What are some examples of research projects that are open to NRT fellows and associates? The list below includes a short summary of potential projects. Each summary corresponds to a 1-2 page whitepaper developed by Syracuse faculty across multiple departments and colleges, vetted by the NRT Executive Committee for alignment with NRT themes and feasibility. These whitepapers emerged from faculty brainstorming sessions to develop ideas for interdisciplinary projects for NRT students.
While these short summaries are available to the public, students and faculty participants in the NRT program have full access to the detailed whitepapers – please contact David Stablein (dstablei@syr.edu) if you would like to request access. The NRT Fellowship and Admissions committee will consider these whitepapers as part of the process for identifying future fellows. It will be considered a strong positive if a fellow nominee is from a lab and/or interested in a project identified in these whitepapers. We expect that these whitepapers can continue to be refined and extended throughout the course of the 5-year NRT project. As there are a limited number of NRT fellowships, these whitepapers could also be utilized (with permission) to help generate ideas as trainees develop their seed grant applications.
Bacteria Interactions With Dynamic Surfaces
This project develops shape memory polymers with dynamic surface topographies that actively disrupt bacterial attachment and biofilm formation, offering a smart alternative to traditional anti-fouling approaches that can promote antimicrobial resistance. Using 3D/4D printing and stimuli-responsive surface coatings, we will characterize how mono- and multi-species bacterial communities respond to on-demand mechanical changes in surface geometry. The work will provide fundamental insights into microbial responses to dynamic mechanical cues and inform the design of next-generation antimicrobial surfaces for healthcare, water treatment, and industrial applications.
Emergent Intelligence in Organoids
This project explores how the physical properties of the extracellular matrix shape early human development using stem cell–derived organoids. By engineering tunable 3D biomaterials, we aim to understand how mechanical cues regulate lumen formation, tissue organization, and cell fate. The work will provide new insights into early developmental disorders and enable improved platforms for drug testing and regenerative medicine.
Identifying Bacterial Metabolites
Neurodegenerative diseases are difficult to treat and are often associated with mitochondrial dysfunction. In this project, we will isolate bacterial species from the underutilized freshwater sponges to be screened for the potential effects of their metabolites on mitochondrial health in an invertebrate system. Metabolites from candidate species will be further tested for effects on human microbiome and gut epithelial cell culture, with the goal of identifying new molecules as therapeutics for brain health.
How do Bacterial Extracellular Vesicles influence the composition and function of the microbiome
The vaginal microbiome plays an important role in reproductive health and disease, but our ability to optimize the microbiome is limited due to a lack of technology to precisely target beneficial and adverse species. Recently, bacteria have been shown to release nano-sized extracellular vesicles for targeted cell-to-cell communication. Our research aims to engineer and enhance these extracellular vesicles as a novel, targeted, and more effective therapeutic in a broad range of women’s health applications.
Viscoelastic memory in biholor sheets
This research introduces perforated elastic sheets (“biholar sheets”) that can store mechanical memory through their viscoelastic properties and bistable structural configurations. When deformed, these metamaterials “remember” their deformation history by maintaining internal stress states that cause them to preferentially return to previously selected configurations, without any electronic components. The work aims to establish design principles for programmable mechanical memory and learning in purely physical systems, opening pathways toward intelligent, self-adaptive materials.
Physics-Guided Optimization of Shark Skin-Inspired Surface Textures for Passive Flow Control
This project develops a physics-guided framework to design shark skin–inspired surface textures that passively control fluid flow for improved efficiency and robustness. By combining high-fidelity simulations with advanced flow analysis, the work identifies how microstructured surfaces can reduce drag and stabilize flow in marine and underwater systems. The project bridges biology and engineering to create scalable, energy-efficient surface designs for applications such as underwater vehicles and sustainable transport.
Emergent Biosensing and Learning in Mycelium Networks for soil and Planet Health Monitoring
This project studies living mycelium networks as bio-inspired sensing systems that can monitor soil conditions and plant health in real time. Using experiments and modeling, the research examines how fungal networks grow, communicate, and adapt to their environment, revealing how intelligent behavior can emerge from living materials. The long-term goal is to develop sustainable biosensing technologies for agriculture while training students at the interface of biology, engineering, and data science.
Hybrid Feedback Systems Based on Shape Memory Polymers with Mechanophore Sensors
This project integrates force-sensitive mechanophore molecules into 3D-printed shape memory polymers to create materials that can both sense and respond to mechanical forces at multiple length scales. By combining experimental fabrication via programming-via-printing with computational modeling from the molecular to continuum level, we will establish how mechanical forces propagate through these smart materials and ultimately enable real-time feedback between synthetic scaffolds and living cells. This work advances the design of adaptive biomaterials capable of sensing, actuating, and learning from their biological environment.
Nuclear Actin as a Physical Regulator of Chromatin-Based Cellular Memory
This project investigates how nuclear actin dynamics serve as a mechanochemical regulator of chromatin organization, enabling cells and organisms to store and maintain biological memory. Using in vivo and in vitro experiments complimented by computation modeling, we will test whether actin-dependent chromatin organization encodes long-term memory of cell identity and prior experience in mammalian and invertebrate systems.
Mechanical Materials that can Learn and Teach other materials
We propose a new paradigm in which materials themselves can learn and even teach one another through purely physical interactions, extending concepts of learning beyond neural systems to mechanical and metamaterial platforms. By combining reconfigurable magnetic particle systems and nonlinear buckling-beam metamaterials, the work develops a unified framework to study how physical systems encode, transfer, and optimize learned behaviors across continuous and discrete state spaces. The project aims to uncover universal principles of physical learning, enabling advances in programmable materials, soft robotics, and material-based AI systems.
Mechanical Adaptation of Cardiomyocytes during Dynamic Eccentric Remodeling
This project investigates how human heart cells respond to changing mechanical stress, a key factor in the development of heart failure. By combining advanced biomaterials, stem cell technology, and genome editing, the research creates a dynamic model that mimics how heart cells adapt—or fail to adapt—over time. The findings will uncover how cellular structures and self-repair mechanisms break down under stress, helping to guide new strategies for preventing and treating cardiac disease.
Modeling the effect of asymmetric distribution of cytoskeletal proteins on the lef-right organizer of zebrafish
This is a multidisciplinary project that brings together physicists (Manning lab, SU) and biologists (Amack lab, Upstate Medical) to leverage both mathematical modeling and in vivo experiments to investigate how physical forces impact organ morphogenesis during embryonic development. We will use a 3D vertex model to predict how asymmetric distribution of force-generating cytoskeletal components and other biomolecules contribute to left-right patterning in zebrafish embryos, and validate with quantitative imaging.
Environmental Stress Drives Epigenetic changes by Altering Cell Shape
Environmental stress during early development can have profound effects on adult behavior and physiology. Based on emerging evidence that cell shape impacts nuclear shape and, therefore, chromatin organization, we will use experimental and computational approaches to test the hypothesis that different environmental conditions force distinct changes in tissue remodeling and chromatin organization that serve as a “memory” of prior experience for the animal.
Shape Adaption by Intestinal Organoids in Cyclically Deforming Environments
This project studies how miniature models of the intestine — called organoids — change their properties in response to repeated cycles of physical stretching. By combining lab experiments with computer simulations, the researchers aim to uncover how these organoids “remember”” past mechanical forces and adapt over time. Ultimately, the work seeks to understand how non-neural living tissues can exhibit intelligence-like learning behaviors driven entirely by physical forces.
Can dynamically engineered substrates drive patterning in human intestinal organoids
Human intestinal organoids — miniature, lab-grown models of the intestine made from stem cells — currently fail to mature properly and don’t form the specialized structures (crypts) essential for a functional gut, limiting their usefulness in medicine and disease modeling research. This project combines laboratory experiments and computer simulations to understand how the physical and mechanical properties of the environment surrounding these organoids can be precisely tuned using light-based patterning technology to create organoids that better match the native human intestine. By uncovering the rules that govern how geometric form and physical forces shape intestinal development, this work could ultimately improve our ability to model human gut diseases and develop new therapies for conditions affecting the intestine.
Bioinspired responsive fiber materials for thermal adaptive textiles
This project aims to develop thermoregulatory textiles via smart materials, and integrate them into apparel and fashion designs. In particular, we will use bioinspired design strategy to investigate responsive and adaptive materials that mimic the leaf stomata that regulate the pore sizes in response to environmental cues such as moisture and light. We will then uncover the physical principles governing how such evolution impacts heat and moisture transport between the human body and the environment via a cloth prototype.
Memory and Anticipation in Myxococcus xanthus as Precursors of Intelligence
This project explores whether communities of the bacterium Myxococcus xanthus can develop simple forms of memory and anticipation when exposed to repeated mechanical stresses. By combining experiments and computational models, it tests whether these cell groups can “learn” from past experiences and respond more quickly or predictively to future changes—behaviors often associated with intelligence. The work aims to reveal how intelligent-like behaviors can emerge in living systems without brains, offering new insight into the physical origins of collective intelligence.
Physical Learning Across Living and Synthetic Systems
This project investigates whether learning emerges in physical vs biological systems by comparing how C. elegans worms and a synthetic particle-based system both adapt to navigating confined spaces like narrow channels and obstacles. By studying a neural organism alongside non-neural adaptive matter performing identical mechanical tasks, the research aims to distinguish learning mechanisms arising from nervous system plasticity versus those emerging from distributed physical feedback alone. The comparative framework treats learning as an embodied, physics-driven process that may operate across both biological and synthetic systems.
Mitotically Driven Cytoskeletal Remodeling as an Emergent Control Mechanism for Tissue Morphogensis in the Zebrafish Left-Right Organizaer
This project investigates how cell division events drive the formation of Kupffer’s Vesicle (KV), a temporary organ in zebrafish embryos that establishes the body’s left-right axis. Researchers Hehnly (Biology) and Manning (Physics) at Syracuse University will combine live imaging and computational modeling to understand how local mechanical forces generated during cell division give rise to the coordinated tissue-scale organization needed for KV to form properly. The work aims to uncover how cells “decide” to transition from dividing to forming a polarized, fluid-filled structure — and whether the physical forces of division drive that decision or follow from it.
Strain-Programmed Construction-Active Joints Enabled by Shape-Memory Polymers
This project develops construction-active joints using shape-memory polymers that can autonomously transform their shape during assembly and then remain stable without ongoing energy input. By embedding actuation directly into materials and geometry, the approach aims to simplify construction processes while improving the adaptability and efficiency of modular civil and architectural systems. The work establishes foundational design and fabrication strategies for next-generation infrastructure that is easier to deploy, more resilient, and less reliant on complex mechanical systems.
Flexible metal-organic frameworks (FMOFs)-integrated Porous Materials for Adaptive Indoor Environmental Control
This project aims to develop flexible metal-organic frameworks (FMOFs)-integrated porous materials for adaptive indoor environment control. In particular, we will use bioinspired design strategy to investigate FMOFs that restructure their internal architecture in response to environmental cues, and enable responsive sensing and/or adsorption of air pollutants such as VOC and PM 2.5 through FMOF-integrated porous materials. We will then set up a customized air flow tester to evaluate the filtration capacity, selectivity, and kinetics of those air pollutants in the porous materials.