ABSTRACT A new series of six imidazolium‐based ionenes containing aromatic amide linkages has been developed. These ionene‐polyamides are all constitutional isomers varying in the regiochemistry of the amide linkages (para, meta) and xylyl linkages (ortho, meta, para) along the polymer backbone. The physical properties as well as the gas separation behaviors of the corresponding membranes have been extensively studied. These ionene‐polyamide membranes show excellent thermal and mechanical stabilities, together with self‐healing and shape memory characteristics. Most importantly, [TC‐API(p)‐Xy][Tf2N] and [IC‐API(m)‐Xy][Tf2N] membranes (TC, terephthaloyl chloride; API, 1‐(3‐aminopropyl)imidazole; Xy, xylyl; Tf2N, bis(trifluoromethylsulfonyl) imide; IC, isophthaloyl chloride), where the amide and xylyl linkages are attached at para and meta positions, exhibit superior selectivity for CO2/CH4and CO2/N2gas pairs. We also demonstrate the transport properties and diverse applicability of our newly developed ionene‐polyamides, particularly [TC‐API(p)‐Xy][Tf2N], for various industrial applications. © 2019 Society of Chemical Industry
more »
« less
Overcoming the barrier: designing novel thermally robust shape memory vitrimers by establishing a new machine learning framework
A sophisticated machine learning framework was developed to design thermally robust shape memory vitrimers (TRSMVs) with superior recycling efficiency, an elevatedTg, and outstanding shape memory properties, surpassing traditional limitations.
more »
« less
- Award ID(s):
- 1946231
- PAR ID:
- 10496342
- Publisher / Repository:
- https://pubs.rsc.org/en/content/articlelanding/2023/cp/d3cp03631f/unauth
- Date Published:
- Journal Name:
- Physical Chemistry Chemical Physics
- Volume:
- 25
- Issue:
- 43
- ISSN:
- 1463-9076
- Page Range / eLocation ID:
- 30049 to 30065
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Abstract Nematic monodomain liquid crystal elastomers (LCEs) undergo efficient temperature‐induced reversible shape‐shifting around the nematic‐isotropic transition temperature (Tni) due to the presence of the liquid‐crystalline order of mesogens. Usually, theTniof nematic LCEs is much higher than the human body temperature, and therefore LCEs are not often considered for biomedical applications. This study describes an LCE system where theTniis tuned by substitution of the rigid mesogens RM257 with a flexible backbone PEGDA250. By systematically substituting the RM257 with PEGDA250, theTniof LCEs was observed to decrease from 66°C to 23°C. A rate‐optimized LCE material was fabricated with 10 mol % rigid mesogens substituted with a flexible backbone that demonstratedTniat 32°C, in‐between the room temperature of 20°C and the body temperature of 37°C. TheTniallowed the programmed shape at room temperature, quick shape‐shifting upon exposure to body temperature, and before‐programmed shape when kept at body temperature. This LCE material displayed reversible length change of 23%, opacity change, and shape change between room temperature and body temperature.more » « less
-
Abstract We present a 3D shape analysis of both dark matter (DM) and stellar matter (SM) in simulated dwarf galaxies to determine whether stellar shape traces DM shape. Using 80 central and satellite dwarf galaxies from three simulation suites (“Marvelous Massive Dwarfs,” “Marvelous Dwarfs,” and the “DC Justice League”) spanning stellar masses of 106–1010M⊙, we measure 3D shapes through the moment of inertia tensor at twice the effective radius to derive axis ratios (C/AandB/A) and triaxiality. We find that stellar shape does follow DM halo shape for our dwarf galaxies. However, the presence of a stellar disk in more massive dwarfs (M* ≳ 107.5M⊙) pulls the distribution of stellarC/Aratios to lower values, while in lower-mass galaxies the gravitational potential remains predominantly shaped by DM. Similarly, stellar triaxiality generally tracks DM triaxiality, with this relationship being particularly strong for nondisky galaxies and weaker in disky systems. These correlations are reinforced by strong alignment between the SM and DM axes, particularly in disk galaxies. Further, we find no detectable difference in either SM or DM shapes when comparing two different supernova feedback implementations, demonstrating that shape measurements are robust to different implementations of baryonic feedback in dwarf galaxies. We also observe that a dwarf galaxy’s shape is largely unperturbed by recent mergers. This comprehensive study demonstrates that stellar shape measurements can serve as a reliable tool for inferring DM shapes in dwarf galaxies.more » « less
-
ABSTRACT Shape transformation upon annealing of fused filament fabrication additively manufacturing structures is investigated as a one‐way shape memory strategy using commodity thermoplastics. Irreversible thermal strain, which is a measurement of shape transformation upon annealing, is shown to depend on both raster angle and layer thickness, both of which are parameters than can be easily adjusted on most FFF printers. We present an algorithm based on our understanding of the underlying micromechanics of the system that allows for input of desired final dimensions and output the necessary print parameters. We also demonstrate that this approach is extensible to other materials and report more complex shape memory geometries. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci.2019,136, 48239.more » « less
-
Abstract Computational methods are increasingly being incorporated into the exploitation of microstructure–property relationships for microstructure-sensitive design of materials. In the present work, we propose non-intrusive materials informatics methods for the high-throughput exploration and analysis of a synthetic microstructure space using a machine learning-reinforced multi-phase-field modeling scheme. We specifically study the interface energy space as one of the most uncertain inputs in phase-field modeling and its impact on the shape and contact angle of a growing phase during heterogeneous solidification of secondary phase between solid and liquid phases. We evaluate and discuss methods for the study of sensitivity and propagation of uncertainty in these input parameters as reflected on the shape of the Cu6Sn5intermetallic during growth over the Cu substrate inside the liquid Sn solder due to uncertain interface energies. The sensitivity results rankσSI,σIL, andσIL, respectively, as the most influential parameters on the shape of the intermetallic. Furthermore, we use variational autoencoder, a deep generative neural network method, and label spreading, a semi-supervised machine learning method for establishing correlations between inputs of outputs of the computational model. We clustered the microstructures into three categories (“wetting”, “dewetting”, and “invariant”) using the label spreading method and compared it with the trend observed in the Young-Laplace equation. On the other hand, a structure map in the interface energy space is developed that showsσSIandσSLalter the shape of the intermetallic synchronously where an increase in the latter and decrease in the former changes the shape from dewetting structures to wetting structures. The study shows that the machine learning-reinforced phase-field method is a convenient approach to analyze microstructure design space in the framework of the ICME.more » « less
An official website of the United States government

