Engineering Commons^™

Electron Beam Irradiation Effects On Bulk Metals: A Comparative Study Of Polycrystalline Versus Single-Crystalline Structures, A. A. Elmustafa, N. A. Sultana, A. H. Al-Allaq, M. Ojha, Y. S. Mohammed, J. Vennekate, H. Baumgart

Mechanical & Aerospace Engineering Faculty Publications

This study investigates the effects of electron beam (e-beam) irradiation on the mechanical and structural properties of eight bulk metallic samples, comprising both polycrystalline (PC) and single-crystalline (SC) forms of Ni, Cr, V, and Ti. These metals were evaluated as potential candidates for beam exit windows in high-power (MW-class) particle accelerators. The primary objective is to identify metals capable of withstanding the conditions of high-power/MW-class e-beam accelerators and serve effectively as exit windows. Selection criteria were based on each metal’s intrinsic properties, power dissipation capability, and irradiation-induced changes in mechanical behavior, including hardness, elastic modulus, and defect density. Comprehensive characterization …

From Comparison To Integration: Building Energy Simulation Tool Variability And The Case For Intelligent Retrofit Workflows, Amir Safari, Dalya Ismael, Mahsa Safari, James Freihaut

Engineering Technology Faculty Publications

As the urgency to address climate change and modernize energy infrastructure grows, the building sector plays a key role in improving energy efficiency and reducing carbon emissions. This study evaluates five energy retrofit strategies for Building 101 at The Navy Yard in Philadelphia, comparing two real-world proposals from energy service companies with three simulation-based packages derived from Building Energy Simulation (BES) tools. The study examined whether advanced BES tools provide greater accuracy and decision-making value compared to simpler alternatives. Electricity savings ranged from 5 % to 40 %, gas savings from 29.7 % to 61 %, and annual cost reductions …

Generative Ai And Llm Applications In Renewable Energy And Smart Grids: A Systematic Review For The Sustainable Energy Transition, Umit Cali, Ugur Halden, Merlinda Andoni, Ferhat Ozgur Catak, Si Chen, Benoit Couraud, Emre Kantar, Samuel Knapper, Ibrahim Kucukdemiral, Huseyin Kusetogullari, Murat Kuzlu, Yashar Mousavi, Sonam Norbu, Taha Selim Ustun, David Flynn

Engineering Technology Faculty Publications

The global energy transition toward decarbonization and digitalization requires advanced methods to manage decentralized, data-intensive cyber-physical energy systems. This systematic review analyzes 106 research studies on Generative Artificial Intelligence (GenAI) and Large Language Models (LLMs) in renewable energy and smart grids, organized into seven application clusters covering forecasting, system design, operation, reliability, data and cybersecurity, and energy markets. The review situates these applications within a Cyber-Physical-Social Systems (CPSS) framework. Results show that GANs dominate current applications (47.2%), followed by LLMs (10.4%) and VAEs (9.4%), with growing adoption of diffusion and score-based models (7.5% each). Selected studies report improved probabilistic forecasting …

Adaptive Electric Vehicle Routing And Charging With Deep Reinforcement Learning, Mandana Farhang Ghahfarokhi, Hyoshin Park, Venktesh Pandey, Gyugeun Yoon

Engineering Management & Systems Engineering Faculty Publications

As electric vehicles (EVs) gain popularity, efficient routing and charging solutions remain challenging due to time-dependent travel variability, sparse charging infrastructure, and heterogeneous user preferences. To address these challenges, this paper introduces a decision-support system that integrates three complementary methods: Temporal Multimodal Multivariate Learning (TMML) for real-time characterization of travel time uncertainty, Time-Dependent Shortest Path (TDSP) for reliability-aware route choice, and Deep Q-Network (DQN) reinforcement learning for adaptive charging decisions in sparse infrastructure environments. TMML updates link-level travel time distributions in real-time through Bayesian inference with cluster-based propagation, reducing uncertainties across the network. TDSP leverages these updated distributions to estimate …

Adaptive Multi-Grade Deep Learning For Highly Oscillatory Fredholm Integral Equations Of The Second Kind, Jie Jiang, Yuesheng Xu

Mathematics & Statistics Faculty Publications

This paper studies the use of Multi-Grade Deep Learning (MGDL) for solving highly oscillatory Fredholm integral equations of the second kind. We provide rigorous error analyses of continuous and discrete MGDL models, showing that the discrete model retains the convergence and stability of its continuous counterpart under sufficiently small quadrature error. We identify the DNN training error as the primary source of approximation error, motivating a novel adaptive MGDL algorithm that selects the network grade based on training performance. Numerical experiments with highly oscillatory (including wavenumber 500) and singular solutions confirm the accuracy, effectiveness and robustness of the proposed approach.

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 …

Formulation Development Of Topical Inserts Containing Doxycycline And Doxycycline Combined With Tenofovir Alafenamide And Elvitegravir For The Prevention Of Sexually Transmitted Infections, Vivek Agrahari, M. Melissa Peet, Jasmin Monpara, Rijo John, Sriramakamal Jonnalagadda, Pardeep K. Gupta, Meredith R. Clark, Gustavo F. Doncel

CONRAD Publications

Despite advances in oral and injectable HIV prevention options and oral prophylaxis for sexually transmitted infections (STIs) of bacterial origin, there remains a critical need for effective on-demand topical (vaginal and rectal) products for pre- and post-exposure prophylaxis (PrEP and PEP). To fill this gap, we have developed single and first-in-kind multi-active topical inserts for bacterial STIs and HIV/STIs prevention. We have formulated two different inserts, one containing doxycycline (DOX) at 10, 50, and 100 mg doses for bacterial STI prevention, and a multipurpose prevention product (TED insert) that combines DOX (10 mg) with the antiretrovirals tenofovir alafenamide (TAF; 20 …

Sulfhydryl-Functionalized Diarylethenes: Synthesis, Photoswitching, And Fluorescent Properties, Pramod Aryal, Jonathan Bietsch, Gowri Sankar Grandhi, Josh Choi, Guijun Wang

Chemistry & Biochemistry Faculty Publications

Sulfhydryl group (SH) plays important roles in reactions with various functional groups, especially in biologically active systems. Photoswitchable diarylethene (DAE) derivatives have demonstrated applications in many research fields. Among the many classes of diarylethene derivatives, thiol derivatives have not been extensively explored. In this study, we systematically synthesized and characterized a series of bis-thiol functionalized dithienylethene derivatives. The thiol groups in this series are attached directly to the thiophene, or through a phenyl or methylene linker. Each series incorporated both dithienyl cyclopentene and hexafluorocyclopentene bridges and total six thiol substituted diarylethenes were synthesized. Among the six sulfhydryl DAE derivatives, four …

Multidentate Surfactant-Dependent Synthesis Of Giant Iridium Superstructures, Ramjee Balasubramanian, Maeren E. Hill

Chemistry & Biochemistry Faculty Publications

Giant superstructures of iridium, comprised of smaller spherical and slightly larger anisotropic nanoparticles, were synthesized by reducing iridium chloride in the presence of resorcinarene, a class of tetrameric macrocyclic polyphenols, with sodium borohydride in ethanol in 30 min under mild conditions. These superstructures were characterized by a range of techniques including TEM, HRTEM, EDS and other spectroscopic methods. The impact of the macrocyclic surfactant, its features and reaction conditions in dictating the formation of giant iridium superstructures was evaluated. The packing density of nanoparticles in these giant iridium superstructures could be altered qualitatively by varying the duration of the reaction, …

Stress-Strain Behavior Of Saturated Clays From Vane Shear Test Results: A Numerical Approach, Gustavo Rodrigues De Avila Oliveira

Master’s Theses

The vane shear test (VST) is widely used to estimate the undrained shear strength of soft cohesive soils; however, it does not directly provide constitutive information such as the stress–strain response. Smoothed Particle Hydrodynamics (SPH), a mesh-free numerical method, offers an attractive alternative for modeling the large deformations involved in the VST and extracting additional information from the test.

This study develops and calibrates a two-dimensional SPH model to simulate the field vane shear test and investigate the stress–strain behavior of soft soils. The VST was implemented within an SPH framework, while field and laboratory data were used to define …

The Professional Constructor, Full Issue

The Professional Constructor

Full Issue, Winter 2026

Volume 50, Number 01

The Development Of A Convenient And Consistent Methodology For Flight Proficiency To Certify Multi-Rotor Uas Pilots For State Departments Of Transportation, Colin H. Dees, Joseph M. Burgett

The Professional Constructor

To fly an unmanned aircraft system (UAS), commonly referred to as a “drone,” the Federal Aviation Administration (FAA) requires pilots to pass a knowledge test. There is no requirement at the state or federal level for drone operators to demonstrate the ability to operate a UAS. The National Institute of Science and Technology (NIST) has created an exam for public and private entities to assess basic UAS flight proficiency. It is the only nationally recognized flight proficiency protocol. NIST does not provide a scoring recommendation and leaves it to the user to determine the minimum criteria to pass. There is …

Feasibility Of Upcycling Spent Lithium-Ion Battery To Carbon Dioxide Capture Adsorbent, Chimezie Frank Onwudinjo

Master’s Theses

This study investigates the feasibility of repurposing spent lithium-ion battery (SLIB) to lithium orthosilicate (Li₄SiO₄), a high temperature carbon dioxide sorbent. Two synthesis pathways including conventional acid-leaching method (Scenario 1) and a pyrolysis-based route (Scenario 2) were explored. Additionally, techno-economic analysis (TEA) and lifecycle assessment (LCA) of the two processes were also performed. Different analytical characterization techniques were performed to understand the material properties of Li₄SiO₄ including surface area, crystallinity, morphology and thermal stability. CO₂ capture performance of the synthesized Li₄SiO₄ was tested in a thermogravimetric analyzer (TGA) using …

Control System Emendation And Ai-Driven Optimization For Enhancing A Smart Residential Microgrid, Anthony Nyoyoko

Master’s Theses

This thesis began with a simple idea: to restore the control system of a smart residential microgrid to respond intelligently to electricity prices while remaining safe, reliable, and practical on low-cost hardware. At the start, the goal was to design an economically aware microgrid that could look at electricity prices from the PJM market and make better operational decisions than traditional rule-based control. The motivation was straightforward. As residential renewable energy adoption increases, microgrids are expected to do more than just supply power. They are expected to respond to price volatility, integrate renewable generation, and operate reliably using embedded controllers …

Discovering Naturally Occurring Antifreeze Peptides From Microbiome By Integrating Protein Language Models And Molecular Dynamics Simulation, Ibrahim A. Imam, Trevor Morey, Yuexu Jiang, Duolin Wang, Dong Xu, Qing Shao

Chemical and Materials Engineering Faculty Publications

Antifreeze peptides inhibit ice crystal growth and recrystallization, and are promising components of cryoprotective formulations for cell, tissue, and food preservation, as well as anti-icing surface coatings. However, the discovery of new antifreeze peptides has been hindered by their sequence diversity and the limited scalability of experimental screening. In this study, we identify novel antifreeze peptide candidates from a microbiome-derived sequence library using ensemble machine learning and molecular dynamics (MD) simulations. We developed an ensemble classifier composed of 10 adapter-tuned protein-language models and a random forest meta-learner. After training on a curated dataset of 73 766 sequences, we applied this …

Effect Of Protective Mutation On Structure And Dynamics Of Apoe: A Molecular Dynamics Simulation Study, Newton A. Ihoeghian, Usman L. Abass, Ibrahim A. Imam, Qing Shao

Chemical and Materials Engineering Faculty Publications

Apolipoprotein E (APOE) plays a significant role in determining the risk of Alzheimer’s disease (AD). Three mutations—APOE3–R136S, APOE3–V236E, and APOE4–R251G—have been reported to reduce the risk of AD. Unveiling the molecular mechanism behind this reduction could lay a foundation for developing therapeutics for AD. To shed light on this subject, we investigate the mutation-induced variation in structural and dynamic properties of APOE3–R136S, APOE3–V236E, and APOE4–R251G in explicit solvent using molecular dynamics simulations. The APOE2, APOE3, and APOE4 were used as the reference. The analysis unveiled that the three protective mutations may exert protection through different mechanisms. The R215G mutation makes …

Tiny Plastic, Big Trouble: How Polystyrene Nanoparticles Impact Dna-Damage Repair Deficient Cervical Cancer Cells, Jordan D. Berezowitz, Mira C. Fish, Lauren E. Mehanna, Breanna Knicely, Claire E. Rowlands, Eva M. Goellner, Brittany E. Givens

Chemical and Materials Engineering Faculty Publications

Microplastics are becoming increasingly abundant waste products; therefore, the risk of human exposure is also increasing. The cytotoxic consequences of microplastic exposure, particularly in cancer, have yet to be explored. We obtained commercially available polystyrene nanoparticles of uniform size (86.61 ± 6.41 nm) and confirmed the chemical composition and shape using Fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM), respectively. We evaluated colloidal stability over a range of concentrations from 1–1000 µg mL⁻¹ using hydrodynamic diameter and zeta potential, determining that higher concentrations exhibit greater colloidal stability compared to lower concentrations. Specifically, the zeta potential increased from …

The Role Of Laminin Isoforms In Glioblastoma Migration, Aseel Ahmed, Faezeh Ghobadi, Hanna Devillier, Qi Cai

Distinguished Undergraduate Researcher Program

Glioblastoma (GBM) remains the most prevalent and lethal invasive brain tumor, denoted by a median survival of 12-15 months despite standard procedures such as safe surgical resection, radiotherapy, and chemotherapy. This limited effectiveness largely arises from the infiltrative nature of GBM cells, which interact with the brain’s extracellular matrix (ECM) by migrating along blood vessels and axonal pathways. The ECM contains the interstitial matrix (IM) and the
basement membrane (BM) made up of proteins and glycans which interact with the malignant cells. While research has mainly been focused on understanding how GBM cells interact with IM components, our knowledge about …

The Healing Power Of Nanoparticles: Bioengineering Gelatin Films With Lignin-Graft-Plga Nanoparticles For Enhanced Tissue Repair, Marie Howe, Cristina Sabliov, Thanida Chuacharoen, Willyam Nikiema

Distinguished Undergraduate Researcher Program

Fish gelatin, a biocompatible material, can be methacrylated to enable its photo-crosslinking and formation of hydrogels for tissue-repair applications (1). This study investigated the incorporation of lignin-grafted PLGA nanoparticles (LNPs) into 3D-printed fGelMA hydrogels as controlled drug delivery systems. Lignin has UV absorbing properties, which could potentially interfere with photocrosslinking of fGelMA (2). These LNPs possess hydrophobic PLGA core and hydrophilic lignin forming the shell providing ample opportunities for delivery of drugs of different chemistries (3). Fluorescent LNPs (FLNPs) were engineered by covalently bonding a fluorophore to the shell prior to nanoparticle synthesis to allow for fluorophore tracking. The understanding …

Innovative Smart Sensing System For Accurate Monitoring Of Uhpc Setting Time, Ted Atera, Khalilullah Taj, Masoud Pasbani, Yen-Fang Su

Distinguished Undergraduate Researcher Program

Ultra-High-Performance Concrete (UHPC) is an advanced concrete material known for its strength and durability. Its superior mechanical properties make it an ideal material for demanding structural applications such as bridges. Accurate setting time measurements are crucial in helping to optimise the performance of UHPC. All conventional methods and standards for measuring the setting time of concrete rely on using expensive specialised equipment, such as the Vicat apparatus, which assesses penetration depth or resistance. However, these methods may not be well-suited for UHPC due to its rapid surface drying while the interior remains fresh. This prevents free needle penetration and leads …

Interpretable Machine Learning For Bridge-Pier Scour Prediction And Flood Resilience, Adil Khan, Dalya Ismael

Engineering Technology Faculty Publications

Bridge-pier scour is a leading cause of flood-induced bridge failure, yet practice still lacks transparent, physics-informed tools that link data-driven prediction with design guidance. This study develops an interpretable, physics-aware machine-learning framework to predict equilibrium scour depth and translate those predictions into actionable strategies for flood-resilient infrastructure. Using the 2014 U.S. Geological Survey Pier-Scour Database (569 laboratory cases), five models: Gradient Boosting, AdaBoost (Tree), XGBoost, Gaussian Process (RBF kernel), and Kernel Ridge (polynomial), were trained and evaluated with K-fold cross-validation. Model performance was evaluated using R², RMSE, and MAE. Gradient Boosting performed best, achieving training and testing R² of 0.99 …

Dynamic Direct Voltage Control Under Maximum Torque Per Ampere For Interior Pmsms, Mohamad Alzayed, Hicham Chaoui, Alaref Elhaj

Electrical & Computer Engineering Faculty Publications

A novel method for controlling the speed of interior permanent magnet synchronous motors (IPMSMs), known as the current-sensing-based dynamic direct voltage control method under the maximum torque per ampere (MTPA) concept, is introduced. This technique achieves precise tracking of machine velocity by determining the optimal combination of voltage amplitude and angle for each specific motor velocity and current/load condition. Unlike previous studies, this approach takes into account the transient model of the machine, resulting in improved accuracy during dynamic operating conditions compared with existing methods in the literature. Moreover, a comparative analysis is conducted involving different direct voltage MTPA speed …

Qubit Lattice Algorithm Simulations Of The Scattering Of A Bounded Two Dimensional Electromagnetic Pulse From The Infinite Planar Dielectric Interface, Min Soe, George Vahala, Linda Vahala, Efstratios Koukoutsis, Abhay K. Ram, Kyriakos Hizanidis

Electrical & Computer Engineering Faculty Publications

Qubit lattice algorithm (QLA) simulations are performed for a two-dimensional spatially bounded pulse propagating onto a plane interface between two dielectric slabs. QLA is an initial value scheme that consists of a sequence of unitary collision and streaming operators, with appropriate potential operators, that recover Maxwell equations in inhomogeneous dielectric media to the second order in the lattice discreteness. For the case of total internal reflection, there is transient energy transfer into the second medium due to the evanescent fields as the Poynting unit vector of the pulse is rotated from its incident to reflected direction. Because of the finite …

Recent Advances In Bioceramics, Fundamental Properties And Future Perspective In Biomedical Applications ‒ A Review, Ayesha Younas, Muhammad Umar Aslam Khan, Mohd Faizal Binte Abdullah, Lobat Tayebi, Shuanghu Wang, Abdalla Abdal-Hay, Yichi Xu

Electrical & Computer Engineering Faculty Publications

Bioceramics are important biomaterials in biomedical engineering because of their biocompatibility, bioactivity, osteoconductivity, and structural resemblance to actual bone tissue. In recent years, materials science and nanotechnology have enabled the use of bioceramics in bone regeneration, dental restoration, tissue engineering, drug delivery systems, and implantable medical devices. This comprehensive review covers advances in bioceramics, including calcium phosphates, hydroxyapatite (HAp), tricalcium phosphate, bioactive glasses, zirconia, alumina, and multifunctional ceramic nanocomposites. Priority is given to techniques such as additive manufacturing, 3D printing, sol-gel processing, electrospinning, and nanostructuring to improve mechanical strength, porosity, bioactivity, and cell interactions. Recent advances include ion doping, surface …

Novel Methods For Environmental Fluoride Measurement, Cable Warren

Chemistry & Biochemistry Dissertations

Fluoride analysis has been an important focus of analytical analysis for many years and will continue to be so going forward. Today, fluorinated compounds, specifically per/polyfluoroalkyl substances (PFAS), better known as “forever chemicals” have captured the moment and are the subject of vast research and regulation. Under this context, I have researched new methods of fluoride separation and concentration in complex media as well as a novel method of PFAS destruction and total organic fluorine analysis for screening of PFAS in aqueous samples. Through research and work on micro-scale detection methods, an understanding of the state of the art and …

Hybrid Model For Phishing Website Detection Using Transfer Learning, Atul Dubal, Mansi Subhedar, Santosh Dhamala, Manasi Patil

ASEAN Journal on Science and Technology for Development

The rapid digitization of human activities has intensified reliance on internet-based platforms, creating fertile ground for cybercriminal exploits such as phishing. Despite advancements in detection mechanisms, phishing attacks continue to evolve, leveraging sophisticated visual mimicry to deceive users. This paper proposes a robust vision-based phishing detection system using ensemble deep learning to analyse webpage screenshots. The framework integrates transfer learning with pre-trained VGG16 and DenseNet121 models, extracting complementary low-level texture features (edges, gradients) and high-level hierarchical patterns (logos, layouts). These features are fused through a custom classifier with dropout regularization to mitigate overfitting. A balanced dataset of 3,000 webpage screenshots …

Design Of An Economic Order Quantity–Based Dashboard For Vaccine Packaging Inventory Management, Hadi Susanto, Susmitha Canny, Alexandra Elizabeth Callistha, Shakira Dwi Purwandari, Naila Davina Aurelia

ASEAN Journal on Science and Technology for Development

Background: Timely availability of vaccine packaging is critical to pharmaceutical supply chain reliability, as packaging materials play a key role in maintaining cold chain integrity during distribution. Inadequate availability of packaging materials can disrupt vaccine delivery even when finished vaccines are ready for shipment. The case company faces frequent delivery delays, insufficient safety stock, and irregular replenishment of vaccine packaging materials, which have jeopardized the organization’s target of achieving a 90% on-time delivery rate.

Objective: To design and evaluate an Economic Order Quantity (EOQ)–based inventory dashboard for vaccine packaging that standardizes ordering decisions and strengthens stock visibility in pharmaceutical distribution …

Labor Savings From Mechanical Rice Transplanting In Bangladesh, India, Nepal, And The Philippines: A Systematic Review And Meta-Analysis, Rodrigo S. David

ASEAN Journal on Science and Technology for Development

Rice production in South and Southeast Asia faces serious challenges, including acute labor shortages and rising wages, which threaten regional food security. Mechanical rice transplanting offers a promising solution; however, evidence on labor savings, especially region-specific data, remains inconsistent. This systematic review and meta-analysis aimed to quantify labor savings from mechanical versus manual transplanting across Bangladesh, India, Nepal, and the Philippines.

Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a systematic search was conducted across four major scientific databases (2000–2026) using Boolean search terms for mechanical transplanting and labor outcomes. Of 284 initial records, 52 met eligibility …

Climate And Seasonal Influences On Indo-Pacific Sea Level: Insights From 30 Years Of Satellite And Tide Gauge Data, Karlina Triana

ASEAN Journal on Science and Technology for Development

We analyze Indo-Pacific sea-level variability using monthly satellite altimetry (1993–2025) validated against records from 16 tide-gauge stations. Cross-comparisons show strong agreement, especially in the western Pacific, confirming the reliability of altimetry for regional assessments. Seasonal SLA variability is largest in the Bay of Bengal and South China Sea and reflects monsoonal forcing, whereas interannual fluctuations in the eastern Indian and western Pacific oceans are dominated by ENSO and modulated by PDO. Harmonic decomposition isolates annual and semi-annual cycles, and an EOF/PCA framework identifies the leading modes: EOF1 (30.8%) captures basin-scale interannual variability and EOF2 (20.9%) reflects the seasonal cycle. Spectral …

Upconversion Photoluminescence In Wsse Alloy Monolayer Under Uniaxial Tensile Strain, Shrawan Roy, Jie Gao, Xiaodong Yang

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The optical responses of monolayer transition metal dichalcogenides (1L-TMDs) can be tuned effectively by using mechanical strain. In this work, the tuning of upconversion photoluminescence (UPL) emission in 1L-WSSe alloy by applying uniaxial tensile strain is investigated. When the uniaxial tensile strain is changed from 0 % to 1.02 %, the peak position of UPL emission has a redshift of around 25.6 nm, and the UPL intensity goes up with an exponential function of the applied strain as the upconversion energy difference is varied from −197 meV to −131 meV. The sublinear power dependence for UPL emission in 1L-WSSe alloy …