Multifunctional Magnetic Optical Sensor Particles with Tunable Sizes for Monitoring Metabolic Parameters and as a Basis for Nanotherapeutics

Magnetic optical sensor particles with multifunctional cores and shells are synthesized via a facile nanoprecipitation method and the subsequent modification of the particle shell. The hydrophobic particle core includes optical oxygen indicators, a light harvesting system, photosensitizers, and magnetic nanoparticles. Further functionalities are introduced by modifying the shell with enzymes, antibodies, multiple layers of polyelectrolytes, stimuli‐responsive polymers, and luminescent indicator dyes. The hydrodynamic diameter is tunable by varying different precipitation parameters.     

Impact of synchrotron radiation on fuel cell operation in imaging experiments

For the clarification of water transport mechanisms in operating fuel cells, synchrotron radiation computed tomography (SR-CT) was applied. A novel fuel cell has been designed that exposes the entire active area (7 mm²) to the SR beam while at the same time allowing for full fuel cell operation during the imaging experiment. This micro fuel cell has been qualified successfully prior to the SR imaging experiments. The cell voltage was 600 mV at 0.2 A cm⁻² (open circuit voltage, OCV > 950 mV) and the operation was stable for hours. However, under SR beam exposition for in situ imaging, severe cell performance degradation within minutes has been reproducibly observed. Even after the SR beam had been switched-off cell operation remained irreversibly degraded whilst OCV could be recovered. Preliminary results indicate a higher degradation sensitivity of the cathode side of the cell. Apparently, the unique setup of the experiment which exposes an operating fuel cell with the entire active area to the SR beam reveals otherwise unnoticeable degradation mechanisms. It may have to be concluded that the very same materials degrade heavily during beam exposure that are subject of the imaging investigation. Consequently, the applicability of SR imaging to study water transport in porous fuel cell materials has to be revisited critically. This publication describes the observations made during fuel cell operation under SR beam exposure and discuss potential mechanisms that may cause beam-induced performance degradation.     

Regenerable MgO-based sorbents for high-temperature CO2 removal from syngas: 1. Sorbent development, evaluation, and reaction modeling

Highly reactive and mechanically strong low-cost regenerable MgO-based sorbents were prepared by modification of dolomite which involved partial calcinations followed by impregnation with a potassium-based salt. The sorbents are capable of removing CO₂ from gasification-based processes such as Integrated Gasification Combined Cycle (IGCC). The sorbents have high reactivity and good capacity toward CO₂ absorption in the temperature range of 300-450 °C at 20 atm. and can be easily regenerated at 500 °C. The reaction appears to be first order with respect to CO₂ concentration with an activation energy of 44 kJ/mol. The reactivity and the absorption capacity of the sorbents increase with increasing temperature, as long as the partial pressure of CO₂ is above the equilibrium value for sorbent carbonation. The reactivity of the sorbents appears to improve in the presence of steam, which is likely due to the increase in the BET surface area and the porosity of the sorbent. A two-zone expanding grain model, consisting of a high-reactivity outer shell and a low-reactivity inner core is shown to provide an excellent fit to the TGA experimental data on sorbent carbonation at various operating conditions.     

Influence of Lubricant on the Nucleate Boiling Heat Transfer Performance of Refrigerant—A Review

This review provides an overview of the lubricant on the heat transfer performance pertaining to nucleate boiling. It appears that the effect of individual parameter on the heat transfer coefficient may be different from study to study. This is associated with the complex nature of lubricant and some compound effects accompanying the heat transport process. Some important effects such as oil concentration, heat flux, geometric configuration, saturation temperature, thermodynamic and transport properties, miscibility, foaming, and additional surface active agent are reported and discussed. In general, the heat transfer coefficient is impaired provided the oil concentration is sufficient high (e.g., >7%), and this is applicable to smooth and structured tubes. But normally structured tubes tend to suffer more from lubricant, yet this is especially conspicuous when the size of the reentrant channel is small. On the other hand, foaming and partial miscibility seem to benefit the heat transfer coefficient.     

Pessimistic cost-sensitive active learning of decision trees for profit maximizing targeting campaigns

In business applications such as direct marketing, decision-makers are required to choose the action which best maximizes a utility function. Cost-sensitive learning methods can help them achieve this goal. In this paper, we introduce Pessimistic Active Learning (PAL). PAL employs a novel pessimistic measure, which relies on confidence intervals and is used to balance the exploration/exploitation trade-off. In order to acquire an initial sample of labeled data, PAL applies orthogonal arrays of fractional factorial design. PAL was tested on ten datasets using a decision tree inducer. A comparison of these results to those of other methods indicates PAL’s superiority.     

A paired comparison experiment for gathering expert judgment for an aircraft wiring risk assessment

Wire failure in aircraft can be attributed to several factors and the assessment of the risk of wire failure is becoming an increasingly important task. This paper will discuss the results of an actual experiment to use the paired-comparison technique for expert judgment to develop a relationship for the probability of wire failure as a function of influencing factors in an aircraft environment. The reasons for using this technique are two-fold. First, the failure probability depends on many variables including wire gauge, vibration, environmental condition, etc. In addition, the wire failure data are sparse and fitting these data to a complex failure function is a nontrivial task that may involve a host of assumptions that may not be provable.We describe a method for using actual failure data and the results from a paired comparison to populate the model parameters. In the approach, paired comparison data from select environments is used to obtain failure rate estimates for the candidate environments. Next, a functional relationship for wire failure as a function of the environments is constructed using a proportional hazards model. A regression model is fit from the failure rate estimates to the environmental variables and is used as an estimate of the failure response surface. This technique is being investigated as a means to generate failure rates for an electrical wiring interconnection system (EWIS) risk assessment software tool currently being developed for the FAA Tech Center.