Slow cooling and efficient extraction of C-exciton hot carriers in MoS2 monolayer

In emerging optoelectronic applications, such as water photolysis, exciton fission and novel photovoltaics involving low-dimensional nanomaterials, hot-carrier relaxation and extraction mechanisms play an indispensable and intriguing role in their photo-electron conversion processes. Two-dimensional transition metal dichalcogenides have attracted much attention in above fields recently; however, insight into the relaxation mechanism of hot electron-hole pairs in the band nesting region denoted as C-excitons, remains elusive. Using MoS2 monolayers as a model two-dimensional transition metal dichalcogenide system, here we report a slower hot-carrier cooling for C-excitons, in comparison with band-edge excitons. We deduce that this effect arises from the favourable band alignment and transient excited-state Coulomb environment, rather than solely on quantum confinement in two-dimension systems. We identify the screening-sensitive bandgap renormalization for MoS2 monolayer/graphene heterostructures, and confirm the initial hot-carrier extraction for the C-exciton state with an unprecedented efficiency of 80%, accompanied by a twofold reduction in the exciton binding energy

Cyber Inference System for Substation Anomalies Against Alter-and-Hide Attacks

Alarms reported to energy control centers are an indication of abnormal events caused by either weather interruptions, system errors, or possibly intentional anomalies. Although these initiating events are random, e.g., faults on transmission lines struck by lightning, the existence of electronically altered measurements may implicate the process to identify root causes of abnormal events. This paper is concerned with alter-andhide (AaH) attacks by tampering the actual measurements to normal states with the background of disruptive switching actions that hide the true values of local events from operators at the control center. A cyber inference system (CyIS) framework is proposed to synthesize all sequential, missing, or altered alarms of related substations against AaH attacks. The stochastic nature of such attack events is modeled with probabilities as an integer programming problem with multiple scenarios. The proposed method is utilized to verify alarm scenarios for a conclusion of the potential AaH attacks on the substations.postprin

Fault estimation for a class of nonlinear dynamical systems

In this paper, model based fault estimation for a class of nonlinear dynamical systems is investigated. The state of the system is assumed unavailable, and a nonlinear observer is used to estimate the state. In the observer, neurofuzzy network is used as the approximator to estimate faults. The network is trained on-line and the convergence of the proposed learning algorithm is established. Abrupt fault and incipient fault are analyzed in the paper and they can be estimated accurately using neurofuzzy network with the proposed learning algorithm.published_or_final_versio

Online fault detection and isolation of nonlinear systems

This paper describes an online fault detection scheme for a class of nonlinear dynamic systems with modelling uncertainty and inaccessible states. Only the inputs and outputs of the system can be measured. The faults are assumed to be functions of the state, instead of the output and the input of the system. A nonlinear online approximator using dynamic recurrent neural network is utilised to monitor the faults in the system. The construction and the learning algorithm of the online approximator are presented. The stability, robustness and sensitivity of the fault detection scheme under certain assumptions are analysed. An example demonstrates the efficiency of the proposed fault detection scheme.published_or_final_versio

Modelling of nonlinear stochastic dynamical systems using neurofuzzy networks

Though nonlinear stochastic dynamical system can be approximated by feedforward neural networks, the dimension of the input space of the network may be too large, making it to be of little practical importance. The Nonlinear Autoregressive Moving Average model with eXogenous input (NARMAX) is shown to be able to represent nonlinear stochastic dynamical system under certain conditions. As the dimension of the input space is finite, it can be readily applied in practical application. It is well known that the training of recurrent networks using gradient method has a slow convergence rate. In this paper, a fast training algorithm based on the Newton-Raphson method for recurrent neurofuzzy network with NARMAX structure is presented. The convergence and the uniqueness of the proposed training algorithm are established. A simulation example involving a nonlinear dynamical system corrupted with the correlated noise and a sinusoidal disturbance is used to illustrate the performance of the proposed training algorithm.published_or_final_versio

Feedback-induced nonlinearity and superconducting on-chip quantum optics

Quantum coherent feedback has been proven to be an efficient way to tune the dynamics of quantum optical systems and, recently, those of solid-state quantum circuits. Here, inspired by the recent progress of quantum feedback experiments, especially those in mesoscopic circuits, we prove that superconducting circuit QED systems, shunted with a coherent feedback loop, can change the dynamics of a superconducting transmission line resonator, i.e., a linear quantum cavity, and lead to strong on-chip nonlinear optical phenomena. We find that bistability can occur under the semiclassical approximation, and photon anti-bunching can be shown in the quantum regime. Our study presents new perspectives for engineering nonlinear quantum dynamics on a chip.Comment: 10 pages, 9 figure

CXCL12/CXCR4 axis: an emerging neuromodulator in pathological pain

The roles of chemokine C-X-C motif ligand 12 (CXCL12) and its receptor chemokine C-X-C motif receptor 4 (CXCR4) reveal this chemokine axis as an emerging neuromodulator in the nervous system. In the peripheral and central nervous systems, both CXCL12 and CXCR4 are expressed in various kinds of nociceptive structures, and CXCL12/CXCR4 axis possesses pronociceptive property. Recent studies have demonstrated its critical roles in the development and maintenance of pathological pain, and both neuronal and glial mechanisms are involved in this CXCL12/CXCR4 axis-mediated pain processing. In this review, we summarize the recent development of the roles and mechanisms of CXCL12/CXCR4 axis in the pathogenesis of chronic pain by sciatic nerve injury, human immunodeficiency virus-associated sensory neuropathy, diabetic neuropathy, spinal cord injury, bone cancer, opioid tolerance, or opioid-induced hyperalgesia. The potential targeting of CXCL12/CXCR4 axis as an effective and broad-spectrum pharmacological approach for chronic pain therapy was also discussed.published_or_final_versio

Thermal annealing and temperature dependences of memory effect in organic memory transistor

We investigate the annealing and thermal effects of organic non-volatile memory with floating silver nanoparticles by real-time transfer curve measurements. During annealing, the memory window shows shrinkage of 23 due to structural variation of the nanoparticles. However, by increasing the device operating temperature from 20 to 90 °C after annealing, the memory window demonstrates an enlargement up to 100. The differences in the thermal responses are explained and confirmed by the co-existence of electron and hole traps. Our findings provide a better understanding of organic memory performances under various operating temperatures and validate their applications for temperature sensing or thermal memories. © 2011 American Institute of Physics.published_or_final_versio

Short circuit current improvement in planar heterojunction organic solar cells by multijunction charge transfer

A multijunction structure was applied on an organic photovoltaic (OPV) device for broadening the absorption spectrum and enhancing the power conversion efficiency through charge transfer process. By inserting the tris[4-(2-thienyl)]amine (TTPA) into a boron subphthalocyanine chloride (SubPc)/C 60 OPV device, the short circuit current density (J sc) showed a 47.5% increases from 3.05 to 4.50 mA/cm 2 in the bilayer planar heterojunction device, while the open circuit voltage (V oc) remained constant. Based on the single junction (TTPA/SubPc) device and photoluminescence absorption results, we confirmed both TTPA/SubPc and SubPc/C 60 junctions are contributing to the exciton dissociation process hence the efficiency enhancement. © 2012 American Institute of Physics.published_or_final_versio

On the architecture of H.264 to H.264 homogeneous transcoding platform

2007-2008 > Academic research: refereed > Invited conference paperVersion of RecordPublishe