arXiv subjects

Chen Pan

Publications and source records attributed to Chen Pan.

36 records · Page 2Linked to original sources

arXiv2022

Joint-optimization of Node placement and UAV's Trajectory for Self-sustaining Air-Ground IoT system

Due to the sustainable power supply and environment-friendly features, self-powered IoT devices have been increasingly employed in various fields such as providing observation data in remote areas, especially in rural areas or post-disaster scenarios. Generally, through multi-hop relay, the sensed data of those self-powered IoT devices are collected by the sink node which connects to the IoT backbones. However, due to the remoteness, the sink needs to be located at the border of the monitoring area where both the backbone of IoT and electrical infrastructures are accessible. Under such deployment, significant data flow and relay overhead will incur considering the large scale of the monitoring area. Motivated by this issue, this paper aims to design a UAV-assisted self-powered heterogeneous system to provide comprehensive monitoring data. In this system, because of the superiority of the unmanned aerial vehicle (UAV) in the easy deployment, We dispatch UAV collects data from self-powered IoT devices, periodically so as to alleviate the data overflow. Moreover, based on that the self-powered IoT devices are expected to have a more considerable capability in the heavy data flow area, we also developed a placement upgrade strategy to upgrade the general homogeneous self-powered IoT system to the heterogeneous self-powered IoT system. Simulation results indicated the developed UAV-assisted self-powered heterogeneous system can achieve around $1.28\times$ the amount of data delivery to sink compared with the homogeneous self-powered IoT system.

eess.SP↗

arXiv2022

Enabling Fast Deep Learning on Tiny Energy-Harvesting IoT Devices

Energy harvesting (EH) IoT devices that operate intermittently without batteries, coupled with advances in deep neural networks (DNNs), have opened up new opportunities for enabling sustainable smart applications. Nevertheless, implementing those computation and memory-intensive intelligent algorithms on EH devices is extremely difficult due to the challenges of limited resources and intermittent power supply that causes frequent failures. To address those challenges, this paper proposes a methodology that enables fast deep learning with low-energy accelerators for tiny energy harvesting devices. We first propose $RAD$, a resource-aware structured DNN training framework, which employs block circulant matrix and structured pruning to achieve high compression for leveraging the advantage of various vector operation accelerators. A DNN implementation method, $ACE$, is then proposed that employs low-energy accelerators to profit maximum performance with small energy consumption. Finally, we further design $FLEX$, the system support for intermittent computation in energy harvesting situations. Experimental results from three different DNN models demonstrate that $RAD$, $ACE$, and $FLEX$ can enable fast and correct inference on energy harvesting devices with up to 4.26X runtime reduction, up to 7.7X energy reduction with higher accuracy over the state-of-the-art.

cs.LG↗

arXiv2022

Energy Harvesting Aware Multi-hop Routing Policy in Distributed IoT System Based on Multi-agent Reinforcement Learning

Energy harvesting technologies offer a promising solution to sustainably power an ever-growing number of Internet of Things (IoT) devices. However, due to the weak and transient natures of energy harvesting, IoT devices have to work intermittently rendering conventional routing policies and energy allocation strategies impractical. To this end, this paper, for the very first time, developed a distributed multi-agent reinforcement algorithm known as global actor-critic policy (GAP) to address the problem of routing policy and energy allocation together for the energy harvesting powered IoT system. At the training stage, each IoT device is treated as an agent and one universal model is trained for all agents to save computing resources. At the inference stage, packet delivery rate can be maximized. The experimental results show that the proposed GAP algorithm achieves around 1.28 times and 1.24 times data transmission rate than that of the Q-table and ESDSRAA algorithm, respectively.

cs.NI↗

arXiv2021

Phase transition and enhanced hardness of LaB4 under pressure

The crystalline structures of lanthanum tetraboride, LaB4, under pressure are investigated using a genetic algorithm method coupled with first-principles calculations. We find two low-enthalpy phases for LaB4 as the thermodynamic ground state up to 200 GPa: a phase previously observed in experiments (P4/mbm) and a novel orthorhombic phase (Pnma-I). The P4/mbm phase transforms to the Pnma-I phase at around 106 GPa, accompanied by breakage of the B-octahedron. The P4/mbm phase of LaB4 exhibits a high hardness (30.5 GPa) at ambient conditions, which is comparable to that of the hard material B4C. The hardness of the two low-enthalpy phases increases with pressure. The electronic band structures shows that all of the competitive phases (two stable and two metastable phases) are metallic. Phonon calculations shows the P4/mbm and Pnma-I phases are thermodynamically stable in their respective pressure ranges. This elucidation of the phase transition behavior and hardness of LaB4 provides new knowledge on the interesting high-pressure behaviors of the rare-earth metal borides.

cond-mat.mtrl-sci↗

arXiv2021

Scalable massively parallel computing using continuous-time data representation in nanoscale crossbar array

The growth of connected intelligent devices in the Internet of Things has created a pressing need for real-time processing and understanding of large volumes of analogue data. The difficulty in boosting the computing speed renders digital computing unable to meet the demand for processing analogue information that is intrinsically continuous in magnitude and time. By utilizing a continuous data representation in a nanoscale crossbar array, parallel computing can be implemented for the direct processing of analogue information in real time. Here, we propose a scalable massively parallel computing scheme by exploiting a continuous-time data representation and frequency multiplexing in a nanoscale crossbar array. This computing scheme enables the parallel reading of stored data and the one-shot operation of matrix-matrix multiplications in the crossbar array. Furthermore, we achieve the one-shot recognition of 16 letter images based on two physically interconnected crossbar arrays and demonstrate that the processing and modulation of analogue information can be simultaneously performed in a memristive crossbar array.

cond-mat.mtrl-sci↗

arXiv2021

Temperature-sensitive spatial distribution of defects in PdSe2 flakes

Defect engineering plays an important role in tailoring the electronic transport properties of van der Waals materials. However, it is usually achieved through tuning the type and concentration of defects, rather than dynamically reconfiguring their spatial distribution. Here, we report temperature-sensitive spatial redistribution of defects in PdSe2 thin flakes through scanning tunneling microscopy (STM). We observe that the spatial distribution of Se vacancies in PdSe2 flakes exhibits a strong anisotropic characteristic at 80 K, and that this orientation-dependent feature is weakened when temperature is raised. Moreover, we carry out transport measurements on PdSe2 thin flakes and show that the anisotropic features of carrier mobility and phase coherent length are also sensitive to temperature. Combining with theoretical analysis, we conclude that temperature-driven defect spatial redistribution could interpret the temperature-sensitive electrical transport behaviors in PdSe2 thin flakes. Our work highlights that engineering spatial distribution of defects in the van der Waals materials, which has been overlooked before, may open up a new avenue to tailor the physical properties of materials and explore new device functionalities.

cond-mat.mes-hall↗

arXiv2020

Gate-tunable van der Waals heterostructure for reconfigurable neural network vision sensor

Early processing of visual information takes place in the human retina. Mimicking neurobiological structures and functionalities of the retina provide a promising pathway to achieving vision sensor with highly efficient image processing. Here, we demonstrate a prototype vision sensor that operates via the gate-tunable positive and negative photoresponses of the van der Waals (vdW) vertical heterostructures. The sensor emulates not only the neurobiological functionalities of bipolar cells and photoreceptors but also the unique synaptic connectivity between bipolar cells and photoreceptors. By tuning gate voltage for each pixel, we achieve reconfigurable vision sensor for simultaneously image sensing and processing. Furthermore, our prototype vision sensor itself can be trained to classify the input images, via updating the gate voltages applied individually to each pixel in the sensor. Our work indicates that vdW vertical heterostructures offer a promising platform for the development of neural network vision sensor.

cond-mat.mtrl-sci↗

arXiv2019

S-type Negative Differential Resistance in Semiconducting Transition-Metal Dichalcogenides

Current-controlled (also known as "S-type") negative differential resistance (NDR) is of crucial importance to many emerging applications including neuromorphic computing and high-density memristors integration. However, the experimental realization of S-type NDR based on conventional mechanisms poses demanding requirements on materials, which greatly limits their potential applications. Here, we experimentally identify that semiconducting transition metal dichalcogenides (TMDs) can host a bipolar S-type NDR devices. Theoretical simulations indicate that the origin of the NDR in these devices arises from a thermal feedback mechanism. Furthermore, we demonstrate the potential applications of TMDs based S-type NDR device in signal processing and neuromorphic electronics.

cond-mat.mes-hall↗

arXiv2018

Experimental identification of critical condition for drastically enhancing thermoelectric power factor of two-dimensional layered materials

Nano-structuring is an extremely promising path to high performance thermoelectrics. Favorable improvements in thermal conductivity are attainable in many material systems, and theoretical work points to large improvements in electronic properties. However, realization of the electronic benefits in practical materials has been elusive experimentally. A key challenge is that experimental identification of the quantum confinement length, below which the thermoelectric power factor is significantly enhanced, remains elusive due to lack of simultaneous control of size and carrier density. Here we investigate gate tunable and temperature-dependent thermoelectric transport in $γ$ phase indium selenide ($γ$ InSe, n type semiconductor) samples with thickness varying from 7 to 29 nm. This allows us to properly map out dimension and doping space. Combining theoretical and experimental studies, we reveal that the sharper pre-edge of the conduction-band density of states arising from quantum confinement gives rise to an enhancement of the Seebeck coefficient and the power factor in the thinner InSe samples. Most importantly, we experimentally identify the role of the competition between quantum confinement length and thermal de Broglie wavelength in the enhancement of power factor. Our results provide an important and general experimental guideline for optimizing the power factor and improving the thermoelectric performance of two-dimensional layered semiconductors.

cond-mat.mes-hall↗

arXiv2018

Negative Photoconductance in van der Waals Heterostructures-Based Floating Gate Phototransistor

Van der Waals (vdW) heterostructures made of two-dimensional materials have been demonstrated to be versatile architectures for optoelectronic applications due to strong light-matter interactions. However, most of light-controlled phenomena and applications in the vdW heterostructures rely on positive photoconductance (PPC). Negative photoconductance (NPC) has not yet been reported in vdW heterostructures. Here we report the observation of the NPC in ReS2/h-BN/MoS2 vdW heterostructures-based floating gate phototransistor. The fabricated devices exhibit excellent performance of nonvolatile memory without light illumination. More interestingly, we observe a gate-tunable transition between the PPC and the NPC under the light illumination. The observed NPC phenomenon can be attributed to the charge transfer between floating gate and conduction channel. Furthermore, we show that the control of NPC through light intensity is promising in realization of light-tunable multi-bit memory devices. Our results may enable potential applications in multifunctional memories and optoelectronic devices.

cond-mat.mes-hall↗

arXiv2018

Gate-Induced Interfacial Superconductivity in 1T-SnSe2

Layered metal chalcogenide materials provide a versatile platform to investigate emergent phenomena and two-dimensional (2D) superconductivity at/near the atomically thin limit. In particular, gate-induced interfacial superconductivity realized by the use of an electric-double-layer transistor (EDLT) has greatly extended the capability to electrically induce superconductivity in oxides, nitrides and transition metal chalcogenides and enable one to explore new physics, such as the Ising pairing mechanism. Exploiting gate-induced superconductivity in various materials can provide us with additional platforms to understand emergent interfacial superconductivity. Here, we report the discovery of gate-induced 2D superconductivity in layered 1T-SnSe2, a typical member of the main-group metal dichalcogenide (MDC) family, using an EDLT gating geometry. A superconducting transition temperature Tc around 3.9 K was demonstrated at the EDL interface. The 2D nature of the superconductivity therein was further confirmed based on 1) a 2D Tinkham description of the angle-dependent upper critical field, 2) the existence of a quantum creep state as well as a large ratio of the coherence length to the thickness of superconductivity. Interestingly, the in-plane approaching zero temperature was found to be 2-3 times higher than the Pauli limit, which might be related to an electric field-modulated spin-orbit interaction. Such results provide a new perspective to expand the material matrix available for gate-induced 2D superconductivity and the fundamental understanding of interfacial superconductivity.

cond-mat.supr-con↗

arXiv2018

Analog Circuit Applications based on Ambipolar Graphene/MoTe2 Vertical Transistors

The current integrated circuit (IC) technology based on conventional MOS-FET (metal-oxide-semiconductor field-effect transistor) is approaching the limit of miniaturization with increasing demand on energy. Several analog circuit applications based on graphene FETs have been demonstrated with less components comparing to the conventional technology. However, low on/off current ratio caused by the semimetal nature of graphene has severely hindered its practical applications. Here we report a graphene/MoTe2 van der Waals (vdW) vertical transistor with V-shaped ambipolar field effect transfer characteristics to overcome this challenge. Investigations on temperature dependence of transport properties reveal that gate tunable asymmetric barriers of the devices are account for the ambipolar behaviors. Furthermore, to demonstrate the analog circuit applications of such vdW vertical transistors, we successfully realized output polarity controllable (OPC) amplifier and frequency doubler. These results enable vdW heterojunction based electronic devices to open up new possibilities for wide perspective in telecommunication field.

cond-mat.mes-hall↗

arXiv2018

Robust memristors based on layered two-dimensional materials

Van der Waals heterostructure based on layered two-dimensional (2D) materials offers unprecedented opportunities to create materials with atomic precision by design. By combining superior properties of each component, such heterostructure also provides possible solutions to address various challenges of the electronic devices, especially those with vertical multilayered structures. Here, we report the realization of robust memristors for the first time based on van der Waals heterostructure of fully layered 2D materials (graphene/MoS2-xOx/graphene) and demonstrate a good thermal stability lacking in traditional memristors. Such devices have shown excellent switching performance with endurance up to 107 and a record-high operating temperature up to 340oC. By combining in situ high-resolution TEM and STEM studies, we have shown that the MoS2-xOx switching layer, together with the graphene electrodes and their atomically sharp interfaces, are responsible for the observed thermal stability at elevated temperatures. A well-defined conduction channel and a switching mechanism based on the migration of oxygen ions were also revealed. In addition, the fully layered 2D materials offer a good mechanical flexibility for flexible electronic applications, manifested by our experimental demonstration of a good endurance against over 1000 bending cycles. Our results showcase a general and encouraging pathway toward engineering desired device properties by using 2D van der Waals heterostructures.

cond-mat.mtrl-sci↗

arXiv2017

Gated Tuned Superconductivity and Phonon Softening in Mono- and Bilayer MoS$_2$

Superconductors at the atomic two-dimensional (2D) limit are the focus of an enduring fascination in the condensed matter community. This is because, with reduced dimensions, the effects of disorders, fluctuations, and correlations in superconductors become particularly prominent at the atomic 2D limit; thus such superconductors provide opportunities to tackle tough theoretical and experimental challenges. Here, based on the observation of ultrathin 2D superconductivity in mono- and bilayer molybdenum disulfide (MoS$_2$) with electric-double-layer (EDL) gating, we found that the critical sheet carrier density required to achieve superconductivity in a monolayer MoS$_2$ flake can be as low as 0.55*10$^{14}$cm$^{-2}$, which is much lower than those values in the bilayer and thicker cases in previous report and also our own observations. Further comparison of the phonon dispersion obtained by ab initio calculations indicated that the phonon softening of the acoustic modes around the M point plays a key role in the gate-induced superconductivity within the Bardeen-Cooper Schrieffer (BCS) theory framework. This result might help enrich the understanding of 2D superconductivity with EDL gating.

cond-mat.mes-hall↗

arXiv2017

Intrinsic p-type W-based transition metal dichalcogenide by substitutional Ta-doping

Two-dimensional (2D) transition metal dichalcogenides (TMDs) have recently emerged as promising candidates for future electronics and optoelectronics. While most of TMDs are intrinsic n-type semiconductors due to electron donating which originates from chalcogen vacancies, obtaining intrinsic high-quality p-type semiconducting TMDs has been challenging. Here, we report an experimental approach to obtain intrinsic p-type Tungsten (W)-based TMDs by substitutional Ta-doping. The obtained few-layer Ta-doped WSe2 (Ta0.01W0.99Se2) field-effect transistor (FET) devices exhibit competitive p-type performances, including ~10^6 current on/off at room temperature. We also demonstrate high quality van der Waals (vdW) p-n heterojunctions based on Ta0.01W0.99Se2/MoS2 structure, which exhibit nearly ideal diode characteristics (with an ideality factor approaching 1 and a rectification ratio up to 10^5) and excellent photodetecting performance. Our study suggests that substitutional Ta-doping holds great promise to realize intrinsic p-type W-based TMDs for future electronic and photonic applications.

cond-mat.mtrl-sci↗

arXiv2017

Room-temperature high detectivity mid-infrared photodetectors based on black arsenic phosphorus

The mid-infrared (MIR) spectral range, pertaining to important applications such as molecular 'fingerprint' imaging, remote sensing, free space telecommunication and optical radar, is of particular scientific interest and technological importance. However, state-of-the-art materials for MIR detection are limited by intrinsic noise and inconvenient fabrication processes, resulting in high cost photodetectors requiring cryogenic operation. We report black arsenic-phosphorus-based long wavelength infrared photodetectors with room temperature operation up to 8.2 um, entering the second MIR atmospheric transmission window. Combined with a van der Waals heterojunction, room temperature specific detectivity higher than 4.9*10^9 Jones was obtained in the 3-5 um range. The photodetector works in a zero-bias photovoltaic mode, enabling fast photoresponse and low dark noise. Our van der Waals heterojunction photodector not only exemplify black arsenic-phosphorus as a promising candidate for MIR opto-electronic applications, but also pave the way for a general strategy to suppress 1/f noise in photonic devices.

cond-mat.mtrl-sci↗

arXiv2014

Martingale Problem under Nonlinear Expectations

We formulate and solve the martingale problem in a nonlinear expectation space. Unlike the classical work of Stroock and Varadhan (1969) where the linear operator in the associated PDE is naturally defined from the corresponding diffusion process, the main difficulty in the nonlinear setting is to identify an appropriate class of nonlinear operators for the associated fully nonlinear PDEs. Based on the analysis of the martingale problem, we introduce the notion of weak solution for stochastic differential equations under nonlinear expectations and obtain an existence theorem under the Hölder continuity condition of the coefficients. The approach to establish the existence of weak solutions generalizes the classical Girsanov transformation method in that it no longer requires the two (probability) measures to be absolutely continuous.

math.PR↗

arXiv2013

A Note on $G$- Optimal Stopping Problems

We consider a class of discretionary stopping problems within the $G$-framework. We first establish the well-definedness of the stopping problem under the $G$-expectation, by showing the quasi-continuity of the stopped process. We then prove a verification theorem for $G$-optimal stopping problem. One corollary is a direct proof for the well-known fact that the $G$-optimal stopping problem is the same as the classical optimal stopping problem with appropriate parameters, when the payoff function is concave or convex.

math.PR↗