Virtual reality (VR) has emerged as a promising tool for transforming science, technology, engineering, and mathematics (STEM) education, yet its adoption in K–12 classrooms remains uneven and often limited to short-term pilots. While prior studies highlight VR’s potential to increase engagement and support conceptual understanding, questions persist about scalability, sustainability, and equity in implementation. This paper addresses these gaps by synthesizing recent scholarship and proposing a structured framework of best practices for integrating VR into K–12 STEM education. Drawing on academic literature, U.S. policy reports, and case studies, we identify persistent challenges that include high costs, lack of teacher preparation, infrastructure disparities, and overlooked accessibility concerns. We use these findings to inform a phased implementation roadmap. Our framework emphasizes assessment and planning, technical integration, teacher preparation, student implementation, and iterative evaluation, providing actionable strategies for schools and districts. Results of this synthesis indicate that successful VR adoption requires coordinated attention to pedagogy, funding, professional development, and equity. We conclude that moving VR from isolated novelty projects to sustainable and equitable tools in STEM classrooms depends on aligning technology with curricular goals, investing in teacher pipelines, and embedding VR within long-term evaluation and improvement cycles.

The presence of silica in iron ore concentrate can have significant negative impacts on the efficiency and quality of steel production. As such, providing engineers with early and reliable information about the purity of iron ore concentrate is crucial for smooth mining operations. This paper reports on the development of a long short-term memory (LSTM) network and an ensemble data interpolation technique to enhance quality prediction in the froth flotation process of an iron ore mine. Our results demonstrate the ability of our model to accurately predict the silica content of iron ore concentrate on a minute-by-minute basis, as well as the ability to forecast hours in advance.

Aldehydes are major intermediates in oxidation and pyrolysis of hydrocarbons and particularly biofuels. While the high temperature oxidation chemistry of C₃-C₅ aldehydes have been studied in the literature, a comprehensive low temperature kinetics remains unaddressed. In this work, acetaldehyde, propanal, and 2-propenal (acrolein) oxidation was investigated at low-temperature combustion condition (500–700 K). The isomer specific products concentrations as well as the time-resolved profiles were studied using Sandia’s multiplexed photoionization mass spectroscopy (MPIMS) with synchrotron radiation from the Advanced Light Source (ALS). The laser pulsed photolysis generates chlorine atoms which react with aldehydes to form the parent radicals. In the presence of excess oxygen, these radicals react with O₂ and form RO₂ radicals. The temperature dependent products yields are determined for 500 K to 700 K and the competition between the channels contributing to the formation of each product is discussed. In acetaldehyde oxidation, the formation of the main products are associated with HO₂ elimination channel from QOOH or direct H atom elimination from the parent radicals. In propanal oxidation, the most intensive signal peak was associated with acetaldehyde (m/z=44) which was formed through the reaction of α′-R with O₂. α′-RO₂ intermediate decomposes to acetaldehyde+OH+CO via Waddington mechanism and formation of five-member ring transition state. In 2-propenal oxidation, the unsaturated radical produced from α-R reacts with O₂ to form the primary products.