A Monte Carlo simulation of ion transport at finite temperatures

We have developed a Monte Carlo simulation for ion transport in hot background gases, which is an alternative way of solving the corresponding Boltzmann equation that determines the distribution function of ions. We consider the limit of low ion densities when the distribution function of the background gas remains unchanged due to collision with ions. A special attention has been paid to properly treat the thermal motion of the host gas particles and their influence on ions, which is very important at low electric fields, when the mean ion energy is comparable to the thermal energy of the host gas. We found the conditional probability distribution of gas velocities that correspond to an ion of specific velocity which collides with a gas particle. Also, we have derived exact analytical formulas for piecewise calculation of the collision frequency integrals. We address the cases when the background gas is monocomponent and when it is a mixture of different gases. The developed techniques described here are required for Monte Carlo simulations of ion transport and for hybrid models of non-equilibrium plasmas. The range of energies where it is necessary to apply the technique has been defined. The results we obtained are in excellent agreement with the existing ones obtained by complementary methods. Having verified our algorithm, we were able to produce calculations for Ar$^+$ ions in Ar and propose them as a new benchmark for thermal effects. The developed method is widely applicable for solving the Boltzmann equation that appears in many different contexts in physics.Comment: 14 page

Measurements and modeling of electron energy distributions in the afterglow of a pulsed discharge in BF

In this paper we use experimental data (Radovanov S. and Godet L., J. Phys.: Conf. Ser., 71 (2007) 012014) for time-resolved electron energy distribution function in boron trifluoride (BF3) discharges together with cross-sections for electron excitation processes and attachment in order to explain electron dynamics in the pulsed plasma doping system. A Monte Carlo simulation (MCS) was used to perform calculations of the electron energy probability function (EEPF) in pulsed DC electric fields as found in practical implantation devices. It was found that in the afterglow, electric field in the plasma is not zero but still has a significant reduced electric field (E/N) albeit below the breakdown condition. Our analysis assuming free diffusion conditions in the afterglow led to the calculation of EEPF for a range of E/N corresponding to different afterglow times of a pulsed DC discharge. Calculated and experimental EEPF agree fairly well for a given set of cross-sections (see paper by Radovanov and Godet quoted above) and assumed initial distributions. In addition we have modeled the kinetics of production of negative ions in the afterglow as observed by experiment and found an increase in the production of negative ions in the early afterglow. Electron attachment in BF3 with 0.1% of F2 is a possible explanation for the observed rate of negative-ion production as predicted by our Monte Carlo simulation. However, the most likely cause for the increase in detected number density of ions is the collapse of the field-controlling electrons

Supplementary materials for Journal of Insects as Food and Feed manuscript 23524588-20230024: <strong>Survey on public acceptance of insects as novel food in a non-EU country: a case study of Serbia</strong>

   The present study aimed to evaluate the state of public perceptions and acceptance of insects as food in Serbia. The data was gathered via an online survey involving 1,102 participants who completed Google Forms questionnaire shared through mailing lists and social media channels. The findings indicate that, while 85.3% of the respondents were aware of the use of insects in human diet, only 12.5% had previously consumed edible insects. The results of the chi-square tests further revealed that both familiarity and experience significantly affected willingness to buy insect-based food, whereas age and educational attainment did not. Men were more open to purchasing edible insects than women. Twice as many participants (49.4%) responded positively to eating insect-based food in which insects were not visible than to consuming recognisable insects (25.4%). Crisis (shortage of conventional sources of protein), curiosity, nutrition, and health benefits were the most frequently chosen reasons for including insect-based products in a diet, whereas disgust was the main reason against. Multiple correspondence analysis resulted in two dimensions that accounted for the largest amount of variance. The first dimension referred to familiarity with entomophagy, experience of eating edible insects, and willingness to buy insect-based products, whereby sustainability, affordability, taste, nutrition, and curiosity were the reasons for including insect-based products in a diet, while high price was a reason against. The second dimension indicated lack of familiarity, experience, or willingness to buy, with crisis as the most common motivating reason, and the perception of insects as pests and socio-cultural unacceptance as the main reasons against. Although almost half of the respondents reported willingness to consume processed insect-based products, the actual acceptance is possibly lower. Therefore, future research should focus on the provision of tasting opportunities as well as information on the benefits associated with the production and consumption of insects.</p

Low-content quantification in powders using Raman spectroscopy: a facile chemometric approach to sub 0.1% limits of detection.

A robust and accurate analytical methodology for low-content (<0.1%) quantification in the solid-state using Raman spectroscopy, sub-sampling, and chemometrics was demonstrated using a piracetam–proline model. The method involved a 5-step process: collection of relatively large number of spectra (8410) from each sample by Raman mapping, meticulous data pretreatment to remove spectral artefacts, use of a 0–100% concentration range partial least squares (PLS) regression model to estimate concentration at each pixel, use of a more-accurate, reduced concentration range PLS model to accurately calculate analyte concentration at each pixel, and finally statistical analysis of all 8000+ concentration predictions to produce an accurate overall sample concentration. The relative prediction accuracy was ~2.4% for a 0.05~1.0% concentration range and the limit of detection was comparable to high performance liquid chromatography (0.03% versus 0.041%). For data pretreatment, we developed a unique cosmic ray removal method and used an automated baseline correction method, neither of which required subjective user intervention and thus were fully automatable. The method is applicable to systems, which cannot be easily analyzed chromatographically such as hydrate, polymorph, or solvate contamination.Research undertaken as part of the Synthesis and Solid State Pharmaceutical Centre, funded by Science Foundation Ireland and industry partners, and Enterprise Ireland (Grant No: TC- 2012-5106).2016-02-2