Search for: All records

It has been recently discovered that the thermosetting matrix of engineering composites can be fully depolymerized in organic solvents through covalent bond exchange reactions (BERs) between the polymer network and solvent molecules. This breakthrough enables the eco-friendly and sustainable recovery of valuable fiber reinforcements using mild processing conditions. However, current investigations have been limited to proof-of-concept experimental demonstrations, leaving unanswered questions regarding the influence of temperature, solvent choice, and fiber arrangement on composite depolymerization performance. These factors are crucial for the commercialization and widespread industrial implementation of this technique. To address this significant knowledge gap, this study aims to establish the relationship between composite depolymerization speed and various material and processing conditions. A multiscale diffusion-reaction computational model is defined based on the finite element method, which links the microscale BER rate to the continuum-level composite depolymerization kinetics. Specifically, it reveals how the processing temperature, solvent diffusivity, fiber content, and fiber arrangement affect the overall composite depolymerization speed. The study enhances our understanding of the underlying mechanisms of composite recycling using organic solvents. As a result, it provides valuable insights for industrial stakeholders, allowing them to optimize depolymerization conditions, make informed material selections, and develop suitable business models for waste management. 

Medical imaging deep learning models are often large and complex, requiring specialized hardware to train and evaluate these models. To address such issues, we propose the PocketNet paradigm to reduce the size of deep learning models by throttling the growth of the number of channels in convolutional neural networks. We demonstrate that, for a range of segmentation and classification tasks, PocketNet architectures produce results comparable to that of conventional neural networks while reducing the number of parameters by multiple orders of magnitude, using up to 90% less GPU memory, and speeding up training times by up to 40%, thereby allowing such models to be trained and deployed in resource-constrained settings. 

We present the first measurement of cosmic-ray fluxes of ${}^6\mathrm{Li}$and ${}^7\mathrm{Li}$isotopes in the rigidity range from 1.9 to 25 GV. The measurements are based on $9.7\times {10}^5$ ${}^6\mathrm{Li}$and $1.04\times {10}^6$ ${}^7\mathrm{Li}$nuclei collected by the Alpha Magnetic Spectrometer on the International Space Station from May 2011 to October 2023. We observe that over the entire rigidity range the ${}^6\mathrm{Li}$and ${}^7\mathrm{Li}$fluxes exhibit nearly identical time variations and, above $\sim 4\mathrm{GV}$, the time variations of ${}^6\mathrm{Li}$, ${}^7\mathrm{Li}$, He, Be, B, C, N, and O fluxes are identical. Above $\sim 7\mathrm{GV}$, we find an identical rigidity dependence of the ${}^6\mathrm{Li}$and ${}^7\mathrm{Li}$fluxes. This shows that they are both produced by collisions of heavier cosmic-ray nuclei with the interstellar medium and, in particular, excludes the existence of a sizable primary component in the ${}^7\mathrm{Li}$flux. Published by the American Physical Society2025 

We report the properties of precision time structures of cosmic nuclei He, Li, Be, B, C, N, and O fluxes over an 11-year solar cycle from May 2011 to November 2022 in the rigidity range from 1.92 to 60.3 GV. The nuclei fluxes show similar but not identical time variations with amplitudes decreasing with increasing rigidity. In particular, below 3.64 GV the Li, Be, and B fluxes, and below 2.15 GV the C, N, and O fluxes, are significantly less affected by solar modulation than the He flux. We observe that these differences in solar modulation are linearly correlated with the differences in the spectral indices of the cosmic nuclei fluxes. This shows, in a model-independent way, that solar modulation of galactic cosmic nuclei depends on their spectral shape. In addition, solar modulation differences due to nuclei velocity dependence on the mass-to-charge ratio ( $A/Z$) are not observed. Published by the American Physical Society2025 

Precision measurements by the Alpha Magnetic Spectrometer (AMS) on the International Space Station of the deuteron ( $D$) flux are presented. The measurements are based on $21\times {10}^6$ $D$nuclei in the rigidity range from 1.9 to 21 GV collected from May 2011 to April 2021. We observe that over the entire rigidity range the $D$flux exhibits nearly identical time variations with the $p$, ${}^3\mathrm{He}$, and ${}^4\mathrm{He}$fluxes. Above 4.5 GV, the $D/{}^4\mathrm{He}$flux ratio is time independent and its rigidity dependence is well described by a single power law $\propto R^{\mathrm{\Delta }}$with ${\mathrm{\Delta }}_{D/{}^4\mathrm{He}}=-0.108\pm 0.005$. This is in contrast with the ${}^3\mathrm{He}/{}^4\mathrm{He}$flux ratio for which we find ${\mathrm{\Delta }}_{{}^3\mathrm{He}/{}^4\mathrm{He}}=-0.289\pm 0.003$. Above $\sim 13\mathrm{GV}$we find a nearly identical rigidity dependence of the $D$and $p$fluxes with a $D/p$flux ratio of $0.027\pm 0.001$. These unexpected observations indicate that cosmic deuterons have a sizable primarylike component. With a method independent of cosmic ray propagation, we obtain the primary component of the $D$flux equal to $9.4\pm 0.5\%$of the ${}^4\mathrm{He}$flux and the secondary component of the $D$flux equal to $58\pm 5\%$of the ${}^3\mathrm{He}$flux. Published by the American Physical Society2024