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U.S. graduate engineering programs traditionally follow a “one-size-fits-all” approach that prioritizes research skills, is slow to adapt to industry trends, and defaults to training students for academic careers. Further, these programs implicitly assume that students start at the same knowledge level, disregarding differences in educational preparation and students’ backgrounds, including socioeconomic and sociocultural factors, prior work experience, and professional development. Through a National Science Foundation Innovations in Graduate Education award, the University of Pittsburgh Swanson School of Engineering is creating and validating a five-component personalized learning model (PLM) for graduate education within the Department of Chemical and Petroleum Engineering. This model, designed around the students' self-identified goals, aims to modernize graduate STEM education through a student-centered approach, advancing existing knowledge on the relationship between personalized learning and student outcomes. The first three components provide an intentional approach to learning: Instructional Goals developed for each student based on a learner profile and individual development plans (IDP), a purposeful Task Environment that breaks the traditional three-credit coursework into modules and co-curricular professional development streams, and a persistent approach to Scaffolding Instruction that leads to students’ mastery. The last two components provide feedback and reflection: Assessment of Performance Learning and Reflection and Evaluation. This paper reports on the methodology, results, and application of work conducted on the second component of the model, the Task Environment. This component purposefully breaks the traditional three-credit coursework into single-credit classes, specifically one-credit fast-paced fundamentals review, one-credit graduate-level core content, and one-credit graduate-level specialized content. This change provides a flexible and personalized learning experience. It enables students to customize their education to fit program requirements and align with their interests, thus allowing students to have agency on the breadth and depth of their intellectual development. To create the modularized curriculum, we initiated a collaborative process that leveraged the collective expertise of our chemical engineering faculty and external subject matter experts (SMEs), including chemical engineers from industry, government, academia, and start-ups. Starting with our faculty's existing learning objectives from each core course, we employed GroupWisdom group concept mapping software to (1) brainstorm on additional graduate-level chemical engineering learning objectives, (2) group the learning objectives into one of three levels: fundamental, graduate core, and specialized topics for each course topic, and (3) rate the importance of each learning objective. The multi-session group concept mapping technique leveraged 25 SMEs. Two sets of learning objectives were produced. The first was a prioritized set of learning outcomes for each content area organized according to the three levels. The second set comprised learning outcomes necessary for graduate students to be successful post-graduation, including technical and non-technical learning objectives. For the first set, faculty have formed a learning community to interpret the results and collectively work on restructuring course content and pedagogy. For the second set, the same SMEs rated the importance of each learning objective, which informed the priority of incorporation into the revised curriculum. 

Despite calls over the past two decades to develop and deploy graduate STEM education models that prepare students for a variety of careers outside of academia, few innovations have emerged to meet students at their current skill and preparation levels when entering their graduate studies while also considering students’ individual desired career paths. The U.S.’s current approach to graduate STEM education does not emphasize preparing students with the professional skills and experience outside the lab. Further, students from differing socioeconomic and underserved backgrounds are often not adequately supported. Through a National Science Foundation Innovations in Graduate Education (IGE) award, the University of Pittsburgh Swanson School of Engineering is creating and validating a personalized learning model (PLM) for graduate education within the Department of Chemical and Petroleum Engineering. The goal of this model is to transform and modernize graduate STEM education through a personalized, inclusive, and student-centered approach, which will, in turn, advance existing knowledge on the relationship between personalized learning and student outcomes. The principles of personalized learning guide the PLM. The PLM is comprised of five components. The first three components provide an intentional approach to learning: Instructional Goals developed for each student based on a learner profile and individual development plans (IDP), a purposeful Task Environment that breaks the traditional three-credit coursework into modules and co-curricular professional development streams, and a resolute approach to Scaffolding Instruction that leads to mastery in the student’s area of focus. The last two components provide feedback and reflection: Assessment of Performance Learning quantifies students’ progress, and Reflection and Evaluation, where improvement opportunities help the student to develop further. Incorporating personalization at every touchpoint of a graduate student’s academic journey creates an authentic, customized, student-centered approach to graduate education. This paper describes in detail the model and the literature behind its development, along with assessments used to guide students. 

CuZrO 3 has been hypothesized to be a catalytic material with potential applications for CO 2 reduction. Unfortunately, this material has received limited attention in the literature, and to the best of our knowledge the exact crystal structure is still unknown. To address this challenge, we utilize several different structural prediction techniques in concert, including the Universal Structure Predictor: Evolutionary Xtallography (USPEX), the Materials Project Structure Predictor, and the Open Quantum Materials Database (OQMD). Leveraging these structural prediction techniques in conjunction with Density-Functional Theory (DFT) calculations, we determine a possible structure for CuZrO 3 , which resembles a “sandwich” morphology. Our calculations reveal that this new structure is significantly lower in energy than a previously hypothesized perovskite structure, albeit it still has a thermodynamic preference to decompose into CuO and ZrO 2 . In addition, we experimentally tried to synthesize CuZrO 3 based on literature reports and compared computational to experimental X-ray Diffraction (XRD) patterns confirming that the final product is a mixture of CuO and ZrO 2 . Finally, we conducted a computational surface energetics and CO 2 adsorption study on our discovered sandwich morphology, demonstrating that CO 2 can adsorb and activate on the material. However, these CO 2 adsorption results deviate from previously reported results further confirming that the CuZrO 3 is a metastable form and may not be experimentally accessible as a well-mixed oxide, since phase segregation to CuO and ZrO 2 is preferred. Taken together, our combined computational and experimental study provides evidence that the synthesis of CuZrO 3 is extremely difficult and if this oxide exists, it should have a sandwich-like morphology.