There are two related projects, both focused on making air safe, including from bioaersols like COVID.

1) Photocatalysis for Air Purification: Photocatalysis is one method for helping degrade harmful airborne particles, like COVID-19, which our lab is investigating in a partnership with a start-up company. Undergraduates interested in designing experimental setups and microbiological experiments are well-suited for this project. Candidates with experience in culturing microorganism/relevant wet lab experience is preferred.

2) Acoustic removal of aerosols: Sound waves can interact with small particles like aerosols, and be used to manipulate their motion. In this project, we aim to invent the first system that can make air safe with sound waves.

Biological Characterization and Imaging, Biological Simulation and Technology, Energy and Environment, Engineering the Built Environment, Fluid Modelling and Simulation, Material Modeling and Simulation, Material Processing and Characterization, Nanotechnology

• No Major Restriction

All applicants should have an interest in photochemistry, microbiology, aerosol sciences, and experimental research. In addition to the required skills mentioned in the points above, applicants with additional experience with some of the following programs are preferred: Python and Adobe Illustrator. What experience will you gain? • Hands on research experience and potential co-authorship in high impact journals • Application of engineering fundamentals to important societal problems • Research credit hours (and potential opportunities for financial compensation in the summer) • Networking opportunities with academic and industry leaders

Mechanical Engineering

David Warsinger

This project is supported by CISTAR, an NSF Engineering Research Center headquartered at Purdue
Electrification of industrial processes is being frequently mentioned as an option to reduce greenhouse gas emissions from energy-intensive industries. Electricity is a versatile energy carrier which presents a variety of electrification options. The increasing availability of cheap renewable electricity provides an opportunity to decarbonize energy intensive processes. As part of this decarbonization effort, the commodity chemical industry is an important target due to its large energy requirements and greenhouse gas emissions. One potential paradigm for electrification involves replacing the use of steam, generated by burning fossil fuels, as a source of heat in chemical processes to processes with direct electrical heating using renewable energy sources. This project aims to identify and quantify areas where energy is currently transferred by steam can be efficiently transferred by renewable electrification. The target commodity chemicals are ammonia, ethylene, propylene, and methanol.

Students working on this project will also have the opportunity to participate in information sessions, tours and informal mentoring with CISTAR's partner companies.

Purdue students are not eligible for this project. Students must be from outside institutions. Participants must be US Citizens. Students with disabilities, veterans, and those from traditionally underrepresented groups in STEM are encouraged to apply.

More information: https://cistar.us/

Chemical Unit Operations, Chemical Catalysis and Synthesis, Energy and Environment

• Chemical Engineering

Chemical Engineering

Cornelius Masuku

In the coming years, countries around the world will make concerted efforts to decarbonize various industries and technologies to help prevent and reverse climate change. Currently, thermal dehydration accounts for 10-20% of all industrial energy consumption and relies heavily on the combustion of fossil fuels. Vapor compression heat pumps, like those used in building air conditioners, offer a high-efficiency, electrically driven heat source for industrial drying applications, however there are many barriers preventing broad implementation. Our team at Purdue has proposed a new thermal drying system concept that employs unique materials and exploits clever thermodynamic design to provide up to 40% energy and emissions savings. As part of this work, we are developing system models/simulations, designing and building prototype systems, and performing advanced materials research, thus providing a breadth of exciting opportunities for aspiring scientists and engineers. This research is also heavily tied to our work on energy efficient thermal systems for buildings and water/energy sustainability, and the student who joins the project will be exposed to many research topics within the Water-Energy Nexus.

Composite Materials and Alloys, Energy and Environment, Engineering the Built Environment, Fluid Modelling and Simulation, Material Modeling and Simulation, Material Processing and Characterization, Microelectronics, Nanotechnology, Thermal Technology

• No Major Restriction

Applicants should have a general interest in energy and sustainability. Should also have a strong background/interest in thermodynamics, heat transfer, and/or materials science. 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.

Mechanical Engineering

Jim Braun

Drones and small unmanned aerial vehicles (UAVs) less than 25 kg, have a wide range of applications, such as surveying and mapping, search and rescue, monitoring and inspecting infrastructures, monitoring crops, delivery goods and services, surveillance, and military operations. In fact, advanced aerial mobility is forecast to be a $1.5 trillion market by the year 2040. However, the short flight endurance (operation time, range, and/or payload) of battery-powered drones and small UAVs has been a long-standing bottleneck that restricts their application in many fields. Currently, a small consumer drone can fly for about 10 minutes on a full battery charge and a professional drone with a larger battery capacity can fly for up to 30 minutes. While this duration may be sufficient for hobbyists, it is not enough for extended surveillance and monitoring missions. Therefore, there is an urgent need for drones with longer flight durations. The goal of this project is to explore novel concept of energy storage and propulsion solutions for drones and UAVs to extend its flight duration. The SURF student will work with closely with the faculty advisor and a PhD student on both experimental and theoretical studies on hybrid propulsion systems.

Energy and Environment

• aerospace engineering
• mechanical engineering
• electrical engineering

We are looking for students who possess design and hands-on experience, preferably with prior research in the area of propulsion. Previous research in this field is highly desirable.

School of Aeronautics & Astronautics

Li Qiao

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/

Energy and Environment, Material Processing and Characterization, Nanotechnology

Chemical Engineering

Letian Dou

High temperature gas-cooled reactors (HTGR) designs are likely candidates for the Next Generation Nuclear Plant (NGNP) due to their varied potential applications including process heat for chemical reactions and direct (Brayton) cycle power conversion. An HTGR fault that needs study is a break in the primary coolant boundary that leads to depressurization of the reactor vessel and loss of forced cooling of the core. In this accident, although most air in the reactor cavity and surrounding building is initially swept out by the helium, any remaining air in this space and the air re-entering from the surrounding building cavities can enter the primary coolant circuit through the break, and can cause severe damage to the graphite structures via oxidation. The amount of air entering the pressure vessel is a complex function of the primary helium inventory, and the discharged helium that displaces, and mixes, with the air in the cavity. A test facility is now built to simulate these phenomena and currently tests are conducted. The SURF students will help in conducting tests using test procedures, and acquiring data for various test condition such as helium flow rate, pressure and temperature and preform data analysis. Adequate training and background will be provided to perform the tests. It is team project with faculty, graduate students and undergraduate students.

Energy and Environment, Fluid Modelling and Simulation, Thermal Technology

• Mechanical Engineering, Nuclear Engineering, Chemical Engineering, Indutrial Engineering, Electrical Engineering
• Nuclear Engineering
• Physics

Course work in fluid mechanics, heat transfer desirable, aptitude to work on experiments, interest in developing laboratory skill, willing to work in team and learn

School of Nuclear Engineeing

Shripad Revankar

The project goal is to investigate the trends in next generation mobility in the US as evidenced by bike-sharing ridership and electric vehicle (EV) ownership. Objectives include: i) exploring the effect of the urban built environment and demographical fabric on the usage of bike-sharing; ii) forecasting EV ownership rates in the future considering the influence of incentives, new technologies, and barriers. The student candidate will collect historical data available from public sources such as US Census, US Department of Energy, FHWA and other sources and compile with bike-sharing ridership data from an open- source website, EV registration data and other survey data collected by the mentor/faculty advisor. Using these data, a baseline model (which can be a time series model, or any machine learning model) will be developed that will incorporate the effects of influencing factors affecting bike-sharing ridership and/or EV ownership. The student will get an opportunity to work with scholars in the STSRG group as well as to collaborate with the ASPIRE Engineering Research Center.

Big Data/Machine Learning, Energy and Environment, Engineering the Built Environment, Other

• No Major Restriction

- Knowledge of MS Excel and programming (R, Python, C++, Java) - Basic knowledge or course work in statistics (regression, time series) - Data analysis skills including downloading, cleaning, and merging different datasets

Civil Engineering

Nadia Gkritza

This project deals with study of heat transfer in very thin film materials using Raman Spectroscopy and Ultrafast laser systems. 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.

Energy and Environment, Nanotechnology, Thermal Technology

• Mechanical Engineering
• Physics

Thermoscience courses, interests in hands-on experiments, GPA>3.5

Mechanical Engineering

Xianfan Xu

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.

Energy and Environment, Material Modeling and Simulation, Material Processing and Characterization, Thermal Technology

Strong analytical skill and desire to learn new experimental and modeling & analysis tools.

Mechanical Engineering

Partha Mukherjee

Water infrastructure is critical to the safety and economic health of communities. The restoration and maintenance of water supply and wastewater infrastructure are ongoing challenges for the Nation. Cured-in-place pipe (CIPP) composites technology is a popular method for repairing buried sewer pipes. CIPP technology is also now growing in popularity for repairing drinking water pipes. This is due in large part to economic considerations, as it can be 60-80% less costly than other repair alternatives. Unfortunately, the process of curing (polymerizing) the new plastic inside the damaged pipe can release hazardous materials into the air. For drinking water applications, the CIPPs can allow chemicals to leach into drinking water. Chemical air releases have resulted in illness to members of the general public and workers, and contributed to one worker fatality. The overall goal of this research is to reduce chemical volatilization from CIPP by understanding mechanisms of chemical release. This research directly addresses multiple National Academy of Science, Engineering, and Medicine grand challenges focused on restoring infrastructure, sustainably supplying water, building healthy cities, and reducing pollution.

The student will work with a graduate student and help evaluate chemical emissions during plastic manufacture using heat and steam. Sewer and drinking water resins will be explored. The student will help conduct the laboratory experiments, sample analysis, data analysis, interpretation, and reporting. Results will be shared with health officials, municipalities, and regulators after study completion. Prior studies where undergraduates have contributed on this topic can be found on the website listed below.

Composite Materials and Alloys, Energy and Environment, Engineering the Built Environment, Environmental Characterization, Material Processing and Characterization

• No Major Restriction

Strong work ethic and commitment to learn and apply knowledge.

Lyles School of Civil Engineering

Andrew Whelton

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.

Big Data/Machine Learning, Ecology and Sustainability, Energy and Environment, Engineering the Built Environment, Environmental Characterization

• No Major Restriction

Preferred skills: experience with MATLAB, Python, or R. Coursework: environmental science and chemistry, physics, thermodynamics, heat/mass transfer, and fluid mechanics.

Lyles School of Civil Engineering

Nusrat Jung

Chalcogenide Perovskites are an exciting class of semiconducting materials that may be useful in a variety of applications, including solar energy harvesting. These materials take an ABX3 composition where A is an alkaline earth metal (Ca, Sr, Ba), B is an early transition metal (Zr, Hf), and X is a chalcogen (S, Se). While preliminary work has shown that these materials have many interesting properties, the synthesis of these chalcogenide perovskites has proven to be very difficult, often requiring excessively high temperatures around 1000 C. Our group has recently made progress in developing lower-temperature methods (below 600 C) to make BaZrS3 and BaHfS3 using soluble molecules that contain bonds between the desired metal and chalcogen. However, this chemistry is relatively unexplored, and tuning the soluble molecules may enable other chalcogenide perovskites and related materials to be synthesized.
In this project, we will investigate the synthesis of new metal-chalcogen bonded molecules and investigate how changes in the structure of the molecules affect their solubility and decomposition. The student on this project will develop skills in chemical handling and synthesis, thin film fabrication, materials characterization, and laboratory safety. Specifically, they will get to work in gloveboxes and utilize techniques such as X-ray diffraction, Raman spectroscopy, and X-Ray fluorescence. Additionally, the student will learn how solution-based chemistry can be applied to the fabrication of solar cells and other semiconductor devices.

Energy and Environment, Material Processing and Characterization, Nanotechnology

• Chemical Engineering
• Chemistry
• Materials Engineering

General chemistry with lab

Chemical Engineering

Rakesh Agrawal

Today’s structures are highly engineered buildings and bridges capable of carrying everyday and extreme loads. In this project, students will get to work on understanding blast engineering design with a special focus on building materials like concrete and steel. Undergraduate researchers will work day-to-day alongside graduate students and permanent staff to create test plans, fabricate test specimens, and test large-scale structures to failure. Students will leave this summer with a greater understanding of engineering principles including structural dynamics, impact and blast loading, and composite behavior.

Composite Materials and Alloys, Energy and Environment, Engineering the Built Environment, Other

• No Major Restriction
• Civil Engineering
• Mechanical Engineering
• Mechanical Engineering Technology
• Aeronautical and Astronautical Engineering
• Aeronautical Engineering Technology
• Construction Engineering
• Construction Management Technology
• Engineering (First Year)
• Materials Engineering

Willing to work in a large-scale structural testing facility which may include some manual labor.

Civil Engineering

Amit Varma

Plastics are ubiquitous in many facets of our lives, and the plastics industry is the third-largest manufacturing sector in the United States. But as plastics production develops rapidly, the long-term environmental challenges are globally recognized. Chemically resistant plastic products have extremely long lifetimes before completely decomposing — a single-use coffee pod can last 500 years in a landfill. Plastic waste accumulation has led to pollution that affects land, waterways and oceans; organisms are being harmed by entanglement or ingestion.

Closed-loop circular utilization of plastics is of manifold significance, yet energy-intensive and poorly selective scission of the ubiquitous carbon-carbon (C-C) bonds in contemporary commercial polymers pose tremendous challenges to envisioned recycling and upcycling scenarios. Our group focuses on a unique topochemical approach for creating elongated C-C bonds with a bond length of 1.57~1.63 Å (in contrast to conventional bonds with a C-C bond length of ~1.54 Å) between repeating units in the solid state with decreased bond dissociation energies. These polymers with elongated and weakened C-C bonds exhibit rapid depolymerization within a desirable temperature range (e.g., 140~260 °C), while otherwise remaining remarkably stable under harsh conditions.

Students will get involved in the following research activities:

1. Synthesis of novel polymer single crystals via topochemical approach
2. Synthesis of polymers with elongated and weakened C-C bonds for circular utilization
3. Processing, characterization, and practical application of chemically recyclable (depolymerizable) polymer single crystals and polyolefin materials.

Chemical Catalysis and Synthesis, Ecology and Sustainability, Energy and Environment, Material Processing and Characterization

• No Major Restriction

Davidson School of Chemical Engineering

Letian Dou

The project goal is to determine how manufacturing workers in the Midwest value different attributes of their jobs that may be impacted by a transition to decarbonized manufacturing. The undergraduate researcher would work with the research team to coordinate and process structured interviews with workers in the steel industry, assist with recruiting for a choice-based-conjoint survey, and conduct preliminary data analysis based on interview and survey data. Some overnight travel (Indiana, Ohio) may be required, and expenses would be covered by project funds.

Energy and Environment, Human Factors

• No Major Restriction

Prior experience conducting interviews or surveys is a plus, as is experience with Python.

Mechanical Engineering

Rebecca Ciez

Synopsis: The goal of this project is to apply quantum mechanics-based density functional theory simulations and machine learning to design novel halide perovskites with targeted photovoltaic, surface, and adsorption behavior for improved photocatalytic performance.

Targeted Need: Challenges of environmental pollution, global energy shortage, and overreliance on fossil fuels can be addressed using photocatalysis, where solar energy is harnessed for chemical processes such as hydrogen production, degradation of pollutants, and CO2 reduction [1]. Many semiconductors have been used as photocatalysts based on suitable band edge positions relative to redox potentials, strong optical absorption, and desirable adsorption and desorption of chemical species; examples include TiO2, Ga2O3, C3N4, CdS, and ZnS [2]. However, many limitations exist owing to wider than desired band gaps, ineffectiveness of charge carriers, and formation of harmful defects, motivating the search for novel and improved materials. Cheap and high-performing photocatalysts can also help avoid the use of transition or precious metals such as Pt and Pd as catalysts [3]. The chemical space of potential semiconductor photocatalysts is massive and not conducive to brute-force experimentation or even computation, which necessitates the use of data-driven strategies combining large computational datasets and state-of-the-art machine learning [4], prior to experimental validation and discovery.

Opportunity: Metal halide perovskites (HaPs) have risen in prominence for solar and related optoelectronic applications, and are suggested as promising photocatalysts. Recent publications report the use of MAPbI3, MAPbBr3 (MA=methylammonium), CsPbI3, Cs2BiAgBr6, and other single/double inorganic/hybrid perovskites, either in bulk crystalline form, 2D variants, nanoclusters, or as part of heterostructures, for water splitting, CO2 reduction, and organic synthesis [1,2]. However, this field remains very much in its infancy—HaPs are desirable photovoltaic (PV) materials with extremely tunable properties, but an exhaustive study of band edges, surface energies, and adsorption behavior across a wide chemical space is missing. Using high-throughput density functional theory (HT-DFT) computations, our research group has developed an initial dataset of the stability, band gap, and optical absorption characteristics of ABX3 HaPs with mixing at A, B, or X sites using common elemental or molecular species [5]. This provides the starting point for exploring photocatalytic activity of HaPs as a function of composition, phase, and surface orientation, by combining HT-DFT with machine learning (ML). Since DFT computations are expensive and cannot be performed endlessly, ML models trained on DFT data can help predict optical, electronic, surface, and adsorption properties of millions of new perovskite compositions, to accelerate by several orders of magnitude the screening of novel HaPs with a suitable combination of properties for catalyzing reactions.

Objectives: In this project, a HT-DFT+ML prediction, screening, and design approach will be applied to discover novel HaP compositions that display desired stability, optical absorption, surface stability, and activity towards species, for next-generation photocatalysis of technologically-important chemical processes, including CO2 reduction, H2 and O2 evolution (water splitting), and synthesis of various hydrocarbons. Specific objectives include: (i) using the existing DFT dataset of HaP crystal structures to build surface slabs, calculate surface energies, and adsorption energies of various molecules on stable surfaces, (ii) unique encoding of each material (descriptors) in terms of structure, composition, surface atoms, adsorbing species, etc. [4], and (iii) training of ML models based on regression techniques such as random forests and neural networks, ensuring rigorous optimization of hyperparameters, training data size, input dimensions, and applicability towards any new data point.

Role of Student Researcher: Using our available codes, software, and computing resources, students can quickly start running and analyzing simulations of photocatalytic properties. A variety of existing schemes can be applied and tested for numerical representation/description of materials and property prediction, such as using graph convolutional neural networks (GCNNs) for automatic crystal structure representation, which our group has good experience with. Student will carry out DFT and ML tasks under the guidance of a graduate student and the professor, and will be given the opportunity to lead one or two potentially high-impact journal publications. Given the prior work that has gone into this project, chances of success are very high, and future prospects will be plenty.

References
1. J. Yuan et al., Nanoscale, 13, 10281 (2021).
2. K. Ren et al., Journal of Materials Chemistry A, 10, 407 (2022).
3. Z. Luo et al., Nature Communications, 11, 4091 (2020).
4. J. Schmidt et al., npj Computational Materials, 5, 83 (2019).
5. A. Mannodi-Kanakkithodi et al., Energy and Environmental Science, 15, 1930-1949 (2022).

Big Data/Machine Learning, Chemical Catalysis and Synthesis, Energy and Environment, Material Modeling and Simulation

• No Major Restriction

Any experience with coding and/or data science will be useful, but not necessary. If student has taken courses on fundamentals of materials science, that will be helpful.

Materials Engineering

Arun Kumar Mannodi Kanakkithodi