Flash Talk Abstracts
Talk 1: Addressing Health Inequities in the Criminal-Legal System
Presenter: Erinn Bacchus
Mentor: Tracy Nichols, Joanna Mishtal, & Eduardo Gomez
Department/College: Community and Global Health and Population Health
My future research at Lehigh will engage the expertise of my mentors to further explore the persistent health inequities of those involved in the criminal-legal system. Through these collaborations, I hope to participate in a broad range of research projects that may include investigations into how the commercial determinants of health (CDOH) intersect with the criminal-legal system as well as the barriers to healthcare pregnant individuals face inside carceral settings, and the policies that impact the health of individuals incarcerated in prisons and jails.
Talk 2: Customer charges and inflation: An analysis of electricity rates for the state of Pennsylvania (2006—2024)
Presenter: Johanna Bolanos
Mentor: Alberto J. Lamadrid
Department/College: Institute for Cyber Physical Infrastructure and Energy (I-CPIE)
This study analyzes the real-term trend of customer charges (fixed cost) for residential electricity in Pennsylvania. Using historical data from the Pennsylvania Public Utility Commission (PUC) and adjusting for inflation with the Personal Consumption Expenditures Price Index (PCEPI), we determine whether consumers are effectively paying more over time, beyond general price level increases from 2006 to 2024. Our inflation-adjusted approximation illustrates how fixed costs have varied in relation to purchasing power, excluding any effects derived from consumption, which provides a context for evaluating the behavior of fixed costs in restructured electricity markets. Our findings align with trends reported in Maryland, where Electric Distribution Companies (EDCs) have increased delivery charges, including monthly customer charges, outpacing inflation. Utilities often use mechanisms that accelerate cost recovery, which in turn raises financial risks for consumers. These trends underscore the importance of separately tracking the real value of customer charges over time, since the maintenance and expansion of energy infrastructure can unfairly impact households, particularly low-income and elderly consumers who may struggle to understand the competition in the electricity market.
Talk 3: Between Rockets and Picasso: Understanding High-Entropy Alloy
Presenter: Daniela Fonseca
Mentor: Ricardo Castro
Department/College: Materials Science and Engineering
With renewed space missions to the Moon, Mars, and beyond, the demand for materials that can endure extreme environments is greater than ever. Imagine designing a spacecraft: it must withstand the heat of launch, the cold of space, and the stress of landing. This requires structural metals that are not only strong, but also flexible, heat-resistant, and durable. Most traditional metals fall short when multiple demanding properties are needed at once. However, a new class of materials is redefining what's possible: High-Entropy Alloys (HEAs). Created by mixing five or more elements in near-equal amounts, HEAs form atomic-scale disorder that leads to exceptional mechanical and thermal properties. These promising materials are attracting attention in aerospace, energy, and advanced manufacturing. My research focuses on HEA nanoparticles — nanoscale metallic building blocks especially relevant for powder-based manufacturing techniques like sintering and 3D printing. Despite their promise, much remains unknown about how these particles behave during thermal processing. Using advanced electron microscopy, I track how they evolve over time and under heat. Through storytelling and vivid visuals, I will take the audience on a journey from the chaotic beauty of atomic arrangements (featuring an inspiring Rembrandt vs. Picasso analogy) to real atomic-resolution images and particle motion captured inside the microscope. This talk will show how understanding HEA nanoparticle behavior can enable smarter powder metallurgy — and how Lehigh University's strong legacy in metallurgy continues to evolve through cutting-edge research.
Talk 4: Kings in the Empire: Sovereignty and State Formation in Central India, c. 1658-1971
Presenter: Sourav Ghosh
Mentor: William Bulman
Department/College: History
As part of my postdoctoral research, I am preparing my book manuscript titled "Kings in the Empire: Sovereignty and State Formation in Central India, c. 1658-1971." It explores the political transformation of the Indian hinterlands from the early modern to the postcolonial period through the lens of three Hindu kingdoms in Central India. While the history of this period is mostly told from the perspective of the bigger empires and their institutions, by focusing on the genesis of Hindu Kingship, I argue that even under the Islamicate Mughal empire (1526-1720s) and British colonial rule (1800s to 1947), smaller Hindu polities remained the fulcrum of political power in the hinterlands. In contrast to the popular perception that Mughal rule erased Hindu kingship, the book argues that Islamic rule in South Asia nurtured novel and dynamic understandings of Hindu kingship. The role of elite Rajput warriors, initially Mughal military servants, is central to my analysis; they rose to political authority, managed local administration, and adopted the mantle of 'Raja' (king)—a durable template embedded in Brahminical (Hindu priestly) traditions. In this way, Hindu kingship gradually became a formative element in the routinized forms of authority and legitimacy within the Mughal Empire, which helped to ensure their continuity after the Mughal Empire's collapse in the eighteenth century. Moreover, I demonstrate how this model of Hindu kingship under Mughal rule laid the groundwork for British indirect rule in India, as these Rajput 'kings' ruled as princes, sharing sovereignty with the British crown. I draw on various sources—imperial archives, vernacular texts, and oral histories—to show how the study of smaller polities reorients our understanding of how power actually works and how empire functions away from the center. Finally, this project has contemporary relevance, as the longing for an idealized ancient Hindu kingship remains a prominent discourse in India; my work reveals how Hindu kingship evolved over time through its dynamic interactions with broader imperial, economic, and global forces such as Islamic polities, the Indian Ocean trade, and Western colonialism.
Talk 5: The Achievement of Acknowledgement: On Responsibility and Being Moved
Presenter: Candace Jordan
Mentor: Michael Raposa
Department/College: Religion, Culture, Society
This lightening talk briefly diagnoses the outsized attention given to blameworthiness and guilt in philosophical and Christian ethical literature on moral responsibility. Then, this talk locates the sympathetic response (a kind of practical wisdom) as a capacity central to the concept of responsibility. The sympathetic response, or acknowledgement of another's suffering, is an achievement fundamental to being responsive to and responsible for others. Drawing from Stanley Cavell's distinction between "knowing" and "acknowledging," this talk dramatizes the claim (that acknowledgment of human suffering is essential to knowledge of it) through insights from the lives and legacies of Mamie Till-Mobley and Frederick Douglass.
Talk 6: Rethinking Super-Eruptions: What Happens When Magma Reabsorbs Gas?
Presenter: Franziska Keller
Mentor: Meredith Townsend
Department/College: Earth and Environmental Sciences
Volcanoes are some of the most fascinating natural phenomena on Earth that shape landscapes, fuel geothermal energy and create precious ore deposits. However, they also pose serious hazards to our global society. Among the most extreme are super-eruptions, such as those produced by Yellowstone, which if they occurred today, could cover almost the whole US with ash, collapse our infrastructure, disrupt global trade, and trigger drastic global climate impacts. Forecasting such rare, but catastrophic events requires a deep understanding of how magma accumulates and what ultimately causes its eruption. Therefore, volcanologists study past eruptions and the physical and chemical properties of preserved magma to unravel the conditions that led to explosive super-eruptions. A critical factor here is the role of gas, which sometimes can be a constituent of magma alongside crystals and molten rock. Once gas is present within a magma, it has been suggested that it expands the magma volume causing internal pressurization that can lead to eruption. However, our research reveals a surprising new mechanism: instead of exsolving gas, some magmas can reabsorb it right before eruption. This volatile resorption reduces the magma's compressibility and counterintuitively, increases internal pressure even more rapidly than steady gas release. We additional find that this process expedites eruption onset increasing the risk posed by such volcanoes. Understanding this new process offers a lens on how super-eruptions might be triggered and why forecasting them remains such a challenge. By identifying this new driver of pressurization, we move closer to anticipating Earth's most powerful volcanic events.
Talk 7: Long-term adaptation in recombinant yeast hybrids highlights proteostasis as a key evolutionary response
Presenter: Artemiza Martinez
Mentor: Gregory Lang
Department/College: Biological Sciences
Hybrid organisms, formed by combining genomes from two different species, offer unique insights into evolutionary processes. However, combining genomes can lead to genetic incompatibilities, resulting in reduced fitness or even inviability of hybrid offspring. To understand how hybrid genomes adapt and overcome these challenges over time, we experimentally evolved 320 yeast populations derived from 20 distinct hybrid strains for approximately 5,000 generations. Each initial hybrid possessed its own unique genetic background and observable traits, allowing us to explore diverse evolutionary paths. By sequencing the complete genomes of the evolved populations, we identified consistent genetic changes in key genes, particularly those involved in protein maintenance and stress responses. Notably, the gene HSP104, responsible for managing damaged proteins and maintaining cellular health, frequently showed specific mutations across different hybrids. Interestingly, these mutations often appeared together with genomic segments containing the SUP35 gene, known for its role in prion regulation—a process crucial for protein stability. Our research highlights that early-generation hybrids commonly face challenges associated with maintaining protein health and managing stress caused by misfolded or damaged proteins. These findings suggest that adaptations improving protein stability and enhancing stress tolerance may help hybrids mitigate some of the consequences of genomic incompatibilities, potentially aiding their evolutionary success.
Talk 8: Generative AI in higher education: instructors' imagined futures and current policies
Presenter: Rosemary Steup
Mentor: Dominic DiFranzo
Department/College: Computer Science and Engineering
Generative AI tools have taken higher education by storm, starting with ChatGPT in late 2022. Their impact has been felt particularly strongly in English and Computer Science courses. Widely accessible AI tools can generate both English text and computer code with impressive accuracy--which means they are able to complete many of the assignments in introductory writing and programming courses. We interviewed instructors of such courses, at a variety of U.S. colleges and universities, to learn how they are approaching AI in their classes and why. What sorts of future do they imagine their students living in, and how do those imagined futures shape their AI policies? Our results contribute to the ongoing, collective conversation about what generative AI means for higher education and what role it should play in students' learning.
Talk 9: Impacts of Portable Air Purifiers on the Oxidative Potential and Sources of Organic Matter in Indoor PM2.5
Presenter: Yixiang Wang
Mentor: Linchen He
Department/College: Community and Population Health
Organic matter (OM) is a major contributor to the oxidative potential (OP) of indoor PM2.5. Portable air purifiers equipped with high-efficiency particulate air (HEPA) filters are known to effectively remove indoor PM2.5 mass concentrations. However, their impacts on the OP and sources of indoor PM2.5 OM and whether these impacts could further affect the OP of indoor PM2.5 metals remain poorly understood. In a crossover trial, each of the 43 asthmatic children underwent a 2-week true filtration (HEPA + activated carbon [AC]) and sham filtration (no HEPA + no AC), with randomized order. PM2.5 samples, simultaneously collected in participants' bedrooms and outside their homes, were measured for mass concentration, composition, mass-normalized OP (OPm, OP per mass), and volume-normalized OP (OPv, OPm × mass concentration). Compared to the sham filtration, indoor PM2.5 OM mass was 34% lower, OPm was 70% lower, and OPv was 80% lower during true filtration. The reduction in OM OPv was largely attributed to removing more reactive outdoor OM and indoor secondary OM. The change in OM composition also contributed to the reduced PM2.5 metals' OPm. Our results suggest that indoor air purifiers with HEPA and AC filters efficiently reduce PM2.5 OPv by removing OM.
Talk 10: Fluid-induced large earthquake evidenced from dense instrument networks
Presenter: Alexander Wickham
Mentor: Anne Meltzer
Department/College: Earth and Environmental Science
What controls large earthquakes in a subduction zone? Events of magnitude larger than 7.5 regularly occur around the world and can be disastrous for populations and cause economic losses. Fluids trapped in faults or produced by dehydration processes are significantly present in subduction zones but are seldom regarded as a trigger mechanism for large earthquakes. Understanding the physical properties of structures that influence such events is key to a better assessment of risks. The Ecuadorian subduction zone is a very seismically active margin where large earthquakes occur. In collaboration with IG-EPN (Instituto Geofisico de la Escuela Politecnica Nacional), the deployment of temporary networks of seismic stations to record earthquakes, in particular with large arrays of nodes in 2020 and 2022, has allowed to refine the role of fluids in the stress build-up process and the influence of large earthquakes on the distribution of fluids. Our work consisted of first building accurate seismicity catalogs for the Ecuadorian forearc. We then performed 3D tomography inversion using P and S-wave local travel times to image the velocity structure of the margin. We have evidenced that the plate interface is highly fractured and that fluid circulation may cause seismicity and promote large ruptures. We note that seismicity and stress conditions are substantially affected by the large magnitude 7.8 earthquake that occurred in Ecuador in 2016.
Poster Abstracts
Poster #1: Development of a Fully Automated Supercapacitive Swing Adsorption (SSA) Process for Carbon Capture
Presenter: Oluwasanmi Adeodu
Mentor: Mayuresh Kothare
Department/College: Chemical & Biomolecular Engineering
Supercapacitive swing adsorption (SSA) is an electrochemical method of CO2 capture that leverages the electrostatic attraction of CO2 and carbonic acid to the electric double layer (EDL) formed within porous electrodes of a supercapacitor that is contacted with CO2-containing gas. The formation of the EDL and subsequent adsorption of CO2 follows the application of a potential difference across the supercapacitor. The release of adsorbed CO2 is achieved by the restoration of the supercapacitor voltage to its pre-adsorption level. Since CO2 sorption is largely electrostatic, SSA offers shorter cycles and higher roundtrip efficiencies than redox-based methods. Previous SSA studies offer insight into the effects of electrode material, electrolyte composition, oxygen content in feed gas and charging parameters on adsorption capacity and efficiency. However, the continuous production of a high purity CO2 stream via SSA for sequestration (or conversion into valuable chemicals) as in a commercial-scale plant, is yet to be addressed. We therefore developed an automated SSA system that extracts and stores high purity CO2 from a continuous gas feed. Coordination between charge/discharge protocols of the dual module system and gas flow sequence is achieved with a programmable microcontroller. We present experimental results using this design with gas feed concentrations ranging from 15% to 400 part per million CO2. Insight gleaned from our architecture will accelerate the development of pilot-scale and ultimately, commercial point source and direct air capture applications.
Poster #2: Gray-box Algorithms for Sequences of Discrete Optimization Problems
Presenter: Federico Battista
Mentor: Ted K. Ralphs
Department/College: Industrial & Systems Engineering
The growing maturity of mixed integer linear programming (MILP) solvers has made possible the solution of large-scale, deterministic optimization problems. Due to its success, research has shifted to addressing more complex models, such as those incorporating uncertainty, considering multiple objectives, or allowing for multiple (possibly competing) decision-makers. Solving these settings usually involves solving a sequence of related MILPs, such as to explore alternative scenarios or tradeoffs among objectives. Although modern solvers can be (and currently are) used as "black-boxes" to solve the sequences of MILPs that arise in these applications, they are not an ideal tool for this task. The subproblems relationship is not leveraged by the black-box algorithm, despite a substantial overlap in the computations required for related instances. The focus of the proposed research is to address this deficiency by developing solvers that are purpose-built for solving sequences of MILPs. The general concept is to introduce "gray-box" capabilities into the current "black-box" solvers, by designing mechanisms to systematically share internally-derived information that existing methods discard at the end of a computation.
Poster #3: Development of Anthracite Coal Derived Silicon Carbide Electrodes for Green Energy Storage Solutions
Presenter: Havva Hande Cebeci
Mentor: Carlos E. Romero
Department/College: Energy Research Center
This study investigates the green synthesis of silicon carbide nanowire (SCNW) electrode materials for supercapacitor applications using anthracite coal, silicon powder, biopolymer binders, and an iron catalyst. Initially, anthracite coal was sieved using U.S. standard sieves to obtain two batches: one with particles smaller than 125 µm and another with particles smaller than 45 µm. The <125 µm sample were subjected to pyrolysis only, while the <45 µm sample underwent both pyrolysis and subsequent steam activation. Pyrolysis was performed at 1400°C under an inert atmosphere, leading to the formation of a three dimensional network of silicon carbide nanowires. The resulting structures were examined using BET surface area analysis, and their morphology and elemental composition were characterized by SEM-EDS. Electrochemical behavior was assessed through CV and GCD measurements in a three-electrode setup using 1 M H₂SO₄ as the electrolyte. Following pyrolysis, a steam activation process was carried out at 800°C for 1 hour in a tube furnace system, using a nitrogen gas flow rate of 0.3 L/min. In total, four samples were prepared and analyzed: anthracite-derived carbon, anthracite-silica based silicon carbide, and their respective steam-activated counterparts. By comparing the results before and after activation, the effects of steam treatment and particle size on the structure and electrochemical performance of the silicon carbide nanowire network were evaluated. The findings reveal that activation significantly influences nanowire morphology, surface properties, and capacitive behavior.
Poster #4: Benefits of numerical and physical modeling in the processing of new advanced engineering materials
Presenter: Charles Chemale Yurgel
Mentor: Wojciech Z. Misiolek
Department/College: Materials Science and Engineering
For years, Finite Element Modeling (FEM) metal forming simulation software packages have been used to develop new technological processes and optimize existing ones. Today, these packages effectively predict state variables such as localized stress, strain, strain rate, and temperature during deformation. The bottleneck remains the lack of material models for less common and newly developed materials. Enhanced numerical tooling capabilities have been achieved by combining numerical simulation with physical modeling and materials characterization. The first case study investigates a forging tool design using a numerical simulation approach to extend the life of the forging die and optimize the tool design through FEM analysis for a steel pinion shaft, which is a component of a wind turbine. The results for the two newly designed geometries show improvements compared to the initial non-optimized die, both in die cavity filling for the proposed dies and in grain flow orientation. The second case study explores the development of a metal matrix composite (MMC) coating, created using the Selective Laser Melting process, to enhance the high-temperature hardness and wear resistance of hot forging tooling. To create the MMC, Inconel 625 (IN625), a nickel superalloy in spherical powder form, is mixed with irregular Titanium Carbide (TiC) powder at varying weight percentages. The results indicate that 5 wt% TiC-reinforced IN625 presents significant advantages over both H13 tool steel (the standard hot forging tooling material) and IN625 without reinforcement.
Poster #5: Addressing the role of genes and regulatory regions on the evolution of vision in Mexican tetra
Presenter: Marcos da Silva
Mentor: Johanna Kowalko
Department/College: Biological Sciences
The understanding of genotype-phenotype interactions is central in biology and critical for determining how and why traits evolve through time. Natural variation in regulatory regions—regions outside protein-coding genes that influence gene expression—is an important driver of phenotype evolution, however establishing genotype-phenotype relationships in such regions poses a challenge. With that in mind, the current work takes into account the repeated loss of eyes found across cave fishes in order to identify the gene regulatory variants that underlie phenotypic evolution. Further, using a genetically tractable cavefish species, the Mexican tetra (Astyanax mexicanus), we sought to directly assess the effects of observed changes in candidate regulatory regions around ten different target genes potentially related to eye degeneration and loss. To do that, first we aimed to identify candidate regulatory regions by identifying regions near these "hit" genes that display high sequence conservation across fish species. For each candidate gene, we will align a 1 Mb region surrounding that gene in the high-quality A. mexicanus surface fish genome 18 to an existing alignment of teleost fishes , and we will identify sub-regions within this larger region that have high levels of sequence conservation across the genomes of teleost fishes and from there build on existing approaches to employ reporter gene assays and CRISPR-Cas9 gene editing to show evidence of genetic variation at the candidate gene regulatory regions identified.
Poster #6: DNA-based Sorting of Carbon Nanotubes Using PEG/Salt Aqueous Two-Phase Extraction
Presenter: Cindy Jin
Mentor: Anand Jagota
Department/College: Bioengineering
Single-wall carbon nanotubes (SWCNTs) exhibit optical properties that are highly dependent on their chirality (n,m). DNA-wrapped SWCNTs further exhibit sequence-dependent fluorescence intensity change or solvatochromic shifts upon analyte modulation, enabling their use as sensitive optical probes for biomolecules such dopamine, hydrogen peroxide, and steroids. To harness the full potential of SWCNTs in sensing, high-purity, single-chirality SWCNTs are essential. We employ a DNA-guided PEG/salt aqueous two-phase extraction (ATPE) system for single-step purification of DNA-wrapped SWCNTs. In this approach, tailored DNA sequences selectively modulate the partitioning of specific SWCNT chiralities between the PEG-rich top phase and salt-rich bottom phase. Compared to traditional polymer/polymer ATPE systems, PEG/salt systems offer advantages in cost-effectiveness, reproducibility, and ionic tunability. We systematically investigated a library of 12-mer DNA sequences that selectively enrich single chirality nanotubes, including (7,6), (8,3), (6,4), (8,5), (9,6), (7,3), and (10,2), through careful control of pH and Na⁺: K⁺ ion ratios in the PEG/salt system. Notably, this separation strategy is effective not only for pristine DNA-wrapped SWCNTs but also for covalently functionalized SWCNTs bearing defect sites. The defect-engineered nanotubes often exhibit enhanced sensitivity due to localized emissive states, making them particularly attractive for biosensing applications. Characterization via fluorescence spectroscopy, UV-Vis-nIR absorption, and circular dichroism (CD) confirmed both the chirality and optical purity of the sorted samples. Our results demonstrate that PEG/salt ATP extraction with DNA sequences offers a robust and versatile platform for producing single-chirality SWCNTs suitable for next-generation optical sensing technologies.
Poster #7: Relation between conformal loop ensemble and Brownian motion
Presenter: Jiaqi Liu
Mentor: Si Tang
Department/College: Mathematics
Imagine a collection of molecules sitting at the vertices of a lattice graph. Each molecule has a spin that can point either up or down, and its direction is influenced by its neighbors. If most neighbors are up, it tends to point up too, and vice versa. This is the Ising model, a fundamental model in statistical physics. As we zoom out and make the grid finer, random curves begin to appear, separating clusters of up and down spins. These curves, known as the conformal loop ensemble, arise in many statistical physics models and have rich geometric properties. On the other hand, imagine a tiny pollen grain floating in a glass of water. Even when the water looks still, the grain constantly jitters and moves in an unpredictable way. This random motion is what scientists call Brownian motion. Surprisingly, these two seemingly unrelated models are deeply connected. In ongoing work with Xin Sun and Nina Holden, we explore how Brownian motion can be used to describe the geometry of conformal loop ensembles.
Poster #8: Heat-stiffening mineral-polymer physical networks
Presenter: Qysar Maqbool
Mentor: Niels Holten-Andersen
Department/College: Bioengineering
The physically crosslinked polymer networks constitute an important class of soft matter useful in several fields ranging from wearable electronics to biomedical applications. Although the physically crosslinked polymer networks oftentimes exhibit tunable mechanical responses, they almost universally weaken mechanically at elevated temperatures. In this presentation, I will discuss our soft materials platform of the mineral-polymer nanocomposite networks, where in situ grown mineral nanoparticles act as physical crosslinkers and thereby drive network formation. Our mineral-polymer networks assembled via in situ growth of mineral nanoparticles exhibit a rare phenomenon of reversible heat-stiffening which is evidenced by increased modulus, decreased dissipation and slower stress relaxation at elevated temperatures. Importantly, the degree of heat-stiffening displayed in our mineral-polymer nanocomposite networks is found to be strongly correlated with the nature of the in situ grown mineral nanoparticles. I will present the experimental evidence suggesting entropic origins of the structural changes driving this observed heat-stiffening in our nanocomposite materials. The particular attention will be paid to carefully obtained thermo-rheological responses and step-strain relaxation mechanics to understand how entropically driven structural changes manifest themselves via unusual material mechanics.
Poster #9: Environmental DNA Metabarcoding is Improved by a Barcode Reference Database Built Through Genome Skimming
Presenter: Luke McCartin
Mentor: Santiago Herrera
Department/College: Biological Sciences
Anthropogenic activities threaten marine animal populations that provide ecosystem services in shallow waters and in the deep ocean. Unfortunately, baseline information regarding the regional distributions of marine species in many taxa is limited, precluding their informed conservation. To address this gap in knowledge, environmental DNA (eDNA) sequencing is poised to accelerate marine biodiversity assessment; however, the effectiveness of eDNA sequencing relies on comprehensive reference databases that include DNA barcodes from taxa occurring in a study area. To evaluate the importance of comprehensive reference databases for eDNA sequencing, we collected coral specimens and filtered seawater samples for eDNA sequencing at deep coral communities offshore Puerto Rico. To assemble 28S ribosomal DNA (rDNA) barcodes from coral collections, we conducted low-coverage whole genome sequencing (genome skimming). We sequenced 28S eDNA metabarcodes from seawater samples and analyzed these data with and without including these new references. We found that including new reference barcodes improved the identification of coral eDNA by 1) capturing previously unidentified intragenomic variability in the 28S barcode; and 2) representing taxa occurring at our dive sites near Puerto Rico that we had not previously sequenced. Together, our collection and eDNA sequencing efforts contribute substantially to our knowledge of the regional and bathymetric distributions of deep-sea corals near Puerto Rico. Our findings emphasize the importance of using comprehensive reference databases for eDNA sequencing, and emphasize the method's complementary power for assessing biodiversity in hard-to-reach marine habitats, like the deep sea.
Poster #10: Modeling differing hole mobility in different DATZAA polymorphs
Presenter: Nambi Mohanam
Mentor: Lisa A. Fredin
Department/College: Chemistry
Fast & Directional (anisotropic & ballistic) hole transport is an important charge transport mechanism in devices, for fast and controlled charge movement, which transfers energy and information. Despite the importance of 'decohering' thermal atomic motion in this transport at realistic temperatures, these motions are often explicitly neglected in 'frozen atoms' hole transport models built around the Boltzmann Transport Equations (BTE); instead, these motions are implicitly included in an arbitrary constant for hole 'wave-packet' scattering time. Recently, the Δ-BTE approach has been proposed to explicitly approximate these thermal atomic motions via displacements of atomic positions. We now apply the BTE and Δ-BTE approach to hole transport in crystals of DATZAA with different shapes and colors (i.e. polymorphs or domains). DATZAA is a fluorescent molecular semi-conductor material, being the simplest dipyrrolyldiketone BF2 complex. Comparing between the yellow and vermilion polymorphs of DATZAA, the crystals only differ by the arrangement of bonds in the molecule and the packing of molecules together (i.e, only their stereo-chemistry differ). As expected, 'frozen atoms' calculations already show important differences from the different stereo-chemistry. In addition, the Δ-BTE approach adds important information about thermal atomic motion, providing a more comprehensive picture of the anisotropic ballistic hole transport. These findings are a reminder to explicitly distinguish crystal polymorphs and grain boundaries in the design, modeling and characterization of molecular organic semi-conductors; and indicate that thermal atomic motion can have important implications for the design of molecular organic semiconductors.
Poster #11: Ricci flow and mean curvature flow
Presenter: Keaton Naff
Mentor: Huai-Dong Cao
Department/College: Mathematics
We present a gentle introduction to two fundamental geometric diffusion equations: the Ricci flow and the mean curvature flow. The Ricci flow can be viewed as a parabolic cousin of Einstein’s field equations (general relativity), evolving a metric in a way that smooths out its curvature. The mean curvature flow is a central model for how interfaces evolve in materials science and physics. Both are nonlinear, heat-type partial differential equations that evolve the geometry of shapes. Just as the heat equation smooths temperature distributions over time, these flows tend to transform shapes toward more uniform, symmetric, and recognizable forms. They have played central roles in major advances in differential geometry and geometric analysis, particularly in low dimensions. A central challenge in higher dimensions is that solutions often develop singularities. Modern research focuses on understanding how these singularities arise. We will highlight recent progress on singularity formation in four-dimensional settings.
Poster #13: MembranomeX for Comprehensive Analysis of Single-Pass Transmembrane Proteins and their Complexes
Presenter: L Ponoop Prasad Patro
Mentor: Wonpil Im
Department/College: Biological Sciences
MembranomeX integrates a database and 3 web servers designed to assist in modeling and analysis of single-pass transmembrane (i.e., bitopic) proteins and their complexes. The MembranomeX database compiles structural and functional information for complete sets of bitopic proteins from 20 different organisms spanning all kingdoms of life. It provides hierarchical classification, topologies, intracellular localizations, interactions, complexes, biological pathways, mutations, and other information about bitopic proteins gathered from various sources, including UniProt, PDB, KEGG, MutDB, Reactome, HINT, APID, Complex Portal, and CORUM. To facilitate comparative studies of bitopic proteins, MembranomeX offers advanced search and retrieval options for proteins, their complexes, and pathways, as well as tools for analyzing protein interaction networks and 3D structure visualization. The website provides access to 3 web servers: FMAP for ab initio modeling and stability assessment of ?-helical peptides in membranes, TMDOCK for generating protein transmembrane dimers, and 1TMnet for analyzing networks of bitopic protein interactions. The database also includes atomic structural models of full-length bitopic proteins and their complexes produced by AlphaFold programs, along with transmembrane helix and dimer models generated by FMAP and TMDOCK. All models are positioned in the lipid bilayer using PPM. Structures of protein monomers from the AlphaFold Protein Structure Database were parsed and reassembled into membranes using our software. Combining AlphaFold with our in-house tools and scripts has enabled us to develop a systematic modeling and verification procedure for biologically important complexes of bitopic proteins. Using this procedure, we have generated and deposited dozens of complexes of human cytokine receptors in the MembranomeX database, thereby supporting research of the biological functions and regulation of these proteins in the membrane environment.
Poster #14: Critical Mineral Recovery from Anthracite Mining Waste
Presenter: Asal Saeidfar
Mentor: Carlos E. Romero
Department/College: Energy Research Center
The growing demand for critical minerals and materials, driven by their essential role in energy storage systems, clean energy technologies, electric vehicles, advanced electronics, and national defense, has placed significant strain on existing supply chains. These challenges are primarily due to the geographic concentration of resources, geopolitical tensions, and significant environmental impacts associated with conventional mining and extraction practices. To address this issue, there is an increasing emphasis on developing sustainable, energy-efficient, and innovative recovery techniques, particularly from secondary sources. The Energy Research Center at Lehigh University has been working on a range of studies related to source characterization and recovery techniques for critical materials. One of these studies investigates the potential of coal and coal-derived byproducts as alternative sources of critical elements. Specifically, the geochemical characteristics and mineralogy of coal-bearing deposits in a target area of Pennsylvania are analyzed to evaluate critical mineral and materials potential. Samples, including coal, acid mine drainage, and refuse rock, are collected from Blaschak, an anthracite mining company in Pennsylvania, United States. The concentrations of rare earth elements (REEs) and lithium (Li) are quantified using inductively coupled plasma mass spectrometry (ICP-MS). Furthermore, an electrochemical method is proposed for the selective recovery of REEs and Li from these materials, offering a potential pathway toward environmentally responsible resource extraction.
Poster #15: Size-dependent protein advection on COS-7 cells induced by shear stress
Presenter: Sreeja Sasidharan
Mentor: Aurelia Honerkamp-Smith
Department/College: Physics
The endothelial cells lining blood vessels respond to flow disturbances by initiating inflammatory responses, which contribute to chronic diseases like atherosclerosis. It is well established that these cells are able to detect shear stress, but the precise mechanism they use to do so is not known. The cell membrane and associated proteins are located at the interface between stationary cytoplasm and flowing blood, a likely site for flow sensing. We investigate a physics-based mechanism for flow mechanosensing: extracellular proteins that are free to diffuse can be directly moved across the cell membrane by shear stress, forming concentration gradients. Flow transport of lipid-anchored proteins has been observed in model systems and on protozoans, but never on the surface of mammalian cells. By confocal imaging of live cells, we investigated the flow transport of two extracellular glycosylphosphatidylinositol (GPI) -anchored proteins, tagged with the green fluorescent protein (GFP): glypican-1-GFP and GPI-GFP, expressed in COS-7 cells. We found that the flow transport of proteins was size-dependent, measured the hydrodynamic force experienced by these proteins under applied flow, and showed that glypican-1-GFP forms gradients under physiologically relevant levels of shear stress. We demonstrated that increasing the size of proteins using antibody labeling enhances the hydrodynamic force and, consequently, the flow transport. This study presents the first real-time evidence of size-dependent protein transport occurring on living cells in response to applied shear stress.
Poster #16: Surface Deformation and Jump-To-Contact Instabilities in Soft Substrates
Presenter: Reshma Siddiquie
Mentor: Anand Jagota
Department/College: Bioengineering
Attraction between two surfaces often leads to jump-to-contact, a nucleation event that is the complement of nucleation of a defect under tensile loading. This event contains important information about the interaction forces, but measuring such mechanical instabilities in soft materials just before and after contact presents significant challenges. In this study, we utilize Newton's ring interference patterns observed through an inverted optical microscope to precisely capture the jump-to-contact and deformation behavior of a soft polydimethylsiloxane (PDMS) substrate as it approached by a glass indenter. The experimentally measured deformation profiles and jump instabilities prior to and contact are used to evaluate adhesive forces between the glass and PDMS. An integral equation is employed to convert measured surface displacements into surface tractions, and is validated using Johnson—Kendall—Roberts (JKR) adhesion theory post-contact. The investigation is further extended to PDMS substrates with controlled adhesion (via UV ozone treatment) and varying elastic moduli, achieved through different base-to-curing-agent mixing ratios. Results reveal that the onset and extent of mechanical instabilities are strongly influenced by the substrate's stiffness. The jump-to-contact occurs at a separation of approximately 700 nm for a soft 40 kPa (40:1) PDMS substrate, compared to 200 nm for a stiffer 1 MPa (10:1) substrate. In contrast, control experiments with rigid glass substrates show a jump-to-contact distance of only 50 nm. These findings highlight the critical role of substrate compliance in adhesion-driven instabilities during near-contact interactions.
Poster #18: Stable formations and hydrodynamics of bio-inspired fish schools
Presenter: Puja Sunil
Mentor: Keith Moored
Department/College: Mechanical Engineering & Mechanics
Fish that swim in schools have considerable energy savings compared to an isolated fish. Recently, there is a lot of interest in developing fish-inspired bio-robots that can be used for underwater surveillance and environmental monitoring. We present experiments conducted using a novel free swimming air bearing platform that allow a pair of tuna-inspired robots to swim side-by-side and independently in the streamwise direction. Results show that fish swimming in schools adopt stable formations and swim faster with an improved cost of transport. Stable school formations are driven by body-to-body interactions. A comprehensive parameter space of mismatched amplitudes, lateral body spacing, and phase synchronization is examined to identify the optimum conditions with stable school formations and improved energetics.
Poster #19: Structural health monitoring of large structures using mobile sensing
Presenter: Kevin Theunissen
Mentor: Shamim N. Pakzad
Department/College: Civil and Environmental Engineering
Structural Health Monitoring (SHM) is crucial for ensuring the safety of structures. It enables early damage detection, extends service life, and reduces repair costs. Today, SHM is widely applied to various types of structures, including bridges. Non-destructive evaluation techniques are used to monitor these structures. Data such as displacements, velocities, and accelerations can be collected and processed into various indicators, such as natural frequencies and mode shapes, which can then be used to compare the current state of a structure with its reference state. If a discrepancy is detected, the structure is considered damaged. One of the main current challenges in SHM is the monitoring of large structures, such as bridges. Monitoring these structures can become costly and inefficient when using traditional sensors like accelerometers. As a result, new monitoring techniques are emerging, such as mobile sensing, a novel paradigm offering numerous advantages over conventional stationary sensor networks. With only a few sensors, mobile systems can capture comprehensive spatial information. Moreover, mobile sensing can be combined with the ubiquity of smartphones and Internet of Things (IoT) to create large-scale sensor networks capable of contributing to structural health assessment. However, a major drawback is the contamination of the collected data. To address this issue, new algorithms based on Artificial Intelligence (AI) are being developed to clean the measured signals and extract the bridge's true accelerations. My current research at Lehigh University focuses on advancing the application of mobile sensors combined with AI approaches and using efficient electric transient systems for SHM.
Poster #20: Non-monotone stochastic derivative-free optimization algorithms
Presenter: Trang H. Tran
Mentor: Luis Nunes Vicente
Department/College: Industrial & Systems Engineering
In derivative-free optimization (DFO) one minimizes functions for which the gradient is unavailable or expensive to compute. In many applications, objective function values and gradients are noisy due to simulations or system randomness. Current DFO algorithms accept trial points when a certain monotone decrease of the objection function is achieved. However, when applied to complex landscapes, such a requirement may trap the algorithm in a neighborhood of sub-optimal solutions. Non-monotone techniques allow the acceptance of trial points with temporary increases in the objective value, but have only been developed in the deterministic case. The innovation in this study is the development of non-monotone DFO techniques in the stochastic case where evaluations are noisy. We have been investigating various non-monotone strategies, including those that replace the estimated function value at the trial point with a convex combination of past and present estimates, or with the maximum of previous observed function values. In this talk, we will present a numerical comparison of the various non-monotone techniques for both linesearch and direct-search methods. The numerical results are obtained for two sets of problems from the CUTEest collection (with different levels of multimodality) and analyzed through performance and data profiles. Our results demonstrate that non-monotone techniques exhibit superior performance compared to their monotone counterparts. This empirical evidence motivates our current theoretical investigation of the rate of convergence of non-monotone stochastic DFO algorithms. This is joint work with Anjie Ding and Luis Nunes Vicente.
Poster #21: Structure of DNA-SWCNT Hybrids for SWCNT Sorting and Biosensing
Presenter: Luke Wang
Mentor: Anand Jagota
Department/College: Bioengineering
Single-walled carbon nanotubes (SWCNTs) hold great promise for optical biosensors, yet isolating single-chirality populations and maximizing signal remain major barriers. Single-stranded deoxyribonucleic acid (ssDNA) wraps SWCNTs in water and imparts strong sequence-dependent selectivity, but the structural principles underlying this recognition are only beginning to emerge. Here we combine coarse-grained molecular dynamics, single-molecule near-infrared fluorescence spectroscopy, and supervised machine learning to map how ssDNA sequence, helical handedness, and binding free energy interrelate. A new handedness-propagation metric quantifies twist transfer along the polymer, while potentials of mean force expose sequence-specific detachment barriers. Comparative analysis across twelve ssDNA sequences and three chiral nanotube species uncovers a spectrum of wrapping geometries—ranging from shallow zig-zags to tight helices—each linked to a characteristic binding-energy fingerprint and optical response. These insights provide a framework for rationally pairing ssDNA sequences with target nanotube chiralities, advancing both high-purity sorting and next-generation biosensor design.
Poster #22: Prompting Transportation Electrification with a 99.55%-Efficient GaN-Based Multilevel High-Power Wireless Power Transfer Converter
Presenter: Yue Wu
Mentor: Fei Lu
Department/College: Electrical and Computer Engineering
In the recent decade, the transportation electrification industry has undergone a booming development. To meet the surging need for efficient and user-friendly charging methods, high-power wireless power transfer (WPT) technologies have attracted increasing attention due to their merits of contactless power delivery, enhanced charging safety, and perfect electrical isolation compared to conventional plug-in charging methods. However, existing WPT technologies suffer from the bottle necks of limited power ratings, and unsatisfactory power transfer efficiency, thus driving urgent demands for better power converters and magnetic couplers. As the core of WPT systems, power converter is critical for improving voltage endurance, rated power level, power density, and conversion efficiency. To address these issues, our research team has proposed a new GaN-based multilevel converter with the straightforward diode-clamped neutral point clamp circuit topology. Meanwhile, a mixed signal driven scheme is proposed to precisely control eight GaN FETs at a high frequency up to 85kHz, enabling efficient and reliable operation without the need for complex close loop control. Experiments prove that this converter achieves a voltage endurance of 1.1kV, a power level of 18.61kW, a peak power conversion efficiency of 99.55%, and a remarkable power density of 206.78kW/m2. This converter offers a simple, high-performance, and cost-effective solution for next-generation high-power WPT systems, with the great potential contributions to the advancement of transportation electrification industry and energy-efficient future.
Poster #23: Ethylene to Propylene through Simultaneous Ethylene Dimerization and Olefin Metathesis with Dual-Site Supported 8%NiSO4-8%ReO4/γ-Al2O3 Catalyst
Presenter: Shuting Xiang
Mentor: Israel Wachs
Department/College: Chemical & Biomolecular Engineering
Propylene is a key petrochemical traditionally produced as a byproduct of steam cracking. However, the shift to lighter feedstocks due to increased shale gas production has reduced propylene yields, creating a need for new "on-purpose" production methods. Ethylene-to-propylene (ETP) conversion via ethylene dimerization and olefin metathesis is a promising alternative. In this study, a dual-site 8%NiSO4-8%ReO4/γ-Al2O3 catalyst was synthesized, where NiSO4 facilitates ethylene dimerization to 2-butene, and ReO4 catalyzes the metathesis of ethylene and 2-butene to propylene. Comprehensive characterization-using in situ Raman, IR, UV-vis, X-ray absorption spectroscopy, and High Sensitivity-Low Energy Ion Scattering (HS-LEIS)-identified surface (O=)2Re7⁺O2, O=S6⁺O3, and Ni2⁺Ox species on the alumina support. Chemical probing via temperature-programmed surface reactions (TPSR) and steady-state catalysis confirmed the distinct roles of these sites. Ethylene dimerization was only observed when both surface SO4 and NiOx were present, indicating a synergistic effect. Neither SO4 nor NiO6 sites catalyzed metathesis alone or together, while ReO4 sites exclusively facilitated olefin metathesis. Notably, incorporating NiSO4 enhanced the metathesis activity of ReO4/Al2O3, attributed to competitive adsorption on surface hydroxyls.