arXiv subjects

Ester Segal

Publications and source records attributed to Ester Segal.

3 recordsLinked to original sources

arXiv2026

Modeling the Thermal Behavior of Photopolymers for In-Space Fabrication

Future long-duration space missions will require in-situ, on-demand manufacturing of tools and components. Photopolymer-based processes are attractive for this purpose due to their low energy requirements, volume efficiency, and precise control of curing. However, photopolymerization generates significant heat, which is difficult to regulate in microgravity where natural convection is absent, leading to defects such as surface blistering and deformation. In this work, we combine experimental studies and modeling to address these thermal challenges. We report results from International Space Station (ISS) experiments and a dedicated parabolic flight campaign, which confirm that suppressed convective heat transfer in microgravity exacerbates thermal buildup and defect formation. Building on these observations, we present a predictive thermal model that couples heat transfer, light absorption, and evolving material properties to simulate polymerization and temperature evolution under terrestrial and microgravity conditions. Laboratory validation demonstrates strong agreement between model predictions and measured temperature profiles. Applying the model to the ISS experiments, we show that the model accurately reproduces experimentally observed blistering in TJ-3704A, a commercial acrylate-based polymer resin, while also predicting defect-free outcomes for Norland optical adhesives. The model functions as a design tool for defect-free in-space manufacturing, enabling selection of polymer properties, exposure strategies, and environmental conditions that together inhibit excess thermal buildup, paving the way for scalable, reliable in-situ manufacturing during future missions.

cond-mat.mtrl-sci↗

arXiv2022

Self-Assembled Fatty Acid Crystalline Coatings Display Non-Toxic Superhydrophobic Antimicrobial Properties

Superhydrophobcity is a well-known wetting phenomenon found in numerous plants and insects. It is achieved by the combination of the surfaces chemical properties and its surface roughness. Inspired by nature, numerous synthetic superhydrophobic surfaces have been developed for various applications. Designated surface coating is one of the fabrication routes to achieve the superhydrophobicity. Yet, many of these coatings, such as fluorine-based formulations, may pose severe health and environmental risks, limiting the applicability. Herein, we present a new family of superhydrophobic coatings comprised of natural saturated fatty acids, which are not only a part of our daily diet, but can be produced from renewable feedstock, providing a safe and sustainable alternative to existing state-of-the-art. These crystalline coatings are readily fabricated via single-step deposition routes, thermal deposition or spray-coating. The fatty acids self-assemble into highly hierarchical crystalline structures exhibiting a water contact angle of about 165 degrees and contact angle hysteresis lower than 6 degrees, while their properties and morphology depend on the specific fatty acid used as well as on the deposition technique. Moreover, the fatty acid coatings demonstrate excellent thermal stability. Importantly these new family of coatings displays excellent anti-biofouling and antimicrobial properties against Escherichia coli and Listeria innocua, used as relevant model Gram-negative and Gram-positive bacteria, respectively. We believe that these coatings have a great application potential in the fields, where other alternatives are prohibited due to safety limitations, while at the same time their usage in other regulation-free applications is not limited.

cond-mat.soft↗

arXiv2021

Signal Processing Techniques to Reduce the Limit of Detection for Thin Film Biosensors

The ultimate detection limit of optical biosensors is often limited by various noise sources, including those introduced by the optical measurement setup. While sophisticated modifications to instrumentation may reduce noise, a simpler approach that can benefit all sensor platforms is the application of signal processing to minimize the deleterious effects of noise. In this work, we show that applying complex Morlet wavelet convolution to Fabry-Pérot interference fringes characteristic of thin film reflectometric biosensors effectively filters out white noise and low frequency reflectance variations. Subsequent calculation of an average difference in phase between the filtered analyte and reference signals enables a significant reduction in the limit of detection (LOD) enabling closer competition with current state-of-the-art techniques. This method is applied on experimental data sets of thin film porous silicon sensors (PSi) in buffered solution and complex media obtained from two different laboratories. The demonstrated improvement in LOD achieved using wavelet convolution and average phase difference paves the way for PSi optical biosensors to operate with clinically relevant detection limits for medical diagnostics, environmental monitoring, and food safety.

eess.SP↗