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Results for “backbone”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Self-Assembly of Charged Diblock Copolymers with Reduced Backbone Polarity
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Bioconjugate Platform for Iterative Backbone N-Methylation of Peptides
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Serum-Stable and Selective Backbone-N-Methylated Cyclic Peptides That Inhibit Prokaryotic Glycolytic
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Oligoether-Functionalized PEDOT: Combining an EDOT Backbone with Polar Side Chains for Solution Processability and High Electrical Conductivity
Conjugated polymers functionalized with oligoether (OE)-based side chains are a key class of materials for various organic electronic applications, including transparent electrodes, thermoelectrics, electrochromic displays, and electrochemical transistors. Herein, we report a highly soluble OE-functionalized poly(3,4-ethylenedioxythiophene) (PEDOT) homopolymer, prepared by direct (hetero)arylation polymerization, which allows solution processing to yield films with comparable redox properties to oxidatively polymerized PEDOT. This polymer, PEDOT(OE3), when optimally oxidatively doped, reaches among the highest electrical conductivities of any OE-functionalized polymer and is comparable to more synthetically complex OE-functionalized polymers. X-ray scattering and spectroscopy were utilized to rationalize the transport properties resulting from varying the doping level. Comparison of PEDOT(OE3) to a series of OE-functionalized dioxythiophenes with varying amounts of 3,4-ethylenedioxythiophene units allows for a deeper understanding of structure–property relationships through charge-transport models. Ultimately, PEDOT(OE3) is shown to be a material with exceptional charge-transport properties and is promising for various applications.
Synergy between Photoluminescence and Charge Transport Achieved by Finely Tuning Polymeric Backbones for Efficient Light-Emitting Transistor
The lack of design principle for developing high-performance polymer materials displaying strong fluorescence and high ambipolar charge mobilities limited their performance in organic light-emitting transistors (OLETs), electrically pumped organic laser, and other advanced electronic devices. Here, a series of semiladder polymers by copolymerization of weak acceptors (TPTQ or TPTI) and weak donors (fluorene (F) or carbazole (C)) have been developed for luminescent and charge transporting properties. It was found that enhanced planarity, high crystallinity, and a delicate balance in interchain aggregation obtained in the new copolymer, TPTQ-F, contributed to high ambipolar charge mobilities and photoluminescent quantum yield. TPTQ-F showed excellent performance in solution-processed multilayered OLET devices with an external quantum efficiency (EQE) of 5.3%.
Backbone Engineering of Monodisperse Conjugated Polymers via Integrated Iterative Binomial Synthesis
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Conformational rearrangements enable iterative backbone N-methylation in RiPP biosynthesis
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Accelerating phase field simulations through a hybrid adaptive Fourier neural operator with U-net backbone
Prolonged contact between a corrosive liquid and metal alloys can cause progressive dealloying. For one such process as liquid-metal dealloying (LMD), phase field models have been developed to understand the mechanisms leading to complex morphologies. However, the LMD governing equations in these models often involve coupled non-linear partial differential equations (PDE), which are challenging to solve numerically. In particular, numerical stiffness in the PDEs requires an extremely refined time step size (on the order of 10 -12 s or smaller). This computational bottleneck is especially problematic when running LMD simulation until a late time horizon is required. This motivates the development of surrogate models capable of leaping forward in time, by skipping several consecutive time steps at-once. In this paper, we propose a U-shaped adaptive Fourier neural operator (U-AFNO), a machine learning (ML) based model inspired by recent advances in neural operator learning. U-AFNO employs U-Nets for extracting and reconstructing local features within the physical fields, and passes the latent space through a vision transformer (ViT) implemented in the Fourier space (AFNO). We use U-AFNOs to learn the dynamics of mapping the field at a current time step into a later time step. We also identify global quantities of interest (QoI) describing the corrosion process (e.g., the deformation of the liquid-metal interface, lost metal, etc.) and show that our proposed U-AFNO model is able to accurately predict the field dynamics, in spite of the chaotic nature of LMD. Most notably, our model reproduces the key microstructure statistics and QoIs with a level of accuracy on par with the high-fidelity numerical solver, while achieving a significant 11, 200 × speed-up on a high-resolution grid when comparing the computational expense per time step. Finally, we also investigate the opportunity of using hybrid simulations, in which we alternate forward leaps in time using the U-AFNO with high-fidelity time stepping. We demonstrate that while advantageous for some surrogate model design choices, our proposed U-AFNO model in fully auto-regressive settings consistently outperforms hybrid schemes.
Functional elucidation of TfuA in peptide backbone thioamidation
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Organophosphorus decorated lithium borate and phosphate salts with extended π-conjugated backbone
Several new bifunctional salts, Li[B(DPN)2] , Li[B(DPN)(ox)] and Li[P(DPN)3] , have been prepared from the phosphorus( v )-containing chelating ligand 2,3-dihydroxynaphthalene-1,4-(tetraethyl)bis(phosphonate) ( H2-DPN ).
Backbone-driven host–dopant miscibility modulates molecular doping in NDI conjugated polymers
Molecular doping is the key to enabling organic electronic devices, however, the design strategies to maximize doping efficiency demands further clarity and comprehension.
Nanoscale layers of precise ion-containing polyamides with lithiated phenyl sulfonate in the polymer backbone
Precise polyamide ionomer produces well-defined nanoscale layers.
Filling the gap with a bulky diaryl boron group: fluorinated and non-fluorinated copper pyrazolates fitted with a dimesityl boron moiety on the backbone
Successful synthesis has been reported of 4-Mes 2 B-3,5-(CF 3 ) 2 PzH and 4-Mes 2 B-3,5-(CF 3 ) 2 PzH bearing sterically demanding diarylboron moieties at the pyrazole ring 4-position, and their corresponding copper(I) pyrazolate complexes. They show visible blue photoluminescence in solution. The X-ray crystal structures revealed that the fluorinated {[4-BMes 2 -3,5-(CF 3 ) 2 Pz]Cu} 3 crystallizes as discrete trinuclear molecules whereas as the non-fluorinated {[4-BMes 2 -3,5-(CH 3 ) 2 Pz]Cu} 3 forms dimers of trimers with two close inter-trimer Cu···Cu separations. The solid {[4-BMes 2 -3,5-(CF 3 ) 2 Pz]Cu} 3 featuring a sterically confined Cu 3 N 6 core displays bright blue phosphorescence while {[4-BMes 2 -3,5-(CH 3 ) 2 Pz]Cu} 3 , which is a dimer of a trimer, is a red phosphor at room temperature. Here, this work illustrates the modulation of photo-physical properties of metal pyrazolates by adjusting the supporting ligand steric features and introducing secondary diarylboron luminophores. Computational analysis of the structures and photophysical properties of copper complexes are also presented.
Accelerating Phase Field Simulations Through a Hybrid Adaptive Fourier Neural Operator with U-Net Backbone
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Backbone Architectures for Space Domain Awareness
Presentation on modifying neural network architectures to function for space domain awareness imagery.