Lauryn Holgado, 2023

Lauryn Holgado is an Eckardt Scholar pursuing a dual degree in chemical engineering and chemistry. At Lehigh, Lauryn is a coordinator of the Eco-Representative Leadership Program, a resident assistant, a Lehigh After Dark Ambassador,  as well as a Rossin Junior Fellow, a member of Tau Beta Pi, and a part of the Martindale Program. Additionally, Lauryn has been a teaching assistant for several courses including Mass and Energy Balances, Methods of Analysis in Chemical Engineering, Reactor Design, and Applied Engineering Computer Methods. She extends activism beyond the classroom as a UN Youth Representative for the Nadam Foundation, an NGO in India that advocates for environmental protection and women’s rights. Lauryn has worked as an undergraduate researcher in Dr. Angela Brown’s lab, developing new techniques to fight antibiotic resistance. Following this, Lauryn was awarded a DAAD Rise scholarship in the summer of 2022 where she interned in Freiberg, Germany. She studied the oxidation of methane and formaldehyde using iron oxide catalysts. Currently, Lauryn is an undergraduate researcher in the lab of Professor Srinivas Rangarajan where she investigates the oxidative coupling of methane. She plans to pursue a Ph.D. in chemical engineering and research sustainable technologies and energies.
During this project, she studied the oxidative coupling of methane (OCM), where methane reacts to produce hydrocarbons like ethane, ethylene, and propane. Natural gas is the cleanest fossil fuel and is an abundant source of methane. OCM is a direct route to transform natural gas into more valuable products. This low-carbon alternative is essential for the end goal of a zero-carbon footprint. In this computational lab, Lauryn uses the open-source code Mesoflow to model the OCM reaction mechanism. The reaction mechanism involves both surface and gas phase reactions, so it is important to take into account the interaction between both the catalytic and gas phase steps. Eventually, this model will be compared to experimental data. This research encompasses both coding skills and chemical engineering knowledge.
Meghan O'Brien, 2023

I’m a rising junior in Chemical and Biomolecular Engineering and I’m also a member of the Women’s Basketball team. I’m interested in renewable energy and material sciences and I had my first experiential opportunity this summer working on Organic Field-Effect Transistors(OFETs). I’m undecided on the path I want to pursue after college and I’m exploring the potential opportunities. I’ve gained an understanding of the work experience and responsibilities, as well as gained an appreciation for the research process that comes with graduate school. I’ve enjoyed the process of applying knowledge, testing hypotheses, and analyzing results. Through my summer research role, I’m grateful for the variety of skills including lab techniques, problem-solving, and interpreting data which are beneficial and relevant for every potential career. In the future, I hope to find a role where I can envision, design, and execute experiments that lead to impactful and valuable contributions to the world.
This summer I worked within the lab of Professor Elsa Reichmanis, assisting PhD student Myeongyeon Lee in his research on Organic Field-Effect Transistors (OFETs). OFETs are made of conjugated polymers that act as semiconductors that have the advantage of low cost, high availability, low energy processing, and mechanical flexibility. These materials have broad potential applicability in flexible electronics. The OFETs are thin films with a channel coated with the conjugated polymer where the charge flows from the source to the drain electrode. The lab work to prepare OFETs includes a multiple-step process of cleaning, pre-treating, coating, and annealing prior to measuring the performance of the devices. The measurements provide data on the charge transport properties including the mobility, current on/off ratio, and the threshold voltage. During my time with the team, we conducted experiments that tested the effect of concentration, aging, and blending solutions on these charge transport properties. This opportunity has shown me that experimentation at this level requires precision in all processes as well as consistent review and analysis of data.
Teja Orchid Patrice, 2023

I am a Junior at Lehigh University majoring in Chemical Engineering. My interest in environmental health and sustainability was influenced by my upbringing on the island of Grenada where I obtained my associate degree in Natural Sciences. After this, I spent the next year as a math and science secondary school teacher, before attending Lehigh University. I am a recipient of the Summer '23 Alumni Experiential Learning Award, which allowed me to engage in research related to electrochemical practices and the improvement of energy generation and storage systems. This opportunity has allowed me to further my knowledge of the possibilities for improvements within the energy industry and granted me invaluable experience as I consider a career in research upon graduation.
Energy production dependent on fossil fuels brings two major issues, climate change and energy crisis, on the environment and the economy. To combat this, there is growing interest in renewable energy which has led to increased research to satisfy the global energy demand. New and more efficient methods of energy generation and storage are needed. One solution is the use and study of electrochemical systems, such as batteries and supercapacitors, which can store electrical energy through chemical reactions. A supercapacitor is an electrochemical device that stores more energy than the capacitor and can accept and deliver charge faster than batteries. It acts as a link between a capacitor and fuel cells/batteries. My project focused on research into making transition metal molybdates that can be used as supercapacitor electrodes. Nickel Molybdate (NiMoO4) is known for its high capacitance, but low rate capability, and Cobalt Molybdate (CoMoO4) has a lower capacitance but has a good rate capability. By combining these two materials, it is hoped to synthesize a composite material that has the advantages of both materials and overall good performance.
Chiwon Yu, 2023

I am from South Korea. I started my career by taking ESL classes in the United States and graduated from Northampton Community College with a Chemistry
Associate degree. I still did not decide what industry I want to contribute to in my life. Chemical Engineering is so broad that it is difficult for me to pick a specific career. I am thinking about process engineering, but not quite sure what field I want to work in. Therefore, this summer program was helpful and meaningful for me to think about my future career. In my project, I needed to redesign various chemical engineering experiments, and this gave me brief ideas of what I can do as a chemical engineer. Even if I still do not decide what I sincerely want to do, I will study hard and participate in various opportunities and activities to find out what I want to do.
In the summer project, I worked with another chemical engineering student, Shane Haycock, and ChBE technicians, Cody Turner and Paul Bader, under Professor Joseph Menicucci. My goal was to redesign the lab experiments for Freshman and Senior courses. Professor gave us ideas of what kind of experiments he wanted to set up, and I needed to research what experiments we can conduct in our laboratory. For example, Professor said he wants to set up the polymer synthesis experiments for Seniors at the first meeting. Then, I started researching what polymer is, how we can synthesize specific polymers, what chemicals and apparatus we need for synthesis, etc. The polymers for our experiments were Polymethyl Methacrylate (PMMA) and Acrylamide based stretchable hydrogel. After the meeting, I wrote down the procedures, checked the hazards of chemicals, and researched the measurable properties of polymers. Next, we run the experiment based on the procedure and checked if there is any problems while doing the experiment. I and another student also set up Algae cultivation to extract Lutein, polymer synthesis, and production of biodiesel with flow chemistry for senior experiments. Also, we redesigned the experiments of coffee and spectrophotometer, PI control to keep the constant water level in the tank, ping-pong ball launcher using fuel cells, and distillation with color differences. We finished most of the Freshman experiments and will keep doing them to finish the others that we did not finish yet in the fall.
Sebastian Zelaya, 2023

I am a rising senior actively engaged in research under the mentorship of ChBE Professor Kelly Schultz. This research opportunity not only serves as an academic pursuit but also as a stepping stone towards a promising and impactful professional journey ahead.

During this summer, my research focused on utilizing bulk rheology and multi-particle tracking techniques to gain comprehensive insights into the mechanical and dynamic properties of hydrogels. By subjecting hydrogel samples to controlled deformations through bulk rheology experiments, I aim to analyze how varying degrees of cross-linking impact their viscoelastic behavior, helping to establish a correlation between cross-link density and mechanical response. Furthermore, employing multi-particle tracking methods enables me to delve into the microscopic dynamics of these materials, observing the individual movements of particles within the hydrogel network and elucidating how cross-linking influences their diffusion and mobility. This interdisciplinary approach not only contributes to the fundamental understanding of hydrogel mechanics at both macroscopic and microscopic scales but also holds potential implications for designing advanced biomaterials with tailored properties for applications ranging from drug delivery to tissue engineering.

Matthew Zhang, 2023

I'm from Guam, a beautiful tropical island that rests in the Pacific Ocean near the Mariana Trench. I enjoy culinary adventures in my free time, partly because of the indulgence in creating something that people find amazing. For the same sentiment, I want to advance further in education as a chemical engineer after my undergraduate time. Although I haven’t decided on an area of interest, I planned to utilize research opportunities to explore the diversity of my major and its interdisciplinary applications. Along the way, I’m hoping to gain skills and experience in different fields that would prepare me for the future and determine what I want to do.

Within the lab of Professor Mayuresh Kothare, I studied the novel design of a medical oxygen generator for patients through simulations in gPROMS, a software provided by Siemen for the digital design of complex models and processes. The device model is configured to generate medical-grade oxygen (~90% purity) from the air (79% Nitrogen and 21% Oxygen) through a cyclic process of separating oxygen as a product from nitrogen. The separation proceeds in four stages: pressurization, adsorption, depressurization, and purge. During pressurization, a feed of air flows and builds pressure into a column packed with zeolite pellets, a material that acts as a sieve to separate oxygen and nitrogen. The pressure build-up holds back nitrogen on the surface of the zeolite (Adsorption), while oxygen remains in free flow and is transferred to a storage tank. Nitrogen is then released into the atmosphere from the column (Depressurization). Lastly, to clean the possibly remaining nitrogen, a small amount of oxygen is used from the storage tank to “blow” the nitrogen off into the atmosphere (Purge), preceding the next repeat of the separation cycle. The entirety uses a single column of zeolite in comparison to the conventional industrial design of a double column. I was able to implement gPROMS in collaboration with Siemen to set up and run the model in a successful simulation. I studied the relationship between the model variables, for example, the combination of time length for each separation stage. Furthermore, I attempted to optimize them to reproduce data imitating patterns of past research, which are taken from analysis performed on real equipment set-up. With enough insight from simulations, we are hoping to develop a predictive control algorithm to optimize the operation of the medical oxygen generator.
Shengping Huang, 2022

Plastic (polyethylene) has been overly produced and used worldwide because of its resilient and lightweight properties. Human lives have become more convenient because of the usage of plastic. However, the large amounts of plastic waste left are starting to cause problems. Until now, over 7.4 billion metric tons of plastics are in the earth’s system. Less than 10% of plastics are recycled worldwide because making new plastic costs less than recycling plastic waste. It is important to recycle or upcycle plastic. One of the methods to depolymerize polyethylene is an organic reaction called olefin cross-metathesis. With sacrificial alkane (pentane in our case) added, olefin cross-metathesis can break down longer polyethylene into a distribution of shorter alkanes. In our research, we want to learn about the most plausible reaction pathways to break down polyethylene and their thermodynamics. However, the reaction networks could be extremely complicated. To help us solve this problem, machine learning and cheminformatics are utilized. For example, RING (Rule Input Network Generator) is used to generate all the possible reaction networks. RDkit, the cheminformatics, is used to generate possible conformers of each molecule. ANI-1, a neural network, is used to calculate the potential energy of each molecule. We have a workflow from generating the reaction network to determining which pathways are the most plausible by their thermodynamics. In the future, we are going to try analyzing other reactants other than plastic, for example, rubber. Also, we want to try to analyze the effect of adding functional groups to polyethylene using metathesis.

David Kramer, 2022

My research, which was conducted in the lab of ChBE Professor James Gilchrist, and under the guidance of Dr. Samuel Wilson-Whitford, investigated the physics of Janus particles. Janus particles are small (>1mm), and they are special because one or both hemispheres of the particle is functionalized- or manufactured in a way to provide different physical properties on either side. Our particles are functionalized on one side using iron, which essentially made the particles behave like little magnets. Therefore, we can manipulate the particles using exterior magnetic fields. The specific topic I was researching related to Janus particles was how they can be utilized to enhance transport through a porous medium (like soil). To test these properties, I created samples in which the substrate was gel beads. The particles were “rolled” through the sample via a wheel with four bar magnets attached to it, which was suspended above the sample. Our apparatus applied a torque to each Janus particle within the sample, causing them to move, when ordinarily, they would remain stationary. We were able to prove that this indeed is an effective method of enhancing transport in porous systems- and this type of research has implications in various fields, such as in medicine- where “microrollers” are already studied as a method of medicine delivery, environmental applications, like cleaning up hazardous waste spills, and even in reactor/catalyst design. "This research was incredibly rewarding, as I could immediately see the effects of any manipulations to the system and I gained invaluable experience" says Kramer. "Doing this research gave me direction."

Megan Stratton, 2022

Chronic skin wounds are a major healthcare issue that have increased the need for treatment methods to be developed and implemented into clinical care. Stem cell therapy has proven to be a valuable treatment option due to their ability to differentiate into other types of cells, aiding in recovery of damaged tissues. To be inserted within the body, they need to be manually deactivated and inserted within a hydrogel, compatible with the composition of the human body. In wound healing, pro-inflammatory and anti-inflammatory cytokines are naturally released to help direct and regulate stem cell motility. Within the lab of ChBE Professor Kelly Schultz, I aided in measuring cell-material interactions in synthetic hydrogels, as well as determining the change of human mesenchymal stem cell (hMSC) motility and pericellular degradation when cytokines appear within wound environments. The design of existing hydrogel scaffolds targets the direct tissue which needs repair but fails to account for the environment surrounding it. My work focused on assessing the effectiveness of varied hydrogel components through creation of a cell gradient. Through the creation of a 3D printed microfluidic chamber, I measured the ability of fluorescent dye to diffuse through hydrogel, which will create a gradient that impacts cell movement. I also assisted with cell tracking through multiple particle tracking (MPT), which is a technique that takes the mean squared displacement of embedded probe particles as they move within cells overtime, helping to characterize changes in a cell's microenvironment. Through MATLAB and Igor software in the MPT process, I was able to generate a value which determined the state of the gel that the cells were contained in.

Samuel Argo, 2021

This summer, I worked in lab of ChBE Professor Angela Brown on a project that dealt with a single mechanism of antibiotic resistance: reduction of intake of antibiotic molecules. Gram-negative bacteria, which are often associated with antibiotic resistance, have an outer membrane which acts as a barrier for the types of nutrients and substrates that are allowed into the cell. Proteins called porins allow for the influx of these molecules, but bacterial cells can modify them to exclude antibiotics specifically, which reduces the effect that the therapeutic will have on the cell. To overcome this issue, our approach was to load bacterial outer membrane vesicles (OMVs) with antibiotics in order to deliver them in a controlled fashion by vesicle fusion; though, this approach had some intrinsic problems because of the biological nature of the OMVs. We supplemented our delivery OMVs by hybridizing them with synthetic liposomes and cholesterol to improve their stability and fusion capabilities and determined that the synthetic liposome-OMVs (L-OMVs) were more effective at delivering antibiotics than OMVs alone. This year, as my senior thesis, I will investigate the effects of lipid charge on L-OMV-bacteria fusion. 

Rani Baidoun, 2021

Over the past summer, I have worked with a PhD student at Lehigh University with the main focus of achieving an efficient and effective targeted drug delivery. This was done using liposomes which are laboratory created spherical vesicle which encapsulates the antibiotic and releases it only when a certain toxin triggers the release. In the future, I hope to expand upon this theory and add pump inhibitors within the liposomes in order to increase the antibiotic efficiency and eliminate one of the drug resistance techniques utilized by Pseudomonas Aeruginosa.

Nicole Rawiszer, 2021

The project that I worked on has the goal of producing cultured meat in the laboratory. This includes engineering a whole cut of meat that has both the texture and taste which allows for their broad adoption. My specific role on the project included beginning the tissue engineering strategy of creating a hybrid hydrogel scaffold that will be used to encourage satellite cells to differentiate into skeletal muscle fibers. The project also continues to develop strategies to efficiently deliver oxygen and glucose to these cells to aid in their growth, as well as mimicking the nervous system to aid in fiber growth.

Jacob Thompson, 2021

This summer, my research consisted of one main project, with the primary goal of learning new and improved methods to simulate proteins. This project lies at the intersection of biophysics and computer science, and I worked in collaboration with another research team from UC Berkeley. The premise of the project revolved around a computer science concept of Machine Learning, where one can use data to train what is called a neural network. For our purposes, we provided the neural network with different data about the amino acid sequence and chain length of various proteins, with the goal that the neural network could train itself to take in that information and use it to predict physical properties of the proteins, such as its radius of gyration. By perfecting our training technique, these neural networks could hopefully be used to predict and model increasingly complicated proteins, allowing us to understand their conformations and simulate them with better success in the future.