Increasing the Thermal Conductivity of Graphene-Polyamide-6,6 Nanocomposites by Surface-Grafted Polymer Chains: Calculation with Molecular Dynamics and Effective-Medium Approximation

By employing reverse nonequilibrium molecular dynamics simulations in a full atomistic resolution, the effect of surface-grafted chains on the thermal conductivity of graphene-polyamide-6.6 (PA) nanocomposites has been investigated. The interfacial thermal conductivity perpendicular to the graphene plane is proportional to the grafting density, while it first increases and then saturates with the grafting length. Meanwhile, the intrinsic in-plane thermal conductivity of graphene drops sharply as the grafting density increases. The maximum overall thermal conductivity of nanocomposites appears at an intermediate grafting density because of these two competing effects. The thermal conductivity of the composite parallel to the graphene plane increases with the grafting density and grafting length which is attributed to better interfacial coupling between graphene and PA. There exists an optimal balance between grafting density and grafting length to obtain the highest interfacial and parallel thermal conductivity. Two empirical formulas are suggested, which quantitatively account for the effects of grafting length and density on the interfacial and parallel thermal conductivity. Combined with effective medium approximation, for ungrafted graphene in random orientation, the model overestimates the thermal conductivity at low graphene volume fraction (<i>f</i> < 10%) compared with experiments, while it underestimates it at high graphene volume fraction (<i>f</i> > 10%). For unoriented grafted graphene, the model matches the experimental results well. In short, this work provides some valuable guides to obtain the nanocomposites with high thermal conductivity by grafting chain on the surface of graphene

Molecular Dynamics Study on the Thermal Conductivity of the End-grafted Carbon Nanotubes Filled Polyamide-6.6 Nanocomposites

It is very important to improve the thermal conductivity of polymer nanocomposites to widen their application. In this work, the effect of grafted chains and mechanical deformation on the thermal conductivity of end-grafted carbon nanotubes (CNTs) filled polyamide-6.6 nanocomposites has been investigated by molecular dynamics simulation. The results show that the thermal conductivity increases with the grafting density, while it first increases and then saturates with the length of the grafted chains. The dependence of the thermal conductivity on the density and the length of the grafted chains is described by an empirical equation. Moreover, it is further improved if all CNTs are linked by chains or CNTs align along one direction, especially the latter. By fitting the present simulation results with an effective medium approximation model, interfacial thermal resistance is obtained, which indicates that a stronger enhancement of the thermal conductivity is realized when chains are grafted at the end atoms of CNTs. Under deformation, the orientation of both the chains and the CNTs improves the thermal conductivity parallel to the tensile direction, but reduces the thermal conductivity perpendicular to it. Finally, the contribution of the polymer alignment and the CNT alignment to the anisotropy of thermal conductivity is quantified

Dynamic Fluorescence Materials Based on Naphthalimide-Functionalized Silica Aerogels and Applications in Advanced Information Encryption

With the progress of forgery and decryption, the traditional encryption technology is apparent not enough, which strongly requires the development of advanced multidimensional encryption strategies and technologies. Photo-stimuli responsive fluorescent materials are promising as candidate materials for advanced information encryption. Here, we have reported new photo-stimuli responsive materials by encapsulating photochromic molecules spiropyrans (SPs) into naphthalimide-functionalized silica aerogels. By introducing different modification groups (dimethylamino) into 1,8-naphthalimide, we obtained two kinds of silica aerogels that emit blue and green colors. The naphthalimide-functionalized silica aerogels/dye composite exhibits a blue (dimethylamino-modified naphthalimide-functionalized silica aerogel showing green) emission from naphthalimide of silica aerogels at 450 nm (520 nm) and a red emission around 650 nm of SP. Under exposure to ultraviolet light, SP gradually transformed into the merocyanine (MC) form, and a strong absorption band appeared near 540 nm. At that time, the fluorescence resonance energy-transfer (FRET) process occurred between naphthalimide and the MC isomer. As the irradiation time is extended, the fluorescence color changes continuously from blue (green) to red through the FRET process. Using the time dependence of fluorescence, dynamic encryption patterns and multiple codes were successfully developed based on these functionalized silica aerogels. This work has provided important guidance for designing advanced information encryption materials

Multichannel Flexible Pulse Perception Array for Intelligent Disease Diagnosis System

Pressure sensors with high sensitivity, a wide linear range, and a quick response time are critical for building an intelligent disease diagnosis system that directly detects and recognizes pulse signals for medical and health applications. However, conventional pressure sensors have limited sensitivity and nonideal response ranges. We proposed a multichannel flexible pulse perception array based on polyimide/multiwalled carbon nanotube–polydimethylsiloxane nanocomposite/polyimide (PI/MPN/PI) sandwich-structure pressure sensor that can be applied for remote disease diagnosis. Furthermore, we established a mechanical model at the molecular level and guided the preparation of MPN. At the structural level, we achieved high sensitivity (35.02 kPa–1) and a broad response range (0–18 kPa) based on a pyramid-like bilayer microstructure with different upper and lower surfaces. A 27-channel (3 × 9) high-density sensor array was integrated at the device level, which can extract the spatial and temporal distribution information on a pulse. Furthermore, two intelligent algorithms were developed for extracting six-dimensional pulse information and automatic pulse recognition (the recognition rate reaches 97.8%). The results indicate that intelligent disease diagnosis systems have great potential applications in wearable healthcare devices