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Demographic data collection is essential in education research, as demographic data allows researchers to better describe the participant population they study and to contextualize findings. However, current research practices for neurodiversity demographics often rely on prescriptive methods (e.g., requiring participants to report official diagnoses) rather than allowing participants to self-identify. This approach can: a) not allow participants to express their intersecting identities in ways that are authentic; and b) limit trustworthiness and reliability of the data and interpretation. In addition, inconsistent dissemination and representation of demographic data across studies hinder the accessibility and usability of this work. Through a literature review of neurodivergent student experiences with learning and performing STEM, we identified widespread discrepancies in how demographic information is collected and reported. This paper explores how neurodivergent identities can be more accurately and inclusively represented in education research. We present findings of a thematic analysis on the ways neurodivergent demographic data collection is done in the literature using data from a systematic literature review on neurodivergent science, technology, engineering, and mathematics (STEM) learning and performance. We call on the PER community to contribute to the development of a framework that centers participant autonomy while supporting clarity, consistency, and future research use. 

Heterogeneous catalysis offers opportunities to enhance valorization of plastic waste via chemical recycling through control of the upcycled product distributions. Minimizing low-value light hydrocarbons is desired; however, fundamental insights into how to control selectivity are lacking. Here we use contrast variation with small-angle neutron scattering (SANS), model perdeuterated polyethylenes (dPEs), and a model liquid hydrocracking product (tetradecane) to quantify polymer partitioning within mesoporous silica (SBA-15). Polyethylene concentration within the mesopores is increased relative to the bulk solution, and this partitioning increases as the temperature increases. However, this polyethylene partitioning is maximized when the radius of gyration of the polymer chains is comparable to the SBA-15 pore size (10 nm). An increased partitioning at higher temperatures is attributed to entropically driven adsorption of PE within the mesopores. There is no observed preferential partitioning of hexatriacontane (a model oligomer) within the mesopores at the temperatures examined. These results suggest that pore size could promote the selective partitioning of polymer species into the mesopores by size. For plastic upcycling, pore-size-dependent partitioning should increase the probability for the reaction of long polymers over oligomeric and small-molecule polyolefin depolymerization products. 

Polyolefins, which dominate the plastics marketplace, require high-temperature size exclusion chromatography (HT-SEC) to characterize their molar masses. Chemical recycling methods designed to deconstruct plastic waste into smaller molecules (i.e., depolymerization methods) rely on HT-SEC to characterize their products, but depolymerization methods often yield a complex mixture, including components below the typical separation range of commercial HT-SEC columns. Herein, we report the accuracy and limitations of triple detection HT-SEC to analyze model chemical recycling products. We examined the chromatographic separation and quantification of individual components and mixtures of short polyethylenes (apparent Mn = 465 and 2722 g/mol), hexatriacontane (C36H74, M = 507 g/mol), dotriacontane (C32H66, M = 451 g/mol), and octadecane (C18H38, M = 254 g/mol). Despite short alkanes exhibiting molar masses below the lower molar mass limit of the columns (500 g/mol), the separation of their mixtures was resolved via refractive index (RI) detection. However, the determined molar masses of these alkane mixtures did not agree with the known molar masses of the short alkanes or their prepared mixtures. Similarly, the SEC analysis of mixtures containing discrete alkanes with low molar mass PE revealed that their individual components are easily resolved in the HT-SEC chromatogram. No obvious shift in the elution volume of the blend components versus the elution volume of the pure components was observed. However, inaccurate molar masses and molar mass distributions for these alkane-PE mixtures are calculated from the HT-SEC data. These inaccuracies are attributable to two factors: (1) molar mass-dependent ∂n/∂c for low molar mass components and (2) the small size of the molecules in solution that limits light scattering. These results highlight the importance of considering measurement limitations for quantitative interpretation of triple detection HT-SEC data obtained from chemical recycling and depolymerization experiments that commonly contain complex mixtures of polymeric, oligomeric, and small molecule alkanes. 

A stepwise copper‐catalyzed boracarboxylation then palladium‐catalyzed Suzuki‐Miyaura cross‐coupling methodology was developed to access 2,3‐diarylpropionic acid derivatives regioselectively by pre‐setting the position of the carboxylic acid in the boracarboxylation reaction. This method provides access to a wide range of aryl and heteroaryl products in up to 80% isolated yield. Pharmaceutical potential was demonstrated by synthesizing a glucagon receptor antagonist drug in three steps (31% overall yield) from commercially available 4‐tert‐butylstyrene. 

Sub-cloud rain evaporation in the trade wind region significantly influences the boundary layer mass and energy budgets. Parameterizing it is, however, difficult due to the sparsity of well-resolved rain observations and the challenges of sampling short-lived marine cumulus clouds. In this study, sub-cloud rain evaporation is analyzed using a steady-state, one-dimensional model that simulates changes in drop sizes, relative humidity, and rain isotopic composition. The model is initialized with relative humidity, raindrop size distributions, and water vapor isotope ratios (e.g., δDv, δ18Ov) sampled by the NOAA P3 aircraft during the Atlantic Tradewind Ocean–Atmosphere Mesoscale Interaction Campaign (ATOMIC), which was part of the larger EUREC4A (ElUcidating the RolE of Clouds–Circulation Coupling in ClimAte) field program. The modeled surface precipitation isotope ratios closely match the observations from EUREC4A ground-based and ship-based platforms, lending credibility to our model. The model suggests that 63 % of the rain mass evaporates in the sub-cloud layer across 22 P3 cases. The vertical distribution of the evaporated rain flux is top heavy for a narrow (σ) raindrop size distribution (RSD) centered over a small geometric mean diameter (Dg) at the cloud base. A top-heavy profile has a higher rain-evaporated fraction (REF) and larger changes in the rain deuterium excess (d=δD-8×δ18O) between the cloud base and the surface than a bottom-heavy profile, which results from a wider RSD with larger Dg. The modeled REF and change in d are also more strongly influenced by cloud base Dg and σ rather than the concentration of raindrops. The model results are accurate as long as the variations in the relative humidity conditions are accounted for. Relative humidity alone, however, is a poor indicator of sub-cloud rain evaporation. Overall, our analysis indicates the intricate dependence of sub-cloud rain evaporation on both thermodynamic and microphysical processes in the trade wind region. 

This study is an exploratory comparison of 69 Hispanic students enrolled in first-semester general chemistry (Chem I) who attended either a Hispanic-Serving or emerging Hispanic-Serving Institution and were not successful in Chem I. Students’ automaticity skills (what can be done without the aid of a calculator) in arithmetic and quantitative reasoning were analyzed based on students’ personal characteristics such as gender, prior knowledge in chemistry and mathematics, entry college (i.e., STEM or not), and parents’ academic background. Findings indicate that without basic automaticity skills, students enter Chem I at a deficit, but these at-risk students can be identified early in the semester to help them succeed. Results also indicate that arithmetic automaticity is more influential than quantitative reasoning in predicting academic success. A suggested high-impact practice is presented as a possible correction for these deficits. 

Isocyanoazulenes (CNAz) constitute a relatively new class of isocyanoarenes that offers rich structural and electronic diversification of the organic isocyanide ligand platform. This article considers a series of 2-isocyano-1,3-X2-azulene ligands (X = H, Me, CO2Et, Br, and CN) and the corresponding zero-valent complexes thereof, [(OC)5Cr(2-isocyano-1,3-X2-azulene)]. Air- and thermally stable, X-ray structurally characterized 2-isocyano-1,3-dimethylazulene may be viewed as a non-benzenoid aromatic congener of 2,6-dimethyphenyl isocyanide (2,6-xylyl isocyanide), a longtime “workhorse” aryl isocyanide ligand in coordination chemistry. Single crystal X-ray crystallographic {Cr–CNAz bond distances}, cyclic voltametric {E1/2(Cr0/1+)}, 13C NMR {δ(13CN), δ(13CO)}, UV-vis {dπ(Cr) → pπ*(CNAz) Metal-to-Ligand Charge Transfer}, and FTIR {νN≡C, νC≡O, kC≡O} analyses of the [(OC)5Cr(2-isocyano-1,3-X2-azulene)] complexes provided a multifaceted, quantitative assessment of the π-acceptor/σ-donor characteristics of the above five 2-isocyanoazulenes. In particular, the following inverse linear relationships were documented: δ(13COtrans) vs. δ(13CN), δ(13COcis) vs. δ(13CN), and δ(13COtrans) vs. kC≡O,trans force constant. Remarkably, the net electron withdrawing capability of the 2-isocyano-1,3-dicyanoazulene ligand rivals those of perfluorinated isocyanides CNC6F5 and CNC2F3.