Search for: All records

Computational methods have gained importance and popularity in both academia and industry for materials research and development in recent years. Since 2014, our team at University of Illinois at Urbana-Champaign has consistently worked on reforming our Materials Science and Engineering curriculum by incorporating computational modules into all mandatory undergraduate courses. The outbreak of the COVID-19 pandemic disrupted education as on-campus resources and activities became highly restricted. Here we seek to investigate the impact of the university moving online in Spring 2020 and resuming in-person instructions in Fall 2021 on the effectiveness of our computational curricular reform from the students' perspective. We track and compare feedback from students in a representative course MSE 182 for their computational learning experience before, during and after the pandemic lockdown from 2019 to 2021. Besides, we survey all undergraduate students, for their online learning experiences during the pandemic. We find that online learning enhances the students' belief in the importance and benefits of computation in materials science and engineering, while making them less comfortable and confident to acquire skills that are relatively difficult. In addition, early computational learners are likely to experience more difficulties with online learning compared to students at late stages of their undergraduate education, regardless of the computational workload. Multiple reasons are found to limit the students' online computational learning, such as insufficient support from instructors and TAs, limited chances of peer communication and harder access to computational resources. Therefore, it is advised to guarantee more resources to students with novice computational skills regarding such limiting reasons in the future when online learning is applied. 

Organic electronics offer a route toward electronically active biocompatible soft materials capable of interfacing with biological and living systems. One class of promising organic electronic materials are π-conjugated peptides, synthetic molecules comprising an aromatic core flanked by oligopeptides, that can be engineered to self-assemble into elongated nanostructures with emergent optoelectronic functionality. In this work, we combine molecular dynamics simulations with electronic structure and charge transport calculations to computationally screen for high charge mobility π-conjugated peptides and to elucidate design rules linking aromatic core character with charge mobility. We consider within our screening library variations in the aromatic core chemistry and length of the alkyl chains connecting the oligopeptide wings to the core. After completing our computational screen we identify particular π-conjugated peptides capable of producing self-assembled biocompatible nanoaggregates with predicted hole mobilities of 0.224 cm^2/(Vs) and electron mobilities of 0.143 cm^2/(Vs), and uncover design rules that enhance understanding of the molecular determinants of charge mobility within π-conjugated peptide assemblies. 

Over the past years, our team has taken a concerted effort to integrate computational modules into courses across the undergraduate curriculum, in order to equip students with computational skills in a variety of contexts that span the field of Materials Science and Engineering. This effort has proven sustainable during the recent period of online transition of many courses, illustrating one of the benefits of computational modules. The most recent addition to our set of modules included a visualization component that was incorporated into our introductory freshman course for the first time in Fall 2019. Students can perform this module either using local computing labs, access those resources remotely, or can use their own computers. In the Fall of 2020, we modified this module and expanded it towards the utilization of a materials database to teach students how to search for materials with specific properties. The results were then interfaced with the previously existing visualization module to connect the structure and symmetry of materials with their properties and to compare them with experimental results. We implement a more detailed survey to learn to what extent students gained the capability of using databases for future research and education. We will also use these responses to further develop and improve our existing modules. 

Computational methods have become increasingly used in both academia and industry. At the University of Illinois Urbana Champaign, the Department of Materials Science and Engineering (MSE), as part of a university-funded educational innovation program, has integrated computation throughout its undergraduate courses since 2014. Within this curriculum, students are asked to solve practical problems related to their coursework using computational tools in all required courses and some electives. Partly in response to feedback from students, we have expanded our current curriculum to include more computational modules. A computational module was added to the freshman Introduction to Materials Science and Engineering class; thus, students will be expected to use computational tools from their first year onwards. In this paper, we survey students who are currently taking courses with integrated computation to explore the effects of gradually introducing students to programming as well as both macro- and micro-scale simulations over multiple years. We investigate the improving confidence level of students, their attitude towards computational tools, and their satisfaction with our curriculum reform. We also updated our survey to be more detailed and consistent between classes to aid in further improvements of our MSE curriculum. 

A computational approach has become an indispensable tool in materials science research and related industry. At the University of Illinois, Urbana-Champaign, our team at the Department of Materials Science and Engineering (MSE), as part of a Strategic Instructional Initiatives Program (SIIP), has integrated computation into multiple MSE undergraduate courses over the last years. This has established a stable environment for computational education in MSE undergraduate courses through the duration of the program. To date, all MSE students are expected to have multiple experiences of solving practical problems using computational modules before graduation. In addition, computer-based techniques have been integrated into course instruction through iClicker, lecture recording, and online homework and testing. In this paper, we seek to identify the impact of these changes beyond courses participating in the original SIIP project. We continue to keep track of students' perception of the computational curriculum within participating courses. Furthermore, we investigate the influence of the computational exposure on students' perspective in research and during job search. Finally, we collect and analyze feedback from department faculty regarding their experience with teaching techniques involving computation.