Glass transition temperature prediction of polymers through the mass-per-flexible-bond principle

Machine learning discovery of high-temperature polymers

To formulate a machine learning (ML) model to establish the polymer's structure-property correlation for glass transition temperatureT g , we collect a diverse set of nearly 13,000 real homopolymers from the largest polymer database, PoLyInfo. We train the deep neural network (DNN) model with 6,923 experimentalT g values using Morgan fingerprint representations of chemical structures for these polymers. Interestingly, the trained DNN model can reasonably predict the unknownT g values of polymers with distinct molecular structures, in comparison with molecular dynamics simulations and experimental results. With the validated transferability and generalization ability, the ML model is utilized for high-throughput screening of nearly one million hypothetical polymers. We identify more than 65,000 promising candidates withT g > 200°C, which is 30 times more than existing known high-temperature polymers (∼2,000 from PoLyInfo). The discovery of this large number of promising candidates will be of significant interest in the development and design of high-temperature polymers.

Glass transition temperature from the chemical structure of conjugated polymers

The glass transition temperature (Tg) is a key property that dictates the applicability of conjugated polymers. The Tg demarks the transition into a brittle glassy state, making its accurate prediction for conjugated polymers crucial for the design of soft, stretchable, or flexible electronics. Here we show that a single adjustable parameter can be used to build a relationship between the Tg and the molecular structure of 32 semiflexible (mostly conjugated) polymers that differ drastically in aromatic backbone and alkyl side chain chemistry. An effective mobility value, ζ, is calculated using an assigned atomic mobility value within each repeat unit. The only adjustable parameter in the calculation of ζ is the ratio of mobility between conjugated and non-conjugated atoms. We show that ζ correlates strongly to the Tg, and that this simple method predicts the Tg with a root-mean-square error of 13 °C for conjugated polymers with alkyl side chains.

Evaluating the in vivo glial response to miniaturized parylene cortical probes coated with an ultra-fast degrading polymer to aid insertion

OBJECTIVE

Despite the feasibility of short-term neural recordings using implantable microelectrodes, attaining reliable, chronic recordings remains a challenge. Most neural recording devices suffer from a long-term tissue response, including gliosis, at the device-tissue interface. It was hypothesized that smaller, more flexible intracortical probes would limit gliosis by providing a better mechanical match with surrounding tissue.

APPROACH

This paper describes the in vivo evaluation of flexible parylene microprobes designed to improve the interface with the adjacent neural tissue to limit gliosis and thereby allow for improved recording longevity. The probes were coated with an ultrafast degrading tyrosine-derived polycarbonate (E5005(2K)) polymer that provides temporary mechanical support for device implantation, yet degrades within 2 h post-implantation. A parametric study of probes of varying dimensions and polymer coating thicknesses were implanted in rat brains. The glial tissue response and neuronal loss were assessed from 72 h to 24 weeks post-implantation via immunohistochemistry.

MAIN RESULTS

Experimental results suggest that both probe and polymer coating sizes affect the extent of gliosis. When an appropriate sized coating dimension (100 µm  ×  100 µm) and small probe (30 µm  ×  5 µm) was implanted, a minimal post-implantation glial response was observed. No discernible gliosis was detected when compared to tissue where a sham control consisting of a solid degradable polymer shuttle of the same dimensions was inserted. A larger polymer coating (200 µm  ×  200 µm) device induced a more severe glial response at later time points, suggesting that the initial insertion trauma can affect gliosis even when the polymer shuttle degrades rapidly. A larger degree of gliosis was also observed when comparing a larger sized probe (80 µm  ×  5 µm) to a smaller probe (30 µm  ×  5 µm) using the same polymer coating size (100 µm  ×  100 µm). There was no significant neuronal loss around the implantation sites for most device candidates except the group with largest polymer coating and probe sizes.

SIGNIFICANCE

These results suggest that: (1) the degree of mechanical trauma at device implantation and mechanical mismatches at the probe-tissue interface affect long term gliosis; (2) smaller, more flexible probes may minimize the glial response to provide improved tissue biocompatibility when used for chronic neural signal recording; and (3) some degree of glial scarring did not significantly affect neuronal distribution around the probe.

Phenolic Compounds from the Flowers of Bombax malabaricum and Their Antioxidant and Antiviral Activities

Three new phenolic compounds 1-3 and twenty known ones 4-23 were isolated from the flowers of Bombax malabaricum. Their chemical structures were elucidated by spectroscopic analyses (IR, ESI-MS, HR-ESI-MS, 1D- and 2D-NMR) and chemical reactions. The antioxidant capacities of the isolated compounds were tested using FRAP and DPPH radical-scavenging assays, and compounds 4, 6, 8, 12, as well as the new compound 2, exhibited stronger antioxidant activities than ascorbic acid. Furthermore, all of compounds were tested for their antiviral activities against RSV by the CPE reduction assay and plaque reduction assay. Compounds 4, 10, 12 possess in vitro antiviral activities, and compound 10 exhibits potent anti-RSV effects, comparable to the positive control ribavirin.

Coating flexible probes with an ultra fast degrading polymer to aid in tissue insertion

We report a fabrication process for coating neural probes with an ultrafast degrading polymer to create consistent and reproducible devices for neural tissue insertion. The rigid polymer coating acts as a probe insertion aid, but resorbs within hours post-implantation. Despite the feasibility for short term neural recordings from currently available neural prosthetic devices, most of these devices suffer from long term gliosis, which isolates the probes from adjacent neurons, increasing the recording impedance and stimulation threshold. The size and stiffness of implanted probes have been identified as critical factors that lead to this long term gliosis. Smaller, more flexible probes that match the mechanical properties of brain tissue could allow better long term integration by limiting the mechanical disruption of the surrounding tissue during and after probe insertion, while being flexible enough to deform with the tissue during brain movement. However, these small flexible probes inherently lack the mechanical strength to penetrate the brain on their own. In this work, we have developed a micromolding method for coating a non-functional miniaturized SU-8 probe with an ultrafast degrading tyrosine-derived polycarbonate (E5005(2K)). Coated, non-functionalized probes of varying dimensions were reproducibly fabricated with high yields. The polymer erosion/degradation profiles of the probes were characterized in vitro. The probes were also mechanically characterized in ex vivo brain tissue models by measuring buckling and insertion forces during probe insertion. The results demonstrate the ability to produce polymer coated probes of consistent quality for future in vivo use, for example to study the effects of different design parameters that may affect tissue response during long term chronic intra-cortical microelectrode neural recordings.

Molecular design and evaluation of biodegradable polymers using a statistical approach

The challenging paradigm of bioresorbable polymers, whether in drug delivery or tissue engineering, states that a fine-tuning of the interplay between polymer properties (e.g., thermal, degradation), and the degree of cell/tissue replacement and remodeling is required. In this paper we describe how changes in the molecular architecture of a series of terpolymers allow for the design of polymers with varying glass transition temperatures and degradation rates. The effect of each component in the terpolymers is quantified via design of experiment (DoE) analysis. A linear relationship between terpolymer components and resulting Tg (ranging from 34 to 86 °C) was demonstrated. These findings were further supported with mass-per-flexible-bond analysis. The effect of terpolymer composition on the in vitro degradation of these polymers revealed molecular weight loss ranging from 20 to 60 % within the first 24 h. DoE modeling further illustrated the linear (but reciprocal) relationship between structure elements and degradation for these polymers. Thus, we describe a simple technique to provide insight into the structure property relationship of degradable polymers, specifically applied using a new family of tyrosine-derived polycarbonates, allowing for optimal design of materials for specific applications.

Design of semi-interpenetrating networks based on poly(ethyl-2-cyanoacrylate) and oligo(ethylene glycol) diglycidyl ether

The synthesis of semi-interpenetrating networks (SIPN) based on linear poly(ethyl 2-cyanoacrylate) (PECA) and oligo(ethylene glycol) diglycidyl ether (OEGDG) based polymer networks was motivated by the hypothesis that the brittleness of polycyanoacrylates may be overcome by incorporating them into a polymer network architecture. A sequential synthetic route was applied, in which first PECA was prepared by anionic polymerization. Subsequently, OEGDG was crosslinked with different anhydrides and curing catalysts to form networks with hydrolyzable ester bonds and interpenetrating PECA. These SIPNs showed a low water uptake compared to other polyether based networks. Some of the obtained materials were transparent and exhibited a great flexibility, which was maintained also after 24 h of immersion in water and subsequent drying. Such networks could be components of future stimuli-sensitive material systems.

Development of Materials Informatics Tools and Infrastructure to Enable High Throughput Materials Design

Polymer nanocomposites (PNC) are complex material systems in which the dominant length scales converge. Our approach to understanding nanocomposite tradespace uses Materials Quantitative Structure-Property Relationships (MQSPRs) to relate molecular structures to the polar and dispersive components of corresponding surface tensions. If the polar and dispersive components of surface tensions in the nanofiller and polymer could be determined a priori, then the propensity to aggregate and the change in polymer mobility near the particle could be predicted. Derived energetic parameters such as work of adhesion, work of spreading and the equilibrium wetting angle may then used as input to continuum mechanics approaches that have been shown able to predict the thermomechanical response of nanocomposites and that have been validated by experiment. The informatics approach developed in this work thus enables future in silico nanocomposite design by enabling virtual experiments to be performed on proposed nanocomposite compositions prior to fabrication and testing.

Ultrafast resorbing polymers for use as carriers for cortical neural probes

We have identified a polymeric system based on a novel tyrosine-derived terpolymer that offers desirable insertion capability for flexible neural prosthetic devices. To test this concept, flexible films were coated with this terpolymer and their suitability for peranchyma insertion was visualized. The effect of the polymer on neural recording was evaluated using coated microwire probes. The stiff but readily resorbable polymer rapidly degrades (molecular weight half-life of 170 min) while turning into a soft gel, followed by complete resorption within 240 min. This polymeric platform maintains sufficient stiffness to facilitate pial penetration with a dry elastic modulus of 393±44 MPa but loses its strength within 30 min once immersed in saline. In vitro, the polymer's ability to locally deliver dexamethasone has been confirmed through a first order release profile over a 360 min period. In vitro, coated microwire probes regained their original impedance values of 0.5 KΩ within 20 min of wetting via water absorption and polymer resorption. In vivo, the retention of electrical recording capability was also demonstrated through multiple waveform detection in live animals. The ultrafast resorbing polymer as a platform to facilitate the implantation of micronized flexible probes can be utilized in future designs of chronic neural devices.

Designing tyrosine-derived polycarbonate polymers for biodegradable regenerative type neural interface capable of neural recording

Next-generation neuroprosthetic limbs will require a reliable long-term neural interface to residual nerves in the peripheral nervous system (PNS). To this end, we have developed novel biocompatible materials and a fabrication technique to create high site-count microelectrodes for stimulating and recording from regenerated peripheral nerves. Our electrodes are based on a biodegradable tyrosine-derived polycarbonate polymer system with suitable degradation and erosion properties and a fabrication technique for deployment of the polymer in a porous, degradable, regenerative, multiluminal, multielectrode conduit. The in vitro properties of the polymer and the electrode were tuned to retain mechanical strength for over 24 days and to completely degrade and erode within 220 days. The fabrication technique resulted in a multiluminal conduit with at least 10 functioning electrodes maintaining recording site impedance in the single-digit kOhm range. Additionally, in vivo results showed that neural signals could be recorded from these devices starting at four weeks postimplantation and that signal strength increased over time. We conclude that our biodegradable regenerative-type neural interface is a good candidate for chronic high fidelity recording electrodes for integration with regenerated peripheral nerves.

Network models in drug discovery and regenerative medicine

Network motifs and modelling paradigms are attracting increasing attention as modelling tools in drug design and development, and in regenerative medicine. There is a gradual but inexorable convergence between these hitherto disparate disciplines. This review summarizes some very recent work in these areas, leading to an understanding of the complementary roles networks play and factors driving this convergence: network paradigms can be excellent ways of modelling and understanding drug molecules and their action, an understanding of the robustness and vulnerabilities of biological targets may improve the efficacy of drug design and discovery, drug design has an increasingly large role to play in directing stem cell properties, stem cell regulatory networks can be modelled in useful ways using network models at a reasonable level of scale, and the network tools of drug design are also very useful for the design of biomaterials used in regenerative medicine.