First-Year Research in Engineering
The First-Year Research in Engineering program provides research opportunities for first year undergraduate students, and provides prospective engineering majors with early hands-on experience and mentoring within engineering. Up to 12 two-term research projects will be available to first-year students who want to participate in engineering research projects.
- Applicants must be in their first term at Dartmouth.
- These are part-time internships ($10 per hour), generally working 8-10 hours per week for two terms (Winter and Spring).
- Students can apply to either the First-Year Research in Engineering program or the Women in Science Project (WISP), but not both. If a student applies for the First-Year Research in Engineering program and is not accepted, she may apply to the second round of WISP.
- At the end of the internship in May, First-Year Research in Engineering program students must participate in the Wetterhan Symposium, joining other Dartmouth undergraduates conducting technical research in presenting a poster based on their own work.
To apply for a project, review the project descriptions below and then fill out the application form (Word). Students will then participate in interviews with faculty mentors, who will then select a student for each project.
- Get hands-on research experience
- Learn important life and work skills
- Explore possible career paths
- Network with scientists and engineers
- Experience the Dartmouth engineering community
- Late September: Projects listed online
- October 11: Student applications due
- Late October: Mentor/student interviews
- Early November: Notification of selection to students
- Mid-November: Informal social gathering for First-Year Research in Engineering program students, faculty advisors, and assistant graduate student mentors
- Mid-January: First-Year Research in Engineering program orientation for students
- Late January: WISP Smart Science Study Skills Session (First-Year Research in Engineering program students invited to attend)
- May 24: Karen E. Wetterhan Symposium (First-Year Research in Engineering program students required to participate)
Self-Assembly, Dynamics, and Actuation of Multistable Thick-panel Origami Structures
Faculty advisor: Professor Zi Chen
The objective of this research is to identify the mechanical principles governing the self-assembly, dynamics, and actuation of multistable thick-panel origami structures. These principles can then be exploited to guide the design and prototyping of novel origami structures with programmable multistability and stimuli-responsiveness under various loading scenarios. Origami has inspired novel designs at all size scales, from metamaterials to biomedical devices to space structures. Origami structures created with thick panels are more challenging to fold than traditional zero-thickness material, but they also provide new opportunities in practice. Multistability is a unique feature of structures that exhibit shape changes in response to certain external stimuli. Origami multistability has recently garnered attention by the research community, but most studies have mainly focused on the statics of a single-vertex unit and in nearly zero-thickness origami. Gaps remain in our understanding of mechanical self-assembly and dynamics in multistable thick-panel origami.
The goals of this project will be accomplished with a combination of theoretical and experimental efforts by: (a) creating a mathematical framework to account for self-assembly and the dynamics of multistable thick-panel origami structures; (b) developing thick-panel origami prototypes using a strain-engineered method to control the shape, multistability, and dynamic transition between stable states; and (c) fabricating programmable thick-panel origami systems using smart materials that can achieve controllable shape changes and tunable multistability under certain external fields (thermal, electric, etc.).
Embark on a journey to create diagnostics for infectious diseases
Faculty advisor: Professor Jane Hill
The Hill Lab focuses on determining the identity of pathogens infecting the lung or other parts of the body using the molecules present on a patient’s breath. Junior researchers will learn the ropes by participating in an ongoing project related to respiratory infection or bloodstream infection. Your project will initially involve learning how to work with bacteria carefully and in a consistent manner. Thereafter, you will conduct experiments in partnership with a graduate student that could lead to the generation of a manuscript for publication. Once you have gained competency in the handling of organisms and hypothesis-generating research, you can then be trained on more tools in the lab and further build your research independence, ultimately to a topic of your choosing.
Identifying Differences in Decision-Making Styles
Faculty advisor: Professor Eugene Santos
Research mentor: Jacob Russell
People have different personalities, beliefs, and ideals; surely the way that they make decisions must be as varied as the decision-makers themselves? Can we identify what constitutes an individual's unique decision making style? How do their experiences, beliefs, personalities, and ideals impact their decision-making style? To solve this problem we turn to reinforcement learning and inverse reinforcement learning, state-of-the-art techniques in unsupervised machine learning. Students will learn to identify a hypothesis, build a dataset, test their hypothesis, and evaluate their results.
A desire to understand human behavior and learn computer programming is required. Help us explore a new paradigm of decision theory accounting for individual differences!
Applying Cultural Insights to Agents in Game Theoretical Modeling
Faculty advisor: Professor Eugene Santos
Research mentor: Jeremy E. Thompson
While game theory has many uses in analyzing and understanding strategies in competitive or combative situations, game theory can fail, however, when players are not rational, or perhaps when players do not appear to be rational. In fact, the players may be acting quite rationally, once their particular circumstance or cultural situation is understood and considered. The basic goal of this project is to enhance and improve the application of game theoretics to complex situations through the introduction of player cultural information processed by an artificial intelligence (AI) reasoning engine. Cultural information will be stored in the form of Bayesian Knowledge Base (BKB) fragments, and the AI reasoning capability of BKBs will be employed to determine the most probable influence this cultural information would have on that particular player’s decisions for strategy or preferences (towards risk, for example).
Intern research efforts on this project will include exploring game theory and practice, researching complex competitive real-world scenarios, development and testing of scenario models, and performing statistical analysis of results.
Analysis of the Effect of Inquiry-Based Learning Approaches
Faculty advisor: Professor Laura Ray
Research shows overwhelmingly that small-group learning strategies are effective in promoting greater academic achievement, more favorable attitudes toward learning, and increased persistence through Science, Mathematics, Engineering, and Technology (STEM) courses and programs; however, the predominant pedagogy nationwide avoids student-centered or collaborative instruction in favor of didactic (lecture-based) instruction. We conducted a need study that identifies multiple obstacles to collaborative instruction in engineering classes and propose to develop and evaluate a set of instructional materials for the systems curriculum. The goal is to enable instructors to adopt student-centered learning approaches and to evaluate outcomes of this pivot in instruction approach. The interviews demonstrate a clear need for small group learning activities with the following characteristics: they are sufficiently engaging and different from homework, can be managed by one instructor, and can be completed within a class period; they are easily adopted by faculty who have time and resource constraints and/or a heavy research emphasis; the materials required are open-source and inexpensive; and the activities build skills and knowledge, are experiential, and deepen learning. In this FYREE project, students will assist in developing these materials in advance of a workshop to be held at Dartmouth during the summer of 2017.
FeNiMnAlCr High Entropy Alloys
Faculty advisor: Professor Ian Baker
Research mentor: Margaret Wu
Recently, high (configurational) entropy alloys (HEAs) have become of interest because of their potentially good mechanical properties. In 2015, we discovered a new FeNiMnAlCr HEA, which we doped with carbon, and shows excellent strength and ductility at room temperature. As cast, this alloy is single phase. However, after heat treatment various precipitates are produced. We now wish to examine the precipitation kinetics and determine if we can produce a single phase HEA from the matrix composition of our current HEA.
The work will involve casting alloys, microstructural characterization by scanning electron microscopy and X-ray diffraction, and mechanical testing. Full training will be provided.
Directional Recrystallization of Tungsten
Faculty advisor: Professor Ian Baker
Research mentor: Margaret Wu
Most single crystals are grown from the melt by directional solidification. However, directional recrystallization of either cold-worked or fine-grained material is a little-used process that is potentially much cheaper and can be used to process more chemically-complex materials.
In this work, the student will attempt to produce tungsten single crystals by directional recrystallization of worked polycrystalline tungsten rods using a floating-zone optical image furnace. The student will characterize the resulting microstructures using scanning electron microscopy.
Developing an implantable resonator for EPR Oximetry
Faculty advisor: Dr. Hal Swartz
Research mentor: Rose Caston
Solid tumors have a characteristic poor oxygen perfusion and sometimes high intratumoral pressure due to their chaotic vasculature. Subsequently, common forms of cancer treatment like chemotherapy and radiation are affected by the low oxygen content in the tumor's tissue. Electron paramagnetic resonance (EPR) oximetry is a technology being developed by the EPR Center for Study of Viable Systems to measure the partial pressure of molecular oxygen in tissues.
EPR relies on the use of paramagnetic probes, but they can only be detected from a surface for only up to 2cm deep due to the non-resonant absorption of microwave energy in tissues. The EPR Center has developed an implantable resonator, which consists of probes along the length of a transmission line. The device allows the oxygen content in deep tissues to be measured. Being able to measure the partial pressure of oxygen in deep tumors will enable cancer treatment to be more effective.
Work with the existing EPR Center Team to move the working model for the implantable resonator to a form suitable for testing in human subjects as part of an FDA compliant clinical trial of safety/efficacy. We are looking for hard-working, motivated students who are interested in learning about translational research while deepening their knowledge in medical science and engineering. This project includes aspects of chemistry, biology, and mechanical/software engineering. Working with animals and conducting testing may be necessary and students willing to do this work should apply for this opportunity.