Polymer-nanoparticle Composites Research Articles

Fabrication of Plasmon-Active Polymer-Nanoparticle Composites for Biosensing Applications

Polymer-nanoparticle composites find relevance in various fields ranging from optoelectronics to the biomedical sciences. Various efforts have been made to devise fabrication strategies that are simple, robust,and reproducible. Herein, we demonstrate a universal strategy to fabricate plasmon-active polymer-nanoparticle composites, exemplified by the incorporation of gold nanoparticles (AuNPs) into a triethylene glycol dimethacrylate (TEGDMA) polymer scaffold. The TEGDMA scaffold was synthesized on a planar glass support substrate via surface-initiated atomic transfer radical polymerization, followed by the immersion of the TEGDMA-coated glass substrate in a solution of AuNPs prepared via conventional wet-chemical synthesis. This led to the strong attachment of AuNPs to the TEGDMA nanolobes, which was confirmed by the UV absorption peak at 527 nm, due to localized surface plasmon resonance of AuNPs. More importantly, the nanolobe architecture facilitates nanoparticle trapping while allowing molecular access to the nanoparticle surface. This enabled us to further functionalize the incorporated AuNPs with thrombin binding aptamer and utilize the biofunctionalized polymer-nanoparticle composite as a thrombin sensor. The synergistic combination of metallic nanoparticles acting as a sensing module with a nonfouling polymer matrix acting both as a nonrigid scaffold and to screen biomolecules allowed the detection of thrombin with good sensitivity down to 0.01 ng/mL with a linear range over three orders of magnitude. Our work paves the way for the fabrication of reliable biomolecular sensors based on the polymer brush-nanoparticle architecture.

An efficient optimization approach for designing machine learning models based on genetic algorithm

Machine learning (ML) methods have shown powerful performance in different application. Nonetheless, designing ML models remains a challenge and requires further research as most procedures adopt a trial and error strategy. In this study, we present a methodology to optimize the architecture and the feature configurations of ML models considering a supervised learning process. The proposed approach employs genetic algorithm (GA)-based integer-valued optimization for two ML models, namely deep neural networks (DNN) and adaptive neuro-fuzzy inference system (ANFIS). The selected variables in the DNN optimization problems are the number of hidden layers, their number of neurons and their activation function, while the type and the number of membership functions are the design variables in the ANFIS optimization problem. The mean squared error (MSE) between the predictions and the target outputs is minimized as the optimization fitness function. The proposed scheme is validated through a case study of computational material design. We apply the method to predict the fracture energy of polymer/nanoparticles composites (PNCs) with a database gathered from the literature. The optimized DNN model shows superior prediction accuracy compared to the classical one-hidden layer network. Also, it outperforms ANFIS with significantly lower number of generations in GA. The proposed method can be easily extended to optimize similar architecture properties of ML models in various complex systems.

Porous composites based on cellulose acetate and alfa-hematite with optical and antimicrobial properties

Polymer nanoparticles (NPs) composites are rapidly gaining attention due to their high potential for application in several technological fields. On one hand, polymers contribute to balance the attractive magnetic and van der Waals forces that act on NPs and thus reduce their agglomeration. On the other hand, NPs can bring into the composites their inherent properties as nanosized objects. In this work, hematite NPs were blended with cellulose acetate (CA) polymer and thin nanocomposite films were produced by the non-solvent induced phase separation technique. A full physicochemical characterization of these composite materials confirmed its superior character in terms of structure, thermal stability, electronic/optical and antibacterial properties when compared to the polymer on its own and opens the door to its further validation in adsorptive and photocatalytic applications.

Integrated Resistive-Capacitive Strain Sensors Based on Polymer–Nanoparticle Composites

Stretchable electronics, including bioelectronics, electronic skins, and artificial intelligence devices have attracted widespread attention. Stretchable nanocomposites have generated a great deal ...

Origin of Mechanical Enhancement in Polymer Nanoparticle (NP) Composites with Ultrahigh NP Loading

Polymer nanoparticle composites (PNC) with ultra high loading of nanoparticles (> 50%) have been shown to exhibit markedly improved strength, stiffness, and toughness simultaneously compared to the neat systems of their components. Recent experimental studies on the effect of polymer fill fraction in these highly loaded PNCs reveal that even at low polymer fill fractions, hardness and modulus increase significantly. In this work, we aim to understand the origin of these performance enhancements by examining the dynamics of both polymer and nanoparticles (NP) under tensile deformation. We perform molecular dynamics (MD) simulations of coarse-grained, glassy polymer in random-close-packed nanoparticle packings with a varying polymer fill fraction. We characterize the mechanical properties of the PNC systems, compare the NP rearrangement behavior, and study the polymer segmental and chain-level dynamics during deformation below the polymer glass transition. Our simulation results confirm the experimentally-observed increase in modulus at low polymer fill fractions, and we provide evidence that the source of mechanical enhancement is the polymer bridging effect.

Antibacterial efficiency assessment of polymer-nanoparticle composites using a high-throughput microfluidic platform.

Over the past decades, inorganic nanoparticles (NPs), particularly metal oxide NPs, have attracted great attention due to their strong bactericidal effects. Researchers have used NPs to fabricate nanocomposite materials which have innate antibacterial capability. Herein, we present a straightforward method to fabricate antibacterial nanocomposites. Ag, TiO2, and ZnO NPs were dispersed within liquid silicone rubber (LSR) structure in four concentrations. Three different methods were used to evaluate the antibacterial efficiency of the NPs forming the nanocomposite materials: (I) the diffusion method, (II) agar counting plate, and (III) a live/dead assay of E. coli. The mechanical properties and hydrophobicity of the nanocomposites were characterized and correlated to the antibacterial efficiency of the NPs. In order to test the antibacterial efficiency in a high-throughput, cost-effective and efficient manner, a microfluidic device fabricated by 3D printing and soft-lithography methods was used. The LSR-15wt% TiO2 nanocomposites showed the best antibacterial efficiency. In addition, TiO2 NPs formed the stiffest nanocomposites with very fine, even surface which increased the hydrophobicity of the surface where bacteria attach to grow, preventing bacteria from further growth.

Polymer and magnetic nanoparticle composites with tunable magneto-optical activity: role of nanoparticle dispersion for high verdet constant materials

The critical role of nanoparticle dispersion on Faraday rotator activity was studied, revealing new routes for fabricating “plastic garnets” as low cost alternatives to existing inorganic materials for optical isolation and magnetic sensing.

Nanoparticle Loading of Unentangled Polymers Induces Entanglement-Like Relaxation Modes and a Broad Sol-Gel Transition.

We combine molecular dynamics simulations, imaging and data analysis, and the Green-Kubo summation formula for the relaxation modulus G(t) to elicit the structure and rheology of unentangled polymer-nanoparticle composites distinguished by small NPs and strong NP-monomer attraction, εNPM ≫ kBT. A reptation-like plateau emerges in G(t) beyond a terminal relaxation time scale as the volume fraction, cNP, of NPs increases, coincident with a structure transition. A condensed phase of NP-aggregates forms, tightly interlaced with thin sheets of polymer chains, the remaining phase consisting of free chains void of NPs. Rouse mode analyses are applied to the two individual phases, revealing that long-wavelength Rouse modes in the aggregate phase are the source of reptation-like relaxation. Imaging reveals chain motion confined within the thin sheets between NPs and exhibits a 2D analogue of classical reptation. In the NP-free phase, Rouse modes relax indistinguishable from a neat polymer melt. The Fourier transform of G(t) reveals a sol-gel transition across a broad frequency spectrum, tuned by cNP and εNPM above critical thresholds, below which all structure and rheological transitions vanish.

Production and characterization of flexible semiconducting polymer-nanoparticle composites for x-ray sensors

Fabrication and characterization of flexible semiconducting polymer-nanoparticles composite membranes for x-ray sensor device applications are presented in this work. Poly(vinyl alcohol) (PVA) polymer was initially doped with glycerol ionic liquid (IL) that permitted the control of its electrical resistivity. Metal-oxide Bi2O3 nanoparticles were prepared by a modified sol-gel method. The average nanoparticle size was found to be 39 ± 10 nm. Thin films of flexible polymer membranes with different nanoparticle concentrations were prepared using a solution casting method. Compositional characterizations revealed the formation of homogeneous polymer-nanoparticle membranes. Electrical impedance measurements of the membranes were performed for the membranes in a form of capacitor structure as a function of temperature and nanoparticle concentration. The measurements demonstrated that the membranes could be modeled with a pair of parallel resistor and capacitor that were assigned to the contributions of grain boundaries as well as the region of electron depletion in the membrane. As nanoparticle concentration increases, the resistivity and activation energy decrease. Current-voltage measurements demonstrated that the produced membranes function as x-ray sensors, and their response increases as a function of nanoparticle concentration. The produced membranes exhibit semiconducting properties that qualify them as potential candidates for device applications in the field of x-ray dosimeter.

A simulation study on the glass transition behavior and relevant segmental dynamics in free-standing polymer nanocomposite films.

In polymer/nanoparticle composite (PNC) thin films, polymer chains experience strong confinement effects not only at the free surface area but also from nanoparticles (NPs). In this work, the influence of NP-polymer interaction and NP distribution on the polymer segmental dynamics and the glass transition behavior of PNC free-standing films are investigated through molecular dynamics simulations. We demonstrate that NPs will migrate to the film surface area and form an NP-concentrated layer when NP-polymer interactions are weak, while NPs are well dispersed in the bulk region when NP-polymer interactions are strong. In both cases, we find increases in the glass transition temperature Tg compared with the pure film without NPs, although with a different degree. The weakly interacting system has the same Tg as the pure bulk system without NPs. The NP layer formed at the surface area reduces both the mobility of the surface polymer beads and the mobility gradient in the film normal direction (MGFND), therefore resulting in an increase in the Tg which highlights the vital role of the mobile surface layer. In contrast, the NPs in the bulk region enlarge the MGFND. NPs have opposite influences on the polymer bead dynamic anisotropy when they interact weakly or strongly with polymers, weakened for the former and enhanced for the latter. These findings offer a clear picture of the segmental dynamics and glass transition behavior in free-standing PNC films with different NP-polymer interaction strengths. We hope these results will be helpful for the property design of related materials.

Effect of Chain Architecture on Phase Behavior of Giant Surfactant Constructed from Nanoparticle Monotethered by Single Diblock Copolymer Chain.

The phase behaviors of the giant surfactant constructed from a nanoparticle (NP) monotethered by a single AB diblock copolymer chain were investigated by combining self-consistent field theory and density functional theory. Three types of giant surfactants with different chain architectures were constructed via changing the location of NP on the diblock copolymer chain. The simulation results show that the introduction of the NP can induce phase separation of the originally disordered AB diblock copolymers, and phase diagrams as a function of the chain length ratio of A block and the attraction between A block and NP were constructed for the three giant surfactant systems. Via changing the location of NP from the end of B block to the AB-junction point and to the end of A block, the conformational entropies of the systems gradually decrease, leading to a significant difference in phase behaviors. When the NP is tethered to the end of B block, the giant surfactant system has the smallest phase-separation region in the phase diagram, and the resulting ordered structures have the smallest feature sizes. However, when the NP is tethered to the end of A block, the giant surfactant system has the largest phase-separation region, as well as the largest feature sizes of ordered structures. Moreover, the distributions of the NPs within microphase-separated domain can be well tailored by changing the chain length ratio of A block or the attraction between A block and NP in all of the three giant surfactant systems. These findings provide the guideline for the preparation of polymer-nanoparticle composites with controllable morphologies, desirable feature sizes, and precise NP distributions in experiments.

Castor oil: a suitable green source of capping agent for nanoparticle syntheses and facile surface functionalization.

Castor oil (CO) is an inedible vegetable oil (VO) that has been employed extensively as a bioresource material for the synthesis of biodegradable polymers, cosmetics, lubricants, biofuels, coatings and adhesives. It is used in medicine, pharmaceuticals and biorefineries, due to its versatile chemistry. However, there has been less focus on CO as an alternative to toxic and expensive solvents, and capping/stabilizing agents routinely used in nanoparticle syntheses. It provides a richer chemistry than edible VOs as a solvent for green syntheses of nanoparticles. CO, being the only rich source of ricinoleic acid (RA), has been used as a solvent, co-solvent, stabilizing agent and polyol for the formation of polymer–nanoparticle composites. RA is a suitable alternative to oleic acid used as a capping and/or stabilizing agent. Unlike oleic acid, it provides a facile route to the functionalization of surfaces of nanoparticles and the coating of nanoparticles with polymers. For applications requiring more polar organic solvents, RA is more preferred than oleic acid. In this review, we discuss the production, chemical and physical properties, triglyceride and fatty acid (FA) compositions and applications of CO, focusing on the use of CO and RA as well as other VOs and FAs in syntheses of nanoparticles and surface functionalization.

Modeling Nanoparticle Dispersion in Electrospun Nanofibers.

The quality of nanoparticle dispersion in a polymer matrix significantly influences the macroscopic properties of the composite material. Like general polymer-nanoparticle composites, electrospun nanofiber nanoparticle composites do not have an adopted quantitative model for dispersion throughout the polymer matrix, often relying on a qualitative assessment. Being such an influential property, quantifying dispersion is essential for the process of optimization and understanding the factors influencing dispersion. Here, a simulation model was developed to quantify the effects of nanoparticle volume loading (ϕ) and fiber-to-particle diameter ratios (D/d) on the dispersion in an electrospun nanofiber based on the interparticle distance. A dispersion factor is defined to quantify the dispersion along the polymer fiber. In the dilute regime (ϕ < 20%), three distinct regions of the dispersion factor were defined with the highest quality dispersion shown to occur when geometric constraints limit fiber volume accessibility. This model serves as a standard for comparison for future experimental studies and dispersion models through its comparability with microscopy techniques and as a way to quantify and predict dispersion in electrospinning polymer-nanoparticle systems with a single performance metric.

Solvent-Driven Infiltration of Polymer (SIP) into Nanoparticle Packings.

Despite their wide potential utility, the manufacture of polymer-nanoparticle (NP) composites with high filler fractions presents significant challenges because of difficulties associated with dispersing and mixing high volume fractions of NPs in polymer matrices. Polymer-infiltrated nanoparticle films (PINFs) circumvent these issues, allowing fabrication of functional composites with extremely high filler fractions (>50 vol %). In this work, we present a one-step, room-temperature method for porous PINF fabrication through solvent-driven infiltration of polymer (SIP) into NP packings from a bilayer film composed of a densely packed layer of NPs atop a polymer film. Upon exposure to solvent vapor, capillary condensation occurs in the NP packing, leading to plasticization of the polymer layer and subsequent infiltration of polymer into the NP layer. This process results in a porous PINF without the need for energy-intensive processes. We show that the extent of polymer infiltration depends on the quality of solvent and the duration of solvent annealing as well as the molecular weight of the polymer. SIP can also be induced using a slightly poor solvent, which offers a great advantage of inducing SIP via liquid solvent annealing, eliminating potential hazards associated with solvent vapor annealing. The SIP process circumvents challenges associated with dispersing high concentrations of nanoparticles in a polymer matrix to prepare a nanocomposite film with high filler fraction. Thus, SIP is a potentially scalable method that can be used for the manufacturing of porous PINFs of a wide range of compositions, structures, and functionalities for applications in structural and barrier coatings as well as electrodes for energy storage and conversion devices.

Self-assembly of polymer-linked nanoparticles and scaling behavior in the assembled phase

An entropic depletion-driven phase separation is known to be observed for mixtures of polymers and nanoparticles. While polymer-linked nanoparticles have been synthesized, their phase behavior has only been predicted for chemically specific interactions. We use integral equation theory to determine the structure and phase behavior of chemically isotropic polymer-linked nanoparticles at high densities. When each end of a linear polymer is grafted to a nanoparticle, we predict an entropy-driven microphase separation of locally segregated polymer-rich and nanoparticle-rich domains. The formation of these self-assembled structures is purely a consequence of the shape of the polymer-linked particle species. The depletion-driven demixing of ungrafted polymer-nanoparticle composites (with small amounts of nanoparticles) is enhanced as particle diameter (D) grows compared to the polymer radius of gyration (Rg). However, this study shows that for polymer-linked nanoparticle systems, the transition from a liquid to microphase separated state shifts to higher densities (i.e. is inhibited) as D/Rg increases. The transition volume fractions attain a unique value (of ∼0.69) at D/Rg ∼ 1.13. The repeating length scale (L*) is 1.4-2.2 times the size of the entire species (D + Rg). Surprisingly, L*/(D + Rg) is a non-monotonic function of the polymer radius of gyration. The repeating length scale also displays a remarkable scaling behavior, as a function of the particle diameter and the polymer density. Additionally, our study implies that two different mechanisms of transitioning to the microphase separated state are possible for these systems, which has important implications for the transition density and the kinds of structures formed.

Aggregation-Dispersion Transition for Nanoparticles in Semiflexible Ring Polymer Nanocomposite Melts.

By employing molecular dynamics simulations, we explored the conformation transition of nanoparticles (NPs) in semiflexible ring polymer nanocomposite melts. A novel aggregation-dispersion transition for NPs in ring polymer nanocomposites occurs when the bending energy of ring chains increases. The conformations of flexible ring chains near NPs are radial distribution, and the entropic depletion interactions between a pair of NPs in flexible ring polymer nanocomposite melts are attractive, however, the rod-like ring chains wrap around the NPs and the entropic depletion interactions between NPs in rod-like ring polymer melts are repulsive. The aggregation-dispersion transition for NPs induced by chain topology in polymer nanocomposites can provide a new access to achieve miscibility in producing high-performance polymer-nanoparticle composites by simply varying the topological structure of polymers.

Precise control of polymer coated nanopores by nanoparticle additives: Insights from computational modeling

Polymer-nanoparticle composites are a promising new class of materials for creation of controllable nano-patterned surfaces and nanopores. We use coarse-grained molecular dynamics simulations augmented with analytical theory to study the structural transitions of surface grafted polymer layers (brushes) induced by infiltration of nanoparticles that are attracted to the polymers in the layer. We systematically compare two different polymer brush geometries: one where the polymer chains are grafted to a planar surface and the other where the chains are grafted to the inside of a cylindrical nanochannel. We perform a comprehensive study of the effects of the material parameters such as the polymer chain length, chain grafting density, nanoparticle size, strength of attraction between nanoparticles and polymer monomers, and, in the case of the cylindrically grafted brush, the radius of the cylinder. We find a very general behavioral motif for all geometries and parameter values: the height of the polymer brush is non-monotonic in the nanoparticle concentration in solution. As the nanoparticle concentration increases, the brush height first decreases and after passing through a minimum value begins to increase, resulting in the swelling of the nanoparticle infused brush. These morphological features may be useful for devising tunable “smart” nano-devices whose effective dimensions can be reversibly and precisely adjusted by changing the nanoparticle concentration in solution. The results of approximate Self-Consistent Field Theory (SCFT) calculations, applicable in the regime of strong brush stretching, are compared to the simulation results. The SCFT calculations are found to be qualitatively, even semi-quantitatively, accurate when applied within their intended regime of validity, and provide a useful and efficient tool for modeling such materials.

Advanced Compositional Analysis of Nanoparticle-polymer Composites Using Direct Fluorescence Imaging.

The fabrication of polymer-nanoparticle composites is extremely important in the development of many functional materials. Identifying the precise composition of these materials is essential, especially in the design of surface catalysts, where the surface concentration of the active component determines the activity of the material. Antimicrobial materials which utilize nanoparticles are a particular focus of this technology. Recently swell encapsulation has emerged as a technique for inserting antimicrobial nanoparticles into a host polymer matrix. Swell encapsulation provides the advantage of localizing the incorporation to the external surfaces of materials, which act as the active sites of these materials. However, quantification of this nanoparticle uptake is challenging. Previous studies explore the link between antimicrobial activity and surface concentration of the active component, but this is not directly visualized. Here we show a reliable method to monitor the incorporation of nanoparticles into a polymer host matrix via swell encapsulation. We show that the surface concentration of CdSe/ZnS nanoparticles can be accurately visualized through cross-sectional fluorescence imaging. Using this method, we can quantify the uptake of nanoparticles via swell encapsulation and measure the surface concentration of encapsulated particles, which is key in optimizing the activity of functional materials.

Multiscale Dynamics of Polymers in Particle-Rich Nanocomposites

We report on the dynamics of entangled polymers in polymer–nanoparticle composites (PNCs) with moderate and high particle loadings. Using composites comprised of poly(ethylene glycol) (PEG)-tethered silica (SiO2) nanoparticles and poly(methyl methacrylate) (PMMA), we show by means of small-angle X-ray scattering (SAXS) analysis that the nanoparticles are uniformly dispersed over a range of particle concentrations. From oscillatory shear rheology measurements, we find that the time–temperature superposition (TTS) principle holds for these SiO2-PEG/PMMA PNCs up to a particle concentration ϕG ≈ 11% where the materials begin to exhibit soft glassy rheological properties. At particle concentrations below ϕG, we take advantage of TTS to create dynamic maps for PNCs that span time scales ranging from fast segmental motions to slow terminal relaxation of polymer chains. These maps reveal that at low ϕ and depending on the host polymer (PMMA) molecular weight (Mw), hairy nanoparticles may either speed up or slow d...

Photothermal Effects and Applications of Polydimethylsiloxane Membranes with Carbon Nanoparticles.

The advent of nanotechnology has triggered novel developments and applications for polymer-based membranes with embedded or coated nanoparticles. As an example, interaction of laser radiation with metallic and carbon nanoparticles has shown to provide optically triggered responses in otherwise transparent media. Incorporation of these materials inside polymers has led to generation of plasmonic and photothermal effects through the enhanced optical absorption of these polymer composites. In this work, we focus on the photothermal effects produced in polydimethylsiloxane (PDMS) membranes with embedded carbon nanoparticles via light absorption. Relevant physical parameters of these composites, such as nanoparticle concentration, density, geometry and dimensions, are used to analyze the photothermal features of the membranes. In particular, we analyze the heat generation and conduction in the membranes, showing that different effects can be achieved and controlled depending on the physical and thermal properties of the composite material. Several novel applications of these light responsive membranes are also demonstrated, including low-power laser-assisted micro-patterning and optomechanical deformation. Furthermore, we show that these polymer-nanoparticle composites can also be used as coatings in photonic and microfluidic applications, thereby offering an attractive platform for developing light-activated photonic and optofluidic devices.