Asymptotically Unbiased Estimator of the Informational Energy with kNN

Motivated by machine learning applications (e.g., classification, function approximation, feature extraction), in previous work, we have introduced a non- parametric estimator of Onicescu’s informational energy. Our method was based on the k-th nearest neighbor distances between the n sample points, where k is a fixed positive integer. In the present contribution, we discuss mathematical properties of this estimator. We show that our estimator is asymptotically unbiased and consistent. We provide further experimental results which illustrate the convergence of the estimator for standard distributions

Small Sample Stochastic Tail Modeling: Tackling Sampling Errors and Sampling Bias by Pivot-Distance Sampling and Parametric Curve Fitting Techniques

We describe two original open source software applications that have been developed to aid model efficiency studies: (1) CSTEP (Cluster Sampling for Tail Estimation of Probability) for reducing sampling error through variations of distance sampling and cluster/pivot processes; and (2) AMOOF2 (Actuarial Model Outcome Optimal Fit Version 2.0) for mitigating small sample bias in parametric, time-efficient probability density function fitting. CSTEP uses the scenario reduction method of representative scenarios to sample scenarios from a population of stochastic scenarios to obtain a sample-run distribution of a financial outcome that can be analyzed by AMOOF2 to fit the optimal probability density function

Spatial organisation of enzymes in the biosynthetic limonene production pathway in Escherichia coli

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Effects of Selfâ Assembled Monolayer Modification of Nickel Oxide Nanoparticles Layer on the Performance and Application of Inverted Perovskite Solar Cells

Entirely lowâ temperature solutionâ processed (â ¤100â °C) planar pâ iâ n perovskite solar cells (PSCs) offer great potential for commercialization of rollâ toâ roll fabricated photovoltaic devices. However, the stable inorganic holeâ transporting layer (HTL) in PSCs is usually processed at high temperature (200â 500â °C), which is far beyond the tolerant temperature (â ¤150â °C) of rollâ toâ roll fabrication. In this context, inorganic NiOx nanoparticles (NPs) are an excellent candidate to serve as the HTL in PSCs, owing to their excellent solution processability at room temperature. However, the lowâ temperature processing condition is usually accompanied with defect formation, which deteriorates the film quality and device efficiency to a large extent. To suppress this setback, we used a series of benzoic acid selfassembled monolayers (SAMs) to passivate the surface defects of the NiOx NPs and found that 4â bromobenzoic acid could effectively play the role of the surface passivation. This SAM layer reduces the trapâ assisted recombination, minimizes the energy offset between the NiOx NPs and perovskite, and changes the HTL surface wettability, thus enhancing the perovskite crystallization, resulting in more stable PSCs with enhanced power conversion efficiency (PCE) of 18.4â %, exceeding the control device PCE (15.5â %). Also, we incorporated the aboveâ mentioned SAMs into flexible PSCs (Fâ PSCs) and achieved one of the highest PCE of 16.2â % on a polyethylene terephthalate (PET) substrate with a remarkable powerâ perâ weight of 26.9â Wâ gâ 1. This facile interfacial engineering method offers great potential for the largeâ scale manufacturing and commercialization of PSCs.Engineered layers: Lowâ temperature solutionâ processed NiOx nanoparticle film is usually accompanied with defect formation. Here, we find that 4â bromobenzoic acid can form a selfâ assembled monolayer (SAM) on the NiOx film and effectively tune the interfacial properties, resulting in high perovskite solar cells (PSCs) efficiency. Also, we incorporate the aboveâ mentioned SAM into flexible PSCsPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/138886/1/cssc201701262_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/138886/2/cssc201701262.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/138886/3/cssc201701262-sup-0001-misc_information.pd

Ultrathin compound semiconductor on insulator layers for high performance nanoscale transistors

Over the past several years, the inherent scaling limitations of electron devices have fueled the exploration of high carrier mobility semiconductors as a Si replacement to further enhance the device performance. In particular, compound semiconductors heterogeneously integrated on Si substrates have been actively studied, combining the high mobility of III-V semiconductors and the well-established, low cost processing of Si technology. This integration, however, presents significant challenges. Conventionally, heteroepitaxial growth of complex multilayers on Si has been explored. Besides complexity, high defect densities and junction leakage currents present limitations in the approach. Motivated by this challenge, here we utilize an epitaxial transfer method for the integration of ultrathin layers of single-crystalline InAs on Si/SiO2 substrates. As a parallel to silicon-on-insulator (SOI) technology14,we use the abbreviation "XOI" to represent our compound semiconductor-on-insulator platform. Through experiments and simulation, the electrical properties of InAs XOI transistors are explored, elucidating the critical role of quantum confinement in the transport properties of ultrathin XOI layers. Importantly, a high quality InAs/dielectric interface is obtained by the use of a novel thermally grown interfacial InAsOx layer (~1 nm thick). The fabricated FETs exhibit an impressive peak transconductance of ~1.6 mS/{\mu}m at VDS=0.5V with ON/OFF current ratio of greater than 10,000 and a subthreshold swing of 107-150 mV/decade for a channel length of ~0.5 {\mu}m

Quantum Size Effects on the Chemical Sensing Performance of Two-Dimensional Semiconductors

We investigate the role of quantum confinement on the performance of gas sensors based on two-dimensional InAs membranes. Pd-decorated InAs membranes configured as H2 sensors are shown to exhibit strong thickness dependence, with ~100x enhancement in the sensor response as the thickness is reduced from 48 to 8 nm. Through detailed experiments and modeling, the thickness scaling trend is attributed to the quantization of electrons which favorably alters both the position and the transport properties of charge carriers; thus making them more susceptible to surface phenomena

Metal-slotted polymer optical waveguide device

Metal-slotted optical waveguides (MSOWs) using an electro-optic polymer material have been experimentally demonstrated. The device consists of a three-layered slab waveguide in that the thin metal (gold) film strips are embedded on top of the lower cladding. The optical mode shapes and effective index of the propagation modes of the proposed waveguide structure were calculated using a simplified effective index method and a simulation tool. The fabrication and the device characteristics of a variable optical attenuator and an optical phase modulator based on MSOWs are discussed.open5

Correlating the nanostructure and electronic properties of InAs nanowires

The electronic properties and nanostructure of InAs nanowires are correlated by creating multiple field effect transistors (FETs) on nanowires grown to have low and high defect density segments. 4.2 K carrier mobilities are ~4X larger in the nominally defect-free segments of the wire. We also find that dark field optical intensity is correlated with the mobility, suggesting a simple route for selecting wires with a low defect density. At low temperatures, FETs fabricated on high defect density segments of InAs nanowires showed transport properties consistent with single electron charging, even on devices with low resistance ohmic contacts. The charging energies obtained suggest quantum dot formation at defects in the wires. These results reinforce the importance of controlling the defect density in order to produce high quality electrical and optical devices using InAs nanowires.Comment: Related papers at http://pettagroup.princeton.ed