LSU College of Engineering High School Summer Research Program

HSSR Program

High School Summer Research Program

About

As part of its strategic plan, mission, and vision, the LSU College of Engineering is dedicated to developing students into the next generation of transformative problem solvers for the local region, the state, and beyond. The High School Summer Research (HSSR) Program is an outreach initiative aimed at engaging high-achieving high school students in real research in the fields of engineering, computer science, and construction management. HSSR interns have opportunities to learn from faculty research groups and understand how they work, what inspires them, and how to continue in fields related to engineering in college and beyond.

In addition to their work on a research team/project, HSSR interns also attend workshops that include trainings on safety, research best practices, ethics in research, and communication. The program culminates in a poster presentation for students to present their research projects, which is mandatory for the completion of the internship.

Program Goals

  • To give high-achieving, highly motivated, and hard-working local high school students meaningful experiences in engineering, computer science, and construction management research during summer.
  • To develop students’ curiosity, research methods, and intellectual abilities before they have completed high school or made decisions about which college to attend and what bachelor’s degree to pursue.
  • To develop students’ abilities to communicate technical content using both written and oral modes of communication.
  • To teach students about the engineering design process and how it can be applied to both fundamental and applied research.
  • To introduce these students to the opportunities available at the LSU College of Engineering and showcase the impressive faculty and research available to them at the state flagship university.
  • To support faculty in their research projects and outreach efforts.

Information Sessions

Three information sessions will be held:

  • October 12, 2021 at 6 pm (in-person)
  • November 2, 2021 at 6 pm (in-person and Zoom)
  • November 30, 2021 at 6 pm (in-person)

Registration is required to attend an information session. Meeting details will be provided via email after registration.

Register for an Information Session

Program Details

Students selected as HSSR interns are matched with a College of Engineering faculty member's research team. They will receive guidance from the professor, as well as graduate-student and undergraduate-student mentors, as they work on a project related to the research team's ongoing research. Here are examples of past research projects and an article about a student/project from summer 2020.

HSSR Interns will not be paid for their work.

HSSR Interns will be held accountable for their work responsibilities by the College of Engineering and will be expected to compete in regional science fair competitions. The program will provide information and training regarding science fair participation.

HSSR Interns will have to complete detailed safety paperwork and training through the course of the spring 2022 semester in order to begin work on a project in summer 2022 and beyond.

HSSR Interns will be required to work about 15-20 hours per week during summer 2022 for a total of about 120-140 hours. Weekly schedules can be flexible depending on summer travel/activity schedules, however students should not miss more than 4 working days.

The HSSR Intern application and selection process will be highly competitive due to high interest and a limited number of available positions.

Apply

Application Deadline: TBA

The LSU College of Engineering is seeking qualified local high school students to apply for a limited number of High School Summer Research (HSSR) Intern positions available in summer 2022. Please see the program details and eligibility before applying. If you have questions about eligibility and program details, please contact Raynesha Ducksworth at rudcksworth@lsu.edu.

To be eligible for this program, you must:

  • Be at least 15 years of age.
  • Be currently enrolled as a 9th, 10th, or 11th grader.
  • Have a 3.5 (or equivalent) high school GPA (as listed on a current high school transcript).
  • Complete and submit this application by end of day (Date TBA).

To apply for this program, you must:

Applications must be completed and received by end of day (Date TBA).

Current Projects

Project Title Abstract Program Student and Mentor
Optimization of Cell-Free Protein Synthesis Cell-Free Protein Synthesis (CFPS) is a high throughput technique used to synthesize proteins without using live cells. Instead, CFPS reactions utilize cell extracts (a solution of cell machinery created by destroying the membrane of a cell) along with other components, such as salts and cofactors, to synthesize proteins from a genetic template of choice. CFPS is widely applicable and assists in protein manufacturing, microbiology, and microbiological engineering. CFPS, however, is limited by its inability to mirror a living cell and requires more resources to match the production rate of in-vitro protein synthesis. This study aims to find the optimal conditions required to maximize Cell-Free Systems' protein production. To accomplish this, we tested the effects of the crowding agents PEG-8000 and Ficoll-400 (two crowding agents that have been proven to increase protein production in Cell-Free Systems using wheat germ and E. coli.) on various Cell-Free Systems made with extracts of BL21 DE3* (a genetically modified strain of E. coli. that is optimized for protein production). Additionally, we varied the Optical Density (O.D.) at which E. coli cells were harvested and lysed to make cell extracts; this resulted in a different amount of cell machinery in each extract. To measure our results, we synthesized Super Folder Green Fluorescent Protein (SFGFP) in our Cell-Free Systems and measured the fluorescent intensity of the Systems after one day of incubation. In the earlier stages of our studies, both crowding agents seemed to have irregular effects on protein production. Fortunately, more recent experiments showed that Cell-Free Systems created with cells harvested at 5.0 O.D. could yield the highest amount of SFGFP out of all our other test samples when composed of 2% PEG-8000; Cell-Free Systems created with cells harvested at 3.0 O.D. could yield a similar amount of SFGFP when composed of 2% Ficoll-400. In the future, we plan to vary Cell-Free Systems' pH value to see how it affects protein production. In fact, as of now, we have begun experimenting with Cell-Free Systems containing Ficoll-400 by varying the Systems' pH value with the HEPES buffer before incubating them. Biological Engineering Samuel X. Adjei, Parker Hannan, Yongchan Kwon
Evaluation of Staining Method for Analysis of Cortical Bone Geometry Cortical bone geometry is a critical factor in bone’s strength and improving its analysis will help to further bone research. Geometry influenced phenomena like fracture failure can be tested and evaluated to determine information about the host of the bone, as well as information that can be later used in the continued sustenance of the host. Current research into how a bone fractures within its layers under wedge indentation serves as a testbed for development of better methods of bone characterization with quality images and analysis. This work was focused on optimizing the bone dye procedure for optical characterization of bovine bone microstructures with methylene blue, Alcian blue, and black ink. Various methods of dye application were tested including dropping, submersing, and smearing in combination with other factors such as time and addition of acetone (for the removal of excess dye on the surface of the bone). Further efforts to improve image quality were introduced through changing the brightness and color temperature of the surrounding lighting during the scientific photography. Other dyes including black ink were similarly tested and evaluated. It was found that for our purposes black ink is better than alcian blue since it characterizes microstructures similarly but does not leave behind large amounts of color on the surface. It was generally found that methylene blue when smeared twice, with acetone applied in between, better characterized microstructures when compared to black ink. Work was then performed into the quantitative analysis of cortical bone images taken after dyeing. This information can later be used in assessing the mechanical performance and other characteristics of the cortical bone sample when fractured through wedge indentation. Biological Engineering, Civil and Environmental Engineering Akshay Basireddy, Simone Muir, Beatriz Garcia, Alexander Lee, Kevin Hoffseth
3D-Printed Co-Culture Platform to Study Bacteria-Induced Chemotherapeutic Resistance in Breast Cancer Previous research has demonstrated the importance of the microbiome in cancer progression and metastasis. The majority of this research has been focused on the role of the gut microbiome; however, recent studies have identified a role for the breast tumor-resident microbiota in metastatic colonization and drug resistance. Unfortunately, there is an incomplete fundamental understanding on which bacterial species exhibit pro- versus anti-cancer behavior due to limited experimental techniques. While mouse models have been helpful in studying this emerging field, there is a need to develop novel co-culture strategies to elucidate how specific strains of bacteria drives drug resistance in breast cancer. The goal of this project is to optimize an experimental strategy to co-culture cancer cells and bacteria using three-dimensionally (3D) printed device previously used to co-culture mammalian cells. The device functions similar to a Transwell assay to physical separate, yet chemically connect, two different cell types. The 3D printed insert was designed to fit into a standard 6-well plate and houses an agarose slab to culture bacteria in the upper chamber and cancer cells in the bottom of the 6-well plate. To demonstrate the feasibility of the device, we co-cultured pro-cancer bacteria (E. coli) and estrogen receptor positive (ER+) breast cancer cells (MCF-7). . The device was thoroughly sterilized, lined with 2 mL of 3 wt% agarose, and is then placed in the 6-well plate pre-filled with Luria-Bertani broth (LB broth) on the bottom. The stock E. coli was diluted to OD650 = 0.001 and then added on top of the agarose as well as more LB broth which is added so that the agarose does not dry out. The 6-well plates containing the inserts were cultured at 37°C to induce bacterial growth. Several optimization steps were performed to prevent contamination of the lower chamber with the E. coli including altering seeding density, changing broth volumes, and altering the dimensions of the insert. Once there were some successes and the bacteria did not contaminate the LB broth at the bottom, the cancer cells were introduced. We attempted two approaches: (1) separately culturing E. coli and cancer cells for 24 h prior to co-culture or (2) directly co-culture E. coli and cancer cells in the 6-well plate. The first approach yielded some success; however, substantial contamination of the cancer cell chamber was observed due to transfer related issues. The second approach yielded far greater success with contamination-free co-culture of MCF-7 cells and E. coli. These results demonstrated the feasibility of the approach and demonstrated a novel approach at co-culture of tumor-resident bacteria and cancer cells laying the foundation for future studies introducing different strains of pro-cancer bacteria and other types of cancer. Chemical Engineering Rocio Larenas Bustos, Stephanie Price, Emmaline Miller, and Adam T. Melvin
Solute Movement in Surface Water With Different Stream and River Geometries As stream restoration projects become more frequent for a variety of reasons, in stream structures are also becoming more common. One reason for the increase in restoration projects is the goal to restore the marshes eroded by salt water. It is known that human interference has made big impacts on ecosystems, especially in Louisiana, where our coastal lands are diminishing. There is also the problem of pollution in our rivers - dissolved nutrients, chemicals, waste products – that can harm the public health and organisms that live in stream habitats. This study investigates how solutes move in stream settings with different structures. Weirs and fake vegetation in a controlled flume setting were used to replicate channel spanning and stream changing structures such as boulder weirs, trees, and logs. A conservative tracer (NaCl + red dye) was injected at a constant rate to study the effect of the in-stream structures on surface water solute transport. Conductivity meters were used to measure the specific electrical conductivity of the water at three constant locations along the flume. This study recorded both quantitative and qualitative data, the former being the conductivity measured with the probes, and the latter being visual observations of the red dye moving throughout. The data from the conductivity meters were used to determine the dispersion coefficients and to create dispersion curves. The change in conductivity for each probe in the straight flume setting (E1) had a steeper average slope than the change in conductivity for each probe in the flume with 9 alternating weirs setting (E2). This shows more dispersion in E2 which is expected, since the weirs cause the solute to take longer to pass through the flume, allowing more time for it to spread. The increased time for the solute to pass through also indicates that the presence of in stream structures can increase transient storage zone and the exchange with transient storage zones. This information can be used in the future to create computer models studying how solutes flow through rivers in different stream types. Civil and Environmental Engineering Emily Chen, Clint Willson
Keystroke Privacy Leakage From Zoom Meetings Acoustic from the keystrokes of keyboards represent a potential and problematic privacy issue for the future. Past studies have shown the possibility that an attacker could potentially steal a user's information from the sound of their keys. However, the results have not shown the best practicability for real world settings. Our goal for this project is being able to determine the difference in keys so we can know for certain that it is possible for someone to steal information based on keystroke. Finding this information can help provide more awareness on the problem and help scientists to begin to find ways to stop this issue without just muting. During our analizations, we used the same keyboard (MackBook Air) since this project is to first determine if it is possible with a high accuracy. Furthermore, we used the same finger (pointer finger) because the finger you use doesn’t affect the sound. However, we still want to be as accurate and efficient as possible. We also pressed each key 20 times and a variable of 5 seconds per keystroke. This way, we will have a good amount of times the keys were pressed, along with the keys not being pressed too close together. This will help to make the analysis as accurate as possible. Furthermore, we had minimal background noise to prevent variations in the sound being pressed. For this project, we studied the keyboard acoustics first to further prove the possibility that an attacker can differentiate the sounds. We did the use of Matlab and the implementation of keystroke segmentation and features. We also studied the accuracy of these different features and keystrokes. Furthermore, we studied how adding more keys will affect the overall accuracy of the keystroke segmentation. Finally, after analyzing these, we can know for certain if someone can steal a person’s information from the sound of keystroke emanations. Computer Science Collin Clement, Long Huang, Chen Wang
Artificial-Intelligence-Aided Laryngeal Cancer Identification  Laryngeal cancer is much easier to treat the earlier it is diagnosed. If it is caught in the early stages, treatment may be less intense, and the cost of treatment tends to decrease. The survival rate of the patient also increases the earlier the cancer is identified. However, an issue is that the diagnosis of laryngeal cancer requires a biopsy. Results from a biopsy can take a time and require taking cells directly from the patient through invasive procedures. This can become problematic when a patient puts wait for biopsy results before being able to being treatment and is needed as soon as possible. This project is part of advancing the use of Raman Spectroscopy and machine learning to identify cancer cells without the need for a biopsy. Earlier diagnosis means less intense treatments and higher chance of surviving. In this project, we started by retrieving the Raman spectra of 200 samples (100 cancerous spectra and 100 non-cancerous spectra) collected in a previous project from cancerous larynx cases. Using Raman spectroscopy provided a Raman fingerprint region unique to each sample. This identification of each sample was used as data input for machine learning. Then, using a random forest model in python, the data was classified as either normal or tumor. 80% of the data was used as training data for the model while the other 20% was used for testing and for measuring accuracy. The model preformed very well with 97.5% classification accuracy overall. Finding ways to increase the accuracy of the model could be researched in a future project by increasing amount of training data given to the model or by using other machine learning models, such as logistics regression. The project shows that Raman spectroscopy working with machine learning models like random forest could very well lead to quicker and less invasive diagnosis of laryngeal or other kinds of cancer.  Electrical Engineering Mariana Cuadra, Zheng Li, Huaizhi Wang, Jian Xu
3D-Printed Soil Bricks Inspired By Mud Dauber Nest The overall goal of this project is to create more sustainable adobe bricks using the method that mud dauber wasp use to construct their nest. A previous researcg showed mud dauber nests have high density and strength. This was able to be determined through trends confirmed from measurements of physical and mechanical properties of mud dabuber nest for over 100 mud dauber nests including penetration resistance, dry density, and moisture and organic contents. A statistical analysis on the data of the physical and mechanical properties was performed to ensure that the nests have consistency across all of their properties. The statistical analysis showed a consistency in density and strength throughout multiple nest samples, confirming the mud dauber’s construction technique is asufficient inspiration to create soil bricks. A 3D printer was used to simulate the mud dauber’s technique and print the soil similar to the wasp. The ultimate goal of using the 3D Printer is to create a soil layer with little to no surface defects,constant soil dimension and only 10% difference of size difference between the before and after drying process. Printing was done with various moisture contents to find optimal moisture content to get the intended goal. Once the optimum moisture content is found, more layers will be added to design soil bricks. Strength tests will be performed to check that the bricks are strong enough to be used for civil structures. Civil and Environmental Engineering Josephine Day, Joon S Park, Hai Lin
Single Cell Analysis of Deubiquitinating Enzyme (DUB) Activity Using a Droplet Microfluidic Trapping Array Cancer is a heterogeneous disease with numerous genetic mutations resulting in unchecked cellular growth. Recent studies have found that drugs specifically targeting the ubiquitin-proteasome system (UPS) have resulted in higher median patient survival rates. This project focuses on two members of the UPS, deubiquitinating enzymes (DUBs) and the proteasome, which regulate protein degradation. DUBs and the proteasome have been shown to be upregulated in several cancers and have emerged as promising therapeutic targets. One challenge in DUB- and proteasome-based therapeutics is the personalized nature of cancer with different patients responding differently to drugs due to variations in enzyme activity. The goal of this work was to perform dynamic single cell analysis on DUB and proteasome activity in a model cancer cell line to provide new insight into distinct subpopulations with enhanced or diminished enzyme activity. This was accomplished using novel, peptide-based, cell-permeable biosensors specifically targeting DUBs or the proteasome. Each peptide consists of a cell-penetrating peptide conjugated to a four amino acid recognition sequence, and a fluorescent marker. The fluorophore is cleaved off by the enzyme after it is recognized, which results in a fluorescent signal whose intensity can be directly correlated to enzyme activity in the cell using fluorescence microscopy. These peptides are combined with droplet microfluidic trapping arrays to study enzyme activity at the single cell level in OPM.2 cells, a model multiple myeloma cell line which has been shown to exhibit enhanced DUB and proteasome activity. Microfluidic experiments using this approach were performed at concentrations (100 and 200 μM) of the DUB reporter showing a heterogeneous response. Additionally, we performed proof-of-concept experiments on a new peptide-based reporter targeting the proteasome. The peptide was characterized in bulk lysates using fluorometry and in live, intact cell studies using fluorescence microscopy. We found proteasome activity increased with time and was also highly heterogeneous across a population of cells. The long term goal of the work is to couple the proteasome reporter with the DUB reporter for multiplex, simultaneous study of DUB and proteasome activity on a single population of cells at the single cell level. This will provide an insight into how the different aspects of the UPS interact during cancer treatment. Understanding variances in cancer cell activity, especially intratumorally, will be crucial to developing the next generation of targeted therapeutics. Chemical Engineering Veda Devireddy, Alireza Rahnama, Adam Melvin
Accelerating Reinforcement Learning Reinforcement learning is a type of machine learning that is based on the human reward system. It is on the forefront of AI development. However, it has few real world applications. Most reinforcement learning applications have been bound to simulated environments because of sampling inefficiency caused by model-free algorithms. A solution to this would be to parallelize training. By using multiple rollout workers in parallel to collect more data, a diverse range of actions can be explored quickly. The increase in exploration can allow a reinforcement learning model to find the optimal solution more rapidly. Parallelizing training can increase sampling-efficiency and reduce overall training time significantly. We can evaluate the effect of parallelization by testing it on a game called CartPole. The game involves a pole attached to a joint on a cart. The goal of the game is to balance the pole. The longer the pole stays balanced, the more reward is given. We will study the PPO, DQN, A3C, and IMPALA algorithms which are among the most used reinforcement learning algorithms. The algorithms will optimize the policy to keep the game going for as long as possible. After studying the results, we have concluded that more workers are able to generate faster exploration which allows the model to converge upon an optimal policy. When tested on a greater maximum reward such as 500, the difference becomes much more apparent. Reinforcement learning can be very beneficial to human society if it becomes more applicable in the real world. Computer Science Ryan Ding, Hao Wang
The Role of the Genus Azospira in Transforming Arsenic-Containing Compounds Groundwater resources in Louisiana, elsewhere in the United States, and several locations abroad, especially in the South Asian country of Bangladesh, are contaminated with naturally occurring arsenic. On account of dissolution of naturally occurring minerals found in subsurface aquifers, groundwater is often contaminated with arsenic in the chemical form of arsenate (AsO43-). Some bacterial species are able to reduce arsenate (oxidation state +5) to arsenite (oxidation state +3), which poses a problem because arsenic in the +3 valence state of arsenite is much more toxic to humans. Research described in this presentation was conducted to evaluate the ability of the type strains of three bacterial species from the genus Azospira (A. inquinata, A. oryzae, and A. restricta) to grow in the presence of arsenate and reduce the compound to arsenite. The research was motivated by the recent finding that the genome sequences from all three bacterial species currently assigned to the genus Azospira contain genes annotated as encoding arsenate reductase, an enzyme responsible for transforming arsenate into arsenite. Objectives of this project were to determine if the bacterial species are able to grow in the presence of arsenate and if they are able to reduce arsenate to arsenite when grown under controlled laboratory conditions. Ultimately, the goal of the research was to assess the role (if any) that species from the genus Azospira may play in arsenate transformation. Each of the bacterial strains were inoculated into media with and without arsenate. Growth was measured spectrophotometrically at 600 nm (A600). Concentrations of arsenate were determined using ion chromatography. All three Azospira type strains grew (increased in A600>0.05) when incubated in anoxic VL70 medium supplemented with nitrate (NO3-) but lacking arsenate. Parallel cultures grown in the same medium but with addition of 1 mM arsenate (supplied in the form of disodium hydrogen arsenate heptahydrate, Na2HAsO4·7H2O) also grew though the amount of arsenate did not decrease. This indicates that the redetection of arsenate did not occur. Further experiments with other mediums, concentrations, and conditions will point to more definite conclusions. Civil and Environmental Engineering Andi Hayes, Kali Martin, Bill Moe

Designing RNA Gene Circuits
With Coherent Feedforward Loops

A genetic circuit is a network of genetic components that regulates gene expression. Gene circuits hold great potential for disease treatment, cleaner energy, and advanced biocomputing. Antithetic gene controllers are known to provide perfect reference tracking but have compromised transient dynamics. In this study a biological motif, known as a coherent feedforward loop, is implemented in the effort to improve the performance of a base controller and provide improved transient dynamics. A coherent feedforward loop (CFFL) is comprised of two coherent regulation pathways. In order to observe the circuits, we take a model-based approach that implements the conversion of the controllers into ordinary differential equations. Within each model, the inducer concentration, transcription rate, sequestration rate, degradation rate, and repression rate are held by variables with constant values. The performance of the base model is tested and compared with the performance of a version of the base model including the CFFL in different locations. Each model is then also run under a sensitivity analysis in order to better understand the effects of each parameter on the performance of the design. Lastly, negative feedback was added to each of the designs. These were compared to the performance of the other models and was subjected to the same sensitivity analysis to better understand model dynamics.  Chemical Engineering Benjamin Hogg, Xun Tang

Demonstrating UAV Propulsion Using an Aircraft and Flight Model With Hardware in Loop Approach

Unmanned aerial vehicles (UAVs) are commonly used in scientific research, mapping, and commercial and public uses. Additionally, UAVs are becoming an important element in the military sector. Most of the military UAVs are either electric, such as the RQ-11 Ravens, or fuel powered, such as the MQ-1C Gray Eagle. However, both power systems have their drawbacks. Fossil fuels have a much higher energy density than batteries, but fuel engines produce loud noises, making fuel-powered UAVs unsuitable for reconnaissance. On the other hand, electric-powered UAVs have the opposite effects: little noise but low flight time. Due to the drawbacks, interest and research in hybrid propulsion are increasing. The goal of this work is to optimize the electric portion of a hybrid UAV, the AAI Aerosonde, to increase time in the air and decrease noise production. This is accomplished by developing a mathematical aircraft model to predict the thrust and energy consumption of a UAV based on a certain mission profile. The mission profile includes the altitude and time The model is then implemented in MATLAB and the code is integrated into the hardware to develop the hardware-in loop-approach system. The experimental setup included a battery-powered propeller with a force sensor to determine the thrust produced by the propeller to make sure it is rotating at the right speed for the mission profile. The hardware-in-loop approach allowed for the testing of different variables that affected energy usage. In our study, we tested the effects of changes in mass, the surface area of wings, air density, and climb rate. Mechanical Engineering Nicole Lin, Shyam K. Menon

An Investigation into the Role of Fluid Shear Stress on Enhanced Cancer Extravasation during Metastasis

Cancer cells are exposed to fluid shear stress (FSS) during metastasis while traveling through the vasculature from a primary tumor to a secondary site. Fluid shear stress is the unit area amount of force acting on the cell parallel to a small element of the surface and has previously been shown to have an effect on cancer cells. Prior studies have shown changes in gene expression and protein activity in estrogen receptor positive (ER+) breast cancer cells suggesting that exposure to FSS during metastasis can enhance proliferation and potentially induce drug resistance. One area that has not been well studied is how exposure to FSS alters the migratory potential of ER+ breast cancer which is not prone to migrate in typical 2D cell culture. It is hypothesized that exposure to FSS will enhance the migratory potential of ER+ breast cancer cells. The goal of this project is to develop a modular microfluidic platform to study FSS-induced migration of a MCF7 cells, a model ER+ breast cancer cell line. The cells are first flowed through a microfluidic device containing a 1 m serpentine fluidic channel to expose them to 10 dyn/cm2 FSS for 1 min. The cells exit this first device and are flowed through a second device consisting of two long channels connected by an array of narrow channels (3 µm, 5 µm, and 7 µm). The small width of the connecting channels forces the cells to choose one channel to migrate through similar to cancer cell extravasation during metastasis. This device is designed to mimic 1D cell migration by allowing the cells only one direction to migrate as studies have shown that 1D migration is more similar to 3D migration, which occurs in the body, than 2D migration more accurately simulate in vivo cell migration. After the cells settled in the migration device, it is placed in a temperature-controlled light microscope to study FSS-induced migration for 16-18 hours. The images collected during this experiment can be analyzed using ImageJTM software to track cell displacement, migration time, and cell velocity. A control experiment without exposing cells to FSS will allow for a direct comparison between exposure to shear and 1D cell migration. The goal is to be able to develop a procedure to optimize the ability to study the effect of FSS on MCF-7 cells. Chemical Engineering Josie Ostrowe, Braulio Ortega Quesada, Adam T. Melvin

Nanoengineering Balsa Wood for Resilient Superwood

Research on timber-based nanomaterials has led to a high-performance structural material called superwood. Superwood is a densified wooden material made by nanoengineering natural wood through a simple two-step treatment system that includes partial delignification and hot-pressing densification. This project’s goal is to discover the most reliable production method for the nanoengineered superwood. At nanoscale, partial delignification reduces lignin and hemicellulose content. Then, hot-pressing causes the cellulose microfibrils to condense. These densely packed cellulose microfibrils have a higher sliding resistance between them and activate more hydrogen bonding formations among them (Carmichael 2018). For this reason, the process notably enhances the mechanical aptitude of superwood. The chemical substances used for partial lignin elimination are Na2SO3 and NaOH. First, nine raw wooden samples are put in a 100°C aqueous solution composed of NaOH, Na2SO3, and water. The solution and samples are then placed in an oil bath. The solid to liquid ratio is 1:20 (volume/weight). The samples are then treated at 3 different boiling times and three different chemical concentrations. After delignification, the wooden samples are then boiled with water five times to achieve neutrality. The target of treating the samples under differing treatment conditions is to determine the most desirable boiling time and chemical concentration. The delignified wood samples are then hot-pressed in a densification machine. The thickness of the wood is on average reduced from five mm to one mm. For the 2.5M NaOH/0.4M Na2SO3 treated samples, the bending test results confirm that the average bending strength of superwood is five times the original strength. The sample that was subjected to a 5M NaOH/ 0.8M Na2SO3 solution and treated for 7 hours exhibits the lowest bending strength. The most likely cause of this sample’s weakness is that it was treated in the harshest conditions, resulting in microcracks, and weakening the crystalline cellulose. Civil and Environmental Engineering Addison Schempf, Hussein Alqrinawi, Hai Lin

Reinforcement Learning in Flappy Bird

As we advance and seek to automate our lives, the need and reliability of technology increases. Because of this, the need for artificial intelligence (AI) increases as well. AI is being rapidly developed and widely deployed by people all over the world. From Google Maps to video games, AI is everywhere. It is not a secret that AI even performs better than humans in a wide array of subjects. Video games are a huge topic in artificial intelligence, with people developing programs that can beat world champions in their own game. Flappy Bird is an example of a video game that is greatly furthered with the implementation of AI. Flappy Bird is an arcade-style game where the player controls a bird by telling it whether to jump or not with the goal of dodging incoming pipes from the right side of the screen for as long as possible. The bird automatically descends unless the player interacts with the game by telling the bird to jump. If the player collides with a pipe or the ground, the game is over and they must restart. Every progression past one pair of pipes awards the player one point. Finding a machine learning algorithm to teach the Flappy Bird how to play the game is crucial in seeking to maximize a score. This problem introduces a reinforcement learning algorithm called Q-learning. Q-learning teaches the bird by assessing the current state of it and choosing the best future action that will keep it alive the longest. With this Q-learning algorithm, the Flappy Bird surpasses scores of over 1,000, with the highest recorded being 1,597. After around 1,000 iterations, convergence of the algorithm starts. The topic of Q-learning expands far past video games, and is used for computer programs regarding self-driving cars, robots, and more. Understanding Q-learning and the other aspects of AI is critical to advancing technology for our lives. Computer Science Kaitlyn Smith, Hao Wang

Steel Fiber Reinforcement in 3D Construction Printed Concrete 

Concrete has many manipulatable qualities that if provided with certain variables can become stronger and more durable. This project test the effectiveness of steel fibers on the flexural strength and compressive strength of 3D Construction printed concrete. The steel fibers used are .2 mm in diameter and 13 mm in length. The concrete mixtures will be tested with no fibers, 1% dosage of fibers, and 2% dosage of fibers. The compressive strength test follows the ASTM C109 procedure, and the flexural strength test follows the ASTM 1609 procedure. The results of this experiment is that as the fiber dosage increased, the compressive strength and the flexural strength of the sample increased. This proves that in future planning of 3D Construction, certain mixtures of concrete and steel fibers may be used to enhance the quality and durability of the concrete.  Construction Management Kaiser Stentiford, Ilerioluwa Giwa, Hassan Ahmed, Ali Kazemian

Detecting Hidden Security Threats With a Thermal Camera 

Biometric authentication has become ubiquitous in the modern world. Other forms of biometric authentication: iris, retina, fingerprint, and face verification, are simple and easy to use, but hand authentication has evident advantages being more cost efficient and universally accepted. In a previous project studying hand biometric authentication, a problem emerged. The cameras could not differentiate between a live hand and a fake hand. The goal of this project is to use a thermal camera to conduct a liveness detection on the hand detected while ensuring two different hands can be distinguished. To do so, we take an image using the FLIR thermal camera and input the image into MATLAB. MATLAB outputs a skeletal image of the hand after removing the only white rows. The pixel points of the hand image are opened in MATLAB. The points on the tips of the fingers and at the intersecting lines are plotted. The measurement was taken of the length of each finger, the length between each finger, and the palm width. After comparing two different hand measurements, the conclusion reached was thermal camera scanning could identify the difference between two hands.  Computer Science Kenzie Stentiford, Ruxin Wang, Chen Wang

The Impact of an Integrated Local Fan in a Central Cooling System on Occupant Thermal Comfort in Working Environments

Centralized cooling systems, such as HVAC, are often costly and inefficient to maintain, especially in increasingly hybrid working environments. One way to mitigate these costs while maintaining occupant thermal comfort is by integrating local cooling systems, such as desk fans. However, while the relationship between thermal comfort, temperature, and airflow is highly documented and studied in centralized systems, there is a lack of research on this relationship with the integration of local and central systems. This study aims to fill this gap in research by indicating how to employ integrated local and central cooling systems for optimal thermal comfort. A series of human-subject experiments in a controlled environment is performed to achieve this goal. During these tests, eight human subjects were introduced to several scenarios of varying combinations of room temperatures (65, 70, 75, and 80 degrees Fahrenheit) and airflow from a desk fan (0, 0.5, and 1 m/s) in a climate chamber, while their perception and physiological responses were collected using surveys and sensors. An Empatica E4 wristband was used in this study to measure the physiological responses of the participants in each scenario, including heart rate, blood volume pulse, electrodermal activity, and skin temperature. The experimental data were documented for further data analysis using a predictive analytics software called JMP Pro 16. Several hypotheses are tested, and a map of occupant comfort under several combinations of the local and central cooling systems is generated. The results indicate occupant thermal comfort and the combination of airflow and room temperature in the integrated system are correlated. Occupants’ skin temperature is similarly correlated to their comfort and whether they deemed the thermal conditions acceptable. The use of integrated local fan systems was shown to effectively maintain occupant comfort at higher temperatures, allowing for energy and money to be saved on centralized cooling. Construction Management Sarah Thomasa, Seddigheh (Tala) Norouziaslb, Amirhosein Jafari

Multimodal Label-Free Monitoring of Stem Cell Differentiation: Confocal Microscopy 

Stem cells are an unspecialized type of cell that go through a differentiation process to become a specialized type of cell. Stem cells are used for research, drug discovery, cancer treatments, tissue regeneration, blood and brain disease treatment, and so much more. Adult stem cells (ASC) can be found in small amount in tissues, such as bone marrow and fat. ASCs undergo the differentiation process and become an osteocyte which is a bone cell. The differentiation process from ASCs to osteocytes take a total of 21 days or 3 weeks. Previous research on adipocytes was able to prove that differentiation occurred by analyzing the lipid presence at different points. It is assumed that visible results in the differentiation process can be noted at week 3 but not week 1 and 2. The goal of this work is to analyze stem cells at different points in the differentiation process in order to prove that stem cells differentiate into osteocytes. This is accomplished by culturing the ASCs in a body-like enviroment, and then preparing slides that contain cell samples from weeks 1, 2, and 3 of the differentiation process. Images of the slides are taken using a confocal microscope. In these images stem cells markers and osteocyte markers should appear. The stem cell marker, Runx2, appears in weeks 1 and 2. And the osteocyte marker, osteocalcin, appears in week 3.  Mechanical Engineering Laura Zapata, Sreyashi Das, Ram Devireddy

Geotechnical Analysis and Comparison of Recycled Glass Sediment for Coastal Restoration

Coastal erosion has long been a prevailing issue along the Louisiana coast. Several methods have been employed throughout recent years in an attempt to curb or resolve the issue, one of which involves filling in the coast with sediment from either off shore or the Mississippi River. Recently, sediment made from recycled glass has been suggested as an alternative source of sediment that may offer a more sustainable and efficient approach. The goal of this project is to examine this glass sediment, including, but not limited to, several geotechnical and mechanical properties and compare these properties to sand from coastal Louisiana and the Mississippi river. This is accomplished by completing several different experiments that each determine a different property. Grain size distribution was found using a sieving technique and then, the cumulative gradation, D10, D50, and D90 of each sediment type were calculated and graphed. Settling velocity for different particle size ranges of each type of sediment was tested in a graduated cylinder, and was subsequently compared with theoretical settling velocities calculated through Ferguson and Church’s settling velocity equation. The dry and wet angle of repose was tested using a fixed funnel, and a tube and jar set up, respectively. A microscope and imaging software was used to capture high-resolution photographs of the sediment particles, and then compared to the ASTM Particle Shape chart. In order to find incipient motion, a 400cm x 13cm x 30.5cm flume was filled with water and 2 cm of sediment was gently placed and leveled on the bottom. Upstream and downstream weirs were used to set the water levels and depths, a current meter was used to measure the water velocity, and a pump was used to induce increasing water velocities over the sediment bed before and during sediment motion. Ultimately, while L5 was more similar to the coastal and river sand than L4, with similar grain size distribution, it became apparent that several qualities could still be refined. The sediment was very easily disturbed, and many particles were so fine that they obscured the water clarity and coated any surface nearby with dust. One particularly noteworthy find was that the shape of the L5 particles are much more angular and irregular, creating a looser mixture. Thus, the resulting angle of repose is higher, and the speed needed to see incipient motion is much lower. Environmental Engineering Louisa Zhu, Julia Mudd, Clint Willson

Past Projects

Project Title Program Mentor
Application of PCR to Detect Aromatic Hydrocarbon Producing Bacterial Populations in Sediment Samples from South Louisiana Civil and Environmental Engineering Bill Moe
Role of the Genus Azospira in Biological Nutrient Removal Civil and Environmental Engineering Tamara K. Martin, Bill Moe
Investigation of Physical and Mechanical Properties of a Mud Dauber Wasp Nest Civil and Environmental Engineering Joon S. Park, Hai Lin
Hurricanes vs. Oil Storage Tanks Civil and Environmental Engineering Sabarethinam Kameshwar
Effect of Sand Content on Metakaolin Based Geopolymers Construction Management Ruwa AbuFarsakh, Gabriel Arce
A Data-Driven Approach to Improving Energy Efficiency in Buildings Construction Management Amirhosein Jafari
Crystal Phases of Metal Oxide Materials Chemical Engineering Yuming Wang, James Dorman
Optimization of Hydrogel Identity and Composition in an Open-Air 3D Printed Microfluidic Device to Study 3D Cell Migration Chemical Engineering Kalena Nichol, Adam Melvin
Development of a Modular Microfluidic Device to Study the Effects of Fluid Shear Stress on ER+ Breast Cancer Chemical Engineering Blake Nassar, Adam Melvin
3D Bio-Printing of Tumor Phantom in the Larynges for Tumor Resection Training Applications Biological and Agricultural Engineering Kaushik Sunder, Michael E. Dunham, Jangwook P. Jung
The Effects of Bone Dye Techniques on Numerical Microstructural Analysis Biological and Agricultural Engineering Kevin Hoffseth
Droplet Interaction with Propagating Shockwaves Mechanical Engineering Shyam Menon
Colorimetric and Spectroscopic Sensing of Biomarker for Cystic Fibrosis Using a Smartphone Mechanical Engineering Elnaz Sheik, Manas Ranjan Gartia 
Preventing Handheld Device Distraction for Drivers Using Smartphone Motion Sensors Computer Science Chen Wang
Preventing Driver Distractions Via Acoustic Sensing Computer Science Long Huang, Chen Wang
Machine Learning Methods on Raman Spectroscopic Cancer Data for Early Diagnosis Electrical Engineering Zheng Li, Jian Xu

Project Title Program Mentor
Simulating Cortical Bone Structure in Large Vertebrates Biological Engineering Kevin Hoffseth
Microstructural Geometry and Damage Detection in Cortical Bone Images Biological Engineering Kevin Hoffseth
Characterization of Fluorescent Proteins Produced in the E. coli Cell-Free Protein Synthesis System Biological Engineering Yongchan Kwon
Meta-Analysis of Cardiac Extracellular Matrix Proteins: Information Extraction for 3D Bio-printing Biological Engineering Philip Jung
Dynamic Photoluminescence Response of Dipole-Modulated Rare Earth Doped Core-Shell Nanoparticles to Local Changes in Temperature and Solution pH Chemical Engineering James Dorman
Machine Learning-Based Feature Analysis and Classification for ICG-Assisted Vibrational Spectroscopic Data of Pancreatic Carcinoma Electrical Engineering Jian Xu
3D Tumor Spheroid Generation Using a Droplet Microfluidic Device Chemical Engineering Adam Melvin
Circulating Microfluidic Co-Culture Device for the Dynamic Analysis of the Tumor Secretome Chemical Engineering Adam Melvin
Development of a Modular Microfluidic Platform to Investigate the Role of Fluid Shear Stress on Cancer Cell Phenotype Chemical Engineering Adam Melvin
Using Pulsed UV Light for Enhancing Advanced Oxidation Water Treatment Environmental Engineering Samuel Snow
Using Pulsed UV Light for Enhanced Water Disinfection Environmental Engineering Samuel Snow
Shockwave Induced Droplet Breakup Mechanical Engineering Shyam Menon
Characterization of Animal Nest-Building Geomaterials Civil Engineering Hai Lin
Breath Monitoring: Analyzing Breathing with Wireless Bluetooth Earbuds Computer Science Chen Wang
Evaluation of the Field Performance of Stabilized and Non-Stabilized Asphalt Overlays in Louisiana Construction Management Momen Mousa
The Use of RAP and WMA Mixtures in South-Central States: Challenges & Limitations Construction Management Husam Sadek
Variability and Uncertainty of Overlay Tester Testing Data, Analysis, and Results Construction Management Husam Sadek

Photos

Zachary Jefferson posing with poster project Ella Benjamin & Vincenza Vendetto posing with poster project John Feet posing with poster project Orna Mukhopadhyay posing with poster project
Lailah Collins posing with poster presentation Student in blue shirt posing with poster presentation Student in teal shirt posing with poster project Catherine Burkhalter posing with poster project
Catherine Shaw posing with poster presentation Catherine Hardouin posing with poster project Kalina Namikas posing with poster project Alexandra Hulse posing with poster presentation
Josephine Day posing with poster presentation Shreya Singh posing with poster presentation Laurel Bourg posing with poster project Mary Dardis posing with poster project
Group photo of 2021 HSSR students Dean Wornat posing with top three HSSR students    

Contact

The program administrators are responsible for the facilitation of the program from start to finish by creating the policy/structure, providing regular communication to all stakeholders, serving as the key liaisons between all stakeholders, and generally supporting/directing the program throughout each cycle.

Program Administrator Contact Info:

Raynesha Ducksworth
Assistant Manager
225-578-5335
rducksworth@lsu.edu

Adam T. Melvin, PhD
Associate Professor
Cain Department of Chemical Engineering
LSU College of Engineering
3314F Patrick F. Taylor Hall, Baton Rouge, LA 70803
melvin@lsu.edu
office: 225-578-3062