linear macromolecules
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Polimery ◽  
2021 ◽  
Vol 66 (5) ◽  
pp. 293-297
Author(s):  
Santiago Ariel Schustik ◽  
Fiorella Cravero ◽  
Maria Jimena Martinez ◽  
Ignacio Ponzoni ◽  
Monica Fatima Diaz

The Polymer Maker SMILES-based (PolyMaS) software was used to generate linear macromolecules from the repeating structural units (SRU) of polymers without limiting their length and molar mass. The SRU input is stored in the SMILES code available on the Internet. PolyMaS makes head-tail junctions to the desired length of the macromolecule.


2020 ◽  
Vol 142 (8) ◽  
Author(s):  
Kotaybah Hashlamoun ◽  
Salvatore Federico

Abstract Due to the avascular nature of articular cartilage, molecular transport occurs via interstitial fluid flow as well as via diffusion. Diffusion in cartilage has been studied experimentally, but no mathematical models have been developed to interpret the experimental results and the observed isotropy or anisotropy in the different cartilage zones. Here, we propose a model for the determination of the diffusivity tensor of uncharged macromolecules in articular cartilage, accounting for the inhomogeneity and anisotropy arising from fiber arrangement, volumetric fraction, and radius. We study a representative element of volume (REV) comprising a fiber surrounded by fluid-saturated proteoglycan matrix. The REV permeability tensor is evaluated using a previously developed model, while the REV diffusivity tensor is obtained by incorporating the hydrodynamic effect and the steric effect of the fiber-reinforced matrix. Both effects are represented by anisotropic second-order tensors. The overall diffusivity tensor is obtained as the averaging integral of the REV diffusivity, weighted by the probability distribution of fiber orientation. The model's predictions of the trend of the magnitude of the diffusivity of spheroidal macromolecules as a function of molecular radius agree with published experimental results. For large linear macromolecules, the model underestimates the diffusivity magnitude (i.e., the equivalent isotropic diffusivity). The model correctly predicts the anisotropic behavior for linear macromolecules, although it underestimates the numerical value of the diffusivity anisotropy ratio of large linear macromolecules in the superficial zone, and overestimates it in the deep zone. In summary, this model constitutes a first step toward understanding the relation between diffusivity and permeability in articular cartilage.


2020 ◽  
Vol 101 (2) ◽  
Author(s):  
Nathaniel Rupprecht ◽  
Dervis Can Vural

2016 ◽  
Vol 7 (1) ◽  
Author(s):  
Nicolas Zydziak ◽  
Waldemar Konrad ◽  
Florian Feist ◽  
Sergii Afonin ◽  
Steffen Weidner ◽  
...  

Abstract Designing artificial macromolecules with absolute sequence order represents a considerable challenge. Here we report an advanced light-induced avenue to monodisperse sequence-defined functional linear macromolecules up to decamers via a unique photochemical approach. The versatility of the synthetic strategy—combining sequential and modular concepts—enables the synthesis of perfect macromolecules varying in chemical constitution and topology. Specific functions are placed at arbitrary positions along the chain via the successive addition of monomer units and blocks, leading to a library of functional homopolymers, alternating copolymers and block copolymers. The in-depth characterization of each sequence-defined chain confirms the precision nature of the macromolecules. Decoding of the functional information contained in the molecular structure is achieved via tandem mass spectrometry without recourse to their synthetic history, showing that the sequence information can be read. We submit that the presented photochemical strategy is a viable and advanced concept for coding individual monomer units along a macromolecular chain.


2016 ◽  
Author(s):  
J. Kahovec ◽  
P. Kratochvíl ◽  
A. D. Jenkins ◽  
I. Mita ◽  
I. M. Papisov ◽  
...  

Soft Matter ◽  
2016 ◽  
Vol 12 (40) ◽  
pp. 8425-8439 ◽  
Author(s):  
Zuzana Benková ◽  
Pavol Námer ◽  
Peter Cifra

Methods ◽  
2011 ◽  
Vol 54 (1) ◽  
pp. 124-135 ◽  
Author(s):  
Georges M. Pavlov ◽  
Igor Y. Perevyazko ◽  
Olga V. Okatova ◽  
Ulrich S. Schubert

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