Low-temperature aerosol flow reactor method for preparation of surface stabilized pharmaceutical nanocarriers

Nanoparticles can be used to improve the delivery of many drugs, especially peptides and proteins. Although several methods are available for polymeric nanoparticle preparation, there are few single-stage processes that produce dry, solid nanoparticles that can be easily re-dispersed in pharmaceutical vehicles. The aerosol flow reactor method is a single-stage process that has been used for the preparation of multicomponent, coated nanoparticles under uniform temperature and gas flow field. However, it is traditionally used with high synthesis temperatures. In the present study, the aerosol flow reactor method was further optimized for processing and surface stabilization of pharmaceutical nanoparticles containing temperature sensitive biomolecules. In the developed method, drug-loaded carrier nanoparticles consisting of a biodegradable polymer (Eudragit L100) and a drug (phenylephrine hydrochloride) were first produced by aerosol droplet drying and subsequently coated in the gas phase. The carrier particles were coated with l-leucine in order to inhibit agglomeration of the nanoparticles in solutions before administration. In the coating process, a side stream of l-leucine vapor was directed into the main aerosol flow containing the drug-loaded carriers. The mixing with the main flow at ambient temperature induced a supersaturation of l-leucine vapor and condensation on the carrier particles. The results demonstrate that solid, hydrodynamically stable drug-loaded polymeric nanoparticles can be produced with a thin l-leucine coating. The low process temperature enables the surface engineering of particles loaded with temperature sensitive drugs or bioactive materials to be utilized for drug delivery purposes.     

Films of Graphene Nanomaterials Formed by Ultrasonic Spraying of Their Stable Suspensions

Graphene, a two-dimensional carbon allotrope, exhibits excellent optoelectronic properties. The assembly of graphene into films provides a platform to deepen the study of its interaction with varying surfaces, to engineer devices, and to develop functional materials. A general approach to produce graphene films consists of preparing a dispersion and laying it on a substrate of choice, followed by solvent evaporation. Here, we report the preparation of stable suspensions of new types of graphene nanomaterials namely, graphene nanoflowers (GNFs) and multi-layer graphene (MLG) flakes, in ethanol, N,N-dimethylformamide (DMF), and N-methyl-2-pyrrolidone (NMP). Sprayable suspensions of both GNFs and MLG were prepared in DMF/ethanol, which showed high stability, without addition of any surfactant. The stable suspensions were used to deposit micrometer-thick MLG/GNF films on glass substrates. Calculations of initial droplet size and of timescale of droplet evaporation are performed and possible thermophoretic effects on droplet deposition discussed as well. Coating glass substrates with a methacrylic acid–methyl methacrylate (MA) copolymer prior to the deposition significantly improved the adhesion of the nanomaterials to the substrate. With the MA coating, a substrate coverage of nearly 100% was achieved at 14-min spraying time for 0.05 wt% GNF and 0.1 wt% MLG suspensions. Raman spectra of the GNF and MLG films reveal that the films were made of MLG in which the individual graphene layers rotated from each other as in turbostratic graphene. This work provides a general approach to prepare graphene nanomaterial suspensions and to create films for a variety of applications. The spraying process applied in the current work is highly scalable and allows control of film characteristics through process parameters.

Copyright 2015 American Association for Aerosol Research     

Hygroscopic Behavior of Aerosol Particles Emitted from Biomass Fired Grate Boilers

This study focuses on the hygroscopic properties of submicrometer aerosol particles emitted from two small-scale district heating combustion plants (1 and 1.5 MW) burning two types of biomass fuels (moist forest residue and pellets). The hygroscopic particle diameter growth factor (Gf) was measured when taken from a dehydrated to a humidified state for particle diameters between 30–350 nm (dry size) using a Hygroscopic Tandem Differential Mobility Analyzer (H-TDMA). Particles of a certain dry size all showed similar diameter growth and the Gf at RH = 90% for 110/100 nm particles was 1.68 in the 1 MW boiler, and 1.5 in the 1.5 MW boiler. These growth factors are considerably higher in comparison to other combustion aerosol particles such as diesel exhaust, and are the result of the efficient combustion and the high concentration of alkali species in the fuel. The observed water uptake could be explained using the Zdanovski-Stokes-Robinson (ZSR) mixing rule and a chemical composition of potassium salts only, taken from ion chromatography analysis of filter and impactor samples (KCl, K₂SO₄, and K₂CO₃). Agglomerated particles collapsed and became more spherical when initially exposed to a moderately high relative humidity. When diluted with hot particle-free air, the fractal-like structures remained intact until humidified in the H-TDMA. A method to estimate the fractal dimension of the agglomerated combustion aerosol and to convert the measured mobility diameter hygroscopic growth to the more useful property volume diameter growth is presented. The fractal dimension was estimated to be ～ 2.5.     

(6<Emphasis Type="Italic">R</Emphasis>, 10<Emphasis Type="Italic">R</Emphasis>)-6,10,14-Trimethylpentadecan-2-one,a Dominant and Behaviorally Active Component in Male Orchid Bee Fragrances

6,10,14-Trimethylpentadecan-2-one (Hexahydrofarnesyl acetone; HHA) previously has been found to be a major component in tibial fragrances of male orchid bees, Euglossa spp. HHA is a chiral molecule with four possible stereoisomers, (6R, 10R)-, (6R, 10S)-, (6S, 10R)-, and (6S, 10S)-6,10,14-trimethylpentadecan-2-one. In the present study, we characterized HHA extracted from Euglossa as the pure enantiomer (6R, 10R)-6,10,14-trimethylpentadecan-2-one. During bioassays in Mexico and Panama, the synthetic RR-isomer attracted males of six species of orchid bees, including three that were known to contain HHA in their tibial fragrances. Possible sources of HHA for wild bees are flowers of euglossophilous orchids and aroids. With a molecular weight of 268, HHA is the largest natural molecule known to attract male orchid bees in pure form. Its attractiveness to males suggests that low-volatility compounds have a function in male signals, e.g., serve as a “base note” in complex odor bouquets.     

A high-resolution stochastic model of domestic activity patterns and electricity demand

Realistic time-resolved data on occupant behaviour, presence and energy use are important inputs to various types of simulations, including performance of small-scale energy systems and buildings’ indoor climate, use of lighting and energy demand. This paper presents a modelling framework for stochastic generation of high-resolution series of such data. The model generates both synthetic activity sequences of individual household members, including occupancy states, and domestic electricity demand based on these patterns. The activity-generating model, based on non-homogeneous Markov chains that are tuned to an extensive empirical time-use data set, creates a realistic spread of activities over time, down to a 1-min resolution. A detailed validation against measurements shows that modelled power demand data for individual households as well as aggregate demand for an arbitrary number of households are highly realistic in terms of end-use composition, annual and diurnal variations, diversity between households, short time-scale fluctuations and load coincidence. An important aim with the model development has been to maintain a sound balance between complexity and output quality. Although the model yields a high-quality output, the proposed model structure is uncomplicated in comparison to other available domestic load models.     

Impacts of distributed photovoltaics on network voltages: Stochastic simulations of three Swedish low-voltage distribution grids

The continuously increasing application of distributed photovoltaics (PV-DG) in residential areas around the world calls for detailed assessment of distribution grid impacts. Both photovoltaic generation and domestic electricity demand exhibit characteristic variations on short and long time scales and are to a large extent negatively correlated, especially at high latitudes. This paper presents a stochastic methodology for simulation of PV-DG impacts on low-voltage (LV) distribution grids, using detailed generation and demand models. The methodology is applied to case studies of power flow in three existing Swedish LV grids to determine load matching, voltage levels and network losses at different PV-DG penetration levels. All studied LV grids can handle significant amounts of PV-DG, up to the highest studied level of 5 kW_p PV per household. However, the benefits of PV-DG in terms of relative improvement of on-site reduction of demand, mitigated voltage drops and reduced losses were most significant at a penetration level of 1 kW_p PV per household.     

Common Breaks in Means for Cross‐Correlated Fixed‐T Panel Data

This note considers a panel data model in which the variable of interest has undergone a common structural break in the mean. The object of interest is the unknown breakpoint. The challenge is to device an estimator that is consistent when the data are cross‐correlated and the number of time periods T is fixed and cannot be increased without bound. The proposed solution involves taking an already existing estimator initially proposed for cross‐section uncorrelated panels and applying it to defactored data. Consistency is established as the number of cross‐section units N grows large, and is verified in small samples using Monte Carlo simulation.