Magnetic Nanoplatelet‐Based Spin Memory Device Operating at Ambient Temperatures

There is an increasing demand for realizing a simple Si based universal memory device working at ambient temperatures. In principle, nonvolatile magnetic memory can operate at low power consumption and high frequencies. However, in order to compete with existing memory technology, size reduction and simplification of the used material systems are essential. In this work, the chiral‐induced spin selectivity effect is used along with 30–50 nm ferromagnetic nanoplatelets in order to realize a simple magnetic memory device. The vertical memory is Si compatible, easy to fabricate, and in principle can be scaled down to a single nanoparticle size. Results show clear dual magnetization behavior with threefold enhancement between the one and zero states. The magnetization of the device is accompanied with large avalanche like noise that is ascribed to the redistribution of current densities due to spin accumulation inducing coupling effects between the different nanoplatelets.     

Real‐time waiting‐price trading interval in a heterogeneous options market: a Bernoulli distribution

Options pricing remains an open research question that is challenging for both theoreticians and practitioners. Unlike many classical binomial models that assume a “representative agent,” the model suggested herein considers two players who are heterogeneous with respect to their estimations of the distribution of the underlying asset price on expiration day, and with respect to their levels of willingness to make a transaction (eagerness level). A two‐player binomial model is developed to find the real‐time optimal option price in two stages. First, we determine a primary feasible pricing domain. We then find a narrower feasible domain, termed the “waiting‐price trading interval,” meaning the region within which the players may either wait for better offers (due to a change in market conditions or player beliefs), or make an immediate transaction. The suggested model is formulated by a nonlinear optimization problem and the optimal price is shown to be unique. We demonstrate that the counter player's eagerness level has a significant effect on the proposed optimal option price. Using empirical analysis, several known lattice‐based models for option pricing, such as CRR and Tian, are compared with the current model (herein, S‐H) in which the price offered by the model player takes into account the subjective beliefs of the opposing market player. The comparison shows significant advantages to the S‐H model in terms of the expected profit on expiration day.     

Synthesis and characterization of near IR fluorescent albumin nanoparticles for optical detection of colon cancer

Near IR (NIR) fluorescent human serum albumin (HSA) nanoparticles hold great promise as contrast agents for tumor diagnosis. HSA nanoparticles are considered to be biocompatible, non-toxic and non-immunogenic. In addition, NIR fluorescence properties of these nanoparticles are important for in vivo tumor diagnostics, with low autofluorescence and relatively deep penetration of NIR irradiation due to low absorption of biomatrices. The present study describes the synthesis of new NIR fluorescent HSA nanoparticles, by entrapment of a NIR fluorescent dye within the HSA nanoparticles, which also significantly increases the photostability of the dye. Tumor-targeting ligands such as peanut agglutinin (PNA) and anti-carcinoembryonic antigen antibodies (anti-CEA) were covalently conjugated to the NIR fluorescent albumin nanoparticles, increasing the potential fluorescent signal in tumors with upregulated corresponding receptors. Specific colon tumor detection by the NIR fluorescent HSA nanoparticles was demonstrated in a chicken embryo model and a rat model. In future work we also plan to encapsulate cancer drugs such as doxorubicin within the NIR fluorescent HSA nanoparticles for both colon cancer imaging and therapy.     

Vertical junction Si cells for concentrating photovoltaics

Vertical junction Si cell has shown a potential to operate at high concentrations, mainly the result of reduced series resistance losses due to its low‐current/high‐voltage design, but tests and analyses have so far only shown a modest efficiency of about 20%. We perform a comprehensive optimization study and show that the conversion efficiency of vertical multi‐junction (VMJ) cells can be significantly higher, close to 30% at concentrations of 1000 and higher. Reaching this efficiency requires junction dimensions that are significantly smaller than previous VMJ cells. This may require a different approach in the fabrication process, possibly by using a monolithic method rather than the wafer stacking approach. We also show that increased photoconductivity, which is usually negligible in conventional cells, produces a significant reduction in series resistance at high concentrations making it a significant contributor to the outstanding performance of the VMJ cell at high concentration. Copyright © 2011 John Wiley & Sons, Ltd.     

Large anisotropic conductance and band gap fluctuations in nearly round-shape bismuth nanoparticles

Unlike their bulk counterpart, nanoparticles often show spontaneous fluctuations in their crystal structure at constant temperature [Iijima, S.; Ichihashi T. Phys. Rev. Lett.1985, 56, 616; Ajayan, P. M.; Marks L. D. Phys. Rev. Lett.1988, 60, 585; Ben-David, T.; Lereah, Y.; Deutscher, G.; Penisson, J. M.; Bourret, A.; Korman, R.; Cheyssac, P. Phys. Rev. Lett.1997, 78, 2585]. This phenomenon takes place whenever the net gain in the surface energy of the particles outweighs the energy cost of internal strain. The configurational space is then densely populated due to shallow free-energy barriers between structural local minima. Here we report that in the case of bismuth (Bi) nanoparticles (BiNPs), given the high anisotropy of the mass tensor of their charge carriers, structural fluctuations result in substantial dynamic changes in their electronic and conductance properties. Transmission electron microscopy is used to probe the stochastic dynamic structural fluctuations of selected BiNPs. The related fluctuations in the electronic band structure and conductance properties are studied by scanning tunneling spectroscopy and are shown to be temperature dependent. Continuous probing of the conductance of individual BiNPs reveals corresponding dynamic fluctuations (as high as 1 eV) in their apparent band gap. At 80 K, upon freezing of structural fluctuations, conductance anisotropy in BiNPs is detected as band gap variations as a function of tip position above individual particles. BiNPs offer a unique system to explore anisotropy in zero-dimension conductors as well as the dynamic nature of nanoparticles.     

Optimal Algorithmic Cooling of Spins

Algorithmic cooling (AC) is a recent spin-cooling approach that employs entropy compression methods in open systems. AC reduces the entropy of spins on suitable molecules beyond Shannon's bound on the degree of entropy compression by reversible manipulations. Remarkably, AC makes use of thermalization, a generally destructive facet of spin systems, as an integral part of the cooling scheme. AC is capable of cooling spins to very low temperatures and provides significant cooling for molecules containing as few as 5–7 spins. Application of AC to slightly larger molecules could lead to breakthroughs in high-sensitivity NMR spectroscopy in the near future. Furthermore, AC may be germane to the development of scalable NMR quantum computers. We introduce here a new practicable algorithm, “PAC3”, and several new exhaustive cooling algorithms, such as the Tribonacci and k-bonacci algorithms. In particular, we present the “all-bonacci” algorithm, which appears to reach the maximal degree of cooling obtainable by the optimal AC approach. AC is potentially beneficial for NMR-derived biomedical applications, which involve bio-molecules with isotope enrichments, such as ¹³ C- and ¹⁵ N-labeled amino acids. We briefly survey AC experiments, including a recent 3-spin experiment in which Shannon's bound was bypassed. The difficulties associated with cooling molecules bearing a greater number of spins are explained. Finally, the potential of selected cooling algorithms (practicable, exhaustive, and optimal algorithms) is illustrated with regard to a highly relevant bio-medical target— ¹³ C-labeled glucose.     

Optimal workload-based weighted wavelet synopses

In recent years wavelets were shown to be effective data synopses. We are concerned with the problem of finding efficiently wavelet synopses for massive data sets, in situations where information about query workload is available. We present linear time, I/O optimal algorithms for building optimal workload-based wavelet synopses for point queries. The synopses are based on a novel construction of weighted inner products and use weighted wavelets that are adapted to those products. The synopses are optimal in the sense that the subset of retained coefficients is the best possible for the bases in use with respect to either the mean-squared absolute or relative errors. For the latter, this is the first optimal wavelet synopsis even for the regular, non-workload-based case. Experimental results demonstrate the advantage obtained by the new optimal wavelet synopses.     

A lower bound on the period length of a distributed scheduler

Ad-scheduling of a graphG is a sequence of rounds, each consisting of some of the nodes of the graph, such that the distance between any two nodes participating in the same round is greater thand. Ad-scheduler is a protocol that determines ad-scheduling ofG. A 1-scheduler is applicable to process scheduling in a resource-sharing system, and to proper communication scheduling of the half-duplex model in communication networks. A 2-scheduler can be used as a collision-free protocol for radio networks.In this paper a simpled-scheduler is analyzed. We first discuss basic properties of this scheduling, and give a complete characterization of this scheduling for trees and cycles. We study the period length of this scheduling, and the main result is a worst-case exponential lower bound for this length.The research of Shmuel Zaks was supported by the Fund for Research in Electronics, Computers, and Communications adminstered by the Israeli Academy of Sciences and Humanities.