Showing papers by "Deyu Li published in 2018"

Thermal Transport in Quasi-1D van der Waals Crystal Ta2Pd3Se8 Nanowires: Size and Length Dependence.

Abstract: Van der Waals (vdW) crystals with covalently bonded building blocks assembled together through vdW interactions have attracted tremendous attention recently because of their interesting properties and promising applications. Compared to the explosive research on two-dimensional (2D) vdW materials, quasi-one-dimensional (quasi-1D) vdW crystals have received considerably less attention, while they also present rich physics and engineering implications. Here we report on the thermal conductivity of exfoliated quasi-1D Ta2Pd3Se8 vdW nanowires. Interestingly, even though the interatomic interactions along each molecular chain are much stronger than the interchain vdW interactions, the measured thermal conductivity still demonstrates a clear dependence on the cross-sectional size up to >110 nm. The results also reveal that partial ballistic phonon transport can persist over 13 μm at room temperature along the molecular chain direction, the longest experimentally observed ballistic transport distance with observ...

Cation Dynamics Governed Thermal Properties of Lead Halide Perovskite Nanowires

Abstract: Metal halide perovskite (MHP) nanowires such as hybrid organic–inorganic CH3NH3PbX3 (X = Cl, Br, I) have drawn significant attention as promising building blocks for high-performance solar cells, light-emitting devices, and semiconductor lasers. However, the physics of thermal transport in MHP nanowires is still elusive even though it is highly relevant to the device thermal stability and optoelectronic performance. Through combined experimental measurements and theoretical analyses, here we disclose the underlying mechanisms governing thermal transport in three different kinds of lead halide perovskite nanowires (CH3NH3PbI3, CH3NH3PbBr3 and CsPbBr3). It is shown that the thermal conductivity of CH3NH3PbBr3 nanowires is significantly suppressed as compared to that of CsPbBr3 nanowires, which is attributed to the cation dynamic disorder. Furthermore, we observed different temperature-dependent thermal conductivities of hybrid perovskites CH3NH3PbBr3 and CH3NH3PbI3, which can be attributed to accelerated ca...

Thermal transport in electrospun vinyl polymer nanofibers: effects of molecular weight and side groups

Abstract: Understanding and enhancing thermal transport in polymers is of great importance, and is necessary to enable next-generation flexible electronics, heat exchangers, and energy storage devices. Over the past several decades, significant enhancement of the thermal conductivity of polymeric materials has been achieved, but several key questions related to the effects of molecular structure on thermal transport still remain. By studying a series of electrospun vinyl polymer nanofibers, we investigate the relationship between thermal conductivity and both molecular chain length and side group composition. For polyethylene nanofibers with different molecular weights, the measured thermal conductivity increases monotonically with molecular chain length, as energy transport along molecular chains is more efficient than between chains. The observed trend is also consistent with structural characterization by Raman spectroscopy, which shows enhanced crystallinity as molecular weight increases. Further, by comparing the measured thermal conductivity of vinyl polymer nanofibers with different side groups, we found that phonons travel along polymer chains more effectively when the side groups are either lighter or more symmetric. These experimental results help reveal the underlying correlation between the molecular structure and thermal conductivity of polymer nanofibers, providing valuable insights into the design of polymeric materials with enhanced thermal conductivity.

Impact of Graphene on the Efficacy of Neuron Culture Substrates

Abstract: How graphene influences the behavior of living cells or tissues remains a critical issue for its application in biomedical studies, despite the general acceptance that graphene is biocompatible. While direct contact between cells and graphene is not a requirement for all biomedical applications, it is often mandatory for biosensing. Therefore, it is important to clarify whether graphene impedes the ability of cells to interact with biological elements in their environment. Here, a systematic study is reported to determine whether applying graphene on top of matrix substrates masks interactions between these substrates and retinal ganglion cells (RGCs). Six different platforms are tested for primary RGC cultures with three platforms comprised of matrix substrates compatible with these neurons, and another three having a layer of graphene placed on top of the matrix substrates. The results demonstrate that graphene does not impede interactions between RGCs and underlying substrate matrix, such that their positive or negative effects on neuron viability and vitality are retained. However, direct contact between RGCs and graphene reduces the number, but increases basal activity, of functional cation channels. The data indicate that, when proper baselines are established, graphene is a promising biosensing material for in vitro applications in neuroscience.

Ultrasensitive Graphene Optoelectronic Probes for Recording Electrical Activities of Individual Synapses.

Abstract: The complex neuronal circuitry connected by submicron synapses in our brain calls for technologies that can map neural networks with ultrahigh spatiotemporal resolution to decipher the underlying mechanisms for multiple aspects of neuroscience. Here we show that, through combining graphene transistor arrays with scanning photocurrent microscopy, we can detect the electrical activities of individual synapses of primary hippocampal neurons. Through measuring the local conductance change of graphene optoelectronic probes directly underneath neuronal processes, we are able to estimate millivolt extracellular potential variations of individual synapses during depolarization. The ultrafast nature of graphene photocurrent response allows for decoding of activity patterns of individual synapses with a sub-millisecond temporal resolution. This new neurotechnology provides promising potentials for recording of electrophysiological outcomes of individual synapses in neural networks.

Measuring nanowire thermal conductivity at high temperatures

Abstract: This work extends the micro-thermal-bridge method for thermal conductivity measurements of nanowires to high temperatures. The thermal-bridge method, based on a microfabricated device with two side-by-side suspended membranes with integrated platinum resistance heaters/thermometers, has been used to determine thermal conductivity of various nanowires/nanotubes/nanoribbons at relatively low temperatures. However, to date, thermal conductivity characterization of nanowires at temperatures above 600 K has seldom been reported presumably due to several technical difficulties including the instability of the microfabricated thermometers, radiation heat loss, and the effect of the background conductance on the measurement. Here we report on our attempt to address the aforementioned challenges and demonstrate thermal conductivity measurement of boron nanoribbons up to 740 K. To eliminate high temperature resistance instability, the device is first annealed at 1023 K for 5 min in an argon atmosphere. Two radiation shields are installed in the measurement chamber to minimize radiation heat loss from the measurement device to the surroundings; and the temperature of the device at each set point is calibrated by an additional thermocouple directly mounted on the chip carrier. The effect of the background conductance is eliminated by adopting a differential measurement scheme. With all these modifications, we successfully measured the thermal conductivity of boron nanoribbons over a wide temperature range from 27 K to 740 K. The measured thermal conductivity increases monotonically with temperature and reaches a plateau of ~2.5 W m−1 K−1 at approximately 400 K, with no clear signature of Umklapp scattering observed in the whole measurement temperature range.

Group User Profile Modeling Based on Neural Word Embeddings in Social Networks

Abstract: How to find a user’s interest from similar users a fundamental research problems in socialized recommender systems. Despite significant advances, there exists diversity loss for the majority of recommender systems. With this paper, for expanding the user’s interest, we overcome this challenge by using representative and diverse similar users from followees. First, we model a personal user profile vector via word2vec and term frequency mechanisms. According to user profiles and their follow relationships, we compute content interaction similarity and follow interaction similarity. Second, by combining two kinds of interaction similarity, we calculate the social similarity and discover a diverse group with coverage and dissimilarity. The users in a diverse group can distinguish each other and cover the whole followees, which can model a group user profile (GUP). Then, by tracking the changes of followee set, we heuristically adjust the number of diverse group users and construct an adaptive GUP. Finally, we conduct experiments on Sina Weibo datasets for recommendation, and the experimental results demonstrate that the proposed GUP outperforms conventional approaches for diverse recommendation.