Multi-Pulse Terahertz Spectroscopy Unveils Hot Polaron Photoconductivity Dynamics in Metal-Halide Perovskites

The behavior of hot carriers in metal-halide perovskites (MHPs) present a valuable foundation for understanding the details of carrier-phonon coupling in the materials as well as the prospective development of highly efficient hot carrier and carrier multiplication solar cells. Whilst the carrier population dynamics during cooling have been intensely studied, the evolution of the hot carrier properties, namely the hot carrier mobility, remain largely unexplored. To address this, we introduce a novel ultrafast visible pump - infrared push - terahertz probe spectroscopy (PPP-THz) to monitor the real-time conductivity dynamics of cooling carriers in methylammonium lead iodide. We find a decrease in mobility upon optically depositing energy into the carriers, which is typical of band-transport. Surprisingly, the conductivity recovery dynamics are incommensurate with the intraband relaxation measured by an analogous experiment with an infrared probe (PPP- IR), and exhibit a negligible dependence on the density of hot carriers. These results and the kinetic modelling reveal the importance of highly-localized lattice heating on the mobility of the hot electronic states. This collective polaron-lattice phenomenon may contribute to the unusual photophysics observed in MHPs and should be accounted for in devices that utilize hot carriers.Comment: 28 pages, 4 figures, 77 reference

Interplay Between Mixed and Pure Exciton States Controls Singlet Fission in Rubrene Single Crystals

Singlet fission (SF) is a multielectron process in which one singlet exciton S converts into a pair of triplet excitons T+T. SF is widely studied as it may help overcome the Shockley-Queisser efficiency limit for semiconductor photovoltaic cells. To elucidate and control the SF mechanism, great attention has been given to the identification of intermediate states in SF materials, which often appear elusive due to the complexity and fast timescales of the SF process. Here, we apply 10fs-1ms transient absorption techniques to high-purity rubrene single crystals to disentangle the intrinsic fission dynamics from the effects of defects and grain boundaries and to identify reliably the fission intermediates. We show that above-gap excitation directly generates a hybrid vibronically assisted mixture of singlet state and triplet-pair multiexciton [S:TT], which rapidly (<100fs) and coherently branches into pure singlet or triplet excitations. The relaxation of [S:TT] to S is followed by a relatively slow and temperature-activated (48 meV activation energy) incoherent fission process. The SF competing pathways and intermediates revealed here unify the observations and models presented in previous studies of SF in rubrene and propose alternative strategies for the development of SF-enhanced photovoltaic materials

Cognitive optical network architecture in dynamic environments

Thesis: Ph. D. in Computer Science and Engineering, Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, May, 2020Cataloged from the official PDF of thesis.Includes bibliographical references (pages 149-154).Emerging network traffic requires a more agile network management and control system to deal with the dynamic network environments than today's networks use. The bursty and large data transactions introduced by new technological applications can cause both high costs and extreme congestion in networks. The prohibitive cost of massive over-provisioning will manifest as huge congestions during peak demand periods. The network management and control system must be able to sense the traffic changes and reconfigure in a timely manner (in tens of milliseconds instead of minutes or hours) to use network resources efficiently. We propose the use of cognitive techniques for fast and adaptive network management and control of future optical networks. The goal of this work is to provide timely network reconfigurations in response to dynamic traffic environments and prevent congestion from building up.We make a simplified model of the expected traffic arrival rate changes as a multistate Markov process based on the characteristics of the dynamic, bursty, and high granularity traffic. The traffic is categorized into different network traffic environments by the length of the network coherence time, which is the time that the traffic is unvarying. The tunneled network architecture is adopted due to its supremacy in reducing the control complexity when the traffic volume is at least one wavelength. In the long coherence time regime where traffic changes very slowly, the traffic detection performances of two Bayesian estimators and a stopping-trial (sequential) estimator are examined, based on the transient behaviors of networks. The stopping trial estimator has the fastest response time to the changes of traffic arrival statistics. We propose a wavelength reconfiguration algorithm with continuous assessment where the system reconfigures whenever it deems necessary.The reconfiguration can involve addition or subtraction of multiple wavelengths. Using the fastest detection and reconfiguration algorithm can reduce queueing delays during traffic surges without over-provisioning and thus can reduce network capital expenditure and prevent wasting resources on erroneous decisions when surges occur. For traffic with moderate coherence time (where traffic changes at a moderate rate) and the short coherence time (where traffic changes quickly), the stopping-trial estimator still responds to the traffic changes with a short detection time. As long as the inter-arrival times of traffic transactions are independent, the algorithm is still optimum. The algorithm provides no prejudice on the exact network traffic distribution, avoiding having to sense and estimate detailed arrival traffic statistics.To deal with fast-changing traffic, we model the transient convergent behaviors of network traffic drift as a result of traffic transition rate changes and validate the feasibility and utility of the traffic prediction. In a simple example when the network traffic rate changes monotonically in a linear model, the sequential maximum likelihood estimator will capture the traffic trend with a small number of arrivals. The traffic trend prediction can help to provide fast reconfiguration, which is very important for maintaining quality of service during large traffic shifts. We further investigate the design of an efficient rerouting algorithm to maintain users' quality of service when the incremental traffic cannot be accommodated on the primary path. The algorithm includes the fast reconfiguration of wavelengths in the existing lit and spatially routed fibers, and the setting up and lighting of new fibers.Rerouting is necessary to maintain users' quality of service when the queueing delay on the primary path (determined by shortest path routing) exceeds the requirement. Our algorithm triggers reconfiguration when a queueing delay threshold is crossed on the primary path. The triggering by a threshold on the queueing delay is used due to its simplicity, and it is directly measurable by the exact traffic transaction sizes and the queue size, which reflect both the current network traffic environment and the network configurations. A dynamic rerouting algorithm implemented with a shortest path algorithm is proposed to find the secondary paths for rerouting. We make the conjecture that it is desirable that the alternate paths for rerouting have small numbers of hops and are disjoint with other busy paths when the hops on the path are independent. In addition, the conjecture suggests that a good candidate network topology should have high edge-connectivity.Wavelength reservation for rerouted traffic does not maximize wavelength utilization. We make the conjecture that traffic with different sizes should be broken up into multi-classes with dedicated partitioned resources and the queueing delay should be normalized by the transmission time for rerouting triggering to realize better network utilization.by Xijia Zheng.Ph. D. in Computer Science and EngineeringPh.D.inComputerScienceandEngineering Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Scienc

Cognitive Management and Control of Optical Networks in Dynamic Environments

Emerging network traffic requires a more agile network management and control system to deal with the dynamic network environments than today's networks. We propose the use of cognitive techniques for the fast and adaptive management of future optical networks. As a first approximation, we model our expected traffic arrivals as a multi-state Markov process and categorize different network traffic environments by the length of the network coherence time. For the traffic with moderate and short coherence times, the stopping-trial estimator still responses to the traffic changes with a short detection time as long as the inter-arrival times of traffic transactions are independent. The algorithm provides no prejudice on the exact network traffic distribution avoiding having to sense and estimate detailed arrival traffic statistics. To further deal with the fast-changing traffic, we model the transient convergent behaviors of network traffic drift as a result of traffic transition rate changes and validate the feasibility and utility of the traffic prediction. When the network traffic rate changes quickly, our sequential maximum likelihood estimator will capture the traffic trend with a small number of arrivals and provide fast reconfiguration, which is very important for maintaining quality of service during large traffic shifts.NSF (Grant 6936827

MAN architecture design for OFS

Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2015.Cataloged from PDF version of thesis.Includes bibliographical references (pages 85-86).Optical Flow switching (OFS) is a key enabler of future scalable all-optical networks for the large traffic flows. In this thesis, we provide design concepts of efficient physical topology and routing architectures for an all-optical Metropolitan Area Network (MAN) that supports OFS. We use all-to-one stochastic flows to model inter-MAN traffic demands and adopt Moore Graphs and Generalized Moore Graphs as the physical topology. We found good MAN architectures are coupled intimately with media access control protocol designs and must be optimized jointly. Two routing architectures that represent extreme cases were proposed and examined: Quasi-Static Architecture (QSA) and Dynamic Per Flow Routing Architecture (DPFRA). The performance and costs are compared to provide an economical architecture building strategy. We find for the MAN, DPFRA always has the lower queueing delay and lower blocking probability than that of QSA at the expense of more complexity in scheduling, switching, and network management and control. Our analysis based on Moore Graphs and Generalized Moore Graphs indicates that QSA becomes cheaper when the product of the average offered load per node and the normalized delay are equal to or larger than ~ 2 units of wavelengths, with both architectures essentially meeting the same delay or blocking probability requirements. Also, the cost boundary shows that DPFRA with shortest-queue node first routing strategy (sq-first strategy) is preferred only when the delay requirement is stringent and the offered load is low, while QSA is much more suitable for the all-optical MAN to accommodate modest to heavy network traffic. Since OFS is only going to be used in heavy load situations brought on by elephants in the traffic, QSA is the preferred architecture. We have shown the hybrid architecture of QSA and DPFRA is impractical and thus it should be avoided.by Xijia Zheng.S.M

Cognitive Management and Control for Wavelength Assignment and Reconfiguration in Optical Networks

We address the design of fast wavelength assignment and reconfiguration using cognitive management and control that can quickly and accurately adapt to the operating conditions for optical networks. The traffic detection performances of two Bayesian estimators and a stopping-trial (sequential) estimator are examined based on the transient behaviors of networks. The stopping-trial estimator has the fastest response time to the changes of traffic arrival statistics. We propose a wavelength reconfiguration algorithm with continuous assessment where the system reconfigures whenever it deems necessary. The reconfiguration can involve addition or subtraction of multiple wavelengths. Using the fastest detection and reconfiguration algorithm can reduce queueing delays during traffic surges without over provisioning and thus can reduce network capital expenditure and prevent waste of resources upon erroneous decision on occurrence of surges.NSF (Grant 6936827

Rent-Seeking Incentives, Corporate Political Connections, and the Control Structure of Private Firms: Chinese Evidence

We examine how the rent-seeking incentives of local government motivate private firms1 listed in China to establish political connections, and whether such connections lead to more concentrated corporate control structures. Our results show that such firms are more likely to establish political connections in regions in which the local economy is less market-oriented or in which the government has more discretion in allocating economic resources. This is consistent with the notion that the presence of incentives for government officials to engage in rent seeking motivates private firms to look for alternative safeguards through political connections. We also find that the controlling owners of politically connected firms tend to concentrate their shareholdings and dominate the board of directors by occupying the position of either chairman or CEO, which supports the conjecture that a concentrated control structure facilitates rent seeking through political connections and allows the controlling owner to retain all of the benefits arising from connections with politicians

Rent-seeking incentives, corporate political connections, and the control structure of private firms: Chinese evidence

We examine how the rent-seeking incentives of local government motivate private firms1 listed in China to establish political connections, and whether such connections lead to more concentrated corporate control structures. Our results show that such firms are more likely to establish political connections in regions in which the local economy is less market-oriented or in which the government has more discretion in allocating economic resources. This is consistent with the notion that the presence of incentives for government officials to engage in rent seeking motivates private firms to look for alternative safeguards through political connections. We also find that the controlling owners of politically connected firms tend to concentrate their shareholdings and dominate the board of directors by occupying the position of either chairman or CEO, which supports the conjecture that a concentrated control structure facilitates rent seeking through political connections and allows the controlling owner to retain all of the benefits arising from connections with politicians.Rent-seeking incentives Political connections Emerging markets

Controlling Quantum Interference by Regulating Charge on the Bridging N Atom of Pyrrolodipyridine Molecular Junctions

Control of quantum interference features: molecular junctions incorporating pyrrolodipyridine-based molecular wires were fabricated by scanning probe methods. Quantum interference effects were introduced by employing meta-connected molecules, and modulated in magnitude by changing the substituent on the pyrrolic N. Dramatic changes in molecular conductance and DFT transport calculations demonstrate the storng effect that small changes in electronic density can have on the overall conductance of a molecular wire