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The Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) field campaign provides accurate data for aerosol characterization and trace gas profiles, and establishes knowledge of the relationships between aerosols and water. The dropsonde dataset provides anin situcharacterization of the vertical thermodynamic structure of the atmosphere during 165 research flights by NASA Langley’s King Air research aircraft between February 2020 and June 2022 and four test flights between December 2019 and November 2021. The research flights covered the western North Atlantic region, off the coast of the Eastern United States and around Bermuda and covered all seasons. The dropsonde profiles provide observations of temperature, pressure, relative humidity, and horizontal and vertical winds between the surface and about 9 km. 801 dropsondes were released, of which 796 were processed and 788 provide complete profiles of all parameters between the flight level and the surface with normal parachute performance. Here, we describe the dataset, the processing of the measurements, general statistics, and applications of this rich dataset.

 

High entropy alloy (HEA) nanoparticles hold promise as active and durable (electro)catalysts. Understanding their formation mechanism will enable rational control over composition and atomic arrangement of multimetallic catalytic surface sites to maximize their activity. While prior reports have attributed HEA nanoparticle formation to nucleation and growth, there is a dearth of detailed mechanistic investigations. Here we utilize liquid phase transmission electron microscopy (LPTEM), systematic synthesis, and mass spectrometry (MS) to demonstrate that HEA nanoparticles form by aggregation of metal cluster intermediates. AuAgCuPtPd HEA nanoparticles are synthesized by aqueous co-reduction of metal salts with sodium borohydride in the presence of thiolated polymer ligands. Varying the metal : ligand ratio during synthesis showed that alloyed HEA nanoparticles formed only above a threshold ligand concentration. Interestingly, stable single metal atoms and sub-nanometer clusters are observed by TEM and MS in the final HEA nanoparticle solution, suggesting nucleation and growth is not the dominant mechanism. Increasing supersaturation ratio increased particle size, which together with observations of stable single metal atoms and clusters, supported an aggregative growth mechanism. Direct real-time observation with LPTEM imaging showed aggregation of HEA nanoparticles during synthesis. Quantitative analyses of the nanoparticle growth kinetics and particle size distribution from LPTEM movies were consistent with a theoretical model for aggregative growth. Taken together, these results are consistent with a reaction mechanism involving rapid reduction of metal ions into sub-nanometer clusters followed by cluster aggregation driven by borohydride ion induced thiol ligand desorption. This work demonstrates the importance of cluster species as potential synthetic handles for rational control over HEA nanoparticle atomic structure. 

The importance of diversifying the national STEM workforce is well-established in the literature (Marrongelle, 2018). This need extends to graduate education in the STEM fields, leading N.C. A&T to invest considerably in graduate education and wraparound support initiatives that help graduate students build science identity and competencies for careers both within and beyond academia. The NSF-funded Bridges to the Doctorate project will integrate culturally reflective mentoring and professional development specifically designed for Black, Latinx, and Native American Ph.D. students. This holistic, graduate student development model includes academic and professional skill-building for STEM careers alongside targeted support for pursuing fellowship opportunities. This paper discusses the planned mentoring approach for the aforementioned program and previous approaches to mentoring graduate students used at N.C. A&T. The BD Fellows program will support formal and informal mentoring relationships, as mentoring contributes towards retention in STEM graduate programs (Ragins, 2007). BD Fellows will participate in monthly one-hour seminars on how to identify, establish, and maintain informal mentoring relationships (Schwartz et al., 2018; Parnes et al., 2020), while STEM faculty will attend seminars on leveraging their social networks as vital sources of mentorship for the BD Fellows. Using a multi-pronged collaborative approach, this model integrates the evidence-based domains of self-efficacy (Laurencelle & Scanlan, 2018; Lent et al., 1994; Lent et al., 2008), science/research identity (Lent et al., 2015; Zimmerman, 2000), and social cognitive career theory (Lent et al., 2005; Lent and Brown, 2006) to recruit, enroll, and graduate LSAMP Fellows with STEM doctoral degrees. Guided by the theories, the following questions will be addressed: (1) To what extent is culturally reflective mentoring identified as a critical driver of B2D Fellows’ success? (2) To what extent are the program’s training components fostering increases in B2D Fellow’s self-efficacy, competency, and science identity? (3) What is the strength of the correlation between participation in the program training components, mentoring activities, and persistence in graduate school? (4) To what extent does the perceived importance of self-efficacy, competency, and science identity differ by race/ethnicity and gender? These data will be analyzed using both formative and summative assessments of program outcomes. Quantitative data will include pre-, post-, and exit surveys. Qualitative data will assess the impact of mentoring and program support. This study will be guided by established protocols that have been approved by the N.C. A&T IRB. It is anticipated that our BD Fellows program will significantly impact the retention and graduation rates of underrepresented minority STEM graduate students in our doctoral programs, thus producing a diverse workforce of STEM professionals. Materials from the program recruiting cycle, mentoring workshops, and the structured fellowship application process will be disseminated freely to other LSAMP and minority-serving institutions across the country. Strategies and outcomes of this project will be published in peer-reviewed journals and shared in conference proceedings. 

Granulomas often form around pathogens that cause chronic infections. Here, we discover an innate granuloma model in mice with an environmental bacterium calledChromobacterium violaceum. Granuloma formation not only successfully walls off, but also clears, the infection. The infected lesion can arise from a single bacterium that replicates despite the presence of a neutrophil swarm. Bacterial replication ceases when macrophages organize around the infection and form a granuloma. This granuloma response is accomplished independently of adaptive immunity that is typically required to organize granulomas. TheC. violaceum-induced granuloma requires at least two separate defense pathways, gasdermin D and iNOS, to maintain the integrity of the granuloma architecture. This innate granuloma successfully eradicatesC. violaceuminfection. Therefore, thisC. violaceum-induced granuloma model demonstrates that innate immune cells successfully organize a granuloma and thereby resolve infection by an environmental pathogen.

 

Deprotonated azabenzene anions require dipole moments in their corresponding neutral radicals of more than 3.5 D in order to exhibit dipole-bound excited states (DBXSs). This is notably larger than the typical 2.0–2.5 D associated with such behavior. Similar computational analysis on deprotonated purine derivatives also conducted herein only requires the more traditional 2.5 D dipole moment, implying that the single six-membered azabenzene rings have additional factors at play in binding diffuse electrons. The present study also shows that the use of coupled cluster singles and doubles with a double-zeta correlation consistent basis set and additional diffuse functions originating from the center-of-charge for all aspects of the computations decreases the error in predicting DBXSs to less than 0.006 eV at worst and likely less than 0.003 eV for most cases. These results can influence the modeling of molecular spectra beyond fundamental chemical curiosity with application to astrochemistry, solar energy harvesting, and combustion chemistry among others.