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Abstract Field‐based experiences enhance cognitive and affective skill sets of undergraduate students. Although field‐based learning is a highly effective pedagogical modality, it is not accessible to all students, necessitating the development and evaluation of alternate modalities that convey equivalent benefits. Virtual reality (VR) may allow students to engage in experiences without requiring them to be physically present within a field environment. Although VR is gaining popularity, there are limited examples of using it to simulate field experiences and of its efficacy in influencing student learning gains and attitudes toward environmental content. Therefore, we created immersive 360° cinematic VR (CVR) experiences focused on coastal marine ecosystems and compared them to traditional modalities: a field course and 2D videos focused on the same content. Students (n = 86) across science, technology, engineering, and mathematics (STEM) and non‐STEM majors from three institutions—Bentley University, Florida International University, and Louisiana Universities Marine Consortium—were given a preassessment/postassessment to understand learning gains and attitude changes related to each modality. Although significant learning gains happened across all modalities, CVR students experienced the greatest learning gains, though postscores were correlated with prescores and CVR students had lower prescores than field course students. There were no cross‐institutional or major‐related differences in learning gains for field course students. Students across all modalities experienced shifts in attitudes, with consistent increases in the use of keywords related to coastal marine ecosystems in postassessments. Ultimately, CVR is an effective supplement or alternative for undergraduate students who cannot access in‐person field‐based experiences and may be particularly impactful for non‐STEM majors. 

A seventh blind test of crystal structure prediction was organized by the Cambridge Crystallographic Data Centre featuring seven target systems of varying complexity: a silicon and iodine-containing molecule, a copper coordination complex, a near-rigid molecule, a cocrystal, a polymorphic small agrochemical, a highly flexible polymorphic drug candidate, and a polymorphic morpholine salt. In this first of two parts focusing on structure generation methods, many crystal structure prediction (CSP) methods performed well for the small but flexible agrochemical compound, successfully reproducing the experimentally observed crystal structures, while few groups were successful for the systems of higher complexity. A powder X-ray diffraction (PXRD) assisted exercise demonstrated the use of CSP in successfully determining a crystal structure from a low-quality PXRD pattern. The use of CSP in the prediction of likely cocrystal stoichiometry was also explored, demonstrating multiple possible approaches. Crystallographic disorder emerged as an important theme throughout the test as both a challenge for analysis and a major achievement where two groups blindly predicted the existence of disorder for the first time. Additionally, large-scale comparisons of the sets of predicted crystal structures also showed that some methods yield sets that largely contain the same crystal structures. 

A seventh blind test of crystal structure prediction has been organized by the Cambridge Crystallographic Data Centre. The results are presented in two parts, with this second part focusing on methods for ranking crystal structures in order of stability. The exercise involved standardized sets of structures seeded from a range of structure generation methods. Participants from 22 groups applied several periodic DFT-D methods, machine learned potentials, force fields derived from empirical data or quantum chemical calculations, and various combinations of the above. In addition, one non-energy-based scoring function was used. Results showed that periodic DFT-D methods overall agreed with experimental data within expected error margins, while one machine learned model, applying system-specific AIMnet potentials, agreed with experiment in many cases demonstrating promise as an efficient alternative to DFT-based methods. For target XXXII, a consensus was reached across periodic DFT methods, with consistently high predicted energies of experimental forms relative to the global minimum (above 4 kJ mol⁻¹at both low and ambient temperatures) suggesting a more stable polymorph is likely not yet observed. The calculation of free energies at ambient temperatures offered improvement of predictions only in some cases (for targets XXVII and XXXI). Several avenues for future research have been suggested, highlighting the need for greater efficiency considering the vast amounts of resources utilized in many cases. 

Large runoff, sediment, and nutrient exports from watersheds could occur due to individual extreme climate events or a combination of multiple hydrologic and meteorological conditions. Using high-frequency hydrologic, sediment, and turbidity data we show that freeze–thaw episodes followed by intense winter (February) rainstorms can export very high concentrations and loads of suspended sediment and particulate organic carbon (POC) and nitrogen (PN) from mid-Atlantic watersheds in the US. Peak suspended sediment (> 5000 mg L−1), POC (> 250 mg L−1) and PN (> 15 mg L−1) concentrations at our 12 and 79 ha forested watersheds for the February rainfall-runoff events were highest on record and the fluxes were comparable to those measured for tropical storms. Similar responses were observed for turbidity values (> 400 FNU) at larger USGS-monitored watersheds. Much of the sediments and particulate nutrients likely originated from erosion of stream bank sediments and/or channel storage. Currently, there is considerable uncertainty about the contribution of these sources to nonpoint source pollution, particularly, in watersheds with large legacy sediment deposits. Future climate projections indicate increased intensification of storm events and increased variability of winter temperatures. Freeze–thaw cycles coupled with winter rain events could increase erosion and transport of streambank sediments with detrimental consequences for water quality and health of downstream aquatic ecosystems. 

Abstract Strong spatial skills are foundational in predicting students' performance in science, technology, engineering, and mathematics education. Decades of research have considered the relationship between thinking spatially and how scientists reason and solve problems. However, few studies have examined the factors that influence improvement in students' spatial thinking during their school science curricula. The present study investigates theThinkSpacecurricula—two middle school astronomy units designed to support students' ability to apply the spatial skill of perspective‐taking (PT) while learning to explain lunar phases (3 days) and the seasons (8 days). U.S. students in 6th and 8th grades (N = 877) across four districts participated in the study, completing assessments before and after theThinkSpacecurricula, along with an additional group of students in 6th and 7th grades (N = 172) who participated as a spatial control group. Data collection included multiple‐choice content assessments, PT skill assessments, and interviews (from a sub‐sample of 96 students), before and after instruction. After participating inThinkSpacecurricula, students demonstrated improved spatial thinking within the domain of astronomy, as measured by improved written content assessments, increased application of PT during conceptual interviews, and a general measurement of PT skill. Higher initial PT skill and higher gain in PT skill predicted greater improvement in students' astronomy understanding, even when accounting for their initial content knowledge. AlthoughThinkSpacestudents in all demographic groups improved PT skill post‐instruction, 8th graders (who were in districts with lower SES), and females were predicted to have smaller gains in their PT skill than the 6th graders (who were in districts with higher SES) and male students. These findings suggest that middle school students' spatial thinking in science can be improved during their middle school science curricula, but questions remain concerning how to reduce spatial‐learning gaps that are associated with gender and possibly SES. 

In this paper, the history, present status, and future of density-functional theory (DFT) is informally reviewed and discussed by 70 workers in the field, including molecular scientists, materials scientists, method developers and practitioners. The format of the paper is that of a roundtable discussion, in which the participants express and exchange views on DFT in the form of 302 individual contributions, formulated as responses to a preset list of 26 questions. Supported by a bibliography of 777 entries, the paper represents a broad snapshot of DFT, anno 2022.