Analytical characterization of the electrospray ion source in the nanoflow regime

A detailed characterization of a conventional low-flow electrospray ionization (ESI) source for mass spectrometry (MS) using solution compositions typical of reversed-phase liquid chromatography is reported. Contrary to conventional wisdom, the pulsating regime consistently provided better ESI-MS performance than the cone-jet regime for the interface and experimental conditions studied. This observation is supported by additional measurements showing that a conventional heated capillary interface affords more efficient sampling and transmission for the charged aerosol generated by a pulsating electrospray. The pulsating electrospray provided relatively constant MS signal intensities over a wide range of voltages, while the signal decreased slightly with increasing voltage for the cone-jet electrospray. The MS signal also decreased with increasing emitter-interface distance for both pulsating and cone-jet electrosprays due to the expansion of the charged aerosol plume. At flow rates below 100 nL/min, the MS signal increased with increasing flow rate due to increased number of gas-phase ions produced. At flow rates greater than 100 nL/min, the signal reached a plateau due to decreasing ionization efficiency at larger flow rates. These results suggest approaches for improving MS interface performance for low-flow (nano- to micro-) electrosprays.     

Creation of Faceted Polyhedral Microgels from Compressed Emulsions

Compressed monodisperse emulsions in confined space exhibit highly ordered structures. The influence of the volume fraction and the confinement geometry on the organized structures is investigated and the mechanism by which structural transition occurs is studied. Based on the understanding of ordering behavior of compressed emulsions, a simple and high‐throughput method to fabricate monodisperse polyhedral microgels using the emulsions as the template is developed. By controlling the geometry of the confined spaces, a variety of shapes such as hexagonal prism, Fejes Toth honeycomb prism, truncated octahedron, pyritohedron, and truncated hexagonal trapezohedron are implemented. Moreover, the edge sharpness of each shape is controllable by adjusting the drop volume fraction. This design principle can be readily extended to other shapes and materials, and therefore provides a useful means to create polyhedral microparticles for both fundamental study and practical applications.     

Remote-sensing reflectance of turbid sediment-dominated waters. Reduction of sediment type variations and changing illumination conditions effects by use of reflectance ratios

Variations of sediment type (grain size and refractive index) and changing illumination conditions affect the reflectance signal of coastal waters and limit the accuracy of sediment-concentration estimations from remote-sensing measurements. These effects are analyzed from numerous in situ remote-sensing measurements carried out in the Gironde and Loire Estuaries and then reduced and partly eliminated when reflectance ratios between the near infrared and the visible are considered. These ratios showed high correlation with the sediment concentration. On the basis of the obtained relationships, performing correspondence functions were established that allow an accurate estimation of suspended sediments in the estuaries from Système Probatoire d'Observation de la Terre, Landsat, and Sea-Viewing Wide Field-of-View Sensor data, independently of the date of acquisition.     

Atomic layer deposition of iron(III) oxide on zirconia nanoparticles in a fluidized bed reactor using ferrocene and oxygen

Conformal films of amorphous iron(III) oxide and α-Fe₂O₃ have been coated on zirconia nanoparticles (26 nm) in a fluidized bed reactor by atomic layer deposition. Ferrocene and oxygen were alternately dosed into the reactor at temperatures between 367 °C and 534 °C. Self-limiting chemistry was observed via in situ mass spectrometry, and by means of induced coupled plasma-atomic emission spectroscopy analysis. Film conformality and uniformity were verified by high resolution transmission electron microscopy, and the growth rate was determined to be 0.15 Å per cycle. Energy dispersive spectroscopy, X-ray diffractometry, and X-ray photoelectron spectroscopy were utilized as a means to determine film composition at each deposition temperature. Over all of the deposition temperatures investigated, films were deposited as amorphous iron(III) oxide. However, after heat treatment at 850 °C in air and N₂ atmospheres, α-Fe₂O₃ was the predominant species.     

Enhanced Solar‐to‐Hydrogen Generation with Broadband Epsilon‐Near‐Zero Nanostructured Photocatalysts

The direct conversion of solar energy into fuels or feedstock is an attractive approach to address increasing demand of renewable energy sources. Photocatalytic systems relying on the direct photoexcitation of metals have been explored to this end, a strategy that exploits the decay of plasmonic resonances into hot carriers. An efficient hot carrier generation and collection requires, ideally, their generation to be enclosed within few tens of nanometers at the metal interface, but it is challenging to achieve this across the broadband solar spectrum. Here the authors demonstrate a new photocatalyst for hydrogen evolution based on metal epsilon‐near‐zero metamaterials. The authors have designed these to achieve broadband strong light confinement at the metal interface across the entire solar spectrum. Using electron energy loss spectroscopy, the authors prove that hot carriers are generated in a broadband fashion within 10 nm in this system. The resulting photocatalyst achieves a hydrogen production rate of 9.5 µmol h^?1 cm^?2 that exceeds, by a factor of 3.2, that of the best previously reported plasmonic‐based photocatalysts for the dissociation of H₂ with 50 h stable operation.     

A Comparision of Starch Granules as Seen by Both Scanning Electron and Ordinary Light Microscopy

Starch being a transparent crystal often give images which are difficult to precisely define with the light microscope due to the diffraction and other effects such as internal structure which may appear as a surface phenomena. The scanning electron microscope (SEM); however, gives only surface detail. In a effort to differentiate between surface and internal details, the same starch granules have been studied by both ordinary light and scanning electron microscopy. In each case the granules were held in the same configuration as was seen with the light microscope when they were studied by SEM. In this way a direct comparison could be made between granules viewed by each microscopy technique. From such comparisons it is possible to determine the starch details that are actually due to internal features. The results for canna, potato and corn starches are given.     

Approximability of Sparse Integer Programs

The main focus of this paper is a pair of new approximation algorithms for certain integer programs. First, for covering integer programs {min cx:Ax≥b,0≤x≤d} where A has at most k nonzeroes per row, we give a k-approximation algorithm. (We assume A,b,c,d are nonnegative.) For any k≥2 and ε>0, if P≠NP this ratio cannot be improved to k−1−ε, and under the unique games conjecture this ratio cannot be improved to k−ε. One key idea is to replace individual constraints by others that have better rounding properties but the same nonnegative integral solutions; another critical ingredient is knapsack-cover inequalities. Second, for packing integer programs {max cx:Ax≤b,0≤x≤d} where A has at most k nonzeroes per column, we give a (2k ²+2)-approximation algorithm. Our approach builds on the iterated LP relaxation framework. In addition, we obtain improved approximations for the second problem when k=2, and for both problems when every A _ij is small compared to b _i . Finally, we demonstrate a 17/16-inapproximability for covering integer programs with at most two nonzeroes per column.     

A fuzzy Grid-QoS framework for obtaining higher grid resources availability

A computational grid ensures the on-demand delivery of computing resources, in a security-aware, shared, scalable, and standards-based computing environment. A major concern is how to evolve a general and an encompassing framework that guarantees users’ satisfaction measured as Quality of Services (QoS). To obtain a higher QoS, effective QoS perceived by subscribers (users) must conform to specified QoS agreements in the Service Level Agreements (SLAs) document—a legal contract between the Grid Services Provider (GSP) and users. Sometimes the effective user QoS does not conform to the specifications in the SLA because of the vagueness in linguistic definitions in the SLA. Existing approaches overcommitted resources to meet QoS. In this paper, we propose a fuzzy logic framework for calibrating a grid resources user-QoS that addresses the vagueness in linguistic definitions of the SLA document without overcommitting grid resources.     

Early bankruptcy prediction using ENPC

Bankruptcy prediction has long time been an active research field in finance. One of the main approaches to this issue is dealing with it as a classification problem. Among the range of instruments available, we focus our attention on the Evolutionary Nearest Neighbor Classifier (ENPC). In this work we assess the performance of the ENPC comparing it to six alternatives. The results suggest that this algorithm might be considered a good choice.     

Adaptive Anomaly Detection in Transaction-Oriented Networks

Adaptive algorithms for real-time and proactive detection of network/service anomalies, i.e., soft performance degradations, in transaction-oriented wide area networks (WANs) have been developed. These algorithms (i) adaptively sample and aggregate raw transaction records to compute service-class based traffic intensities, in which potential network anomalies are highlighted; (ii) construct dynamic and service-class based performance thresholds for detecting network and service anomalies; and (iii) perform service-class based and real-time network anomaly detection. These anomaly detection algorithms are implemented as a real-time software system called TRISTAN ( ansaction n antaneous nomaly otification), which is deployed in the AT&T Transaction Access Services (TAS) network. The TAS network is a commercially important, high volume (millions of transactions per day), multiple service classes (tens), hybrid telecom and data WAN that services transaction traffic such as credit card transactions in the US and neighboring countries. TRISTAN is demonstrated to be capable of automatically and adaptively detecting network/service anomalies and correctly identifying the corresponding "guilty" service classes in TAS. TRISTAN can detect network/service faults that elude detection by the traditional alarm-based network monitoring systems.