2022 Research Projects
Projects are posted below; new projects will continue to be posted. To learn more about the type of research conducted by undergraduates, view the archived symposium booklets and search the past SURF projects.
This is a list of research projects that may have opportunities for undergraduate students. Please note that it is not a complete list of every SURF project. Undergraduates will discover other projects when talking directly to Purdue faculty.
You can browse all the projects on the list or view only projects in the following categories:
Energy and Environment (27)
A Hyperspectral imager for Propulsion Testing
Description:
The SURF student will work with a PhD student and Professor Gore to contribute to the following project.
The feasibility of utilizing a mid-infrared hyperspectral imager as a general-purpose ground testing diagnostic for rocket propulsion systems will be demonstrated. Purdue University compared temperatures deconvoluted from the hyperspectral images of a hydrogen air premixed flame with our measurements of temperature using Rayleigh scattering at identical operating conditions. This comparison has helped sponsor address a key issue involving the establishment of feasibility of obtaining spatially and temporally resolved information from mid-infrared hyperspectral imager measurements.
Purdue University work in Phase II is focused on evaluating the imager for different flame configurations to help deliver the system to NASA. Purdue University will demonstrate the use of the hyperspectral imager using: (i) two previously studied turbulent premixed hydrogen air jet flames, (ii) two previously studied turbulent premixed and partially premixed methane air jet flames, and (iii) a plume emerging from an existing rocket propellant combustion test apparatus.
The feasibility of utilizing a mid-infrared hyperspectral imager as a general-purpose ground testing diagnostic for rocket propulsion systems will be demonstrated. Purdue University compared temperatures deconvoluted from the hyperspectral images of a hydrogen air premixed flame with our measurements of temperature using Rayleigh scattering at identical operating conditions. This comparison has helped sponsor address a key issue involving the establishment of feasibility of obtaining spatially and temporally resolved information from mid-infrared hyperspectral imager measurements.
Purdue University work in Phase II is focused on evaluating the imager for different flame configurations to help deliver the system to NASA. Purdue University will demonstrate the use of the hyperspectral imager using: (i) two previously studied turbulent premixed hydrogen air jet flames, (ii) two previously studied turbulent premixed and partially premixed methane air jet flames, and (iii) a plume emerging from an existing rocket propellant combustion test apparatus.
Research categories:
Big Data/Machine Learning, Energy and Environment, Thermal Technology
Preferred major(s):
- Aeronautical and Astronautical Engineering
- Mechanical Engineering
School/Dept.:
Mechanical Engineering
Professor:
Jay
Gore
More information: https://engineering.purdue.edu/GRG
AAMP-UP: Additive Manufacturing
Description:
This research project seeks to additively manufacture (3D print) highly viscous materials using a novel 3D-printing method: Vibration Assisted Printing (VAP). This technique uses high frequency vibrations concentrated at the tip of the printing nozzle to enable flow of viscous materials at low pressures and temperatures. VAP has the potential to create next-generation munitions with more precision, customizability, and safety than traditional additive manufacturing methods. The objective of this project is to design formulations which are capable of being vibration-assisted printed, maintain energetic performance, and retain desirable mechanical properties after printing. The REU student would be mentored by graduate students and work within a team to design experiments, perform experiments, analyze data, and disseminate the results. The REU student will have the opportunity to present the findings in regular meetings, poster sessions, formal presentations, and papers.
Research categories:
Chemical Unit Operations, Composite Materials and Alloys, Energy and Environment, Engineering the Built Environment, Fabrication and Robotics, Material Modeling and Simulation, Other
Preferred major(s):
- No Major Restriction
Desired experience:
U.S. Citizenship Required
Must have completed 1 semester of undergraduate courses
School/Dept.:
Mechanical Engineering
Professor:
Jeff
Rhoads
More information: https://engineering.purdue.edu/ME/People/ptProfile?resource_id=34218
Data Driven Modeling of Electric Vehicle Impacts on Traffic Safety
Description:
As the Biden administration recently announced a national target for electric vehicle (EV) sales, more and more EVs will be on road in the future. Meanwhile, there will be an increasing possibility of traffic crashes between EVs and Internal Combustion Engine (ICE) vehicles or between EVs and pedestrians/cyclists. However, we have a limited understanding of how EVs will influence traffic safety, especially at road intersections. This study will leverage affluent historical traffic crash data (including driver demographic information, driver behavior, and traffic conditions) in Indiana and conduct data-driven modeling to uncover what factors are associated with crashes involving EVs. In specific, this study will focus on crashes on all interstate and state highways in Indiana. The expected outcome will lead to policy recommendations on developing EV safety regulations, improving vehicle safety features and highway design in the future.
Research categories:
Big Data/Machine Learning, Energy and Environment, Other
Preferred major(s):
- Civil Engineering
- Computer Science
- Statistics - Applied Statistics
Desired experience:
This research will involve statistical modeling and spatial-temporal data analysis and require basic programming skills (e.g., Python or R). Other desired qualifications include ability to work independently, strong work ethic, ability to work in diverse teams, and tehnical writing skills.
School/Dept.:
Lyles School of Civil Engineering
Professor:
Konstantina (Nadia)
Gkritza
More information: https://engineering.purdue.edu/ASPIRE; https://engineering.purdue.edu/STSRG
Design and Control of Hybrid Thermal Management Systems
Description:
Thermal management systems are used in a wide range of systems primarily for electronics cooling, and are becoming increasingly critical for aircraft as air vehicles become increasingly electrified or even hybridized. However, designing these systems is becoming increasingly challenging because the heat loads that they need to manage vary frequently in duration and magnitude. A "hybrid" thermal management system (TMS) is one that also includes a thermal battery (thermal energy storage device) to improve the system's ability to respond quickly to unexpected heat loads. These systems are similar in nature to hybrid electric vehicles that balance the use of the engine and a battery to achieve a common objective.
Designing a thermal energy storage (TES) device that has a large enough capacity, can absorb heat quickly, and is lightweight is challenging because it needs to perform well under many different load conditions, including when the heat loads are random. Performance metrics need to be simple enough that they can be evaluated by iterative optimization algorithms while capturing the complexity of the design requirements. In this project, the student(s) will design a TES device using optimization algorithms to find the best dimensions and test it in simulation against previously-designed TES devices. They will also support experimental work related to ongoing research in the area of design and control of these complex thermal systems.
Designing a thermal energy storage (TES) device that has a large enough capacity, can absorb heat quickly, and is lightweight is challenging because it needs to perform well under many different load conditions, including when the heat loads are random. Performance metrics need to be simple enough that they can be evaluated by iterative optimization algorithms while capturing the complexity of the design requirements. In this project, the student(s) will design a TES device using optimization algorithms to find the best dimensions and test it in simulation against previously-designed TES devices. They will also support experimental work related to ongoing research in the area of design and control of these complex thermal systems.
Research categories:
Energy and Environment, Thermal Technology, Other
Preferred major(s):
- Mechanical Engineering
- Aeronautical and Astronautical Engineering
Desired experience:
Ideally the student will have completed Differential Equations, Thermodynamics I, as well as dynamics or controls courses in their major. Proficiency coding in MATLAB or Python is also desirable.
School/Dept.:
School of Mechanical Engineering
Professor:
Neera
Jain
More information: https://engineering.purdue.edu/JainResearchLab/
Development of Automated Load-Based Testing Apparatus for Air Conditioners & Heat Pumps Performance Evaluation
Description:
Project Description: The energy demands for space conditioning is continuously increasing with population growth, rising temperatures, and improving standards of living. To counteract the effect of growing air-conditioners and heat-pumps demand on overall energy consumption, improving the energy efficiency of systems sold in the market is crucial. One of the effective and tested approaches for this has been to set energy efficiency benchmarks based on the minimum energy performance standards (MEPS) which drive technological innovation. For air-conditioners and heat pumps, a testing and rating procedure forms the technical basis for these energy efficiency standards to estimate equipment seasonal performance. However, with current rating standards for residential heat pumps, significant dissimilarities have been observed between the equipment rated performance and the equipment's actual operational performance in field applications. Load-based testing is evolving as an alternative approach for obtaining equipment performance data that captures the effects of dynamic interactions between a heat pump or air conditioner, its integrated controls, and a prototypical building that it serves. Current load-based testing requires the use of psychometric chambers to vary ambient temperatures and building loads which is time-consuming and expensive, particularly for residential split systems when different combinations of indoor and outdoor units need to be tested. Thus, there is a need for a low-cost, automated, load-based method of test that doesn’t require psychrometric chambers and where multiple units could be tested in a single large test room similar to a life-test facility. In this project, we are working on the development of a low-cost and automated testing apparatus and methodology for direct expansion air conditioners and heat pumps. The student who joins this project will have the opportunity to contribute to important experimental work will learn about air-conditioners working and their testing approach, thermodynamics, and heat transfer applicable to thermal systems, and will also learn about the test facility development process.
Final Deliverables: The student will work closely with the graduate student mentor on test facility development and experiments related to the performance evaluation of heat-pumps and air-conditioners based on the load-based testing methodology. The student will also assist in analyzing the experimental data. Students will partake in weekly literature reading and discussion, small group meetings, and will keep a log of their weekly progress. They will present their updates at weekly meetings and will present a talk or poster at the end of the summer. Students will end the summer with a greater understanding of the energy challenges in space conditioning and will develop a broad range of technical skills pertinent to the experimentation and performance evaluation of residential air-conditioning and heat-pumping systems.
Final Deliverables: The student will work closely with the graduate student mentor on test facility development and experiments related to the performance evaluation of heat-pumps and air-conditioners based on the load-based testing methodology. The student will also assist in analyzing the experimental data. Students will partake in weekly literature reading and discussion, small group meetings, and will keep a log of their weekly progress. They will present their updates at weekly meetings and will present a talk or poster at the end of the summer. Students will end the summer with a greater understanding of the energy challenges in space conditioning and will develop a broad range of technical skills pertinent to the experimentation and performance evaluation of residential air-conditioning and heat-pumping systems.
Research categories:
Energy and Environment, Engineering the Built Environment, Thermal Technology
Preferred major(s):
- Mechanical Engineering
- Civil Engineering
Desired experience:
Applicants should have a general interest in energy and sustainability. Should also have a strong background/interest in thermodynamics and heat transfer. Applicants with experience in some (not all) of the following are preferred: LabVIEW, Python, Engineering Equation Solver, MATLAB, 3D-CAD Software. 2nd semester Sophomores, Juniors, and 1st semester Seniors are preferred.
School/Dept.:
Mechanical Engineering
Professor:
Travis
Horton
Developmental, Behavioral & Environmental Determinants of Infant Dust Ingestion
Description:
Our project is funded by the U.S. Environmental Protection Agency (EPA) and involves an interdisciplinary collaboration between engineers, chemists, and psychologists at Purdue University and New York University (NYU). We will elucidate determinants of indoor dust ingestion in 6- to 24-month-old infants (age range for major postural and locomotor milestones). Specific objectives are to test: (1) whether the frequency and characteristics of indoor dust and non-dust mouthing events change with age and motor development stage for different micro-environments; (2) how home characteristics and demographic factors affect indoor dust mass loading and dust toxicant concentration; (3) how dust transfer between surfaces is influenced by dust properties, surface features, and contact dynamics; and (4) contributions of developmental, behavioral, and socio-environmental factors to dust and toxicant-resolved dust ingestion rates. In addition, the project will (5) create a shared corpus of video, dust, toxicant, and ingestion rate data to increase scientific transparency and speed progress through data reuse by the broader exposure science community.
Our transdisciplinary work will involve: (1) parent report questionnaires and detailed video coding of home observations of infant mouthing and hand-to-floor/object behaviors; (2) physical and chemical analyses of indoor dust collected through home visits and a citizen-science campaign; (3) surface-to-surface dust transfer experiments with a robotic platform; (4) dust mass balance modeling to determine distributions in and determinants of dust and toxicant-resolved dust ingestion rates; and (5) open sharing of curated research videos and processed data in the Databrary digital library and a public website with geographic and behavioral information for participating families.
The project will provide improved estimates of indoor dust ingestion rates in pre-sitting to independently walking infants and characterize inter-individual variability based on infant age, developmental stage, home environment, and parent behaviors. Dust transport experiments and modeling will provide new mechanistic insights into the factors that affect the migration of dust from the floor to mouthed objects to an infant’s mouth. The shared corpus will enable data reuse to inform future research on how dust ingestion contributes to infants’ total exposure to environmental toxicants.
U.S. EPA project overview: https://cfpub.epa.gov/ncer_abstracts/index.cfm/fuseaction/display.abstractDetail/abstract_id/11194
Our transdisciplinary work will involve: (1) parent report questionnaires and detailed video coding of home observations of infant mouthing and hand-to-floor/object behaviors; (2) physical and chemical analyses of indoor dust collected through home visits and a citizen-science campaign; (3) surface-to-surface dust transfer experiments with a robotic platform; (4) dust mass balance modeling to determine distributions in and determinants of dust and toxicant-resolved dust ingestion rates; and (5) open sharing of curated research videos and processed data in the Databrary digital library and a public website with geographic and behavioral information for participating families.
The project will provide improved estimates of indoor dust ingestion rates in pre-sitting to independently walking infants and characterize inter-individual variability based on infant age, developmental stage, home environment, and parent behaviors. Dust transport experiments and modeling will provide new mechanistic insights into the factors that affect the migration of dust from the floor to mouthed objects to an infant’s mouth. The shared corpus will enable data reuse to inform future research on how dust ingestion contributes to infants’ total exposure to environmental toxicants.
U.S. EPA project overview: https://cfpub.epa.gov/ncer_abstracts/index.cfm/fuseaction/display.abstractDetail/abstract_id/11194
Research categories:
Biological Characterization and Imaging, Ecology and Sustainability, Energy and Environment, Engineering the Built Environment, Environmental Characterization, Human Factors
Preferred major(s):
- No Major Restriction
Desired experience:
We are seeking students passionate about studying environmental contaminants and infant exposure to chemicals in the indoor environment. Preferred skills: experience with MATLAB, Python, or R. Coursework: environmental science and chemistry, microbiology, physics, thermodynamics, heat/mass transfer, fluid mechanics, developmental psychology.
School/Dept.:
Lyles School of Civil Engineering
Professor:
Brandon
Boor
More information: www.brandonboor.com
Electrical Dehydrogenation Reactor Optimization for The Production of Ethylene Using Renewable Energies
Description:
Ethylene is one of the most important building blocks of the chemical industry1. Its global market was estimated at ~160 million Tons in 2020 and it is forecast to reach ~210 million Tons by 20272. Between 1.0 and 1.6 tons of CO2 are emitted per ton of Ethylene produced. This means Ethylene production accounted for around 0.47-0.75% of the world’s total carbon emissions in 2020, estimated at 34 billion tons3. The U.S. has set a course to reach net-zero emissions economy-wide by no later than 20507,8. This makes it imperative decarbonizing Ethylene production.
Ethylene is mainly produced by Steam Cracking (SC), where hydrocarbons transform into ethylene in the presence of steam at high temperatures11. SC normally implements hydrocarbon combustion to produce the necessary energy for reaction. This is the main reason why SC emits so much CO21. The NSF Center for Innovative and Strategic Transformation of Alkane Resources (CISTAR)5 is currently researching the coupling of SC with renewable electricity. This would allow a significant reduction of CO2 emissions during SC4.
As part of its research, CISTAR carries out detailed Computational Fluid Dynamics (CFD) simulations. This allows evaluating the impact of fluid behavior during reactions. Several geometries are currently under evaluation. As part of the SURF Program, CISTAR is interested in recruiting one student to support the CFD simulations team. The goal is to evaluate the performance of the different reactor geometries considered, as well as propose potentially attractive new configurations. No previous experience with CFD simulations is necessary. However, it is advisable the student has a strong motivation for computer simulations. Experience working with Ansys Fluent and Aspen Plus could be beneficial.
Ethylene is mainly produced by Steam Cracking (SC), where hydrocarbons transform into ethylene in the presence of steam at high temperatures11. SC normally implements hydrocarbon combustion to produce the necessary energy for reaction. This is the main reason why SC emits so much CO21. The NSF Center for Innovative and Strategic Transformation of Alkane Resources (CISTAR)5 is currently researching the coupling of SC with renewable electricity. This would allow a significant reduction of CO2 emissions during SC4.
As part of its research, CISTAR carries out detailed Computational Fluid Dynamics (CFD) simulations. This allows evaluating the impact of fluid behavior during reactions. Several geometries are currently under evaluation. As part of the SURF Program, CISTAR is interested in recruiting one student to support the CFD simulations team. The goal is to evaluate the performance of the different reactor geometries considered, as well as propose potentially attractive new configurations. No previous experience with CFD simulations is necessary. However, it is advisable the student has a strong motivation for computer simulations. Experience working with Ansys Fluent and Aspen Plus could be beneficial.
Research categories:
Chemical Unit Operations, Energy and Environment, Fluid Modelling and Simulation, Material Modeling and Simulation, Thermal Technology
Preferred major(s):
- Chemical Engineering
- Mechanical Engineering
- Electrical Engineering
Desired experience:
• It is advisable the student has a strong motivation for computer simulations
• Experience working with Ansys Fluent and Aspen Plus could be beneficial
School/Dept.:
Davidson School of Chemical Engineering
Professor:
Rakesh
Agrawal
More information: https://engineering.purdue.edu/RARG/ and https://cistar.us/
Evaluation of a Prototype Membrane Energy Exchanger for Efficient Buildings
Description:
Buildings are the largest source of energy consumption in the U.S., constituting roughly 48% of our primary energy consumption, and air conditioning is one of the largest uses of energy within buildings. As global temperatures rise from global warming, populations grow, and greater emphasis is put on indoor air quality and comfort, cooling energy demand will grow too. The long-standing conventional technologies we rely on for space cooling are inherently inefficient in warm, humid climates where a large portion of the cooling energy goes to the condensation dehumidification process instead of air cooling. Thus, there is a great need for innovative, disruptive technological development that can challenge the way we’ve provided space cooling for decades. In this project, we are developing a novel technology that mechanically separates water vapor out of air using water vapor selective membranes, which is much more efficient than condensing water out of air. Additionally, we are exploring innovative heat and mass transport phenomena using novel materials. The student who joins this project will have the opportunity to contribute to important experimental work, will learn about energy use and the thermodynamics and heat transfer in buildings, and will learn about material development, too.
The student will work closely with the graduate student mentor on experiments related to porous membrane fabrication and characterization along with the testing of the novel membrane energy exchanger’s performance (heat transfer and dehumidification properties). The student will also assist in validating thermodynamic models using the experimental data. Students will partake in weekly literature reading and discussion small group meetings and will keep a log of their weekly progress. They will present their updates at weekly meetings and will present a talk or poster at the end of the summer. Students will end the summer with a greater understanding of the energy challenges in the building sphere and will develop a broad range of scientific skills pertinent to the design and evaluation of new technologies.
The student will work closely with the graduate student mentor on experiments related to porous membrane fabrication and characterization along with the testing of the novel membrane energy exchanger’s performance (heat transfer and dehumidification properties). The student will also assist in validating thermodynamic models using the experimental data. Students will partake in weekly literature reading and discussion small group meetings and will keep a log of their weekly progress. They will present their updates at weekly meetings and will present a talk or poster at the end of the summer. Students will end the summer with a greater understanding of the energy challenges in the building sphere and will develop a broad range of scientific skills pertinent to the design and evaluation of new technologies.
Research categories:
Energy and Environment, Engineering the Built Environment, Thermal Technology
Preferred major(s):
- Mechanical Engineering
Desired experience:
Applicants should have a general interest in energy and sustainability. Should also have a strong background/interest in thermodynamics and heat transfer. Applicants with experience in some (not all) of the following are preferred: LabVIEW, Python (Jupyter, Google Colab, etc.) Engineering Equation Solver, MATLAB, 3D-CAD Software, prototype design/manufacturing, and Adobe Illustrator. 2nd semester Sophomores, Juniors, and 1st semester Seniors are preferred.
School/Dept.:
Mechanical Engineering
Professor:
James
Braun
More information: https://engineering.purdue.edu/CHPB
Experimental Methods for Aerothermal Environments
Description:
The student will help graduate students and faculty to design and develop experimental methods and instrumentation for research in high-enthalpy aerothermal flow systems relevant to advanced propulsion devices. They will integrate and operate flow hardware, install and evaluate instrumentation and data acquisition system, and help collect and analyze data acquired during testing. The student will gain valuable hands-on experience culminating in a final presentation that will be graded by the advisor.
Research categories:
Energy and Environment, Thermal Technology
Preferred major(s):
- Mechanical Engineering
- Aeronautical and Astronautical Engineering
Desired experience:
CAD, MATLAB, P&ID, fabrication
School/Dept.:
School of Mechanical Engineering
Professor:
Terrence
Meyer
More information: engineering.purdue.edu/trmeyer
Experimental Study of Heat Transfer in Nanomaterials
Description:
This project deals with the study of heat transfer in very thin film materials using Raman Spectroscopy and Ultrafast Laser Spectroscopy. Heat transfer in nanoscale materials including 2D materials (very thin layered materials bonded by van der Waal’s force) shows superior characteristics for applications in numerous advanced devices. Their thermal transport behaviors are also different compared with bulk materials, and an understanding of the transport process is important for applications of these materials. We use non-contact, optical method (i.e., lasers etc.) to investigate heat flow in these materials. The undergraduate student will work with graduate students to learn to use state-of-the-art experimental facilities, carry out experiments, and analyze experimental results.
Research categories:
Energy and Environment, Nanotechnology, Thermal Technology
Preferred major(s):
- Mechanical Engineering
- Physics
Desired experience:
Junior or Senior standing
School/Dept.:
Mechanical Engineering
Professor:
Xianfan
Xu
More information: https://engineering.purdue.edu/~xxu/; https://engineering.purdue.edu/NanoLab/
Geospatially resolved model of heat pump operating costs & emissions
Description:
Commercial and residential buildings account for 13% of greenhouse gas emissions in the United States. Most of these emissions are driven by heating and cooling energy demand. Heat pumps, especially new technologies that make use of low global warming potential refrigerants, offer higher energy efficiency but can still be cost prohibitive. Working as part of a larger research project, this summer project would use performance testing data of a new heat pump technology to estimate the energy consumption for operating a new heat pump technology at different locations with different weather conditions in the United States. Using this energy consumption data, we can then estimate the greenhouse gas emissions associated with these new technologies using today’s electricity grid, and the cost of operating these new heat pumps. The results will be incorporated into a broader study of the geospatial environmental and energy burdens to residents.
Research categories:
Big Data/Machine Learning, Energy and Environment
Preferred major(s):
- Mechanical Engineering
- Industrial Engineering
- Chemical Engineering
- Environmental and Ecological Engineering
- Electrical Engineering
Desired experience:
Completed introductory thermodynamics and electrical engineering coursework (ME200, ECE20001 or similar). Working familiarity with Python and/or Matlab. Experience with data science and/or GitHub is also a plus.
School/Dept.:
Mechanical Engineering
Professor:
Rebecca
Ciez
High Performance Perovskite Solar Cells
Description:
Sunlight is the most abundant renewable energy resource available to human beings, and yet it remains one of the most poorly utilized sources of clean energy. Solar cell modules incorporating single crystalline silicon and gallium arsenide currently provide the highest efficiencies for solar energy conversion to electricity but remain limited due to their high costs.
In the past few years, perovskite solar cell technology has made significant progress, improving in efficiency to ~25%, while maintaining attractive economics due to the use of inexpensive soluble materials coupled with ultra low-cost deposition technologies. However, the real applications of these devices requires new breakthroughs in device performance, large-scale manufacturing, and improved stability. Among these, stability and degradation are among the most significant challenges for perovskite technologies. Perovskite absorber layer and organic charge transport materials can be sensitive to water, oxygen, high temperatures, ultraviolet light, and even electric field, all of which will be encountered during operation. To address these issues, significant efforts have been made, including mixed dimensionality and surface passivation; alternative absorber materials and formulations, new charge transport layers, and advanced encapsulation techniques, etc. Now, T80 lifetimes (i.e., the length of time in operation until measured output power is 80% of original output power) of over 1,000 hours have been demonstrated. However, it is still far below the industry required 20 years lifetime, indicating the ineffectiveness of current approaches. To make this advance, non-incremental and fundamentally new strategies are required to improve the intrinsic stability of perovskite active materials.
In this project, we propose a new paradigm to develop intrinsically robust perovskite active layers through the incorporation of multi-functional semiconducting conjugated ligands. In preliminary work, we have demonstrated that semiconducting ligands can spontaneously organize within the active layer to passivate defects and restrict halide diffusion, resulting in dramatic improvements in moisture and oxygen tolerance, reduced phase segregation, and increased thermal stability. Combining a team with expertise spanning the gamut of materials synthesis, computational materials design, and device engineering, we will develop a suite of multi-functional semiconducting ligands capable of improving the intrinsic stability perovskite materials while preserving and even enhancing their electronic properties. Through this strategy, we aim to achieve over 25% cell efficiency with operational stability over 20 years for future commercial use.
More information: https://letiandougroup.com/
In the past few years, perovskite solar cell technology has made significant progress, improving in efficiency to ~25%, while maintaining attractive economics due to the use of inexpensive soluble materials coupled with ultra low-cost deposition technologies. However, the real applications of these devices requires new breakthroughs in device performance, large-scale manufacturing, and improved stability. Among these, stability and degradation are among the most significant challenges for perovskite technologies. Perovskite absorber layer and organic charge transport materials can be sensitive to water, oxygen, high temperatures, ultraviolet light, and even electric field, all of which will be encountered during operation. To address these issues, significant efforts have been made, including mixed dimensionality and surface passivation; alternative absorber materials and formulations, new charge transport layers, and advanced encapsulation techniques, etc. Now, T80 lifetimes (i.e., the length of time in operation until measured output power is 80% of original output power) of over 1,000 hours have been demonstrated. However, it is still far below the industry required 20 years lifetime, indicating the ineffectiveness of current approaches. To make this advance, non-incremental and fundamentally new strategies are required to improve the intrinsic stability of perovskite active materials.
In this project, we propose a new paradigm to develop intrinsically robust perovskite active layers through the incorporation of multi-functional semiconducting conjugated ligands. In preliminary work, we have demonstrated that semiconducting ligands can spontaneously organize within the active layer to passivate defects and restrict halide diffusion, resulting in dramatic improvements in moisture and oxygen tolerance, reduced phase segregation, and increased thermal stability. Combining a team with expertise spanning the gamut of materials synthesis, computational materials design, and device engineering, we will develop a suite of multi-functional semiconducting ligands capable of improving the intrinsic stability perovskite materials while preserving and even enhancing their electronic properties. Through this strategy, we aim to achieve over 25% cell efficiency with operational stability over 20 years for future commercial use.
More information: https://letiandougroup.com/
Research categories:
Energy and Environment, Material Processing and Characterization, Nanotechnology
Preferred major(s):
- No Major Restriction
School/Dept.:
Chemical Engineering
Professor:
Letian
Dou
More information: https://letiandougroup.com/
High-efficiency solar-powered desalination
Description:
Water and energy are tightly linked resources that must both become renewable for a successful future. The United Nations predicts that 6 billion people will face water scarcity by 2050. This warrants the need to develop efficient and realizable engineering solutions for desalination using the vast availability of solar energy.
This project aims to design, prototype, and test novel configurations for membrane-based desalination (reverse osmosis), powered by solar-thermal engines. The student will be part of a team of graduate and undergraduate students responsible for process design, thermal-fluid modeling and simulation, hydraulic circuit prototyping and testing, and experimental data analysis.
All students will be required to read relevant, peer-reviewed literature and keep a notebook or log of weekly research progress. At the end of the semester or term, each student will present a talk or poster on their results.
This project aims to design, prototype, and test novel configurations for membrane-based desalination (reverse osmosis), powered by solar-thermal engines. The student will be part of a team of graduate and undergraduate students responsible for process design, thermal-fluid modeling and simulation, hydraulic circuit prototyping and testing, and experimental data analysis.
All students will be required to read relevant, peer-reviewed literature and keep a notebook or log of weekly research progress. At the end of the semester or term, each student will present a talk or poster on their results.
Research categories:
Ecology and Sustainability, Energy and Environment, Fluid Modelling and Simulation, Internet of Things, Nanotechnology, Thermal Technology
Preferred major(s):
- No Major Restriction
Desired experience:
Applicants should have an interest in thermodynamics, water treatment, and sustainability. Applicants with experience in some (not all) of the following are preferred: experimental design and prototyping, manufacturing, Python, LabView, EES, MATLAB, 3D CAD Software, & Adobe Illustrator. Rising Juniors and Seniors are preferred.
School/Dept.:
Mechanical Engineering
Professor:
David
Warsinger
More information: www.warsinger.com
High-performance Radiative Cooling Nanocomposites
Description:
Radiative cooling is a passive cooling technology without power consumption, via reflecting sunlight and radiating infrared heat, both into the deep space. Compared to conventional air conditioners, radiative cooling not only saves energy, but also combats climate crisis since all the heat goes to deep space instead of stays on the earth. Recently, our group has invented commercial-like particle-matrix paints (nanocomposites) that cool below the surrounding temperature under direct sunlight. The Purdue cooling paints attracted remarkable global attention and won a Guinness World Record. Read, for example, the BBC News coverage here: https://www.bbc.com/news/science-environment-56749105. Currently we are working to improve the performance and create new radiative cooling solutions.
In this SURF project, we are looking for self-motivated students to work with our PhD students. The student will first synthesize nanocomposites via some wet chemistry and/or 3D printing methods. The optical, mechanical, and other relevant properties will then be characterized with spectrometers and other specialized equipment. Field tests will be performed to measure the cooling performance of the materials and devices. The work is expected to results in journal paper(s) of high impact. Students who make substantial contributions to the work can expect to be co-authors of the paper(s).
In this SURF project, we are looking for self-motivated students to work with our PhD students. The student will first synthesize nanocomposites via some wet chemistry and/or 3D printing methods. The optical, mechanical, and other relevant properties will then be characterized with spectrometers and other specialized equipment. Field tests will be performed to measure the cooling performance of the materials and devices. The work is expected to results in journal paper(s) of high impact. Students who make substantial contributions to the work can expect to be co-authors of the paper(s).
Research categories:
Energy and Environment, Material Processing and Characterization, Nanotechnology, Thermal Technology
Preferred major(s):
- Mechanical Engineering
- Environmental and Ecological Engineering
Desired experience:
courses in heat transfer and thermodynamics are a plus but not required
School/Dept.:
Mechanical Engineering
Professor:
Xiulin
Ruan
More information: https://engineering.purdue.edu/NANOENERGY/
Identification, Verification and Validation of a Surfactant Formulation for Chemical Enhanced Oil Recovery in the Illinois Basin
Description:
Challenge: The Enhanced Oil Recovery (EOR) Lab has an ardent interest in developing a practical and economical program for the Illinois Basin. The Illinois basin is characterized as a mature asset that is typified by its shallow depths and low temperatures. Many of the fields have been waterflooded for the last several decades to aid in the recovery of the stranded oil within the sandstone and carbonate reservoirs. Significant progress has been made in understanding the brine constituents, oil viscosity/API gravity and reservoir mineralogy of the Illinois Basin; however, suitable chemical formulations, primarily surfactant/polymer combinations are still elusive. Considerable chemical testing is necessary to complement the Illinois Basin reservoir characteristics in order to move a project to pilot scale implementation.
The most pressing technical challenge is the design of a surfactant formulation that provides technical confidence (performance) for the reservoir brine and the crude oil. Notwithstanding, the areas of low/ultralow IFT, phase behavior and core flood are all key areas that need to demonstrate performance before implementing a field pilot program. Once a suitable surfactant formulation is determined, its stability, compatibility and performance with respect to the addition of polymer must also be understood and evaluated.
Targeted Goal: This project will focus on using the library of commercial surfactant products available in the EOR lab to find a suitable formulation for a target reservoir in the Illinois Basin. Once a surfactant formulation is determined through satisfactory phase behavior testing, Interfacial tension testing followed by core flood validation experiments will be carried out. Students should expect to learn about chemical enhanced oil recovery while performing experiments with surfactants, various brine solutions and oils.
The most pressing technical challenge is the design of a surfactant formulation that provides technical confidence (performance) for the reservoir brine and the crude oil. Notwithstanding, the areas of low/ultralow IFT, phase behavior and core flood are all key areas that need to demonstrate performance before implementing a field pilot program. Once a suitable surfactant formulation is determined, its stability, compatibility and performance with respect to the addition of polymer must also be understood and evaluated.
Targeted Goal: This project will focus on using the library of commercial surfactant products available in the EOR lab to find a suitable formulation for a target reservoir in the Illinois Basin. Once a surfactant formulation is determined through satisfactory phase behavior testing, Interfacial tension testing followed by core flood validation experiments will be carried out. Students should expect to learn about chemical enhanced oil recovery while performing experiments with surfactants, various brine solutions and oils.
Research categories:
Energy and Environment, Material Processing and Characterization
Preferred major(s):
- No Major Restriction
School/Dept.:
Chemical Engineering
Professor:
Nathan
Schultheiss
More information: https://engineering.purdue.edu/cheeor/
Identifying and reducing health and environmental impacts of plastic used to repair buried pipes
Description:
Drinking water and sewer pipes are decaying across the nation, and inexpensive methods for repairing these assets are being increasingly embraced. One method called cured-in-place-pipe (CIPP) involves workers chemically manufacturing a new plastic pipe inside an existing damaged pipe. This is the least expensive pipe repair method and, as such, is preferred by utilities and municipalities. The practice is often conducted outdoors and industry ‘best’ practice involves discharging the plastic manufacturing waste into the environment and nearby pipelines. Under some conditions, this waste finds its way into public areas and buildings prompted illnesses and environmental damage. Another consequence can be direct leaching of unreacted chemicals into water or volatilization of chemicals from the new plastic into air.
This project will involve the student working with a graduate student as well as leading experts on plastics manufacturing, chemistry, public health, civil/environmental engineering, and communications. The student will learn plastic manufacturing methods, environmental sampling and analysis methods, and participate in the process of reducing human health and environmental risks of the practice. To complete this work, the student will learn and apply infrastructure, environmental, and public health principles.
This project will involve the student working with a graduate student as well as leading experts on plastics manufacturing, chemistry, public health, civil/environmental engineering, and communications. The student will learn plastic manufacturing methods, environmental sampling and analysis methods, and participate in the process of reducing human health and environmental risks of the practice. To complete this work, the student will learn and apply infrastructure, environmental, and public health principles.
Research categories:
Composite Materials and Alloys, Energy and Environment, Engineering the Built Environment, Environmental Characterization, Other
Preferred major(s):
- Chemical Engineering
- Environmental and Ecological Engineering
- Civil Engineering
- Public Health
- Chemistry
- Environmental Health Sciences
Desired experience:
Strong interest in learning and applying scientific methods and techniques to help solve a pressing day problem; Basic understand of chemistry; General lab experience desirable as the student will help manufacture plastics in the lab using chemical formulations
School/Dept.:
CE & EEE
Professor:
Andrew
Whelton
Interpreting paleoclimate data from Antarctica using numerical models
Description:
Scientists study the Earth's past climate in order to understand how the climate will respond to ongoing global change in the future. One of the best analogs for future climate might the period that occurred approximately 3 million years ago, during an interval known as the mid-Pliocene Warm Period. During this period, the concentration of carbon dioxide in the atmosphere was similar to today's and sea level was 15 or more meters higher, due primarily to warming and consequent ice sheet melting in polar regions. However, the temperatures in polar regions during the mid-Pliocene Warm Period are not well determined, in part because we do not have records like ice cores that extend this far back in time. We are studying surface temperatures in Antarctica during the mid-Pliocene Warm Period using a new type of climate proxy, known as cosmogenic noble gas (CNG) paleothermometry. In this project, the SURF student will be involved with improving numerical models that we use to interpret CNG data.
Research categories:
Energy and Environment, Other
Preferred major(s):
- No Major Restriction
Desired experience:
Applicants should have an interest in climate science. Applicants who are rising juniors or seniors and who have experience coding with Python, MATLAB, or Julia are preferred.
School/Dept.:
Earth, Atmospheric, and Planetary Sciences
Professor:
Marissa
Tremblay
More information: https://www.purdue.edu/science/geochronology/thermochron/
Metal Polyselenide Chemistry for Photovoltaic Applications
Description:
Fabrication of metal chalcogenide semiconductors by solution-based methods is a promising route to inexpensive and high-throughput manufacturing of photovoltaic devices. However, these methods often rely on simple metal salts (such as metal halides, nitrates, or acetates) as precursors, and the anions in these salts can lead to impurities in the final product. To bypass this challenge, researchers have developed chemistries that allow for the dissolution of metal and metal chalcogenide precursors through a reactive dissolution that produces a soluble complex with metal-sulfur bonding. While this is suitable for the synthesis of metal sulfides, similar routes for metal selenides are lacking.
In this project, we investigate a new and facile route to directly produce soluble metal polyselenides and the application of these complexes as solution-phase precursors for metal selenide synthesis. Researchers will crystallize the metal polyselenides and utilize X-Ray Diffraction to determine the exact structure of the complexes. Additionally, researchers will utilize these precursors to make metal selenide thin films for application in solar cells. In this work, researchers will gain experience in chemical synthesis, thin-film fabrication, and materials characterization, while learning how these concepts can be applied to photovoltaics.
In this project, we investigate a new and facile route to directly produce soluble metal polyselenides and the application of these complexes as solution-phase precursors for metal selenide synthesis. Researchers will crystallize the metal polyselenides and utilize X-Ray Diffraction to determine the exact structure of the complexes. Additionally, researchers will utilize these precursors to make metal selenide thin films for application in solar cells. In this work, researchers will gain experience in chemical synthesis, thin-film fabrication, and materials characterization, while learning how these concepts can be applied to photovoltaics.
Research categories:
Energy and Environment, Material Processing and Characterization
Preferred major(s):
- Chemical Engineering
Desired experience:
General Chemistry-level lab experience
School/Dept.:
Davidson School of Chemical Engineering
Professor:
Rakesh
Agrawal
More information: https://engineering.purdue.edu/RARG/members/solar-energy/
Physics and Analytics of Lithium Batteries
Description:
Lithium ion (Li-ion) batteries are ubiquitous. Thermal, electrochemical, and degradation characteristics of these systems are critical toward safer and high-performance batteries for electric vehicles. As part of this research, physics-based and data-driven analytics of experimental and simulated performance under normal and anomalous operating conditions of lithium-ion and lithium metal batteries will be performed.
The final deliverable will be one research report (based on weekly progress presentations and updates) and one final presentation.
The final deliverable will be one research report (based on weekly progress presentations and updates) and one final presentation.
Research categories:
Energy and Environment, Material Modeling and Simulation, Material Processing and Characterization, Thermal Technology
Preferred major(s):
- No Major Restriction
Desired experience:
Strong analytical skill and desire to learn new experimental and modeling & analysis tools.
School/Dept.:
Mechanical Engineering
Professor:
Partha
Mukherjee
More information: https://engineering.purdue.edu/ETSL/
Physics-Informed Machine Learning to Improve the Predictability of Extreme Weather Events
Description:
Atmospheric blocking events and 'Bomb Cyclones' are an important contributor to high impact extreme weather events. Both these weather extremes lead to heat waves, cold spells, droughts, and heavy precipitation episodes, which have dire consequences for the public health, economy, and ecosystem. For example, the blocking-induced heat waves of 2003 in Europe led to tens of thousands of human casualties and tens of billions of dollars of financial damage.
Traditionally, prediction of extreme weather events is based on direct numerical simulation of regional or global atmospheric models, which are expensive to conduct and involve a large number of tunable parameters. However, with the rapid rise of data science and machine learning in recent years, this proposed work will apply convolutional neural network to an idealized atmospheric model to conduct predictability analysis of extreme weather events within this model. With this proposed machine-learning algorithm, our project will provide a robust forecast of heat waves and atmospheric blocking with a lead-time of a few weeks. With more frequent record-breaking heat waves in the future, such a prediction will offer a crucial period of time (a few weeks) for our society to take proper preparedness steps to protect our vulnerable citizens.
This project is based on developing and verifying the machine learning algorithm for detecting extreme weather events in an idealized model. We will use Purdue’s supercomputer Bell to conduct the simulations. The undergraduate student will play an active and important role in running the idealized model, and participate in developing the algorithms. As an important component of climate preparedness, the proposed work aims to develop a physics-informed machine learning framework to improve predictability of extreme weather events.
Closely advised by Prof. Wang, the student will conduct numerical simulations of an idealized and very simple climate model, and use python-based machine learning tools to predict extreme weather events within the model. Prof. Wang will provide weekly tutorial sessions to teach key techniques along with interactive hands-on sessions. The students will get access to the big datasets on Purdue’s Data Depot, analyze and visualize data of an idealized atmospheric model. The student will use convolutional neural networks (CNNs) to train and assess a Machine-Learning model. The student will further use feature tracking algorithm to backward identify the physical structure in the atmosphere that is responsible for the onset of extreme weather events.
Traditionally, prediction of extreme weather events is based on direct numerical simulation of regional or global atmospheric models, which are expensive to conduct and involve a large number of tunable parameters. However, with the rapid rise of data science and machine learning in recent years, this proposed work will apply convolutional neural network to an idealized atmospheric model to conduct predictability analysis of extreme weather events within this model. With this proposed machine-learning algorithm, our project will provide a robust forecast of heat waves and atmospheric blocking with a lead-time of a few weeks. With more frequent record-breaking heat waves in the future, such a prediction will offer a crucial period of time (a few weeks) for our society to take proper preparedness steps to protect our vulnerable citizens.
This project is based on developing and verifying the machine learning algorithm for detecting extreme weather events in an idealized model. We will use Purdue’s supercomputer Bell to conduct the simulations. The undergraduate student will play an active and important role in running the idealized model, and participate in developing the algorithms. As an important component of climate preparedness, the proposed work aims to develop a physics-informed machine learning framework to improve predictability of extreme weather events.
Closely advised by Prof. Wang, the student will conduct numerical simulations of an idealized and very simple climate model, and use python-based machine learning tools to predict extreme weather events within the model. Prof. Wang will provide weekly tutorial sessions to teach key techniques along with interactive hands-on sessions. The students will get access to the big datasets on Purdue’s Data Depot, analyze and visualize data of an idealized atmospheric model. The student will use convolutional neural networks (CNNs) to train and assess a Machine-Learning model. The student will further use feature tracking algorithm to backward identify the physical structure in the atmosphere that is responsible for the onset of extreme weather events.
Research categories:
Big Data/Machine Learning, Deep Learning, Energy and Environment, Environmental Characterization, Fluid Modelling and Simulation
Preferred major(s):
- Physics
- Planetary Sciences
- Atmospheric Science/Meteorology
- Computer Science
- Mathematics - Computer Science
- Mathematics
- Environmental Geosciences
- Mechanical Engineering
- Civil Engineering
- Aeronautical and Astronautical Engineering
- Computer Engineering
- Engineering (First Year)
- Multidisciplinary Engineering
- Natural Resources and Environmental Science (multiple concentrations)
Desired experience:
Familiar with Machine Learning or prior knowledge of convolutional neural networks (CNNs);
Have basic level training on PHYS172 Modern Mechanics or PHYS 15200 Mechanics or equivalent courses from other institutions; Familiar with Python scripting and visualization
School/Dept.:
Earth, Atmospheric, and Planetary Sciences
Professor:
Lei
Wang
More information: https://www.eaps.purdue.edu/people/profile/wanglei.html
Real-Time Measurements of Volatile Chemicals in Buildings with Proton Transfer Reaction Mass Spectrometry
Description:
The objective of this project is to utilize state-of-the-art proton transfer reaction mass spectrometry (PTR-MS) to evaluate emissions and exposures of volatile chemicals in buildings. My group is investigating volatile chemical emissions from consumer and personal care products, disinfectants and cleaning agents, and building and construction materials. You will assist graduate students with full-scale experiments with our PTR-MS in our new Purdue zEDGE Tiny House and process and analyze indoor air data in MATLAB.
Research categories:
Big Data/Machine Learning, Ecology and Sustainability, Energy and Environment, Engineering the Built Environment, Environmental Characterization, Human Factors, Internet of Things
Preferred major(s):
- No Major Restriction
Desired experience:
Preferred skills: experience with MATLAB, Python, or R. Coursework: environmental science and chemistry, physics, thermodynamics, heat/mass transfer, and fluid mechanics.
School/Dept.:
Lyles School of Civil Engineering
Professor:
Nusrat
Jung
More information: https://www.purdue.edu/newsroom/stories/2020/Stories%20at%20Purdue/new-purdue-lab-provides-tiny-home-for-sustainability-education.html
Renewable energy-powered water technologies
Description:
Water and energy are tightly linked resources that must both become renewable for a successful future. However, today, water and energy resources are often in conflict with one another, especially related to impacts on electric grids. Further, advances in nanotechnology, material science and artificial intelligence allow for new avenues to improve the widespread implementation of desalination and water purification technology. The team is pursuing multiple projects that aim to explore solar and wind-powered desalination, nanofabricated membranes, light-driven reactions, artificial intelligence control algorithms, and thermodynamic optimization of energy systems. The student will be responsible for fabricating membranes, building hydraulic systems, modeling thermal fluid phenomenon, analyzing data, or implementing control strategies in novel system configurations. More information here: www.warsinger.com
Research categories:
Big Data/Machine Learning, Chemical Catalysis and Synthesis, Ecology and Sustainability, Energy and Environment, Engineering the Built Environment, Environmental Characterization, Fluid Modelling and Simulation, Material Modeling and Simulation, Nanotechnology, Thermal Technology
Preferred major(s):
- Mechanical Engineering
- Civil Engineering
- Environmental and Ecological Engineering
- Chemistry
- Chemical Engineering
- Materials Engineering
Desired experience:
Applicants should have an interest in thermodynamics, water treatment, and sustainability. Applicants with experience in some (not all) of the following are preferred: experimental design and prototyping, manufacturing, Python, LabView, EES, MATLAB, 3D CAD Software, & Adobe Illustrator. Rising Juniors and Seniors are preferred.
School/Dept.:
Mechanical Engineering
Professor:
David
Warsinger
More information: www.warsinger.com
Sustainable Drinking Water Filtration Systems
Description:
Clean drinking water is a universal right, but on the global scale, we still struggle to provide water free of contaminants to everyone. By developing more efficient systems to purify water, we can expand the availability of clean drinking water and reduce the environmental impact of treatment operations. This project will explore the operation of reverse osmosis membranes as a means of efficiently purifying water.
Reverse osmosis membranes are traditionally an expensive and energy intensive drinking water treatment method, and the membranes can suffer from biofouling that reduce the life of the membrane. Operating reverse osmosis membranes intermittently has profound implications for energy savings, and is still an effective form of water treatment. It is unclear if these systems will also be subject to biofouling, or growth of organisms on and after the filter. In this project, the student will utilize real-time microbiology tools and community sequencing to measure and characterize the microbes able to survive fluctuating salinity levels. It is hypothesized that the fluctuations in salinity will prevent significant growth of any microorganisms, thus extending the life and optimizing the operation of reverse osmosis membranes.
Reverse osmosis membranes are traditionally an expensive and energy intensive drinking water treatment method, and the membranes can suffer from biofouling that reduce the life of the membrane. Operating reverse osmosis membranes intermittently has profound implications for energy savings, and is still an effective form of water treatment. It is unclear if these systems will also be subject to biofouling, or growth of organisms on and after the filter. In this project, the student will utilize real-time microbiology tools and community sequencing to measure and characterize the microbes able to survive fluctuating salinity levels. It is hypothesized that the fluctuations in salinity will prevent significant growth of any microorganisms, thus extending the life and optimizing the operation of reverse osmosis membranes.
Research categories:
Biological Characterization and Imaging, Ecology and Sustainability, Energy and Environment, Engineering the Built Environment
Preferred major(s):
- No Major Restriction
Desired experience:
Biology or engineering background. Lab skills in drinking water characterization, microbiology (e.g. culture plating), or mechanical engineering are desired but not required.
School/Dept.:
Environmental and Ecological Engineering
Professor:
Caitlin
Proctor
Testing and analysis of simulated reactor cavity building depressurization experiments
Description:
The main goal of the research is to perform tests on an experimental facility that simulates nuclear reactor building response in the event of a depressurization accident caused by a break in the primary coolant boundary of a high temperature nuclear reactor and obtain first-of-a-kind data on the oxygen concentration distribution for validation of reactor safety codes and Computational Fluid Dynamics (CFD) models.
The SURF researcher will: (i) Participate in an experimental testing program along with team members- test preparation-that include checking loop, instruments, conduct of tests, and data acquisition. (ii) Suppot data analysis. (iii) Support CFD analysis using ANSYS-FLUENT
The SURF researcher will: (i) Participate in an experimental testing program along with team members- test preparation-that include checking loop, instruments, conduct of tests, and data acquisition. (ii) Suppot data analysis. (iii) Support CFD analysis using ANSYS-FLUENT
Research categories:
Energy and Environment, Fluid Modelling and Simulation
Preferred major(s):
- Nuclear Engineering
- Mechanical Engineering
Desired experience:
Fluid mechanics, thermodynamics, heat transfer, nuclear engineering courses. Prefer previous experience in Experimental work on thermal and fluid systems, CFD such as ANSYS - FLUENT. Willingness to learn and work with a team on a thermalhydraulics test facility
School/Dept.:
School of Nuclear Engineering
Professor:
Shripad
Revankar
Thermal management of electronic devices
Description:
The continued miniaturization of electronic devices, with expanded functionality at reduced cost, challenges the viability of products across a broad spectrum of industry applications. The electronics industry is driven by global trends in storage, transmission, and processing of extreme quantities of digital information (cloud computing, data centers), increasing electrification of the transportation sector (electric vehicles, hybrid aircraft, batteries), and the proliferation of interconnected computing devices (mobile computing, IoT, 5G). Proper thermal management of electronic devices is critical to avoid overheating failures and ensure energy efficient operation. In view of these rapidly evolving markets, most of the known electronics cooling technologies are approaching their limits and have a direct impact on system performance (e.g., computing power, driving range, device size, etc.).
Research projects in the Cooling Technologies Research Center (CTRC) are exploring new technologies and discovering ways to more effectively apply existing technologies to addresses the needs of companies and organizations in the area of high-performance heat removal from compact spaces. One of the distinctive features of working in this Center is training in practical applications relevant to industry. All of the projects involve close industrial support and collaboration in the research, often with direct transfer of the technologies to the participating industry members. Projects in the Center involve both experimental and computational aspects, are multi-disciplinary in nature, and are open to excellent students with various engineering and science backgrounds. Multiple different research project opportunities are available based on student interests and preferences.
Research projects in the Cooling Technologies Research Center (CTRC) are exploring new technologies and discovering ways to more effectively apply existing technologies to addresses the needs of companies and organizations in the area of high-performance heat removal from compact spaces. One of the distinctive features of working in this Center is training in practical applications relevant to industry. All of the projects involve close industrial support and collaboration in the research, often with direct transfer of the technologies to the participating industry members. Projects in the Center involve both experimental and computational aspects, are multi-disciplinary in nature, and are open to excellent students with various engineering and science backgrounds. Multiple different research project opportunities are available based on student interests and preferences.
Research categories:
Big Data/Machine Learning, Energy and Environment, Fluid Modelling and Simulation, Material Modeling and Simulation, Nanotechnology, Thermal Technology
Preferred major(s):
- No Major Restriction
School/Dept.:
School of Mechanical Engineering
Professor:
Justin
Weibel
More information: https://engineering.purdue.edu/CTRC/research/
Understanding Nanosilica in Concrete Science for Low Carbon Materials
Description:
The project’s goal is to improve the properties of concrete by the incorporation of nano silica. The performance of the concrete such as strength and durability will be evaluated. In this project, the student will be trained to conduct the related experiments and learn how to analyze the data. Undergraduate student works will include the concrete preparation, scanning electron microscope (SEM), pore structure evaluation, and data analysis.
Research categories:
Energy and Environment, Engineering the Built Environment
Preferred major(s):
- No Major Restriction
School/Dept.:
civil engineering
Professor:
Luna
Lu
More information: https://engineering.purdue.edu/SMARTLab
Validation of Miniature Coreflood Equipment for Chemical Package Evaluation in the Petroleum Industry
Description:
Challenge: Over the lifespan of a typical oil well one can expect to recover only 20-40% of the total oil in a field, to access the remaining 60-80% advanced technological solutions need to be leveraged. One solution is chemical enhanced oil recovery (cEOR), this technique utilizes a field specific chemical package, consisting of surfactants, polymers, and brine solutions, to mobilize and sweep the remaining oil. In the laboratory we can recreate the subsurface environment and optimize the chemical package to maximize oil recovery through coreflood testing. However, these tests are expensive and it takes weeks to complete a single test. By decreasing the time and cost required to obtain an optimal chemical package, by means of higher throughput, it is expected that cEOR could become a more widely utilized recovery technique.
Target Goal: This project will have both a background review and a hands-on (in laboratory) component with the possibility of being an author in future publications. The initial literature review will introduce the student(s) to the cEOR methodology and industry standards. Once a thorough understanding of accepted processes is obtained the student(s) will begin working on the miniaturized coreflood apparatus designing experiments and performing tests. The student(s) will use the collected data to evaluate the miniature coreflood device performance, throughput, and finally compare results with data collected on a larger, lab-scale coreflood device. Ultimately, the time and cost savings will also be evaluated, and device usefulness will be assessed.
Target Goal: This project will have both a background review and a hands-on (in laboratory) component with the possibility of being an author in future publications. The initial literature review will introduce the student(s) to the cEOR methodology and industry standards. Once a thorough understanding of accepted processes is obtained the student(s) will begin working on the miniaturized coreflood apparatus designing experiments and performing tests. The student(s) will use the collected data to evaluate the miniature coreflood device performance, throughput, and finally compare results with data collected on a larger, lab-scale coreflood device. Ultimately, the time and cost savings will also be evaluated, and device usefulness will be assessed.
Research categories:
Energy and Environment
Preferred major(s):
- No Major Restriction
School/Dept.:
Chemical Engineering
Professor:
Nathan
Schultheiss
More information: https://engineering.purdue.edu/cheeor/