Digital Commons Network^™

Flexural Strength Of (Hf,Nb,Ta,Ti,Zr)B2–(Hf,Nb,Ta,Ti,Zr)C High-Entropy Dual-Phase Ceramics, Rubia Hassan, William G. Fahrenholtz, Gregory E. Hilmas, Jeremy Watts

Materials Science and Engineering Faculty Research & Creative Works

The room and elevated temperature flexural strengths were measured for (Hf,Nb,Ta,Ti,Zr)B2–(Hf,Nb,Ta,Ti,Zr)C high-entropy dual-phase ceramics. The fracture of ceramics originated from two distinct flaw populations that were either surface defects introduced during specimen preparation or volume defects introduced during processing. The average strength at room temperature was 638 ± 94 MPa with individual bars strengths as high as ∼800 MPa. At 1800°C, average strength increased to 786 ± 265 MPa with individual bar strengths as high as ∼1050 MPa. Above 1800°C, creep dominated resulting in deformation of the bars without fracture. The fracture mode changed from completely trans granular at room …

Roadmap To 100 Gwdc: Scientific And Supply Chain Challenges For Cdte Photovoltaics, B. Edward Sartor, Samantha B. Reese, Lorelle M. Mansfield, Ryan Muzzio, Chun Sheng Jiang, Eric Colegrove, John S. Mangum, Camden L. Kasik, Daniel Z. Shaw, James R. Sites, Ramesh G. Dhere, Alex B. Goldstone, Michael S. Moats

Materials Science and Engineering Faculty Research & Creative Works

This roadmap highlights pathways to expand the CdTe module manufacturing capacity per year to 100 GWDC by 2030 by improving Te extraction from existing supply chains, minimizing Te usage in modules by leveraging thinner absorbers, and focusing research efforts in key areas to improve module efficiencies. Both scientific and supply chain innovations will be necessary to maintain the high compound annual growth rate of the CdTe photovoltaic (PV) industry and cement its role as a key technology for multi-TW-scale PV deployment.

Ms-Yolo: Infrared Object Detection For Edge Deployment Via Mobilenetv4 And Slideloss, Jiali Zhang, Thomas S. White, Haoliang Zhang, Wenqing Hu, Donald C. Wunsch, Jian Liu

Mathematics and Statistics Faculty Research & Creative Works

Infrared imaging has emerged as a robust solution for urban object detection under low-light and adverse weather conditions, offering significant advantages over traditional visible-light cameras. However, challenges such as class imbalance, thermal noise, and computational constraints can significantly hinder model performance in practical settings. To address these issues, we evaluate multiple YOLO variants on the FLIR ADAS V2 dataset, ultimately selecting YOLOv8 as our baseline due to its balanced accuracy and efficiency. Building on this foundation, we present MS-YOLO (MobileNetv4 and SlideLoss based on YOLO), which replaces YOLOv8's CSPDarknet backbone with the more efficient MobileNetV4, reducing computational overhead by 1.5% …

How Do Human And Ai Gender Bias Interact In Hiring Decisions?, Eyuel Getahun, Daniel Burton Shank, Casey I. Canfield, Jessica L. Cundiff, Jenny L. Davis, Celia Freed

Psychological Science Faculty Research & Creative Works

The hiring process is crucial for organizational success but has long been troubled by human biases. Many organizations now include AI in their hiring protocols to mitigate these biases and increase efficiency. However, AI itself can have biases baked-in. Human biases and AI biases are distinct but related; here, we examine how human and AI biases interact to affect hiring outcomes. Through an online experiment, we examine this question in the context of gendered hiring for a male-dominated leadership position in electrical engineering. The study tests how elevated and depressed AI recommendations for male and female job candidates affect participant …

Comparison Of Cnn And Lstm Networks On Human Intention Prediction In Physical Human-Robot Interactions, Khosro Ghorbani Zadeh, Niloofar Zendehdel, George L. Holmes, Keyri Moreno Bonnett, Amy Costa, Devin Michael Burns, Ming-Chuan Leu, Yun Seong Song

Psychological Science Faculty Research & Creative Works

Advancements in robotics and AI have increased the demand for interactive robots in healthcare and assistive applications. However, ensuring safe and effective physical human-robot interactions (pHRIs) remains challenging due to the sophistication of human motor communication and intent recognition. Traditional physics-based models struggle to capture the dynamic nature of human force interactions, limiting robot adaptability. To address these limitations, neural networks (NNs) have been explored for force-movement intention prediction. While multi-layer perceptron (MLP) networks show potential, they struggle with temporal dependencies and generalization. Long Short-Term Memory (LSTM) networks effectively model sequential dependencies, while Convolutional Neural Networks (CNNs) enhance spatial feature …

Insights In Adaptation: Examining Self-Reflection Strategies Of Job Seekers With Visual Impairments In India, Akshay Kolgar Nayak, Yash Prakash, Sampath Jayarathna, Hae-Na Lee, Vikas Ashok

Computer Science Faculty Publications

Significant changes in the digital employment landscape, driven by rapid technological advancements and the COVID-19 pandemic, have introduced new opportunities for blind and visually impaired (BVI) individuals in developing countries like India. However, a significant portion of the BVI population in India remains unemployed despite extensive accessibility advancements and job search interventions. Therefore, we conducted semi-structured interviews with 20 BVI persons who were either pursuing or recently sought employment in the digital industry. Our findings reveal that despite gaining digital literacy and extensive training, BVI individuals struggle to meet industry requirements for fulfilling job openings. While they engage in self-reflection …

Design And Manufacturing Of Multifunctional Piezoelectric Composites, Huan Zhao

Dartmouth College Ph.D Dissertations

Piezoelectric materials possess a unique ability to convert mechanical energy into electrical signals and have broad industrial applications. However, monolithic piezoelectric materials such as piezoceramics and piezopolymers often suffer from inherent trade-offs among mechanical strength, elasticity, and durability. Piezoelectric composites, typically consisting of a polymer matrix with ceramic reinforcements, offer a solution by combining the advantages of each constituent. Nevertheless, maintaining stable mechanical performance in high-temperature environments remains a significant challenge as conventional polymer matrices usually experience structural degradation.

In this thesis, a novel piezoelectric composite is developed using a preceramic polymer (PCP) matrix with barium titanate (BTO) inclusions. PCPs …

A Study Of The Properties Of Fleece Knitted Fabrics Made From Cotton And Different Types Of Regenerated Cellulosic Fibers For Apparel Use, Mohamed Hakam, Alaa Arafa Badr, Ashraf El-Nahrawy

Mansoura Engineering Journal

Yarn material and fabric type affect the quality of knitted fabric. Weather temperature, humidity, and moisture resistance of the garment are the primary factors that determine the evaporation rate of sweat from the body surface. Also, some physical and mechanical properties control the comfort level required by the customer. The present research work was carried out by varying the following parameters: Yarn type with different materials was changed by changing yarn cones through the creel of the knitting machine. Machine Parameters, in this study samples were made on Two- Thread Fleece, and Three- Thread Fleece Machines. These parameters have been …

Leveraging Physiological Signal Activity And Self-Report Data To Assess Students’ Trust In “My Friendly Mind” App And Its Impact On Their Mental Health Knowledge: A Mixed-Method Phase 1 Clinical Trial Focusing On Depression And Attention Deficit Hyperactivity Disorder From Human Factors Standpoint., Yeganeh Shahsavar

Graduate Theses, Dissertations, and Problem Reports (ETD)

Mental health issues have become a significant global public health concern, especially among younger generations. The growing number of mental health challenges, combined with limited access to quality care, makes the problem even worse. Studies reveal that over 70% of individuals worldwide in need of mental health services do not receive appropriate care. Digital health technologies have the potential to enhance mental health services by making them more accessible and affordable. Despite the increasing popularity of mental health mobile applications (mHealth), there remains a lack of robust evidence of their effectiveness and the level of user trust, particularly in areas …

Artificial Intelligence Event Video Collection (2025), Peaaii Umass Boston

Paul English Applied Artificial Intelligence (AI) Institute Publications

This submission contains a collection of recorded videos and promotional materials from artificial intelligence events organized by the Paul English Applied AI Institute (PEAAII) at the University of Massachusetts Boston in 2025. These events include AI Frontier Day, the Fall Symposium, and the AI Applications Hackathon.

The video collection highlights student research, academic collaboration, and applied learning experiences in artificial intelligence. These materials are intended to support education, increase accessibility to AI-related content, and showcase the work of students and faculty involved in PEAAII programs.

Optimizing Ai Language Models: A Study Of Chatgpt-4 Vs. Chatgpt-4o, Md Nurul Absar Siddiky, Muhammad Enayetur Rahman, Md Fayaz Bin Hossen, Muhammad Rezaur Rahman, Md. Shahadat Jaman

Electrical & Computer Engineering Faculty Publications

This paper presents a comparative analysis of OpenAI's GPT-4 and its optimized variant, GPT-4o, focusing on their architectural differences, performance, and real-world applications. GPT-4, built upon the Transformer architecture, has set new standards in natural language processing (NLP) with its capacity to generate coherent and contextually relevant text across a wide range of tasks. However, its computational demands, requiring substantial hardware resources, make it less accessible for smaller organizations and real-time applications. In contrast, GPT-4o addresses these challenges by incorporating optimizations such as model compression, parameter pruning, and memory-efficient computation, allowing it to deliver similar performance with significantly lower computational …

Scalable Fabrication Of High-Payload Dendrimer-Based Nanoparticles For Targeted Atherosclerosis Therapy, Huari Kou, Lin Qi, Da Huang, Jiandong Wu, Honglan Shi, Hu Yang

Chemistry Faculty Research & Creative Works

Nanoparticle-based therapeutics hold promise for the treatment of atherosclerosis, but challenges such as low drug-loading capacity and a lack of scalable, controllable production hinder their clinical translation. Flash nanoprecipitation, a continuous synthesis method, offers a potential solution for scalable and reproducible nanoparticle production. In this study, we employed a custom-designed multi-inlet vortex mixer to perform cross-linking reaction-enabled flash nanoprecipitation, facilitating controlled and scalable synthesis of cross-linked Poly amidoamine (PAMAM) dendrimer nanoparticles. Notably, this approach allows simultaneous nanoparticle cross-linking and drug loading in a single step. The mannose moiety enabled specific targeting of macrophages via mannose receptors, enhancing the localization of …

Aqueous Carbonation Of Steel Slags: A Comparative Study On Mechanisms, Nannan Zhang, Gao Deng, Wenyu Liao, Hongyan Ma, Chuanlin Hu

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

This study investigated the aqueous carbonation mechanisms of three typical steel slags: ladle metallurgy furnace (LMF) slag containing high Al content, electric arc furnace (EAF) slag featuring high Si content and relatively low Al content, and ladle-arc fusion (LAF) slag with medium-Al content. It was found that the carbonation kinetics of the three slags were similar and followed the surface coverage model within the first 6 h of carbonation. Initially, the carbonation process was primarily governed by the reaction product precipitation. After 3 h of carbonation, the process was dominated by mineral dissolution, controlled by the uncovered reactive sites. The …

Hydraulic Connectivity And Hydrochemistry Influence Microbial Community Structure In Agriculturally Affected Alluvial Aquifers In The Midwestern United States, Hunter W. Schroer, Kendra Markland, Fangqiong Ling, Craig L. Just

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Alluvial aquifers can provide ecosystem services and drinking water but much remains unknown about human effects on aquifer microbiomes. Therefore, we used amplicon sequencing and hydro chemical characterization to pair microbial communities with environmental conditions across 37 alluvial aquifer wells. The study region spanned eastern Iowa and southern Minnesota (USA) and contained a combination of drinking water and monitoring wells. In terms of microbial ecology, dominant phyla across the wells included Proteobacteria, Bacteroidota, Patescibacteria, Planctomycetota, and Nitrospirota. Tritium, an indicator of infiltration and surface water influence, was the highest correlated variable with the Shannon index (α-diversity) by the Spearman rank …

Performance-Based Approach To Characterize External Sulfate Attack For Reactive Powder Concrete, Umut Bakhbergen, Chang Seon Shon, Dichuan Zhang, Jong Ryeol Kim, Jenny Liu

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Reactive powder concrete (RPC) is a relatively new type of high-performance concrete, offering enhanced load-bearing capacity, mechanical strength, and durability. The enhanced microstructural density of RPC with the incorporation of reinforcing fibers significantly increases its resistance to durability challenges, particularly against external sulfate attack (ESA). However, conventional laboratory testing methods for evaluating the resistance of RPC to ESA are limited. Hence, a new performance-based approach was developed to evaluate the durability of RPC exposed to ESA. Expansion of nine RPC mixtures designed by Taguchi L9 orthogonal array method with four factors (steel fiber content, water-to-binder ratio (w/b), silica fume content, …

Mars Sample Return Earth Entry System Uncertainty Analysis, Michael D. Squire, Victor Cabrera, Eric Christiansen, Alan Jenkin, Kevin Hoffman, Quincy Mckown, Peter Parker, Glenn Peterson, Bruno Victorino Sarli, William P. Schonberg, Katie Steward, Brian Tulaba, Joel Williamsen

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Spacecraft designers and operators use micrometeoroid and orbital debris (MMOD) risk assessments to predict the probability that an MMOD particle impact will cause a critical failure to their systems. An important aspect of MMOD risk and associated requirements is the treatment of uncertainty, often difficult to quantify, or even estimate, for many elements of MMOD risk. This paper describes recent efforts to estimate uncertainties in inputs to the MMOD risk assessment process for a portion of the planned Mars Sample Return (MSR) campaign. The uncertainty bounds developed were used to examine their effect on overall mission MMOD risk.

Every Publication Needs An Author Verified Tl;Dr Statement, Sarah Oerther, Daniel B. Oerther

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

No abstract provided.

Oxidation Behavior Of Silicon Carbide, Matrix Graphite, And Refractory Multi-Principal Element Alloy, Visharad Jalan

Doctoral Dissertations

"The present study focuses on the investigation of the oxidation behavior of silicon carbide, matrix graphite in a water vapor environment. It also examines the oxidation behavior of refractory multi-principal element alloys when exposed to air. The oxidation behavior of silicon carbide and matrix graphite were investigated in conditions pertaining to off-normal incidents in high-temperature gas-cooled nuclear reactors. Understanding this is crucial for the prediction of their performance in such accidents and ensuring that the nuclear reactor is accident tolerant. Upon exposure to water vapor, the two A3-based matrix graphite exhibited different behaviors. The A3-27 type showed oxidation in all …

Mitigating Frost Heave And Thaw Weakening In Roads Using Wicking Geotextile, Javad Galinmoghadam

Doctoral Dissertations

"Excess water is known to be the primary cause of soil and foundation problems. In cold regions, water-related problems are exacerbated by seasonal freezing and thawing cycles. Frost heave and thaw weakening is the leading cause of premature pavement failure and consume considerable budgets of the Department of Transportations in cold regions. The first step to designing mitigation measures is the ability to predict frost heave under different conditions. This study aims to introduce a new method for quantifying frost heave using a prediction model based on the state surface approach. This proposed model addressed many inconsistencies and limitations of …

Improving System-Level Outcomes Via Artificial Intelligence Decision Support In Kidney Utilization, Casey I. Canfield, Cihan H. Dagli, Daniel Burton Shank, Krista Lentine, Mark Schnitzler, Henry Randall, V. Sriram Siddhardh Nadendla, Brendon Cummiskey

Engineering Management and Systems Engineering Faculty Research & Creative Works

Transplantation provides patients suffering from end-stage kidney disease a better quality of life and long-term survival. However, over 20% of deceased donor kidneys are not utilized and never transplanted. While this is sometimes medically appropriate, this also reflects missed opportunities. We are designing Artificial Intelligence decision support for the kidney offer process to support both demand at the transplant center and supply at the organ procurement organization. This includes (1) developing deep learning models, (2) evaluating the effect of explainable interfaces, (3) improving fairness in the model output, (4) identifying factors that influence adoption decisions, and (5) conducting a randomized …

Time Series Forecasting With Lstm: An Extensive Content Analysis, Andri Pranolo, Xiaofeng Zhou, Yingchi Mao

Knowledge Engineering and Data Science

This paper presents a comprehensive bibliometric and content review of the trend, architecture, and application of long short-term memory (LSTM) models for time series forecasting. The study aims to provide insights into the overall statistics and distribution of papers focused on LSTM for forecasting. Additionally, the research questions address the most highly cited papers based on LSTM approaches in forecasting, the most productive journals in this field, and identifying trends, gaps, summary tasks and their performance, datasets availability, and future research directions for LSTM in forecasting. This paper is a comprehensive review of LSTM for forecasting from 2017 to 2023 …

Characterizing Heat Transfer Performance In A Slurry Bubble Column Reactor Equipped With A Real Heat Exchanger, Dalia S. Makki, Hasan Sh Majdi, Amer A. Abdulrahman, Abbas J. Sultan, Bashar J. Kadhim, Muthanna H. Al-Dahhan

Chemical and Biochemical Engineering Faculty Research & Creative Works

Abstract: This study examines the impact of equipping a real heat exchanger in a slurry bubble column SBC on instantaneous and local heat transfer coefficients IHTC and LHTC, as well as the overall heat transfer coefficient U, employing advanced heat transfer techniques. The experiments were conducted in a 0.15 m inner diameter Plexiglas SBC with varying gas flowrates Ug (0.14–0.35) m/s at several radial sites along the column's diameter (±0.18, ±0.46, and ± 0.74) and three axial locations (H/D = 2, 3 and 4). To simulate the industrial Fischer–Tropsch bubble column reactor FT-BCR, a real heat exchanger consisting of 18 …

Tumor Microenvironment Immunomodulation By Nanoformulated Tlr 7/8 Agonist And Pi3k Delta Inhibitor Enhances Therapeutic Benefits Of Radiotherapy, Mostafa Yazdimamaghani, Oleg V. Kolupaev, Chaemin Lim, Duhyeong Hwang, Sonia J. Laurie, Charles M. Perou, Alexander V. Kabanov, Jonathan S. Serody

Chemical and Biochemical Engineering Faculty Research & Creative Works

Infiltration of immunosuppressive cells into the breast tumor microenvironment (TME) is associated with suppressed effector T cell (Teff) responses, accelerated tumor growth, and poor clinical outcomes. Previous studies from our group and others identified infiltration of immunosuppressive myeloid-derived suppressor cells (MDSCs) and regulatory T cells (Tregs) as critical contributors to immune dysfunction in the orthotopic claudin-low tumor model, limiting the efficacy of adoptive cellular therapy. However, approaches to target these cells in the TME are currently lacking. To overcome this barrier, polymeric micellular nanoparticles (PMNPs) were used for the co-delivery of small molecule drugs activating Toll-like receptors 7 and 8 …

Machine Learning Modeling For Hydrolysis Recycling Of Pet Waste, Jie Li, Lanjia Pan, Hossein Abedsoltan, Hailong Wang, Taiyang Liu, Xiangzhou Yuan, Yong Sik Ok, Yin Wang

Chemical and Biochemical Engineering Faculty Research & Creative Works

The hydrolysis of polyethylene terephthalate (PET) into terephthalic acid (TPA) can efficiently recycle waste PET, but achieving high conversion efficiency through smart reaction design remains challenging. To develop a robust and accurate machine learning (ML) model for the in-depth understanding and intelligent design of PET hydrolysis, we compiled a new dataset comprising 942 data points and comprehensive information of 44 variables involved in heating type, acid/base catalyst (ABC), organic solvent (OS), co-solvent (CS), phase transfer catalyst (PTC), and operational conditions. The developed Neural Network model demonstrated the best performance in predicting PET conversion, with a testing determination coefficient (R^{2 …}

3d Printing Of A Solid-State Battery, Maurizio A. Brozzi

Honors Undergraduate Theses

Solid-state battery research has gained significant attention in recent years, as it provides a unique solution for several common issues in conventional Li-ion batteries. Additionally, as additive manufacturing technologies continue to advance, they have the potential to fabricate solid-state batteries with new materials. The objective of this study is to explore the feasibility of 3D printing of a solid-state battery. By creating an initial PEO-PSF hybrid polymer matrix dissolved in DMSO and adding a lithium salt, the base electrolyte ink was formed. With the addition of conductive additives and active material, electrode inks were also produced. Super P was used …

Salinity Effects On Cu(Ii) Bioremediation By Chlamydomonas Reinhardtii Microalgae, Jennifer Hughes

Honors Undergraduate Theses

Microalgae offer a sustainable approach to wastewater treatment by removing pollutants such as excess nutrients, CO₂, and heavy metals. Among various species, Chlamydomonas reinhardtii shows strong potential in removing Cu(II) ions from wastewater. In addition, salinity stress in C. reinhardtii has been linked to morphological and metabolic changes that enhance lipid and phytochemical production. While salinity stress has been studied for enhancing biofuel production, its impact on microalgal removal of heavy metals, particularly Cu(II), remains largely unexplored. Understanding how varying salinity conditions affect both algal growth and the efficiency of Cu(II) remediation could provide critical insights for improving integrated wastewater …

Identification Of Fiducial Points In Seismocardiographic Cycles Using Manual And Automated Annotation Methods, Jasmine-Vy T. Truong

Honors Undergraduate Theses

There is currently a need for complementary methods for non-invasive cardiac monitoring. Seismocardiography (SCG), the measurement of cardiac-induced vibrations at the chest surface, has shown potential clinical utility. Improving the reliability of detecting fiducial points of electrocardiography (ECG) and SCG, which collectively capture the electro-mechanical cardiac activities, could expand ECG/SCG utility as a low-cost, accessible tool for clinical assessment. This study identifies commonly accepted criteria for fiducial point detection in SCG and ECG through an extensive literature review and signal processing techniques. The previous criteria were evaluated to identify their strengths and weaknesses. Based on the findings, an improved set …

Supporting Human-Ai Interaction From User Expectations To Mental Models, Harishankar Vasudevanallur Subramanian

Doctoral Dissertations

Explainable AI (XAI) aims to unravel the "black box" nature of AI systems and provide insights into the inner workings that lead to a prediction. However, the best XAI communication varies depending on the individual, task, and broader context. It is challenging to anticipate the best XAI for a particular use case. One strategy is for users to build an appropriate mental model of AI with both prediction and system level XAI. To date, little research has focused on quantitatively measuring users interacting with system-level XAI. This dissertation has three primary contributions. The first contribution is a scoping review paper …

Microwave Photonics-Assisted Interrogation Of Fiber-Optic Interferometric Sensors With Joint Frequency-Time Domain Analysis, Ruimin Jie, Jie Huang, Chen Zhu

Electrical and Computer Engineering Faculty Research & Creative Works

Fiber-optic interferometers are widely used in localized sensing applications due to their compact size, high sensitivity, and immunity to electromagnetic interference. In this paper, we propose and experimentally demonstrate a novel interrogation scheme for fiber-optic interferometric sensors, utilizing microwave photonics (MWP) and joint frequency-time domain analysis. As a proof of concept, a miniature fiber in-line Fabry-Perot interferometer (FPI) is integrated with a microwave photonic single-passband filter, enhanced by a dispersion compensation module to improve sensing performance. By applying an inverse Fourier transform to the system's complex frequency response, the time-domain representation of the signal is obtained, translating spectral shifts of …

Spin Mechanisms In Gd-Doped Gan Implanted With Oxygen Carbon At Room Temperature, Vishal Saravade, Amirhossein Ghods, Chuanle Zhou, Ian Ferguson

Electrical and Computer Engineering Faculty Research & Creative Works

Gadolinium-doped gallium nitride implanted with oxygen and carbon show carrier-mediated spin mechanisms at room temperature. As-grown Gd-doped GaN grown by metal-organic chemical vapor deposition using a tris(cyclopentadienyl) gadolinium precursor shows Ordinary Hall Effect and no ferromagnetism at room temperature. Upon O or C implantation in Gd-doped GaN, Anomalous Hall Effect that is indicative of carrier-mediated spin and ferromagnetism is observed. A good crystal quality is maintained even after implantation. O and C favor interstitial sites and occupy deep-level acceptor-type states in Gd-doped GaN. Room-temperature spin and ferromagnetism that is induced by gadolinium in Gd-doped GaN is activated by O and …