The application process for summer 2022 fellowships is now closed. Information is provided for reference only.

Application Instructions

Chang Nurf 2019Fellowship recipient Alfred Chang

1) Review the summer 2022 NURF project descriptions (below) and select a project of interest.

2) Complete the APPLICATION, and save the file with your last name and your first name as the first words in the file name. (Ex: Smith-Barb 2022 NURF Application)

3) By 8:00am Eastern on February 9, email your completed application and current resumé (saved with the same name convention -- Smith-Barb 2022 NURF resumé) to the project’s faculty mentor(s) for consideration, and cc: NDnano faculty will follow-up with selected applicants directly. Award notifications will begin in early March.

Students are welcome to apply for more than one project. However, please list and prioritize on your application(s) all the projects for which you are applying. Please include project title and faculty first/last name.


Review the Frequently Asked Questions or feel free to contact Heidi Deethardt

Please Note

For purposes of the NURF program, undergraduates are students who will not yet have completed their undergraduate studies at the start of their summer fellowship.

The University allows students to work a maximum of 40 hours per week during the summer (all campus jobs combined). This means that students cannot participate in the NURF program on a full-time basis and at the same time hold any other paid, on-campus, summer position. (Fellowships of less than 40 hours per week would be considered on a case-by-case basis.)

In addition, fellowship recipients who attend Notre Dame and have 2021-2022 on-campus, academic-year jobs may have restrictions on their NURF start date; contact Heidi Deethardt for more details. 

Summer 2022 NURF Project Descriptions

Project: Improving sensitivity of infrared nanoantenna detectors

Faculty mentors:
Professor Gary H. Bernstein • Electrical Engineering • 225 Cushing Hall • 574-631-6269 • (Send applications to Professor Bernstein)

Professor Edward Kinzel • Aerospace & Mechanical Engineering • 377 Fitzpatrick Hall • 574-631-8941 •

Professor Bernstein is member of a group of NASA-funded researchers developing novel infrared (IR) sensors, called thermoelectrically coupled nanoantennas (TECNAs), that can be tuned well into the long-wave infrared, namely from wavelengths as short as 5 microns to those exceeding 200 microns. These long wavelengths are not easily detected by conventional technology. Our sensors are based on nanoantennas (50 nm wide and thick, few microns long) that are suspended over a silicon reflecting cavity, much like a satellite dish is constructed. The resonant wavelengths create current flow on the TECNA, heating the antenna and creating a voltage in a nanothermocouple. TECNAs have many advantages over conventional IR detectors, including small size and weight and low power (due to room-temperature operation), high-speed, wavelength selectivity, and polarization sensitivity. The NASA-funded project includes the use of the antennas on a terrestrial telescope whose purpose is to view the Sun at various IR wavelengths. We have identified many paths to improving the sensitivity of our TECNAs, including using various materials for the antenna and the thermocouple, operating in a vacuum to decrease heat conduction, and changing the properties of the reflecting cavity. A student working on this project will work in the laboratory developing a vacuum chamber for testing with the goal toward future satellite applications. Also, the student will learn to use COMSOL simulation tools and perform device modeling. 


Project: First-principles calculations of thermoelectric properties in nanothermocouples

Faculty mentors:
Professor Gary H. Bernstein • Electrical Engineering • 225 Cushing Hall • 574-631-6269 • (Send applications to Professor Bernstein)

Professor Erik Blair • Electrical & Computer Engineering • Baylor University

Professor Bernstein is a member of a group of NASA-funded researchers developing novel infrared (IR) sensors, called thermoelectrically coupled nanoantennas (TECNAs), that can be tuned well into the long-wave infrared, namely from wavelengths as short as 5 microns to those exceeding 200 microns. These long wavelengths are not easily detected by conventional technology. Our sensors are based on nanoantennas (50 nm wide and thick, few microns long) that are suspended over a silicon reflecting cavity, much like a satellite dish is constructed. The resonant wavelengths create current flow on the TECNA, heating the antenna and creating a voltage in a nanothermocouple. TECNAs have many advantages over conventional IR detectors, including small size and weight and low power (due to room-temperature operation), high-speed, wavelength selectivity, and polarization sensitivity. The NASA-funded project includes the use of the antennas on a terrestrial telescope whose purpose is to view the Sun at various IR wavelengths. Fruitful, ongoing experimental work continues to improve the sensitivity of TECNAs, but theoretical and calculational work may clarify physical processes that affect device performance. In one design, a single-metal nanothermocouple (SM-NTC) converts a thermal gradient into a voltage. It is known that the geometry of the SM-NTC may be optimized for sensitivity, but the mechanism for this effect has not yet been described at the atomistic level. A student working on this project will develop first-principles calculations of electron scattering in nanostructures. The student will use computational tools including Python and open-source atomistic modeling software such as OpenMX DFT to study the thermoelectric properties of arbitrary nanostructures. The student will develop and perform calibration calculations on simple 1D structures and 2D structures such as graphene. The objective here is to develop computational workflows that can be scaled to the larger 3D systems. These computational workflows will help explore how device geometry affects thermoelectric properties of the SM-NTCs. The student must have computer programming experience and have some familiarity with or willingness to learn elementary semiconductor devices and physics.



Project: Advanced integrated circuit design for sustainable privacy-preserving wireless resource allocation

Faculty mentor:
Professor Ningyuan Cao • Electrical Engineering • 221 Cushing Hall • 574-631-6618 •

Cao 2022 Nurf Image

The major objective of the summer project is to investigate hardware/software co-design methods that enable wireless resource management on encrypted data under time and energy constraints for mobile ad-hoc networks (MANET). With billions of wirelessly connected devices and emergence of 6G technology, wireless spectrum, antenna power, D2D mode, network connection, etc., have become highly constrained resources that require real-time management for optimized global throughput and/or minimized network congestion. This is particularly demanding for MANETs, where the channel condition and network topology constantly change overtime. However, for a base station to make decisions for optimization, two major concerns for individual users are data security and fairness: whether my information (location, radio configuration, etc.) will leak and whether the base station is making unbiased decisions. This problem can be theoretically solved by full homomorphic encryption (FHE), where the server can conduct full mathematical operations on encrypted data without knowing the content of data as well as the result. Only individual nodes with private keys can decipher the final result. However, due to the intensive FHE computation operations (106-1012x overhead) and lack of cryptographic algorithm for wireless networks, a secure and fair wireless source allocation sustainable implementation that meets time (<1ms) and energy (<mW) requirements requires thorough investigation.

The project is organized in these major tasks:

  1. Privacy-preserved algorithm design: inspired by recent studies on graph-based wireless resource allocation (REGNN, Ising Machine) and end-to-end cryptographic machine learning algorithm (Crypto-NET), this sub-task works on advanced privacy-preserving algorithms for global optimization while leveraging highly parallel computation architecture for hardware acceleration.
  2. Software implementation and simulation: the task will emulate large scale mobile networks with high-definition wireless communication modeling to validate algorithm performance.
  3. Hardware implementation: the validated algorithm will be implemented with both off-the-shelf processors (CPU, GPU, FPGA) as well as customized solid-state implementation on state-of-the-art techniques (compute-in-memory, quantum-inspired analog computation, network-on-chip, etc.).

As such, this research program presents an opportunity to make significant progress toward secure and unbiased collaborative decision making, which will lead to a more secure and equally connected society in the long run. Students will get trained with full-stack capabilities, including python programming, wireless communication simulation, hardware optimization, circuit design and simulation and so on. Students with a background in computer science, computer architecture, communication, circuit design, devices are all welcome to apply.



Project: Nanocatalytic membranes for water treatment

Faculty mentors:
Professor Kyle Doudrick • Civil and Environmental Engineering and Earth Sciences • 166 Fitzpatrick Hall • 574-631-0305 • (Send applications to Professor Doudrick)

Professor William A. Phillip • Chemical & Biomolecular Engineering • 205F McCourtney Hall • 574-631-2708 •

Membranes are an effective water treatment method for physically separating out contaminants from the source water. While this produces a clean water, it does not really solve the problem as the contaminant still needs to be degraded to reduce its toxicity. Catalysts are an effective method for destroying contaminants, but they are not used at commercial scales due to their high cost (e.g., palladium). Costs can be reduced by decreasing the size of the catalysts so less mass can be used while still achieving the same treatment efficiency. This, however, is challenging to implement in a reactor setting. This project marries the two concepts with the goal of developing polymeric membranes loaded with metal nanocatalysts for treating recalcitrant contaminants found in drinking water. The student’s roles in this project will be: synthesizing the catalytic membranes, testing the membranes, analyzing data, and disseminating results to the group via presentations and writings. Students should have a strong background or understanding of basic chemistry with a preferred academic discipline in either environmental engineering or chemical engineering (or closely related).



Project: Molecular and process design framework for the separation, recycling, and reuse of hydrofluorocarbon mixtures

Faculty mentors:
Professor Alexander W. Dowling • Chemical & Biomolecular Engineering • 369 Nieuwland Hall • 574-631-4041 •

Professor Edward J. Maginn • Chemical & Biomolecular Engineering • 250 Nieuwland Hall • 574-631-5687 •

Dowling Maginn NURF Image 2020Figure 1. The proposed framework integrates mixture physical property measurements, atomistic molecular simulations, process optimization, and demonstration to create innovative ionic liquid mixtures and separation processes that could enable global recycling of HFCs. The student researcher will work with a graduate student on molecular simulations and data analysis (Specific Aims 2 and 3).

Refrigerators and heat pumps use a substance called a refrigerant to transfer heat between two spaces. Prior to the late 1980s, refrigerants often contained chlorfluorocarbons, but these materials were phased out because of their high ozone depletion potential. Mixtures of hydrofluorocarbons appeared on the market as a replacement. Hydrofluorocarbons (HFC) do not deplete the Earth's ozone layer, but many are potent greenhouse gases with much higher global warming potentials than CO2, prompting a concerted effort to phase out the use of high global warming potential HFCs. Phasing out these materials is complicated by the fact that there are thousands of tons of refrigerant mixtures that contain both low and high global warming potential compounds, and there is no viable method for separating and reclaiming the components. The separation of low and high global warming HFCs is complex because they are azeotropic or near-azeotropic materials, meaning they are chemically similar and behave like a single (pure) fluid. The goal of the project is to develop tools and processes that enable the separation of high and low global warming potential HFCs, allowing the recovery and reuse of the low global warming potential HFCs. To accomplish this goal, an integrated molecular and chemical process design framework will be developed to engineer novel ionic liquid-based HFC separation technologies. The approach will unify "top down" computer-aided molecular design with "bottom up" experimentally driven approaches to more efficiently identify new separation agents for HFC azeotropic mixtures. The engineering framework will be widely applicable to other chemical separation processes, including that of next-generation refrigerants such as hydrofluoro-olefins and hydrochlorofluoro-olefins.

The work is organized in four specific aims:

  1. Carry out pure and mixed gas solubility measurements of R-32, R-125 and R-134a in a wide range of ionic liquids (ILs). (collaborator at KU)
  2. Conduct high throughput molecular simulations of IL solvents for HFCs. (Notre Dame)
  3. Systematically screen process designs and determine IL physical property targets via rigorous mathematical modeling and superstructure optimization. (Notre Dame)
  4. Demonstrate viability of the most promising IL entrainers in lab-scale extractive distillation systems. (collaborators at KU)

As such, this research program presents an opportunity to make significant progress towards integrating molecular design and end-use application optimization. In contributing to this ambitious project, the student researcher will be asked to elucidate molecular-level phenomena governing complex IL and HFC interactions. Specifically, the student will work with a Notre Dame graduate researcher to conduct and analyze molecular simulations. Self-motivated, independent student researchers will have the ability to focus their research efforts on the aspect of the project that appeals to their skills and interests. Prior Python programming or *nix command line experience will be helpful, but comfort with any computer programming language is sufficient. Students in chemical engineering, mechanical engineering, environmental engineering, electrical engineering, and computer science are well-suited to undertake this research project.



Project: Data-driven approaches to elucidating molecular design principles for nanostructured membranes capable of separating similarly sized molecules

Faculty mentors:
Professor Alexander W. Dowling • Chemical & Biomolecular Engineering • 369 Nieuwland Hall • 574-631-4041 •

Professor William A. Phillip • Chemical & Biomolecular Engineering • 205F McCourtney Hall • 574-631-2708 •

Dowling Phillip NURF Image 2020a. A schematic showing the physical and chemical properties of the membrane that can be tuned easily. Exploring how transport through chemically selective pores is affected when the physical and chemical interactions occur in confined geometries is critical to this project. b. Parameter estimation for a single filtration experiment. The mass of the material that permeated through the membrane was measured every 5s and is marked with red dots. Best fit parameters, directly to the nanostructural features of the membrane, were computed by minimizing difference between data and predictions.

The goal of the proposed research is to develop the fundamental scientific knowledge that informs the design and fabrication of nanostructured membranes with pore wall chemistries tailored to facilitate the separation of molecules with comparable sizes, especially rare earth elements (REEs). Membrane separations have demonstrated significant advantages in sustainability and energy efficiency. However, the majority of state-of-the-art membranes are size-selective and unable to distinguish between species of comparable molecular sizes. As such, there are significant opportunities for membranes that distinguish between molecules based on chemical, rather than steric, factors. Unfortunately, knowledge regarding the molecular design features that enable this class of transport mechanisms is lagging, which hinders the rational development of chemically selective membranes. Thus, there is a critical need to execute systematic, experimental studies on such membranes to elucidate the relationships between their nanostructure, surface chemistry, and selective transport mechanisms. Here, this engineering opportunity will be met by integrating membrane science and statistical learning paradigms into a convergent framework to develop the knowledge that guides the molecular design of these membranes. Self-assembled membranes that are amenable to post-assembly functionalization offer orthogonal control over membrane nanostructure and chemistry such that a diverse array of interfacial and transport phenomena can be interrogated. It is hypothesized that three molecular properties – solute-carrier affinity, spacer arm length, and pore diameter – control chemically selective transport mechanisms. Statistical learning and dynamic diafiltration experiments will be utilized to efficiently navigate this vast molecular design space and to elucidate the desired structure-property relationships up to 100 times faster than Edisonian searches.

The work is organized in three objectives:

  1. Identify molecular design strategies for copolymer membranes tailor-made to promote the efficient separation of REEs. This effort will generate a family of membranes with rationally engineered nanostructures and pore wall chemistries.
  2. Develop a statistical learning framework to identify the dominant transport and interfacial phenomena from dynamic diafiltration experiments. Model-based design of experiments will be used to discern between model permutations in a proposed model hierarchy.
  3. Utilize statistical learning to guide the development of structure-property relationships for chemically selective transport mechanisms that are capable of separating REEs.

As such, this research program presents an opportunity to make significant progress toward elucidating the critical structure-property relationships for membranes capable of transporting target solutes based on chemical, rather than steric, factors, with applications well beyond REEs. In contributing to this ambitious, potentially transformative project, the student researcher will be asked to elucidate how the nanoscale structure and chemistry of the membranes impact the observed transport properties through experimental water flow and solute filtration tests. The student will also assist in developing new data analysis capability ultimately leading to new optimal design-of-experiments capabilities. Self-motivated, independent student researchers will have the ability to focus their research efforts on the aspect of the project that appeals to their skills and interests. Students in chemical engineering, mechanical engineering, environmental engineering, electrical engineering, and computer science are well-suited to undertake this research project.



Project: Engineering biomimetic materials to control stem cell morphogenesis

Faculty mentor:
Professor Donny Hanjaya-Putra • Aerospace & Mechanical Engineering, Bioengineering Graduate Program • 141 Multidisciplinary Research Building • 574-631-2291 •

Hanjaya Putra 2022 Nurf Image

Blood and lymphatic vasculatures are two important components of the tumor microenvironments. Blood vessels supply nutrients important for tumor growth and serve as a conduit for hematogenous tumor spread, while the lymphatic vessels are used by the cancer cells to interact with the immune system as well as for lymphatic tumor metastasis. Consequently, the growth of blood and lymphatic vasculatures surrounding the tumor have been associated with tumor metastases and poor patient prognosis. The objective of this project is to understand what governs the formation of blood and lymphatic vessels from stem cells, how these processes are affected by the tumor microenvironment, and how we can use these insights to develop novel therapies. The student will synthesize and characterize biomaterials for in vitro evaluation using stem cell. The student is expected to maintain stem cell culture, study cell-materials interaction using microscopy and molecular biology techniques. Students with a background in mechanical engineering, chemical/bio-engineering, material science, or biochemistry are encouraged to apply. Prior lab experience is preferred.


  1. Laura Alderfer, Elizabeth Russo, Adriana Archilla, Brian Coe, Donny Hanjaya-Putra, “Matrix Stiffness Primes Lymphatic Tube Formation Directed by Vascular Endothelial Growth Factor-C Regulate Lymphatic Tube Formation,” FASEB, 2021 March 27, 35:e21498. PMID: 33774872.
  2. Laura Alderfer, Eva Hall, Donny Hanjaya-Putra, “Harnessing Lymphatic Tissue Engineering to Modulate the Immune System,” Acta Biomaterialia, 2021 June 9. PMID:34118451.
  3. Zehao Pan, Loan Bui, Vivek Yadav, Fei Fan, Hsueh-Chia Chang, Donny Hanjaya-Putra, “Conformal Single Cell Hydrogel Coating with Electrically Induced Tip Streaming at an AC Cone,” Biomaterials Science, 2021, 9, 3284-3292. PMID: 33949367.


Project: Magneto-silica nanoparticles (MagSiNs) for combinatorial chemotherapeutics and gene delivery against metastatic cancers

Faculty mentors: 
Professor Paul Helquist • Chemistry & Biochemistry • 361 Stepan Hall • 631-7822 •

Professor Prakash D. Nallathamby • Aerospace & Mechanical Engineering • 105C McCourtney Hall • 631-7868 •

We intend to target non-targetable cancer cells by tuning the magnetic field-induced force exerted by label-free magnetic nanomaterials at the cell membrane to selectively permeabilize the more compliant cancer cell membranes but not the stiff healthy cell membranes. Systemic delivery chemotherapeutics is toxic to all cells but more so to cancer cells due to the high metabolic rate of cancer cells. Targeted drug delivery using antibody tagged drug carriers reduces the dosage required to kill cancer cells and thereby mitigate the toxicity associated with systemic drug delivery. But the lack of unique targetable biomarkers on aggressive cancer cells such as 3º negative breast cancer makes the targeted drug delivery option a non-starter. But with the recent advances in biophysics, it is well documented that cancer cells have significantly different cell membrane stiffness in comparison to healthy cells. Cancer cell membranes are less stiff and more compliant, and the cells as a whole are easily deformable. The difference in membrane physical properties can be exploited by applying a force that is above the threshold required to permeabilize the cancer cells, but the force is still below the threshold required to permeabilize normal cells. While the cancer cell permeabilization and cancer cell-specific drug delivery have been validated in vitro, it is not known how effective such systems are in vivo. Studies that have tried to validate magnetic field directed drug delivery systems in vivo did so by sticking a permanent magnet on the tumor site before administering the nanocarriers intravenously or intratumorally. The requirement to know the tumor location beforehand to use magnetic targeting is the shortcoming of previous studies. As such, targeting modes offer no advantage over surgical re-sectioning, which is the current standard of care. Therefore, in this proposed study we will validate a label-free magnetic nanocarrier system (PEG-MagSiNs, PEG-Dox-MagSiNs) that will localize to cancer cells without the need for prior knowledge of the cancer cells’ location in vivo. We will exploit this property for selective drug-delivery and gene delivery to cancer cells. In this project  the students will get exposure to (a) the conjugation of multiple therapeutics to PEG-MagSiNs; (b) design multiple modes of drug delivery from the PEG-MagSiNs (ON-demand, stimuli dependent, enzymatic release, etc.) and (c) execute in vitro cell and in vivo mouse studies that show selective targeting of PEG-MagSiNs to metastatic breast cancer cell and improved survivability in the sample group.

Suggested readings:

  1. Chen Q1, Schweitzer D, Kane J, Davisson VJ, Helquist P. “Total synthesis of iejimalide B” J Org Chem. 2011 Jul 1;76(13):5157-69.   
  2. Guduru, R.; Liang, P.; Runowicz, C.; Nair, M.; Atluri, V.; Khizroev, S., Magneto-electric Nanoparticles to Enable Field-controlled High-Specificity Drug Delivery to Eradicate Ovarian Cancer Cells. Scientific Reports 2013, 3, 2953.
  3. Nallathamby, P. D.; Hopf, J.; Irimata, L. E.; McGinnity, T. L.; Roeder, R. K., Preparation of fluorescent Au-SiO2 core-shell nanoparticles and nanorods with tunable silica shell thickness and surface modification for immunotargeting. Journal of Materials Chemistry B 2016, 4 (32), 5418-5428.



Project: Phononic nanoparticles for low-loss, tunable nanophotonics in the mid- and far-infrared

Faculty mentors:
Professor Anthony Hoffman • Electrical Engineering • 266 Cushing Hall • 631-4103 •

Professor Ryan K. Roeder • Aerospace & Mechanical Engineering, Bioengineering Graduate Program • 148 Multidisciplinary Research Building • 631-7003 •

Hoffman-Roeder NURF image 2019
Schematic depicting the technology-space for phononics.

Phononic nanoparticles are a new class of optical materials with untapped potential for realizing new mid- and far-infrared detection and sensing nanotechnologies that are functionally analogous to ultraviolet and near-infrared plasmonic nanotechnologies but with even greater sensitivity. Phononic nanotechnologies have potential application in analytical chemistry, biomedicine, environmental science, homeland security, astrophysics, and geology. However, basic scientific knowledge of the governing structure-property relationships for engineering the optical properties of phononic nanoparticles are not well understood or developed. Therefore, students on this project will investigate the optical properties of candidate phononic materials using both modeling and experimental characterization of synthesized nanoparticles. As such, this interdisciplinary research experience will cut across both materials science and optical science.



Project: Machine-learning quantum phases in non-equilibrium systems

Faculty mentor:
Professor Yi-Ting Hsu • Physics • 312 Nieuwland Hall • 574-631-5856 •

Hsu 2022 Nurf ImageFigure 1. Schematics for the network-based approach and the result from a three-phase classifier. The three phases are the manybody localized phase (MBL), the non-ergodic metal (NEM), and the thermalized phase (Thermal).

Non-equilibrium quantum phenomena in isolated interacting systems are an intriguing subject that cannot be described by the framework of equilibrium statistical mechanics. One main challenge lies in the fact that there are no well-established order parameters that can help to determine the number and nature of possible dynamical phases. In recent works, we proposed that the combination of machine-learning techniques and informationally rich quantities in the system can serve as a novel and effective diagnostic for quantum dynamical phases. This is a theoretical / computational project that aims to apply novel network-based approaches to study the quantum phase diagrams in interacting systems with quasi-periodic potentials. Specifically, the project focuses on understanding the existence and origin of a hypothetical phase, the non-ergodic metal, which was conjectured to exist in the presence of a single-particle mobility edge. The project requires computational dexterity. Applicants are expected to be fluent in MATLAB or python. Those familiar with machine learning methods will be given priority. Students from any science and engineering background are well-suited to undertake this project. Those with interests and background in physics or computer science are preferred. 

Suggested Readings:  

  1. Hsu, Y.-T., Li, X., Deng, D.-L., & Sarma, S. D., Machine learning many-body localization: Search for the elusive nonergodic metal. Physical Review Letter 125, 097001 (2018).
  2. Xu, S., Li, X., Hsu, Y.-T., Swingle, B., Sarma, S. D., Physical Review. Research 1, 032039 (2019).



Project: Electrical and electrochemical analysis of hybrid bronzes

Faculty mentor:
Professor Adam Jaffe • Chemistry & Biochemistry • 375 Stepan Hall • 574-631-2696 •

Jaffe 2022 Nurf ImageFigure 1. A schematic hybrid bronze structure. The inorganic layers contain blue metal atoms coordinated by red O atoms. Polyhedra are drawn to show connectivity. The organic layer is depicted with purple ellipses and multicolored spheres representing the varied possibilities for molecular centers and functional handles, respectively. The inset shows electron or proton transfer between inorganic and organic layers.

Achieving a sustainable energy future means developing new classes of tunable materials that facilitate clean energy technologies and that can ideally be synthesized under mild conditions. Crystalline metal oxides are ubiquitous materials that display myriad electronic properties of interest and high chemical and thermal stability. They are vital for clean energy technologies such as batteries, fuel cells, and photovoltaics. These inorganic solid-state materials, however, can require high-temperature syntheses and exhibit low post-synthetic tunability, therefore diminishing their versatility and ease of integration in devices. Conversely, molecular species are highly tunable, but can lack the desirable mechanical and electronic properties associated with extended solids (materials with infinitely repeating bonding in at least one dimension), including facile intermolecular electron transfer. Our lab is developing new materials called hybrid bronzes that address this challenge by placing molecular centers in close contact with inorganic conduction pathways that possess high electron mobility (Figure 1). The objective of this project is to gain understanding of the structural and electronic property relationships in hybrid bronzes that will inform future implementation efforts in energy-related technologies. The student will assist in synthesis and characterization of hybrid bronzes. The student is expected to learn basic materials characterization techniques such as powder X-ray diffraction and infrared (IR) spectroscopy, followed by electrochemical characterization techniques such as cyclic voltammetry and impedance spectroscopy to determine how choice of components of these hybrid materials and the resulting atomic structure affect their redox and conductivity properties. Questions to answer include: (1) How is electronic conductivity modulated by molecular functional groups? (2) Can we enhance stability relative to all-inorganic materials? and (3) Can we reliably induce switching between conductive and insulating states? Students with a background in chemistry, chemical engineering, materials science, or applied physics are encouraged to apply. Some prior lab experience is preferred.



Project: Scalable nanofabrication of metasurfaces using microsphere photolithography

Faculty mentor:
Professor Edward Kinzel • Aerospace & Mechanical Engineering • 377 Fitzpatrick Hall • 574-631-8941 •

Kinzel NURF Image 2020

Metasurfaces have shown dramatic potential to control radiation. However, the fabrication methods used for prototyping metasurfaces at visible and infrared wavelengths are cost prohibitive for most practical applications. Microsphere photolithography (MPL) uses a self-assembled microsphere array as an optical element to focus ultraviolet radiation to sub-diffraction limited photonic jets. Hierarchical structures can be produced by controlling the intensity of the incident illumination or its angular spectrum. This approach works well on non-planar substrates, including optical fiber. The objective of this project is to use the MPL technique to create functional devices such as sensors and surfaces for controlling radiation heat transfer (e.g., daytime radiative cooling) depending on the student’s interest. The student will iteratively design the structure to perform the desired function, fabricate the device using microsphere photolithography, and characterize its performance using infrared spectroscopy. Other possible research projects could involve improving the fundamentals of the fabrication process. The project is multidisciplinary. Students with a background/interest in optics and/or microfabrication (physics, electrical engineering, mechanical engineering or chemistry) are encouraged to apply.



Project: Nano-enabled electronic nose

Faculty mentors:
Professor Nosang V. Myung • Chemical & Biomolecular Engineering • 105E McCourtney Hall • 574-631-3468 • (Send applications to Professor Myung)

Professor Jennifer L. Schaefer • Chemical & Biomolecular Engineering • 205G McCourtney Hall • 574-631-5114 •

Significant scientific efforts have been made to mimic and potentially supersede the mammalian nose using artificial noses based on arrays of individual cross-sensitive gas sensors over the past few decades. Nanoengineered materials possessing high surface area for enhanced reaction kinetics and uniquely tunable optical, electronic, and optoelectronic properties have been extensively used as gas sensing materials in single gas sensors and sensor arrays1. Therefore, nanoengineered materials address some of the shortcomings in sensitivity and selectivity inherent in microscale and macroscale materials for chemical sensors. Multiple opportunities are available ranging from materials synthesis, embedded system, and machine learning.  Students with a background in chemical engineering, chemistry, electrical engineering, computer science and engineering, or materials science and engineering are preferred.


  1. Kim Sanggon, Brady Jacob, Al-Badani Faraj, Yu Sooyoun, Hart Joseph, Jung Sungyong, Tran Thien-Toan, Myung Nosang V. “Nanoengineering Approaches Toward Artificial Nose”, Frontiers in Chemistry, 9, 2021, 11.



Project: Squeezing light energy into small volumes with gold and silver nanoparticles 

Faculty mentor:
Professor Svetlana Neretina • Aerospace & Mechanical Engineering, Chemistry & Biochemistry • 370 Fitzpatrick Hall • 574-631-6127 •  

Neretina 2022 Nurf Image

Gold and silver nanoparticles, when illuminated, have the remarkable property of being able to “squeeze” light energy into a volume that is much smaller than the wavelength of light. This ability is being widely exploited in emerging applications in areas where these nanoparticles act as (i) sensors for cancer, cardiovascular disease, explosives, and hazardous pollutants, (ii) agents that enhance solar cell efficiencies, and (iii) photocatalysts that increase the rate of chemical reactions that are performed under illumination. Fully exploiting this capability requires that such nanoparticles be placed in very close proximity to each other without actually touching. With the distances required between nanoparticles being less than five nanometers, the formation of these so-called nanogaps is quite challenging. Our research team has developed a straightforward benchtop technique for producing periodic arrays of spherical gold and silver nanoparticles such as the one shown in the image on the left. The goal of this summer NURF project is to develop the techniques needed to place a second nanoparticle to the right of every arrayed structure as shown schematically in the image on the right. This so-called “dimer” array is a far more valuable product because of the nanogaps formed between particles. A NURF fellowship recipient will team up with a graduate student to forward this project where his/her primary responsibilities will be nanofabricating nanoparticle arrays and synthesizing the nanoparticles used in the dimer assembly process. Students with a strong background in chemistry or materials science and excellent hands-on skills are preferred.



Project: Nanoparticle carriers for novel anti-Leishmania chemotherapeutics

Faculty mentors:
Professor Ryan K. Roeder • Aerospace & Mechanical Engineering, Bioengineering Graduate Program • 148 Multidisciplinary Research Building • 574-631-7003 •

Professor Mary Ann McDowell • Chemistry & Biochemistry • 215 Galvin Life Science Center • 574-631-9771 •

Roeder 2022 Nurf Image

Leishmaniasis is a grouping of diseases caused by the protozoan parasites Leishmania spp., affecting 12 million people per year, with almost 350 million people at risk. Therefore, the World Health Organization has declared leishmaniasis a Category I Neglected Tropical Disease. Leishmaniasis has a range of clinical manifestations, from self-healing skin lesions to hepatomegaly to fatality. Current anti-leishmania chemotherapeutics are limited by disease resistance, high off-target toxicity and low solubility. Therefore, we are investigating nanoparticle carriers for targeted delivery of a novel, hydrophobic small molecule chemotherapeutics. Gold nanoparticles are surface functionalized with amphiphilic molecules that facilitate loading hydrophobic small molecules within the monolayer and water solubility with terminal hydrophilic ligands. Students on this project will investigate nanoparticle synthesis and surface functionalization, drug loading and release, and in vitro cytotoxicity.



Project: Polymers in next-generation rechargeable batteries

Faculty mentors:
Professor Jennifer L. Schaefer • Chemical & Biomolecular Engineering • 205G McCourtney Hall • 574-631-5114 • (Send applications to Professor Schaefer)

Professor Nosang V. Myung • Chemical & Biomolecular Engineering • 105E McCourtney Hall • 574-631-3468 •

Schaefer NURF Image 2020

Advanced energy storage devices are sought after for use in electric vehicles and in conjunction with solar farms and wind farms for load leveling of the electric grid. To meet the cost and performance requirements of these applications, new battery chemistries are under development. Many of these battery designs incorporate functional organic components, such as polymer electrolytes, polymer coatings at the electrode-electrolyte interface, and polymer binders in the electrodes. In this project, the student will synthesize and characterize new organic materials for applications in next-generation batteries (such as lithium, magnesium, aqueous-based, or self-charging). Multiple opportunities are available. Students in chemical engineering, chemistry, polymer science or engineering, or materials science and engineering are preferred.

Suggested readings:

  1. H. O. Ford, B. Park, J. Jiang, M. E. Seidler, and J. L. Schaefer, “Enhanced Li+ conduction within single-ion conducting polymer gel electrolytes via reduced cation-polymer interaction,” ACS Materials Letters, 2, 272-279, 2020. (On the Most Highly Downloaded list)
  2. J. Liu, P. D. Pickett, B. Park, S. P. Upadhyay, S. Orski, and J. L. Schaefer, “Non-solvating, side-chain polymer electrolytes as lithium single-ion conductors: synthesis and ion transport characterization,” Polymer Chemistry.
  3. H. O. Ford, L. C. Merrill, P. He, S. P. Upadhyay, and J. L. Schaefer, "Cross-Linked Ionomer Gel Separators for Polysulfide Shuttle Mitigation in Magnesium–Sulfur Batteries: Elucidation of Structure–Property Relationships," Macromolecules, 2018. (Cover)



Project: Adiabatic capacitive logic for ultra-low power electronics 

Faculty mentors:
Professor Gregory Snider • Electrical Engineering • 275 Fitzpatrick Hall • 574-631-4148 •

Professor Alexei Orlov • Electrical Engineering • 227 Stinson-Remick Hall • 574-631-8079 •

Snider NURF Image 2020Cross-section of MEMS ACL structure to be fabricated.

Anyone who owns a laptop knows that power dissipation and the associated heat are a problem for the microelectronics industry. As electronic devices scale down in size, they use less power (and hence energy), but is there a lower limit to the energy that must be dissipated by each device? Are there devices other than transistors that able to dissipate less power? This project will investigate adiabatic capacitive logic (ACL), which uses variable capacitors in pull-up and pull-down networks to form a voltage divider that will be used to as a logic element. The variable capacitors will be built using micro-electro-mechanical structures (MEMS) to make nano-relay like devices. These devices map well onto adiabatic reversible computing approaches that can reduce power dissipation far below what is possible with conventional approaches. The student will work in the cleanroom on device fabrication and measurement. Students in electrical engineering, physics, or computer science are preferred. Some knowledge of programming and soldering is helpful.



Project: Nanoantenna directivity characterization

Faculty mentors:
Professor Gergo Szakmany • Electrical Engineering • 228 Stinson-Remick Hall • (Send applications to Professor Szakmany)

Professor Alexei Orlov • Electrical Engineering • 227 Stinson-Remick Hall • 574-631-8079 •

Thermoelectrically coupled nanoantennas (TECNAs) are a new class of infrared sensor. TECNAs are sensitive from mid- to far-wave infrared radiation by using a nanoantenna that operates similarly as RF and microwave antennas, but they are about a million times smaller. The nanoantenna resonantly absorbs incident IR radiation and heats a nanothermocouple junction that creates an electrical signal by the Seebeck effect. Due to the antenna nature of the TECNAs, attributes of an incident IR radiation (wavelength, polarization, and directivity) that are otherwise not available or hard to sense with conventional IR detectors can be easily determined. This project, funded by the National Reconnaissance Office, focuses on the design, fabrication and characterization of TECNAs for angle-of-incidence (AOI) sensitivity. The student will characterize AOI at various angles and implement read-out electronics. In particular, the student will work with a 5-axis motorized stage that is used to characterize the directivity of nanoantennas. The student will develop an interface between the stage and our existing acquisition platform and build read-out electronics that allow multiple nanoantenna measurements at the same time. Students with any science or engineering background will be considered, but those with a background in electrical engineering or mechanical engineering are preferred. Experience with basic C/C+ programming is a plus.



Project: Control theory of ecosystems

Faculty mentor:
Professor Dervis Vural • Physics • 384G Nieuwland Hall • 574-631-6977 •

Vural NURF image 2019

Evolutionary control has a long history starting with agricultural domestication and culminating into contemporary genome editing technologies. However, this history is largely limited to controlling individual species. We view ecological and biosocial networks as the new circuit board, and evolution as a manufacturing process capable of fabricating eco-machines. Evolutionary control promises terraforming worlds, degrading pollution, and manufacturing astonishing compounds. This is a theoretical / computational project that aims to establish an analytical framework to steer the evolution of multiple populations that strongly interact with one another. Specifically, we wish to theoretically understand how to manipulate the connectivity of networks representing ecological or biosocial webs, which range from bacterial biofilms to rainforests. The project particularly focuses on ecological control under noisy or incomplete knowledge of the existing interactions and population levels of species. The project requires mathematical and computational dexterity. Applicants are expected to be familiar with MATLAB, differential equations / dynamic systems, and linear algebra.



Project: Targeting therapeutics through supramolecular affinity

Faculty mentor:
Professor Matthew Webber • Chemical & Biomolecular Engineering • 205B McCourtney Hall • 574-631-4246 •

We are motivated to advance the practice of therapeutic nanotechnology by capturing several of the benefits of antibody targeting while avoiding some known complications. Antibodies are used for targeting due to high affinity and biological tissue-specificity. There are, however, downsides to antibody use in nanomedicine that could present issues in application moving forward: (i) Antibodies are fundamentally opsonins, a bio-recognizable signal that promotes cell-mediated uptake and clearance of foreign particles (e.g., viruses) by the reticuloendothelial system. Can we use alternative high-affinity targeting groups that would not be subjected to active biological clearance? (ii) A typical therapeutic nanoparticle (diameter ~50-100 nm) endowed with antibodies (hydrodynamic diameter of ~10 nm) would be expected to have its surface properties and function altered by addition of this bulky appendage; furthermore, there is limited area on the nanoparticle surface to attach such a large targeting group. Can we design targeting based on minimal groups that have comparable affinity while limiting impact on the properties of the functional nanoparticle? Using ultra-high affinity supramolecular interactions as a type of “molecular Velcro,” our group envisions a new therapeutic nanoparticle targeting axis built on minimal small molecule affinity motifs that serve as drivers of localization, in lieu of large targeting antibodies, while at the same time not sacrificing any affinity relative to an antibody-antigen interaction. The student will be expected to learn techniques for formulating synthetic nanoparticles to contain drugs and quantifying drug release using a combination of spectroscopy and chromatography. Additionally, the student will be tasked with validating this mechanism for targeting in vitro through microscopy of fluorescent nanoparticles on cultured cells. Students in chemistry, chemical engineering, materials science, or bioengineering are encouraged to apply. A minimum of some prior laboratory coursework is expected.



Project: Stimuli-directed nanoscale assemblies for glucose-responsive therapy

Faculty mentor:
Professor Matthew Webber • Chemical & Biomolecular Engineering • 205B McCourtney Hall • 574-631-4246 •

We are motivated to address the challenges inherent to blood glucose control in diabetes with materials that are capable of sensing blood glucose level and undergoing a transformation in nanoscale form to release a corresponding hormone (insulin or glucagon) to raise blood glucose levels. This approach would leverage smart nanotechnologies to replace the patient-centered approach central to current therapeutic management. Our lab is interested in studying the design and responsiveness of such materials, with particular emphasis on supramolecular assemblies of hydrogen-bonded peptide materials and on electrostatic nanoprecipitation of charged polymers. An undergraduate working on this project will be expected to learn techniques for formulating synthetic peptide materials and polymer materials to contain proteins, quantifying release using a combination of spectroscopy and chromatography. Additionally, this individual will be tasked with validating this mechanism for glucose-responsive function in vitro using microscopy and spectroscopy techniques. Students in chemistry, chemical engineering, materials science, or bioengineering are encouraged to apply. A minimum of some prior laboratory coursework is expected.



Project: Scalable nanomanufacturing and hybrid printing of multifunctional devices 

Faculty mentor:
Professor Yanliang Zhang • Aerospace & Mechanical Engineering • 374 Fitzpatrick Hall • 574-631-6669 •

Zhang 2022 Nurf Image

The mission of Professor Zhang’s lab is to innovate materials processing methods and transform manufacturing technology to improve energy and environment sustainability and individual wellbeing by addressing grand challenges our society is facing. To do so, we have established a transformative nanoscale-to-macroscale engineering approach that synergistically integrates fundamental and applied research programs into a coherent effort. The overarching goal of this thrust is to develop and integrate versatile additive manufacturing (AM) and scalable nano manufacturing (NM) methods to transform nanoscale building blocks into macroscale functional systems in a scalable, controllable, and affordable manner. Students will have opportunities to work on scalable nanoparticle and ink synthesis, and multifunctional device design and printing using a suite of innovative AM methods. We aim to harmoniously integrate functional and structural materials into autonomous systems for a range of emerging applications such as clean and sustainable energy, self-powered wireless sensor systems for monitoring of structural health and human health, human-machine interfaces, and soft robotics. Students with any engineering or science background are welcome to apply.