Electric winds driven by time oscillating corona discharges

We investigate the formation of steady gas flows—so-called electric winds—created by point-plane corona discharges driven by time oscillating (ac) electric fields. By varying the magnitude and frequency of the applied field, we identify two distinct scaling regimes: (i) a low frequency (dc) regime and (ii) a high frequency (ac) regime. These experimental observations are reproduced and explained by a theoretical model describing the transport and recombination of ions surrounding the discharge and their contribution to the measured wind velocity. The two regimes differ in the spatial distribution of ions and in the process by which ions are consumed. Interestingly, we find that ac corona discharges generate strong electric forces localized near the tip of the point electrode, while dc corona discharges generate weaker forces distributed throughout the interelectrode region. Consequently, the velocity of the electric winds (>1 m/s) generated by ac discharges is largely independent of the position of the counter electrode. The unified theoretical description of dc and ac electric winds presented here reconciles previous observations of winds driven by dc corona and ac dielectric barrier discharges; insights from the model should also prove useful in the design of other plasma actuators.Chemistry and Chemical Biolog

AC Electric Fields Drive Steady Flows in Flames

We show that time-oscillating electric fields applied to plasmas present in flames create steady flows of gas. Ions generated within the flame move in the field and migrate a distance δ before recombining; the net flow of ions away from the flame creates a time-averaged force that drives the steady flows observed experimentally. A quantitative model describes the response of the flame and reveals how δ decreases as the frequency of the applied field increases. Interestingly, above a critical frequency, ac fields can be used to manipulate flames at a distance without the need for proximal electrodes.Chemistry and Chemical BiologyEngineering and Applied Science

Misrepresentation and Nonadherence Regarding COVID-19 Public Health Measures

IMPORTANCE: The effectiveness of public health measures implemented to mitigate the spread and impact of SARS-CoV-2 relies heavily on honesty and adherence from the general public. OBJECTIVE: To examine the frequency of, reasons for, and factors associated with misrepresentation and nonadherence regarding COVID-19 public health measures. DESIGN, SETTING, AND PARTICIPANTS: This survey study recruited a national, nonprobability sample of US adults to participate in an online survey using Qualtrics online panels (participation rate, 1811 of 2260 [80.1%]) from December 8 to 23, 2021. The survey contained screening questions to allow for a targeted sample of one-third who had had COVID-19, one-third who had not had COVID-19 and were vaccinated, and one-third who had not had COVID-19 and were unvaccinated. MAIN OUTCOME MEASURES: The survey assessed 9 different types of misrepresentation and nonadherence related to COVID-19 public health measures and the reasons underlying such behaviors. Additional questions measured COVID-19–related beliefs and behaviors and demographic characteristics. RESULTS: The final sample included 1733 participants. The mean (SD) participant age was 41 (15) years and the sample predominantly identified as female (1143 of 1732 [66.0%]) and non-Hispanic White (1151 of 1733 [66.4%]). Seven hundred twenty-one participants (41.6%) reported misrepresentation and/or nonadherence in at least 1 of the 9 items; telling someone they were with or about to be with in person that they were taking more COVID-19 preventive measures than they actually were (420 of 1726 [24.3%]) and breaking quarantine rules (190 of 845 [22.5%]) were the most common manifestations. The most commonly endorsed reasons included wanting life to feel normal and wanting to exercise personal freedom. All age groups younger than 60 years (eg, odds ratio for those aged 18-29 years, 4.87 [95% CI, 3.27-7.34]) and those who had greater distrust in science (odds ratio, 1.14 [95% CI, 1.05-1.23]) had significantly higher odds of misrepresentation and/or nonadherence for at least 1 of the 9 items. CONCLUSIONS: In this survey study of US adults, nearly half of participants reported misrepresentation and/or nonadherence regarding public health measures against COVID-19. Future work is needed to examine strategies for communicating the consequences of misrepresentation and nonadherence and to address contributing factors

Quantitative trait loci for sensitivity to ethanol intoxication in a C57BL/6J × 129S1/SvImJ inbred mouse cross

Individual variation in sensitivity to acute ethanol (EtOH) challenge is associated with alcohol drinking and is a predictor of alcohol abuse. Previous studies have shown that the C57BL/6J (B6) and 129S1/SvImJ (S1) inbred mouse strains differ in responses on certain measures of acute EtOH intoxication. To gain insight into genetic factors contributing to these differences, we performed quantitative trait locus (QTL) analysis of measures of EtOH-induced ataxia (accelerating rotarod), hypothermia, and loss of righting reflex (LORR) duration in a B6 × S1 F2 population. We confirmed that S1 showed greater EtOH-induced hypothermia (specifically at a high dose) and longer LORR compared to B6. QTL analysis revealed several additive and interacting loci for various phenotypes, as well as examples of genotype interactions with sex. QTLs for different EtOH phenotypes were largely non-overlapping, suggesting separable genetic influences on these behaviors. The most compelling main-effect QTLs were for hypothermia on chromosome 16 and for LORR on chromosomes 4 and 6. Several QTLs overlapped with loci repeatedly linked to EtOH drinking in previous mouse studies. The architecture of the traits we examined was complex but clearly amenable to dissection in future studies. Using integrative genomics strategies, plausible functional and positional candidates may be found. Uncovering candidate genes associated with variation in these phenotypes in this population could ultimately shed light on genetic factors underlying sensitivity to EtOH intoxication and risk for alcoholism in humans

Contact Charge Electrophoresis: Experiment and Theory

Contact charge electrophoresis (CCEP) uses steady electric fields to drive the continuous, oscillatory motion of conductive particles and droplets between two or more electrodes. These rapid oscillations can be rectified to direct the motion of objects within microfluidic environments using low-power, dc voltage. Here, we compare high precision experimental measurements of CCEP within a microfluidic system to equally detailed theoretical predictions on the motion of a conductive particle between parallel electrodes. We use a simple, capillary microfluidic platform that combines high-speed imaging with precision electrical measurements to enable the synchronized acquisition of both the particle location and the electric current due to particle motion. The experimental results are compared to those of a theoretical model, which relies on a Stokesian dynamics approach to accurately describe both the electrostatic and hydrodynamic problems governing particle motion. We find remarkable agreement between theory and experiment, suggesting that particle motion can be accurately captured by a combination of classical electrostatics and low-Reynolds number hydrodynamics. Building on this agreement, we offer new insight into the charge transfer process that occurs when the particle nears contact with an electrode surface. In particular, we find that the particle does not make mechanical contact with the electrode but rather that charge transfer occurs at finite surface separations of >0.1 μm by means of an electric discharge through a thin lubricating film. We discuss the implications of these findings on the charging of the particle and its subsequent dynamics

Self-Assembly of Nanoparticle Amphiphiles with Adaptive Surface Chemistry

We investigate the self-assembly of amphiphilic nanoparticles (NPs) functionalized with mixed monolayers of hydrophobic and hydrophilic ligands in water. Unlike typical amphiphilic particles with “fixed” surface chemistries, the ligands used here are not bound irreversibly but can rearrange dynamically on the particles’ surface during their assembly from solution. Depending on the assembly conditions, these adaptive amphiphiles form compact micellar clusters or extended chain-like assemblies in aqueous solution. By controlling the amount of hydrophobic ligands on the particles’ surface, the average number of nearest neighborsthat is, the preferred coordination numbercan be varied systematically from ∼1 (dimers) to ∼2 (linear chains) to ∼3 (extended clusters). To explain these experimental findings, we present an assembly mechanism in which hydrophobic ligands organize dynamically to form discrete patches between proximal NPs to minimize contact with their aqueous surroundings. Monte Carlo simulations incorporating these adaptive hydrophobic interactions reproduce the three-dimensional assemblies observed in experiment. These results suggest a general strategy based on reconfigurable “sticky” patches that may allow for tunable control over particle coordination number within self-assembled structures

Impact of prior COVID-19 infection on perceptions about the benefit and safety of COVID-19 vaccines

In this online survey of 1,733 US adults in December-2021, respondents believed COVID-19 vaccines are less beneficial and less safe for someone who had already had COVID-19. Those who experienced COVID-19 after being vaccinated believed that the vaccines are less beneficial and less safe than those who had not. Findings highlight the need to better communicate evolving evidence of COVID-19 vaccine benefit and safety and to tailor communications to peoples’ COVID-19 history and vaccination status

Parallel Optimization of Synthetic Pathways within the Network of Organic Chemistry

Finding a needle in a haystack : The number of possible synthetic pathways leading to the desired target of a synthesis can be astronomical (1019 within five synthetic steps). Algorithms are described that navigate through the entire known chemical???synthetic knowledge to identify optimal synthetic pathways. Examples are provided to illustrate single???target optimization and parallel optimization of syntheses leading to multiple targets