cardiovascular (CV) regulation. This study presents a theoretical and experimental investigation of how motion artifacts (MA) influence IF-and thus HRVmeasured with a tactile sensor, emphasizing underlying mechanisms rather than population-level validation. Approach: Building on a previously developed single-degree-of-freedom (SDOF) model of the tissue-contact-sensor (TCS) stack between the sensor and the artery, MA is represented as low-frequency baseline drift and time-varying system parameters (TVSP) of the TCS stack. Analytical expressions quantify the effect of MA on the IF of each harmonic …

Mechanical-Medical Convergence In Heart Failure: Artificial Intelligence, Finite-Element Modeling, And 3d Printing For Diagnosis And Prognosis, Quazi Noor E. Sabrina, Quazi Md Zobaer Shah, Quazi Noor E. Sohela, Md Mahabub Hasan Mousum, Md. Moyeen Uddin Chisty, Quazi Md. Akbar Shah

Mechanical & Aerospace Engineering Faculty Publications

Heart failure remains a leading cause of global morbidity and mortality, yet routine clinical indices often miss the regional biomechanical disturbances that drive progression and shape treatment response. This State-of-the-Art review examines how finite-element (FE) modeling, additive manufacturing, and artificial intelligence (AI) are converging to improve the diagnosis, phenotyping, procedural planning, and prognostic assessment of heart failure (HF). Although these technologies have matured in structural heart disease and transcatheter intervention research, their greatest translational potential may lie in HF, where patient-specific ventricular remodeling, myocardial stress–strain heterogeneity, valve-ventricular coupling, and device-tissue interaction are incompletely captured by conventional clinical indices. We synthesize …

Radical-Based Oxidative Pretreatment Enhances Biofuel Production From Lignocellulosic Biomass Via Hydrothermal Liquefaction, João Vitor Dos Santos, Louis C. Bondurant, Patrick G. Hatcher

Chemistry & Biochemistry Faculty Publications

The sustainable production of biofuels from lignocellulosic biomass is a central goal in the transition to low-carbon energy systems. However, hydrothermal liquefaction (HTL), a promising thermochemical conversion pathway, is constrained by the high oxygen content and complex aromatic structure of lignin, which lowers bio-oil quality. Here, we used a model system of brown-rot-degraded white oak (Quercus alba) to test whether radical-based oxidative pretreatment could enhance HTL performance by converting lignin into more aliphatic intermediates. Oxidation was performed under simulated Fenton conditions using fixed Fe(II) (60 ppm) and two hydrogen peroxide concentrations (3 and 8 M), resulting in extensive lignin depolymerization …

Scanning Electron Microscopy As A Potential Tool For Distinguishing Charcoal From Dark, Oxidized, Biomass, João Vitor Dos Santos, Aleksandar I. Goranov, Lais Gomes Fregolente, Joao Marcos De Lima-Faria, Diego Stefani Teodoro Martinez, Patrick G. Hatcher

Chemistry & Biochemistry Faculty Publications

Condensed aromatic carbon (ConAC) is widely used as a proxy for organic materials derived from biomass burning. However, recent evidence shows that ConAC can be also formed through nonpyrogenic oxidative processes. This study presents a proof-of-concept investigation using scanning electron microscopy (SEM) to distinguish charcoal from dark, ConAC-rich materials produced by ambient oxidation of biomass. Pine wood exposed to long-term iron-mediated oxidation was compared with unaltered wood and a controlled laboratory-generated charcoal reference. Conventional geochemical analytical methods, including benzenepoly(carboxylic acid) (BPCA) analysis, Fourier transform–ion cyclotron resonance–mass spectrometry (FT-ICR-MS), solid-state 13C nuclear magnetic resonance (NMR) spectroscopy, and elemental analysis, confirmed substantial …

Integrating Design Thinking In A Stem Methods Course, Demetrice Smith-Mutegi

Teaching & Learning Faculty Publications

Design thinking, a problem-solving approach, has been offered as a strategy to address the challenges of growing and complex teaching expectations. In this narrative, I describe an adapted model of design thinking that was implemented in a secondary STEM methods course for teacher candidates in a graduate program. A description of the key activities, including the fundamental role of empathizing, is shared. Design thinking, when implemented by teachers and teacher candidates, allows the teacher to design and improve a lesson or unit based on student feedback and engagement. This is especially important in today's rapidly evolving educational landscape, where educators …