Villanova Match Research Program for First Year Students

Student application deadline: Friday, November 11, 2022 at 11:59 p.m.
 

The Villanova Match Research Program for First Year Students provides opportunities for motivated first-year undergraduates to pursue undergraduate research in their first spring semester. Applicants do not need substantial experience and will serve as research assistants to faculty mentors.

If selected for the Match program, students will conduct research for 10 hours per week for 10 weeks for which they are paid $1000. In addition to conducting undergraduate research, Match grantees participate in professional development seminars on resumes, cover letters, oral presentations, and proposal writing during the Spring semester.  
 

Student Application Instructions

For all opportunities presented by the Villanova Match Research Program for First Year Students, please complete the following steps:

1. Review the Spring 2023 research projects listed below and identify a project that interests you. You may apply for opportunities outside of your college and major. You may apply for multiple opportunities. 
   
   
2. Email your application directly to the Faculty Research Mentor by Friday, November 11th at 11:59p.m.
   A complete application consists of the following:
   
   • One-page resume
   • One-page cover letter
   • Combine resume and cover letter into one PDF file
     
   • This PDF file should be named: LastName_FirstName_Match Application
   • Email subject line should contain: Match Research Program Application, LastName
      
3. The Faculty Research Mentor will review your application and should contact you to interview for the position in November or early December.

If you would like to discuss undergraduate research and formulate a plan for becoming involved in undergraduate research at Villanova, you are welcome, though not required, to make an appointment with the CRF team via Handshake.

Students interested in applying for Match projects through the Clare Booth Luce Engineering Scholars Program (CBL-ESP) must follow specific guidelines for completing their applications. Below, please find a summary of the Match projects offered through CBL-ESP and click on the Application Instructions link to learn more.
 

Cover Letter & Resume Templates & Tips

Current Projects - Spring 2023

Summaries of the Spring 2023 projects are listed below the table

Current Project Summaries - Spring 2023

 

Arts & Social Sciences

 

Amy Way, Communication, College of Liberal Arts and Sciences

Reproductive Healthcare at the Margins

A 2019 report from the Centers for Disease Control shows that black women are at least three times more likely to die during and after pregnancy than white women. Queer and transgender folks often delay or avoid seeking medical care for fear of negative treatment by health care providers. With the knowledge of these disparities in health care, scholars like myself are eager to take action to eliminate inequitable treatment in the health care system. As such, I am currently in the midst of a multi-year ethnographic research project partnering with the Philadelphia Midwife Collective (PMC) to consider how to best meet the needs of traditionally marginalized folks in need of care before, during, and after pregnancy. PMC, located in nearby Germantown, is committed to serving comprehensive reproductive health care for marginalized communities including people of color, LGBT/Queer clients, low-income individuals, and Medicaid recipients. PMC is currently working to open a nonprofit birth center to empower community members to envision and enact reproductive health care that best serves their unique needs and position those community members who have been marginalized to take the lead in serving as experts for reproductive care. Therefore, this project, developed in partnership with the PMC, is designed to help the organization gather data about the needs of the community, through interviews and focus groups, that will inform the creation of the new birth center. Findings from this project will offer a case study on organizing locally around reproductive healthcare for marginalized folks, contributing to scholarly literature and offering best practices for any organization who might benefit from such a close look at the process.

A research assistant is needed to help in the early process of data analysis, primarily by transcribing audio recordings from interviews and focus groups. Such a project is well suited for a new research assistant who wants exposure to qualitative methods and is interested in the topics of community engagement and access to health care. Depending on how the project progresses and the proficiency of the student, a research assistant may be trained to use qualitative analysis software to assist in the early analysis of these transcripts by working with me to generate descriptive codes to categorize and sort the data. The research assistant would be expected to work independently (with necessary guidance) to code data for further analysis. 

 

Judith Giesberg, History, College of Liberal Arts and Sciences

Last Seen: Finding Family After Slavery

The Last Seen Project is identifying, digitizing, and publishing Information Wanted ads taken out by formerly enslaved people looking for family members from whom they were sold away during America's domestic slave trade. These ads are published on an open-access database that is now being used by the descendants of enslaved people to find their ancestors. These ads describe enslaved families, information that can be found nowhere else--not in the census, not in marriage or birth records.

Student will read reels of digitized and microfilmed Black newspapers from the nineteenth century to identify advertisements placed by formerly enslaved people looking for family members from whom they were sold away in America's domestic slave trade. They will work with other Last Seen staff members to load these advertisements to our Omeka website and to add requisite metadata so that the ads can be discovered by users of the Last Seen database.

 

Sally Scholz, Philosophy, College of Liberal Arts and Sciences

Solidarity and Sanctuary

Solidarity is both a call to action opposing injustice, oppression, and violence to create social change, and a reminder to sustain and support one another through the struggle. It is also a moral relation between people that necessitates positive duties among fellow solidary actors. Civic solidarity, the solidarity among consociates in an organized society, has come to be associated with the welfare state, identifying a responsibility to help fellow members of society when they are in need and a reciprocal right to receive help from others when help is needed. This traditional understanding of civic solidarity presumes a bounded community. Global challenges—migration, climate change, nuclear proliferation, and pandemics among others—call for a rethinking of bounded civic solidarity.

Using contemporary social philosophy and the history of the just war tradition, Solidarity and Sanctuary develops an unbounded concept of civic solidarity for globalized relations. Drawing on the tradition of sanctuary and the inspiring contemporary examples of collective action in solidarity, the book argues for a civic solidarity that emphasizes the purpose and nature of society rather than the boundaries of polities or the criteria of membership within a political community. Issues of migration and refugee resettlement illustrate the importance of connecting solidarity and sanctuary. The displacement of peoples due to conflict, economic exploitation, or social unrest serves as a reminder of the need for sanctuary. The ‘crimes of solidarity’ enacted by activists and advocates around the globe illustrate the limitations of policing the boundaries of solidarity while providing an engaged example of the political potential for unbounded civic solidarity.

Solidarity and Sanctuary challenges the discourse of civic solidarity based on national identity and security, contributing to literatures on global justice, migration, solidarity, and citizenship studies by refocusing on civilian enactment of civic solidarity.

As a research assistant, the student will gather and survey some recent cases of so-called “crimes of solidarity” in both the U.S. and Europe. States have taken to prosecuting humanitarian actions in efforts to control immigration and secure borders. But the activists and advocates engaged in helping the people on the move consider their actions justified violations of state law. By gathering examples of recent cases and categorizing them according to the types of justifications used, the student will contribute to a chapter of the book and, perhaps more immediately, contribute to a standalone article on intergenerational solidarity within efforts to support people on the move. In addition to work on honing and making accessible philosophical argumentation that is aimed at a generalist audience, the student will be given the opportunity to add their name to a professional article and/or co-author an associated professional blog post aimed an audience of philosophers and philosophy students. 

 

Grant Berry, Spanish, College of Liberal Arts and Sciences 

Can machines learn to speak with an accent? Simulating phonetic drift with speech-to-text

Virtual assistants, a concept relegated to sci-fi and fantasy as recently as ten years ago, are ubiquitous today. Nearly every smartphone has access to Siri, Alexa, Google, or another disembodied voice that can interact with and complete tasks for the device owner. Speech-to-text technology gives each of these assistants their own unique voice, a voice created from millions of curated training examples. Is the way a virtual assistant develops this voice fundamentally different from the way humans develop theirs? This research uses publicly available speech data from non-native speakers of English—the largest second-language in the world—to explore how the voices of virtual assistants adapt when trained with accented speech. Specifically, we will fine-tune existing speech-to-text algorithms with English speech data to explore the rate at which speech-to-text algorithms integrate non-native features of speech into their own production. Findings will then be compared to the wealth of research regarding how humans develop speech in a second language with the goal of better understanding the mechanisms guiding language learning and adaptation.

The Research Assistant (RA) will collaborate actively with members of the Language Use and Variation (LUV) Lab’s Computation cluster to create stimulus lists and baseline recordings, write scripts for fine-tuning out-of-the-box speech-to-text models, and conduct acoustic analyses of machine-generated speech. Importantly, the RA will work in collaboration with lab members and the Faculty Mentor to disseminate findings to interested parties on campus and in the academic community at large via research talks at conferences and publication of an academic manuscript in a peer-reviewed journal. At the end of the funding period, the Faculty Mentor will work in collaboration with Villanova’s Career Center to guide the RA in applying for an internship at a technical industry developing speech science applications (e.g., Amazon, Google).

 

Business

 

Lucy Chen, Accountancy, Villanova School of Business

Acquirers’ Use of Fairness Opinions and Subsequent Litigation Risk

In this research project, I examine the association between the acquirers’ use of fairness opinions and subsequent shareholder lawsuits against acquirers in a merger or an acquisition (M&A). M&As play an increasingly important role to fuel corporate growth. In 2021 alone, the number of global M&A exceeds 62,000 deals and the value of these M&A totals more than $5 trillion (PWC 2022). A fairness opinion in an acquisition is a professional evaluation by a financial advisor as to whether the term of the acquisition is fair from the financial point of view. Usually, it is accompanied by a detailed report on the valuation analyses. These advisors rely predominantly on accounting-based (such as earnings, cash flow, and revenue) valuation methodologies to evaluate the range of “fair value” for the companies under current business conditions, using discounted cash flow model as the most common valuation methodology (DeAngelo 1990; Liu 2020). Regulators and practitioners question the value of fairness opinions, as providing fairness opinions is one of the easiest money-making activities on Wall Street (Davis 2004). Prior research is inconclusive on the value of fairness opinions, as some argue that fairness opinions can be used for acquiring managers and board of directors merely for legal protection, while others argue the use of fairness opinions can reduce investors’ uncertainty on pricing of M&As. My research project examines whether the purchase of fairness opinions will reduce shareholders’ lawsuits against acquiring managers and board of directors. I will also examine the conflict of interest involved and fee structure for financial advisors in providing fairness opinions and how they affect shareholder litigation. My research has implications for regulators to evaluate the M&A transactions.

The student will start collecting data on fairness opinions and shareholder lawsuits. He/she will also review the literature and conduct some analytical/statistical work to test the hypotheses. Knowing SAS or STATA will be a plus but not a requirement. I will teach the student the basic analytical skills as long as the student is willing to learn. I will meet with my RA periodically to review and modify our plan for research. He/she can also provide feedback and discussions on research ideas. I will guide my RA step-by-step on how to conduct the research. My research topic is in the interaction of accounting and corporate finance. I would love to work with anyone who is interested in understanding more in accounting and finance. No background of accounting or finance is needed, but a love for research and great sense of responsibility is needed. 

 

Kyoung Yong Kim, Management and Operations, Villanova School of Business

Servant leaders serve others before themselves inside and outside their organizations, including their local communities (Greenleaf, 1977). Although servant leadership was introduced five decades ago in a classic essay by Robert Greenleaf (1970), it was slow to gain the attention of academics. During the past fifteen years, however, scholars’ interest in servant leadership has significantly increased. Leadership scholars have developed and validated servant leadership scales and have demonstrated that servant leadership is positively related to individual performance (Hunter et al., 2013; Liden et al., 2014), citizenship behaviors (Hunter et al., 2013; Liden et al., 2014; Neubert et al., 2008), organizational commitment, identification, and work engagement (Liden et al., 2014; van Dierendonck et al., 2014). At the work group level, servant leadership has been shown to be positively related to group potency.

Now that accumulated evidence has consistently demonstrated relationships between servant leadership and key outcomes, the servant leadership literature can be extended in an important way. Given the importance of leadership, servant leadership may positively impact team and organizational performance. However, little is known about the mechanisms via which servant leadership contributes to team and organizational performance. In this project, I aim to examine how servant leadership impacts team and organizational performance.

The Match student research assistant will carry out literature searches, design surveys, perform statistical analysis, and conduct data entry.

 

Business/Science

 

Jen Santoro & Chris Jeffords, Economics & Geography and the Environment, College of Liberal Arts and Sciences

Analyzing the Impact of Science Communication in the Community: A Case Study of Science on Tap

We aim to collect data about science communication gaps through our unique community education program called Science on Tap (SoT) - Phoenixville. SoT is a monthly event held at a brewery in Phoenixville where a scientist (or individual with broad scientific knowledge) leads a conversation in a family-friendly environment. We’ve held five talks so far on topics from environmental security to yeasts. As we continue to expand SoT, we want to ensure each conversation is broadly accessible to individuals of all sociodemographic and educational backgrounds. As organizers, however, we often lack the basic background knowledge required to fully understand each topic. To remedy this, we plan to develop a series of guidelines and processes for each invited speaker to ensure that they: (1) understand the nature of the audience; (2) include practical or applied aspects of their research; and (3) engage the audience in a way that is different from a typical academic presentation.

Our second goal is to ensure that we have a diverse and inclusive environment, especially as it relates to the community members in attendance and the speakers who lead talks. We believe this is also part of the science communication gap. To address this, we will source effective communication strategies, based on applied and theoretical research findings, to implement at SoT.

Our third goal is to learn about the community’s interests and use this information to create a more meaningful aspect of the SoT series. To accomplish this, we will informally survey the attendees and reach out to local business and government offices to do the same.

We plan to eventually write a research paper (with the student) about the launch of SoT and how its evolution has created a safe, diverse, and inclusive space for community conversations about topics within the natural and social sciences.

The student will develop and/or implement the following items: (goal 1) research and draft the guidelines for each speaker as highlighted in the project description; (goal 2) analyze and apply effective communication strategies to increase the diversity and inclusion aspects of the SoT events and to effectively engage the local community in a continued, monthly conversation about different topics in the natural and social sciences; and (goal 3) help develop the survey questions for the local community.

 

Engineering

Clare Boothe Luce Engineering Scholars Program (CBL-ESP)

***Please note special application instructions***

 

Wenqing Xu, Civil and Environmental Engineering, College of Engineering

The occurrence of per- and polyfluoroalkyl substances (PFAS) in groundwater has been consistently confirmed at Department of Defense (DoD) facilities at μg/L to mg/L levels. Recently, there have been increasing concerns over the discharge of stormwater containing PFAS due to the historical use of aqueous film-forming foam (AFFF) and the possible intrusion and infiltration of AFFF-impacted groundwater into stormwater systems. PFAS have also been frequently detected in stormwater runoff from residential, commercial, and industrial areas. Notably, many reported values exceeded the Environmental Protection Agency human health advisory level of 70 ng/L. Although biofilters are one of the widely used stormwater best management practices (BMPs), current knowledge suggests that these systems may fail to remove PFAS. As a result, there is an urgent need to develop sustainable BMPs to effectively prevent the introduction of PFAS from stormwater to receiving water bodies. The objective of this limited-scope project is to provide proof-of-concept evidence to show that tailored biochar can be employed as an amendment to augment the performance of biofilters for PFAS removal.

As a proof of concept, we will tailor biochar materials from metal-rich waste feedstocks under a range of pyrolysis temperatures to alter their anion-exchange capacities, polyaromatic surfaces, and pore characteristics. We will also develop strategies to covalently graft quaternary ammonium groups on selected biochar to facilitate interactions with anionic PFAS. Throughout the biochar modification process, we will work closely with a biochar company to ensure method transferability and thus foster the market availability of the developed materials down the line. The efficacy of these materials will be evaluated under conditions relevant to field BMP operations using bench-scale batch and column tests. To better incorporate the complexities involved with field conditions, we will perform column tests using authentic stormwater collected from a DoD facility and assess the removal of PFAS under varying dissolved organic carbon contents as well as flow dynamics that allow the soil column to fluctuate between saturated and unsaturated conditions. Commercially available adsorbents will be included as a benchmark.

The student will aid in producing anion-exchange capacity (AEC)-enhanced biochar from waste feedstocks, which involves collecting dried waste, pretreating them with metal salts, performing pyrolysis, and grinding/sieving the pyrolyzed waste to generate the biochar. The student will also help determine the adsorption kinetics and capacities for PFAS. This will be performed through adsorption experiments with lab-scale batch reactors; the student will help prepare the samples for adsorption experiments, collect the samples at their respective reaction times, and generate plots from the collected data. Lastly, the student will help with authentic stormwater transport experiments in soil columns amended with biosolids with or without biochar by helping set up the soil columns, monitoring the PFAS transport results, and producing plots from the gathered data. 

 

Stephanie Walkup, Civil and Environmental Engineering, College of Engineering

Strength of concrete beams reinforced with glass fiber reinforced polymer (GFRP) vs. traditional steel reinforcing bars

Concrete with steel reinforcement experiences deterioration due to corrosion of the embedded reinforcing steel when the concrete cover is no longer sufficient to provide corrosion protection. For this reason, research continues on the use of glass fiber reinforced polymer (GFRP) bars which are non-corrosive with anticipatedly better life-cycle costs.

On September 2, 2022, the American Concrete Institute codified (mandated) language for the design of concrete reinforced with GFRP reinforcement with their publication of ACI 440.11-22 Code Requirements for Structural Concrete Reinforced with GFRP Bars. Previous experimental research conducted by Villanova faculty in the Faris Structural Engineering Teaching and Research Laboratory (SETRL) and the associated publications directly contributed to serviceability (primarily beam deflection) provisions in this code. Over sixty concrete beams reinforced with both GFRP and/or traditional steel reinforcement were cast and tested as part of these research studies. In this proposed research project, existing reinforced concrete beams will be tested to failure in SETRL to verify the acceptability of the recently codified language for beam strength including both nominal bending capacity and nominal shear capacity and to perform a sensitivity analysis of the data related to beam geometry and reinforcement ratios.

Given that we would eventually like to publish a paper about this process and its outcome, perhaps as a case study or qualitative analysis of science communication, the student research assistant would be a co-author on our research paper and help formulate various aspects of the project from the literature review to summarizing their findings associated with implementing the goals described above.

 

Chenfeng Xiong, Civil and Environmental Engineering, College of Engineering

Human Mobility Patterns under the Influence of Climate Change

The project will employ passively collected mobile device location data to quantify human mobility patterns, such as number of trips made, size of daily activity cycles, and visits to different point of interests (POIs, such as restaurants, healthcare facilities, public transportation). Such mobility pattern measurements will then be linked with extreme weather event records (e.g., hurricanes, extreme heat, droughts) and study how climate-change-induced extreme weather has influenced human mobility via statistical approaches and data mining methods. The study will focus on two application sites: Nigeria and South Africa.

The undergraduate researcher will participate in daily operations and discussions within this project. The research assistant will provide assistance to the PI and graduate researchers in terms of information collection and literature search, data visualization and processing, modeling development, and report drafting. 

 

Pali Singh, Electrical and Computer Engineering, College of Engineering

Nickel Metal Hydride Battery Characterization 

This project involves the characterization of used nickel metal hydride batteries from Toyota Priuses. The idea is to repurpose these batteries for use in solar home systems in Fiji. Developing a methodology for screening good batteries from bad ones using electrochemical impedance spectroscopy will be the goal of this project.

Seeking a motivated student interested in renewable energy with some basic programming skills as well as some background in circuits and electronics. 

 

Meltem Izzetoglu, Electrical and Computer Engineering, College of Engineering

Design, Development and Evaluation of Physical and Digital Optical Head Phantoms

Growing importance is being given to the technologies deployed in providing measures of brain functioning and physiology in real time under real world settings. Understanding and monitoring of the state, inner workings, and functional make-up of the human mind by properly adapting these brain imaging methodologies, can guide the clinicians, scientists, and researchers in improving the diagnosis, treatment and prevention of brain disorders and injury. Near-infrared spectroscopy (NIRS) is an optics-based brain imaging technology that holds untapped potential for clinical use and research applications by allowing the design of safe, portable, wearable, noninvasive, and affordable brain monitoring systems with rapid application time, superior immunity to movement noise, and near-zero run time cost. As NIRS gain more widespread use, calibration, testing, characterization and validation of the device design, analysis algorithms and measurements become essential. Human head-mimicking models (phantoms) have been an integral, necessary, and important part in those processes such as standard system quality tests, characterization of signal-to-noise ratio or performance comparisons among systems or algorithms. The objective of this research is to design, develop and evaluate optically, anatomically, and physiologically realistic physical and digital human head mimicking phantoms based on 3D printing technology and Monte Carlo simulations.

Major tasks include, but are not limited to: (1) Research on human head mimicking physical phantom designs of solid, liquid and fluid channel types made out of different materials including silicon, gelatin, 3D printing; (2) Building solid phantoms using 3D printing technology with appropriate materials mimicking human head with/without (a) superficial layers of different optical characteristics and thicknesses (b) lesions of different sizes and depths (c) fluid channels of different anatomical structures and with mechanisms to mimic blood flow at different rates; (3) Testing and evaluation of the designed phantoms using various NIRS devices; (4) Research on human head mimicking digital phantom designs using open-source Monte Carlo simulation codes that will be built anatomically and optically similar to physical phantom designs; (5) Testing and evaluation of physical and digital phantom measurements in comparison to each other 

Meltem Izzetoglu, Electrical and Computer Engineering, College of Engineering

This is an on-going, multi-year project. The goal of this project is to develop a smart stroke rehabilitation device that can modulate the assistance provided based on the muscle activity, brain activity and position of the unassisted limbs. First part of the project includes the development of a mechanical arm with sufficient degrees of freedom to mimic basic motions such as bending the elbow and making and opening a fist. The arm will be fitted with actuators to aid in the movement, but these actuators must be controlled by varying activity received from human muscle groups. Second part of the project involves the development of the therapeutic device that can sense muscle and brain activity and position of the joints and provide appropriate assistance. The student selected for this project will continue working on previous iterations of this project.

The student for this project can expect to work on the following tasks; (1) develop or refine a multi-degree of freedom mechanical arm with sufficient degrees of freedom to test the efficacy of the therapeutic device, (2) conduct experiments with the current prototype, instrumented on a mechanical arm, to evaluate efficacy of the therapeutic device, (3) optimize the location of the actuators and sensors on the wearable device, (4) refine the comfort and ergonomics of the device to make it easier for patients to use. 

 

Jiafeng Xie, Electrical and Computer Engineering, College of Engineering

Post-quantum cryptography (PQC) is a new generation of cryptosystems that can resist attacks from mature quantum computers. The recent U.S. National Security Memorandum determined that the U.S. must transit to quantum-resistant cryptosystems by 2035. Meanwhile, a number of PQC algorithms have been proposed for possible standardization. Following this trend, the recent advance in the field is to determine the implementation performance of a PQC algorithm on the hardware platform.

In this project, we follow this trend to conduct research on efficient hardware acceleration of a PQC algorithm that is currently under the standardization consideration by the National Institute of Standards and Technology (NIST), the code-based cryptography HQC. We have identified that one of the most complicated arithmetic operations for HQC is the polynomial multiplication over binary field. Hence, in this project, we will: (1) train and equip the supported undergraduate research student with the required hardware skills for implementing this polynomial multiplication (mathematical background will be introduced by the Project Mentor); (2) learn the hardware design language coding skills and hardware design techniques to transfer the targeted operations into efficient hardware architectures (testing will be carried out as well); (3) explore possible optimization techniques to improve the hardware accelerator’s final implementation further.

This project will be led by Dr. Jiafeng Harvest Xie from the Electrical and Computer Engineering Department and the whole project will last for 10 weeks with 10 hours per week. The Project Mentor will advise the supported student to conduct the research proposed above. A complete version of the polynomial multiplication accelerator for HQC is expected to be finalized by the end of the project. The results obtained from this project will be documented and compiled into a paper for possible publication in an IEEE Conference or even Journal.

The Security and Cryptography (SAC) Lab of the Department of Electrical and Computer Engineering, led by Dr. Jiafeng Harvest Xie, is seeking one undergraduate research assistant under the support of Villanova Match Program project -- Hardware Accelerator for Quantum Resistant Cryptosystem.

Basic requirements: knowledge of computer design and programming languages such as Python; prior experiences in hardware design will be desirable (though not required).

Results: It is expected that by the end of the project time, the student will be familiar with and handle hardware design languages and tools like VHDL/verilog, Quartus Prime, Vivado, and ModelSim. A possible paper will also be submitted for publication based on the obtained results.

Background information: Dr. Xie has been actively involved with quantum resistant cryptosystem research. He has supervised a successful student project that led to a publication in IEEE Computer Architecture Letters, which was awarded the Brian Anderson Memorial Award (ECE Department) and the prestigious 2022 IEEE Philadelphia Section Merrill Buckley Jr. Student Project Award.

 

Mike Simard, Mechanical Engineering, College of Engineering

Literature Search on Nanocellular Polymer Materials’ Properties and Manufacturing Methods

I am currently collaborating on a research project with colleagues at the Universidad de Valladolid (Spain), specifically researchers in the Institute of Bioeconomy. This collaboration resulted in a grant from the Spanish Ministry of Science and Innovation in October 2021.

This project basically consists of using both sub and supercritical water with carbon dioxide to create foaming of Poly Methyl Meth Acrylate (PMMA), resulting in a nanocellular polymer of very low density. This material will have very low weight and high heat transfer resistance, allowing end products with outstanding properties as an insulator, both thermal and acoustic. The material will have innumerable applications in many fields of industry.

The basic process is to continuously feed water, CO2, and PMMA to a pressurized and thermally controlled vessel, and then severely drop the pressure to explosively froth the material through a die into a solid, continuous foam.

A thorough search of published literature to identify a breadth of good quality references relevant to a specific topic is a fundamental element of the methodology of any research project. In this project, the freshman student will be tasked with: (1) Learning the basics of the overall research project; (2) Identifying relevant search terms; (3) Identifying the resources to search; (4) Searching - using standard search techniques; (5) Collating and summarizing the results.

There will be opportunity for the student to interact and work with researchers at the Universidad de Valladolid, in particular a PhD student, who can help support the work (in addition to the Villanova mentor). A working knowledge of the Spanish language is beneficial but not necessary.

This opportunity is open to all students, but may be of particular interest to students planning to major in either chemical or mechanical engineering.

 

Deeksha Seth, Mechanical Engineering, College of Engineering

Experimental Robot to Investigate Ornithischian (Dinosaur) Jaw

Validation is an important part of scientific modeling, but without a living organism it is difficult to do so. The goal of the overall project is to design and build an experimental, robotic model of the unique jaws of ornithischian dinosaurs. This group includes Triceratops, Edmontosaurus, and their relatives. The current robot closely models the biology of these dinosaurs, specifically the pre-dentary bone and has components that can facilitate data collection to answer specific evolutionary questions and to compare experimental results to computer models. Freshman Match 2023 project will focus on completing the assembly of the robot, conducting experiments, and collecting and analyzing data to examine the functionality of the pre-dentary bone. This work is being done in collaboration with Dr. Kristyn Voegele from Rowan University.

Student will use computer models and engineering drawings to complete the assembly of the robot, design and manufacture any additional components needed to successfully actuate the robotic jaw, attach and calibrate all required sensors, use the MATLAB graphical user interface (already built) to test the kinematics of the jaw, collect kinematic (position, speed, acceleration) and dynamic (force and torque) data from the actuation, analyze all data using statistical methods and draw conclusions, in collaboration with the paleobiologist, Dr. Voegele. Student can expect to use tools such as Microsoft Office, MATLAB, and SolidWorks.

 

Deeksha Seth, Mechanical Engineering, College of Engineering

Qualitative and Quantitative Statistical Analysis of Human Subject Data

This project is a continuation of a multi-year, evolving project. The goal of the project is to evaluate a classroom activity designed to help early-college students make connections between areas of study within their major and academic disciplines outside their major through decomposing complex, real innovations such as 3D printers, virtual reality goggles and electric cars. The sets of quantitative and qualitative data collected from students, faculty and experts from various academic disciplines will help evaluate the efficacy of the class activity.

Freshman Match 2023 project will focus on analyzing large data sets collected from prior studies to draw conclusions and formulate hypotheses for future investigations. Project may also include gathering additional raw data from research subjects (faculty and students) and developing new data collection instruments.

The student researcher for this project will delve into advanced statistical analysis techniques for categorial quantitative data and qualitative data. Responsibilities include: (a) organize, analyze and visualize numerical data using SPSS, R, PowerPoint, Excel and/or MATLAB (b) use coding techniques to convert qualitative data to quantitative data, (c) visualize qualitative data using charts, graphs, and other creative ways, (d) draw conclusions or formulate hypotheses that need investigation and (e) conduct additional literature research on the topic. Depending on the progress of the project, the student may also conduct interviews or focus groups with research subjects (students or faculty) to gather additional raw data or develop and validate new data collection instruments.

Calvin Li, Mechanical Engineering, College of Engineering

Nanostructures and Atomic Layer Deposition for Adhesion Mechanisms on Ceramic Substrates

The most widely studied technical ceramics is silicon nitride, in part due to its usefulness in a variety of applications, including electronics, aerospace, and energy. Resistance to chemical attack and thermal shock makes silicon nitride ideal for handling molten aluminum, while its hardness and wear resistance have proven extremely useful in industrial seals and bearings. However, under some circumstances, the performance of such critical components has been demonstrably degraded by the adhesion of corrosion products to their ceramic surfaces. This project will utilize nanostructures and atomic layer deposition to investigate the adhesion mechanisms on silicon nitride surface and explore the solutions for the critical problem in the wide applications of silicon nitride.

This undergraduate student will work with a graduate student as a research assistant in conducting experiments and processing data under the guidance and advising of Dr. Calvin Li.

 

Bo Li, Mechanical Engineering, College of Engineering

3D printed porous ceramics for bone scaffolds replacement

Bone has porous ceramic structures to provide critical functionalities such as strong mechanical support and protection and channels for blood and nutrition transportation, as well as storage site for minerals and blood cells. While bone regeneration is extremely slow, researchers are seeking alternative materials to mimic the functionality of the bones. 3D printing has emerged as a promising route to achieving complex bone structures. A critical challenge in the current 3D printing of bone scaffolds is not mimicking the shape of the bone, but the microstructures and mechanical strength. The research team at Villanova is trying to tackle this challenge using a nanomaterial-based Direct Ink Writing (DIW) printing technology. By tailoring the size and content of ceramic nanoparticles, we hope to design artificial bone scaffolds with similar porosity and mechanical strength to the real bone. Our lab is equipped with a DIW bioprinter and has established capability for ceramic material printing. This project will attract and train students for new applications of 3D printing in bone scaffolds and generate Villanova-owned IP for future funding opportunities.

The undergraduate student’s responsibilities include (1) Prepare the slurry-based ink (2) Design the scaffolds’ structure using 3D format software such as CAD or Solidworks (3) Perform the DIW printing using the bioprinter (4) Characterize the printed products using an optical microscope, scanning electron microscope, Raman spectrometer (5) Read and summarize literature and generate reports (6) Perform data sorting, treatment, plot, and present the results

 

Bo Li, Mechanical Engineering, College of Engineering

Smart Textiles for Space Exploration

The goal of this project is to create smart textiles for next-generation light-weighted multifunctional spacesuits. The mission of space exploration desires spacesuits to protect astronauts from extreme environments (low and high temperatures), strong electromagnetic (EM) waves or radiation, high-speed dust, and many unforeseeable dangers. However, the current spacesuit is bulky and heavy because, in addition to multi-layer textiles, multiple life-supporting systems such as temperature control, oxygen, and water supply, and EM wave shielding must be added. If we can apply ultrathin functional coating on the textiles and create smart textiles that can offer functions of some life-supporting systems such as temperature control and EM wave shielding, the weight and thickness of spacesuits will be significantly reduced. As a result, the astronauts will be comfortable carrying more equipment for the space mission. High-performance polymer textiles are used in spacesuits because of their high mechanical performance and thermal stability at ultra-low and high temperatures. However, the inert surfaces of these textiles prevent the effective coating of the required materials. While some harsh chemical processes can be applied to modify the surface properties of textiles to facilitate the coating, they can also damage the mechanical integrity of textiles which is not acceptable for the space mission. We have invented a non-destructive acoustic assembly method to achieve conformal coating of functional nanomaterials on polymers. In this project, we will examine the capability of our method on high-performance textiles which is a new system for us. We will design the properties of nanomaterials to enable their effective assembly on these textiles. We will examine the functions of smart textiles for self-heating, heat conservation, and EM wave shielding. We hope this project will inspire and attract students to the fields of advanced materials, manufacturing, and aerospace.

The undergraduate student’s responsibilities include: (1) Prepare the nanomaterial solution (2) Perform the assembly on fabrics (3) Characterize the assembly using the optical microscope, scanning electron microscope, and Raman spectrometer (4) Read and summarize literature and generate reports (5) Perform data sorting, treatment, plot, and present the results.

Nursing

 

Tresa Kaur, Fitzpatrick College of Nursing

Evaluating #nursingeducation Videos on TikTok: Cross-sectional, Descriptive Content Analysis

Social Media platforms have been used in nursing education to promote active teaching. TikTok is a popular social media tool that uses short videos ranging from 15 seconds to 10 minutes. The hashtag "#nursingeducation" currently has 6.6 million views, however, the content and expertise of these videos remain ambiguous.

This project will evaluate the content of nursing education videos on TikTok. Using a matrix method, videos will be coded and then analyzed for content, knowledge, attitudes, and skills related to nursing students' development. Other areas of analysis include content creator background, application to NCLEX blueprint, domains of learning, the validity of the content, and safety.

This position is for a tech-savy, highly motivated, and organized student who is interested in social media and nursing education. It is expected that the student is familiar with Dropbox, Excel, Word, Outlook, TikTok, YouTube, Twitter, Instagram, and Facebook. The student will collate data, code, and analyze data. 

 

Tracy Oliver, Fitzpatrick College of Nursing

Weight Bias Reduction Among Nurse Practitioner Students Utilizing Simulation

Obesity is one of the leading public health concerns in America today, with more than 72% of the US adult population reported as living with overweight or obesity (Ogden et al., 2006). Discrimination and weight stigmatization are unfortunate experiences individuals with obesity encounter in healthcare (Puhl & Brownell, 2001). Healthcare providers may harbor biased attitudes about weight, which can contribute to discrimination (Budd, Mariotti, Graff & Falkenstein, 2009). Weight bias may directly affect a patient’s involvement in healthcare; therefore, it is essential to identify and alleviate weight bias among future healthcare professionals. Since nursing professionals are often at the frontline of care, they must first identify if they unknowingly harbor any personal biases against patients with obesity. Thereby, conducting weight sensitivity reduction education among nursing students may be imperative to not only teach students about the complexities of obesity but to provide a skill-set to combat weight bias in their future nursing practice.

This sensitivity training program will be a part of the nurse practitioners (NP) course sequence. The program will include a curriculum-embedded weight-bias reduction program. The nurse practitioner students will participate in three simulation encounters across two practicum courses that utilize a standardized patient (SP) living with obesity. Students will participate in educational debriefings, PowerPoint educational lessons, journaling exercises, interactive components, and video segments.

The student research assistant will serve the following roles in this weight sensitivity program: (1) Quantitative data entry from questionnaires (both pre, mid-point, and post) (2) Participate in data analysis (3) Assist in manuscript development, abstract development, and conference submission (4) Potential active involvement in simulation scenarios with standardized patients and simulation video review.

 

Daniel Smith, Fitzpatrick College of Nursing

From Data Science to Community Action: Environmental Justice Research

I conduct work that includes principles of both environmental justice and harm reduction. Broadly, my research interest is on the impacts of climate change on human health with specific emphasis on the impact of high heat conditions on renal functioning in immigrant communities. I have projects that focus on utilizing data science methodologies to understand the association between heat waves and hospitalizations due to renal dysfunction. Other data science projects include data mining of primary care health records of farmworkers to understand climate sensitive diagnoses with the ultimately goal of identifying and developing interventions to reduce the impact of climate change on farmworker health. I am also developing a lead remediation program in Norristown, PA, that will be developed using a participatory action framework in collaboration with the Latinx residents of the area. Finally, I have collaborations with harm reductionists to support the occupational health of service industry workers who respond to opioid overdoses while at work. My research program is varied and would provide fantastic experience to any student who is considering a career in healthcare or public health. I enjoy collaborating with trainees to help develop their research skills and support them in their career development.

The undergraduate research assistant will be responsible for a range of activities from completing literature reviews and write ups to data collection & analysis. The student will likely be interacting with research participants and community facing with the Latinx community in the Greater Philadelphia region. That being said, Spanish proficiency is highly recommended for any student applying to this position. However, it is not required. For a student that would be interested in the data science piece of this position, experience coding in R or willingness to learn is recommended. Nonetheless, the student will work with the PI to create an individual development plan that will guide the student's growth as a researcher and specific work activities on the project. 

 

Carol Toussie Weingarten & Deena Leh, Fitzpatrick College of Nursing

A study of the existence of health programming and nursing presence in Federal Communications Commission (FCC) licensed collegiate radio stations

Throughout the United States, college radio stations broadcast music, news, sports, and other features. How many, if any, stations include health programming? How many, if any, have a nursing presence in their broadcasts and leadership? What opportunities exist for nurses in media broadcast and streaming?

Using a clear, defined protocol for the purposes of this study, this project is in the process of evaluating each of the 484 collegiate radio stations included in the Record Locator listing of FCC licensed collegiate stations. Data collection has begun so no delay in waiting for approvals or access will take place. Findings from the study will address a new nursing role for health promotion through broadcast and streaming and give opportunity and direction for health programming led by the Fitzpatrick College of Nursing (FCN) in partnership with WXVU and in collaboration with the Office of Health Promotion and others.

Using software including Microsoft Office Suite and G-Suite, the student will assist the investigators with analysis of the FCC-licensed collegiate radio stations and with literature reviews. In addition, the student may assist with radio station activities such as health programming and reviewing submissions for broadcast and streaming. 

 

Sciences

 

Stephanie Campos, Biology, College of Liberal Arts and Sciences

The impacts of social status on the stress hormone corticosterone and social dynamics in territorial lizards

This research seeks to understand how an individual’s social interactions are shaped by their social status and are impacted by hormones. My lab uses behaviorally and ecologically diverse lizard taxa to better understand the relationship between hormones and behavior. Lizards use visual and odor signals to communicate with each other, performing visual displays of aggression and courtship using color and push-ups. In this project, we use green anole lizards (Anolis carolinensis) to ask whether social status (dominance or subordinance) in males has lasting impacts on that individual’s future social interactions (male-male or male-female) or hormonal state (corticosterone, a hormone associated with stress responses). We housed two males together in the same tank for 10 days and recorded their interactions with one another twice per day. After the tenth day, the males were separated for 24 hours and then allowed to interact with a new lizard (male or female) for 30 minutes. We filmed these behavioral interactions and measured aggressive behavior (in male-male interactions) or courtship behavior (in male-female interactions). We also collected and analyzed the hormone corticosterone from both males in each pair. The incoming undergraduate researcher will be intellectually involved in the data analysis stage of this research project. This includes watching behavioral videos, exploring the data in a spreadsheet, creating results figures, researching previous literature, and offering insight into the impacts of social status on future social interactions and stress responses.

The research student will be working with a subset of data that is part of a larger project examining the impacts of social status on the hormones, brain, and behavior of territorial lizards. Primary duties include watching films of animal behavior and using an ethogram to familiarize oneself with common social behaviors performed by lizards, conducting a literature review on the impact of corticosterone on territoriality and social dominance, creating data plots or graphs to visualize data, and performing t-tests to determine statistical significance of experimental treatments. The student will also have the option to develop and test their own research hypothesis by measuring a behavior of their choosing using filmed lizard interactions and behavioral scoring software. Other minor duties will include some daily maintenance of our lizard colony (pink belly swift lizards), such as feeding, watering, and cleaning husbandry supplies. Students that excel at this position may be offered an extended undergraduate research position to examine the impacts of social dominance on brain activity.

 

Sarah Cooney, Computing Sciences, College of Liberal Arts and Sciences

Using natural language processing to explore how sustainability-oriented mobile apps present ethics of care

One of the major hurdles faced by the Sustainable Human-Computer Interaction (SHCI) community is figuring out how to move beyond individually-oriented, data-centered approaches for encouraging people to make more sustainable choices. Applications have been developed to span aspects of life from shopping for clothing to household chores and transportation. Taking a cue from the CHI '21 paper "Selling Glossy, Easy Futures" by Spors et al., this project will map and explore the landscape of sustainability-oriented mobile applications available on the Apple App Store.

The project will consist of three core parts: (1) Literature Review: The project will start with a literature review covering various theories on ethics of care, particularly as they relate to sustainability. It will also look at how theories of care have been applied in other areas of Human-Computer Interaction (HCI) such as mobile health. (2) Building a dataset: The second part of the project will consist of building a dataset of app descriptions and metadata. First, a manual exploration of the App Store will be conducted using a few known apps and initial keywords. This exploration will be used to develop a comprehensive set of keywords to search the space. A script will be used to automate the process of searching for candidate applications and scraping the associated data. Finally, using qualitative techniques, post-processing will be to determine inclusion criteria and refine the list of candidate apps into a final dataset. (3) Natural Language Processing: Using the app descriptions from the dataset, various natural language processing techniques will be applied to tease out themes related to the ways in which care is (or is not) presented. Techniques may include, but are not limited to, dictionary-based analysis, sentiment analysis, and topic modeling.

The project will conclude in a report summarizing the literature review, methodology, and findings.

The Match research assistant will play a prominent role in all three phases of the project. The student will begin by reading and summarizing selected literature to gain an understanding of SHCI and ethics of care. The student will then assist with the manual exploration of the data space, data collection, and post-processing to form a complete dataset. This will include both using code to automate data collection as well as the qualitative techniques used to refine the automatically captured results. During the data analysis phase, the student will work through the entire pipeline from pre-processing to post-processing. The student will clean and format data for use in various language processing algorithms, program, and run these algorithms. This will be done primarily in the Python programming language. The student will learn how to interpret the results, which will include becoming aware of the limitations of various techniques and weighting results appropriately. Finally, the student will write a post-project report in the style of an academic paper by summarizing the literature review, data collection, processing methodology, and findings. 

 

Jason Grant, Computing Sciences, College of Liberal Arts and Sciences

Identifying Images for Dataset Redundancy Reduction

For the past decade, researchers have relied on large volumes of noisy, unclean data to generate new algorithms and build high quality models. This has created a culture of data hoarding. Nevertheless, as we generate ever-increasing amounts of data, this model becomes untenable and costly. This paradigm shift can be seen in corporate business models as large entities such as Google have migrated away from unlimited storage services. Recently, photo cloud storage services have equipped users with tools to help them remove unimportant images, such as blurry photos, screen shots, etc. in an effort to reduce storage needs. Similarly, tools are needed in research communities to clean datasets and remove data that provides limited to no value, or no additional value.

This project aims to quantify images in recognition tasks that provide little to no additional information. A common example would be images that were taken in a burst sequence. Any one of the images within the burst of photos may provide significant value to the dataset, but having several replicas of nearly identical shots provides little value for most applications. To analyze this, recognition experiments will be performed using deep-learning models, and the accuracy will be evaluated when images are added into and removed from the dataset. Additionally, images will be clustered, and metrics such as the silhouette distance will be calculated while again adding and removing images from the dataset. This process will highlight images that provide little to no changes in recognition rates and that can reduce the size of the dataset without detrimentally impacting the ability to generate new algorithms and models.

Responsibilities of the research assistant (RA) include finding and/or curating datasets to be used for this study. Through visual analysis and automated tools, the RA will determine a dataset’s suitability for the study. Once the datasets have been selected, the RA will perform recognition/matching experiments using an open-source deep learning algorithm. The RA will have the flexibility to design various hold-out experiments to evaluate the change in accuracy when individual or groups of photos are removed from the dataset.

 

Justin DeBenedetto, Computing Sciences, College of Liberal Arts and Sciences 

Making Natural Language Generation Systems Sound More Natural

Natural language processing (NLP) systems work with human language data for tasks such as automatic machine translation, digital assistants, and more. For many of these systems, one step is producing human language text output. Despite recent advances, we can often tell the difference between machine generated text and human generated text. In this project we investigate these differences for machine generated text. By identifying the differences between machine generated and human generated text, we can make modifications to improve the output of our system.

The specific type of system used in this project is Abstract Meaning Representation (AMR) to text. AMR uses a graph structure to capture the meaning of a sentence. While text is typically written in one dimension (left-to-right in English), we know that words often refer back to words used much earlier in the sentence. By using a graph structure, we can capture these and other dependencies which help the computer better represent the meaning of the text.

The Match student research assistant for this project will gain exposure to various parts of the NLP system pipeline. Their specific responsibilities will include: (1) Comparing computer generated text to human text (2) Formulating a list of testable differences (3) Automating testing of these differences over larger datasets (4) Helping inform changes to the system to improve text generation (5) Writing the results for presentation

 

Michael Robson, Computing Sciences, College of Liberal Arts and Sciences

Analyzing the Performance of a GPU-Accelerated Bioinformatics Machine Learning Application

The fastest supercomputers in the world derive the majority of their computational power from specialized hardware originally used to render computer graphics. Over the past decade these graphics processing units, or GPUs, have become the dominant source of computing performance, due in part to their performance per unit energy. However, a majority of scientific applications still do not leverage their benefits. Our lab is currently developing a GPU accelerated version of the bioinformatics code clustermatch correlation coefficient (CCC). This code utilizes machine learning techniques to identify patterns in biological datasets, and can be used to identify associations in human gene expression data. In this project, we will evaluate the effectiveness of CCC-GPU in comparison to existing single- and multi-threaded CPU versions implemented in C/C++ and Python. To perform our experiments we will utilize departmental resources as well as Villanova's newly installed cluster, Augie. The student will be responsible for conducting repeatable runs of this new application, collecting data, presenting results, and analyzing them in order to draw initial conclusions regarding performance. This work will support the inclusion of GPU kernel in the upcoming release of CCC as well as supporting an upcoming article. Long term, we plan to scale this application up to run on some of the largest computers available on the planet and these preliminary results are crucial to this endeavor.

In this position, the student will be expected to conduct several experiments on the newly implemented GPU version of CCC. This will involve accessing both departmental and university resources, including the Augie cluster. The student will utilize existing test infrastructure to select input data and parameters and record execution times and efficiency numbers for executions of CCC on various platforms. After this data is collected, the student will analyze and summarize these results in both raw and visual form, e.g. tables, charts, and graphs. Together we will work on drawing conclusions about the relative performance of CCC-GPU and possible future directions including new experiments and other areas of study, e.g. energy efficiency or cloud costs.

 

Steven Goldsmith, Geography and the Environment, College of Liberal Arts and Sciences

Delineating the Sources and Environmental Impact of Macroplastic Pollution in Streams

Each year, the world produces over 200 million metric tons of plastics. Through mismanagement, approximately 10% of this amount enters the environment where it can be delivered to waterways via stormwater runoff. Upon entering a riverine environment, plastics can physically and chemically degrade into smaller particles, which can then be ingested by aquatic environments and/or birds. Additionally, these plastic particles can leach harmful metals and organic compounds both during transport and once ingested by organisms. Understanding the types of plastic materials that make their way to waterways, and their potential environmental impact, can better inform conservation and regulatory practices in upstream areas.

For this study, we will both characterize macroplastics (>5mm diameter; e.g. LDPE, HDPE, PE, etc.) found in streams as well as their ability to leach heavy metals, such as cadmium, copper, lead, nickel, and zinc. Characterization of plastics will be determined using Fourier transform infrared spectroscopy. Total metal content of macroplastics will be determined using x-ray fluorescence spectrometry while the bioavailable fraction will be determined using acid digestion and inductively coupled plasma mass spectrometry. Finally, relative differences in the types of plastics found in streams (e.g., water bottles, eating utensils, grocery bags, etc.) will be linked to landcover practices in the upstream areas.

The Match student would be required to meet with the faculty mentor on a weekly basis to discuss all aspects of the project, including reading relevant literature, sample preparation, and analysis techniques. In particular, the student should set aside a 2-3 hour block of time to work with the mentor on the characterization as well as the determination of metal concentrations in macroplastics. It is anticipated that the student would gain more independence with the data analysis techniques over the course of the semester. 

 

Lisa Rodrigues, Geography and the Environment, College of Liberal Arts and Sciences

Building an FTIR Library: Infrared Spectra Analysis of Common Products to Characterize Marine Debris

Marine debris is litter, including plastic, metal, rubber, and glass, that has been intentionally or unintentionally abandoned in the environment. My research is focused on studying the source locations of marine debris and the sites where it is deposited to understand how marine debris moves through tropical ecosystems in southwest Puerto Rico. Marine debris often accumulates in large quantities along coastlines, especially on beaches, where it can become buried, fragmented, and/or degraded by exposure to sunlight and seawater. To characterize or identify the types of marine debris in the environment, one tool we use is Fourier-transform infrared spectroscopy (FTIR) that can identify specific compounds from their unique infrared spectra. However, this technique can be difficult to use and apply when the items we study have been substantially degraded by time spent in the natural environment. To enable better identification of marine debris samples, we are building an FTIR library of common items from single-use products to household items to fishing gear. We will then be able to compare the spectra of the marine debris fragments we find in the environment to the library of spectra we have created. This study will: (1) improve our identification of items discarded in the environment, perhaps to specific brands and/or products; and (2) improve our understanding of the effects of degradation on the spectra of marine debris. Together this knowledge can be applied to determine the residence time of different marine debris in the environment.

My laboratory has an FTIR instrument, and we are accumulating empty containers of common items (personal care products, detergents, single-use plastic bottles, etc.) of different brands to analyze. The next step is to analyze the samples and build a library. The Match student research assistant will learn and assist with the following techniques to assist with this study: (1) prepare the samples; (2) learn how to use the FTIR; (3) analyze samples; and (4) add spectra to a library. The student will work closely with the faculty mentor at each step to learn techniques and protocols. The student will also be encouraged to attend weekly lab group meetings and will have the opportunity to present their findings to our lab group. 

 

Kabindra Shakya, Geography and the Environment, College of Liberal Arts and Sciences

Comparison of air quality instruments for measuring air pollution

Exposure to air pollutants cause several adverse health effects. There are various types of air quality monitors available that range from very low cost to high cost. Low cost air quality monitors have been getting wider use because of its ease of use and its potential to monitor air quality from several locations. It is important to evaluate such monitors to ensure good data quality before being deployed for air quality monitoring. In this project, measurement of several types of air quality monitors ranging from very low cost to high cost will be made to compare differences and evaluate the performance of low cost air quality monitors. The comparisons will be made in laboratory and ambient environments and the effect of weather variables on measurement will also be assessed.

The Match student will work with the mentor to design the experiment. This student will be responsible to operate instruments, download data, and do data analysis. This student will review the literature on the topic, will be familiar on the topic of air pollution measurement, and be familiar with calibration techniques.

 

Scott Dietrich, Physics, College of Liberal Arts and Sciences

Electron Crystals in Graphene

Many people consider electricity flowing like water in a pipe, but this analogy breaks down when electrons interact strongly. This collective behavior of electrons in a material is often greater than the sum of its parts – more is different. Exciting new electronic properties result when electrons interact strongly: they can crystallize, superconduct, coalesce, or more. This project uses microwave radiation to characterize these unconventional electronic states. Understanding this collective behavior could lead to new technology in the areas of energy-efficient electronics, data storage, and even quantum computation.

Graphene – a single layer of carbon atoms arranged into a honeycomb lattice – is the most efficient carrier of electric current yet discovered. It has been the center of 15 years of intense research and industrial interest since its discovery. While its remarkable current-carrying ability promises a major revolution in energy-efficient electronics, this project aims to understand the crystallization of graphene’s electrons that occurs at very low temperatures and high magnetic fields. Just like phases of matter, these electron crystals melt at certain temperatures and often compete with other phases such as liquid or gas. Characterizing the properties of these crystals will allow us to better understand the interaction between electrons and the preference for solid phases to exist.

Measuring the properties of fragile electronic crystals is a difficult task. This project uses a technique called microwave transmission spectroscopy (MWTS) to study electron crystals. Microwave radiation is passed down a waveguide built on top of the graphene layer. When these electromagnetic waves pass near the graphene, some fraction gets absorbed while the rest continues through to a detector. By analyzing what makes it to the detector, we can understand how the electrons are acting at different temperatures and magnetic fields.

All measured structures are built from scratch by the student. This student begins by exfoliating bulk graphite and hexagonal boron nitride crystals to obtain single and few-layer flakes. The thickness and quality of these flakes will be studied using an atomic force microscope (AFM) and then stacked using a dry transfer technique to form heterostructures (layered stacks of different materials). The student will learn about the nanofabrication techniques used to place waveguides on top of these heterostructures using the cleanroom facilities of both Villanova University and the Singh Center for Nanotechnology at the University of Pennsylvania. The student will then work with (and possibly travel to) collaborators at the National High Magnetic Field Laboratory in Tallahassee, FL for experiments at low temperatures and strong magnetic fields.

 

Amber Stuver, Physics, College of Liberal Arts and Sciences

Gravitational Wave Data Quality Investigations for LIGO's Fourth Observing Run

The LIGO (Laser Interferometer Gravitational-Wave Observatory) observatories in Hanford, WA and Livingston, LA are preparing for their next observing run, referred to as O4, seeking small changes in gravity propagating though the universe known as gravitational waves. These gravitational waves are produced by some of the most violent and energetic events in the universe, like black holes or neutron stars colliding. Observing gravitational waves has opened a new way to observe the universe that does not depend on electromagnetic (EM) radiation (i.e. light). These observations provide us with new information about black holes and neutron stars and, when paired with EM observations, give us a more complete picture of the universe than we’ve ever had before. To make detections of gravitational waves, the LIGO observatories must make the smallest length measurements ever made by humans – less than 10,000 times smaller than the diameter of a proton. Besides being sensitive to gravitational waves, the observatories are also extremely sensitive to environmental and instrumental disturbances which produce a constant noise background in the data. Detailed studies of this noise are required to maximize confidence estimates of candidate gravitational wave detections and to improve future data by identifying and mitigating sources of noise.

This project will focus on data quality studies of gravitational wave data and the impact of noise on the search for gravitational waves. The results of this will produce lists of times of confirmed data contamination to be excluded (vetoed) from the search for gravitational waves which will directly improve the resulting confidence of candidate detections.

Research assistants will become members of the international LIGO Scientific Collaboration and work with actively acquired gravitational wave data from their two observatories (in Louisiana and Washington state). Investigations will involve the use of existing analysis tools with the possibility of adapting or developing new tools; assistants will be trained on the use of tools and mentored if any modifications are required. Regular progress reports will be made in research group meetings. The assistant will also be expected to attend regular collaboration meetings as their schedules allow. Presentation of results at professional meetings is also encouraged.

 

Deena Weisberg, Psychological and Brain Sciences, College of Liberal Arts and Sciences

How can fictional stories teach science?

Although the stories presented in books and videos are fictional, they often present information that is true in reality. For example, the Berenstain Bears books are meant to teach children that it’s good to share or that it’s not healthy to eat too much junk food. But do children learn these lessons from these fictional stories? Or do they think that the information presented in the books only applies within the stories, and isn’t relevant to the real world? This is particularly a problem for science information, which can seem strange and fantastical even when it’s real.

To address this issue, this project investigates whether children learn science information from fictional stories and what features of these stories make their learning easier. A current study focuses specifically on anthropomorphism, which is the most common fantastical element in children’s media: How might anthropomorphic characters help or hinder children’s science learning? Gaining a better understanding of children’s interactions with stories can help us to create better educational media and to learn more about how children’s scientific thinking skills develop.

The student will assist the professor and graduate students in all aspects of conducting and running psychological studies on this topic. Duties will primarily include running testing sessions, coding data, reading the scientific literature, and recruiting subjects. Applicants should have completed some coursework in psychology, cognitive science, and/or neuroscience. Previous experience with children is desirable but not required.