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While K-12 schools are increasingly adopting Artificial Intelligence (AI)-powered learning environments to provide dynamic support and enhance student engagement, the integration of advanced AI applications in specific domains remains uneven. Generative design, an innovative approach in design and engineering that leverages AI and computational power to explore and generate multiple design solutions, has gained traction in the engineering design field. However, integrating generative design into the teaching and learning of engineering design remains a relatively unexplored area. This study introduces an instructional model guiding the integration of generative design into students’ engineering design processes. We validated this model through an AI-powered engineering design curriculum, which involved a total of 109 students from two suburban high schools in the Midwestern United States. Results revealed significant increases in students’ perceived engineering design knowledge, actual engineering design knowledge, and confidence in iterative design. Additionally, students acknowledged the benefits of generative design following their engagement with the curriculum. Nonetheless, concerns emerged regarding the ease of use and students’ comfort levels in utilizing generative design. This study presents implications for STEM research and practice, particularly regarding integrating generative design into K-12 classroom settings for engineering design processes. Furthermore, it offers insights for researchers aiming to optimize AI-powered learning environments. 

Self-regulation is crucial for student success in scientific inquiry and engineering design. However, it remains unclear how students dynamically engage in self-regulated learning (SRL) processes to achieve high performance. In this study, we investigated the temporal nature of self-regulation during engineering design by leveraging computer trace data from 101 high school students who designed an energy-plus house in a simulated learning environment. Using sequential mining, we found that high-performing students were more engaged in the Observation, Analysis, and Evaluation phases of SRL than low-performing students. Additionally, high-performing students demonstrated consecutive sequential patterns between Observation and Analysis, Reformation and Evaluation, and Analysis and Evaluation behaviors. These findings provide insights into students’ SRL processes and the design of scaffoldings. 

The Engaging Communities in Developing Technologies to Support Community Flourishing workshop was held in response to the NSF CRISES program call. The workshop explored integrating methods from community-based participatory research (CBPR) and computational social science (CSS) to advance social science research surrounding barriers to community flourishing with a focus on how emerging technologies should be designed and engaged. In this paper, we provide a brief report of the workshop and preliminary outcomes related to a roadmap for integrating CBPR and CSS approaches. We end with a call to the CSSSA community to intentionally move toward incorporating best practices from CBPR where appropriate to advance the value and impact of research on social issues affecting communities. 

Oxidation of the sub-arc mantle driven by slab-derived fluids has been hypothesized to contribute to the formation of gold deposits in magmatic arc environments that host the majority of metal resources on Earth. However, the mechanism by which the infiltration of slab-derived fluids into the mantle wedge changes its oxidation state and affects Au enrichment remains poorly understood. Here, we present the results of a numerical model that demonstrates that slab-derived fluids introduce large amounts of sulfate (S⁶⁺) into the overlying mantle wedge that increase its oxygen fugacity by up to 3 to 4 log units relative to the pristine mantle. Our model predicts that as much as 1 wt.% of the total dissolved sulfur in slab-derived fluids reacting with mantle rocks is present as the trisulfur radical ion, S₃^–. This sulfur ligand stabilizes the aqueous Au(HS)S₃^–complex, which can transport Au concentrations of several grams per cubic meter of fluid. Such concentrations are more than three orders of magnitude higher than the average abundance of Au in the mantle. Our data thus demonstrate that an aqueous fluid phase can extract 10 to 100 times more Au than in a fluid-absent rock-melt system during mantle partial melting at redox conditions close to the sulfide-sulfate boundary. We conclude that oxidation by slab-derived fluids is the primary cause of Au mobility and enrichment in the mantle wedge and that aqueous fluid-assisted mantle melting is a prerequisite for formation of Au-rich magmatic hydrothermal and orogenic gold systems in subduction zone settings. 

Abstract This study explores the Antarctic sea ice concentration (SIC) response to multiyear (MY) and single-year (SY) El Niños using a 2200-yr CESM1 preindustrial simulation. During the first austral winter, MY El Niño weakens the amplitude of the typical SIC anomaly pattern induced by SY El Niño but maintains the same impact pattern. During the second winter, MY El Niños not only intensify the amplitude but also shift the typical impact pattern of SY El Niños eastward. The amplitude variation effect on SIC is caused by an Indian Ocean memory mechanism, while the zonal shifting effect on SIC pattern is caused by an Atlantic Ocean memory mechanism. These mechanisms result from the different responses of the two oceans to different locations and intensities between SY and MY El Niños. Observed MY El Niños during 1979–2020 confirm the distinct impacts during the second austral winter revealed by the CESM1 simulation. These results demonstrate that SIC in the Ross and Amundsen–Bellingshausen–Weddell Seas is sensitive to the SY or MY types of El Niño. 

Described herein are the synthesis, structure, and photophysics of the iodo-substituted cyclic trinuclear copper( i ) complex, Cu 3 [4-I-3,5-(CF 3 ) 2 Pz] 3 supported by a highly-fluorinated pyrazolate in comparison with its previously reported 4-Br/4-Cl analogues. The crystal structure is stabilised by multiple supramolecular interactions of Cu 3 ⋯I and hydrogen/halogen bonding. The photophysical properties and supramolecular interactions are investigated experimentally/computationally for all three 4-halo complexes vis-à-vis relativistic effects. 

Abstract Twisted moiré photonic crystal is an optical analog of twisted graphene or twisted transition metal dichalcogenide bilayers. In this paper, we report the fabrication of twisted moiré photonic crystals and randomized moiré photonic crystals and their use in enhanced extraction of light in light-emitting diodes (LEDs). Fractional diffraction orders from randomized moiré photonic crystals are more uniform than those from moiré photonic crystals. Extraction efficiencies of 76.5%, 77.8% and 79.5% into glass substrate are predicted in simulations of LED patterned with twisted moiré photonic crystals, defect-containing photonic crystals and random moiré photonic crystals, respectively, at 584 nm. Extraction efficiencies of optically pumped LEDs with 2D perovskite (BA)₂(MA)_n−1Pb_nI_3n+1ofn= 3 and (5-(2′-pyridyl)-tetrazolato)(3-CF₃−5-(2′-pyridyl)pyrazolato) platinum(II) (PtD) have been measured.