Towards an automated, standardized protocol for determination of equilibrium potential of ion-selective electrodes

An automated real-time method for determination of ISE steady state value and response time is developed, following most recent IUPAC recommendations. Specifically, detection of the ‘steady state’ is related to (1) the time derivative of the emf as it reaches a limiting value (ΔE/Δt_limit, e.g., 0.1–1.0 mV min⁻¹) and (2) the duration of time for which the absolute value of the time derivative remains less than this limiting value (stability window, denoted win_st). A suite of representative ISEs, including glass, solid state, and polymer-based electrodes, is examined to determine sensitivity of results to parameterization choice. Measurements taken over a wide range of concentration values and in un-processed samples (i.e., without use of ionic strength adjustment) provide insight into behavior of ISEs in applications where analyte concentrations span a wide range and/or sample pre-processing may not be an option, e.g., use of sensors for in situ environmental sampling. Results show that declared steady state emf is strongly sensitive to variations in ΔE/Δt_limit but relatively unaffected by changes in the stability window when win_st ≥30 s. Linearity of calibration curves produced, quantified by root mean squared error (RMSE) against a linear fit, improves as ΔE/Δt_limit decreases, however the percentage of measurements which reach a declared steady state within the prescribed sample window (∼6.5 min) falls with corresponding decreases in the ΔE/Δt_limit parameter. Response time, defined as the time required to reach declared steady emf, is also a strong function of parameterization. Dependence of response times on sample composition and/or ISE membrane composition and type are also discussed; results for ISEs in samples comprised exclusively of interfering ions are included. In general, limiting emf derivatives of {0.25–0.4 mV min⁻¹} and stability windows of {30–40 s} achieve both good analytical accuracy and compliance with potentially short sampling window requirements. Methodology based on use of these parameters can improve sampling speed and accuracy as well as promote inter-comparison of data and ISE characterizations among research teams.     

Nonlocal instability analysis of FCC bulk and (1 0 0) surfaces under uniaxial stretching

The objective of this paper is to examine the instability characteristics of both a bulk FCC crystal and a (1 0 0) surface of an FCC crystal under uniaxial stretching along a 〈1 0 0〉 direction using an atomistic-based nonlocal instability criterion. By comparison to benchmark atomistic simulations, we demonstrate that for both the FCC bulk and (1 0 0) surface, about 5000–10,000 atoms are required in order to obtain an accurate converged value for the instability strain and a converged instability mode. The instability modes are fundamentally different at the surface as compared to the bulk, but in both cases a strong dependence of the instability mode on the number of atoms that are allowed to participate in the instability process is observed. In addition, the nonlocal instability criterion enables us to determine the total number of atoms, and thus the total volume occupied by these atoms, that participate in the defect nucleation process for both cases. We find that this defect participation volume converges as the number of atoms increases for both the bulk and surface, and that the defect participation volume of the surface is smaller than that of the bulk. Overall, the present results demonstrate both the necessity and utility of nonlocal instability criteria in predicting instability and subsequent failure of both bulk and surface-dominated nanomaterials.     

Die Elementaranalyse mittels einer Kalorimeterbombe

Ohne Zusammenfassung     

Zur Unterscheidung von prim?ren, sekund?ren und terti?ren Aminen

Ohne Zusammenfassung     

Control of multi-node mobile communications networks with time-varying channels via stability methods

Consider a communications network consisting of mobiles and random external data processes, each destined to a particular destination. Each mobile can serve as a node in the multi-hop path from source to destination. At each mobile the data is queued according to the source destination pair. The quality of the connecting channels are randomly varying. Time is divided into small scheduling intervals. At the beginning of each interval, the channels are estimated and this information is used for the decisions concerning allocation of transmission power and/or time, bandwidth, and perhaps antennas, in a queue and channel-state dependent way. Under a natural (and “almost” necessary) “average flow” condition, stochastic stability methods are used to develop scheduling policies that assure stability. The policies are readily implementable and allow a range of tradeoffs between current rates and queue lengths, under very weak conditions. Because of the non-Markovian nature of the problem, we use the perturbed Stochastic Liapunov function method. The choice of Liapunov function allows a choice of the effective performance criteria. All essential factors are incorporated into a “mean rate” function, so that the results cover many different systems. Extensions concerning acknowledgments, multicasting, non-unique routes, and others are given to illustrate the versatility of the method, and a useful method for getting the a priori routes is discussed.     

A bisection-extreme point search algorithm for optimizing over the efficient set in the linear dependence case

The algorithms and algorithmic ideas currently available for globally optimizing linear functions over the efficient sets of multiple objective linear programs either use nonstandard subroutines or cannot yet be implemented for lack of sufficient development. In this paper a Bisection-Extreme Point Search Algorithm is presented for globally solving a large class of such problems. The algorithm finds an exact, globally-optimal solution after a finite number of iterations. It can be implemented by using only well-known pivoting and optimization subroutines, and it is adaptable to large scale problems or to problems with many local optima.