A computational framework for rational materials design and development.
The intellectual focus of this RIMSE Summer School is on understanding how nanoscale building blocks can be assembled into functional, tunable materials that operate at the meso- to macroscales. Such materials are broadly relevant to energy, environmental sustainability, and human health problems. Led by Professor Tod Pascal, the course provides training on the computational aspects of the self-assembly problem—students will learn how to deploy high-performance computing to build predictive models that capture the chemical and physical complexities of mesoscale materials and the dynamics of their formation.  Students will be employ a multiscale theoritical framework to solving these problems, combining first-principles electronic structure calculations, atomistic and coarse-grained (CG) models. The structure and dynamics of these system will be explored by means of molecular dynamics (MD) simulations, while Monte-Carlo (MC) simulations will be used to determine the long-term, thermodynamic behavior. Trainees will learn how to: (1) simulate assembly at atomistic, nanoscopic, and mesostructural scales; and (2) how to predict the properties of the resulting structures.

2022 Application Deadlines are closed. Please check back in next year for 2023 program information.

For questions, please contact mrsec@ucsd.edu
UC San Diego MRSEC 2022 RIMSE Summer Schools flyer

2022 Participants

Kianna Black

BIO: Kianna is a student at Francis Parker High School in San Diego (Class of 2024). She is participating in the RIMSE Summer School on Predictive Assembly at UC San Diego.
ORCID: 0000-0001-7026-2637

Diego Contreras Mora

BIO: Diego is an undergraduate student at Texas A&M University (class of 2022) majoring in chemical engineering. Diego’s computational research with plasmonics and experience in the semiconductor industry, has nurtured an interest in exploring the intersection between computational work and fabrication. He is pursuing his interest by participating in the UC San Diego MRSEC REU program and RIMSE summer school on Predictive Assembly. Diego hopes to continue his studies as a doctoral student following his graduation in December.
ORCID: 0000-0002-9077-3650

Michael Dai

BIO: Michael is an incoming sophomore at Folsom High School, participating in the 2022 RIMSE summer school on Predictive Assembly. He has a strong interest in biology and engineering, winning top 20 internationally in the FIRST Innovation Challenge and assisting doctors and patients in the Mercy San Juan hospital. He hopes that his prior experience will come in handy while he studies how to apply the use of computational tools and simulations in order to better understand how self-assembly functions.
ORCID: 0000-0001-8426-0448

Emily Infante

BIO: Emily is an undergraduate B.S. Biochemistry major at UC San Diego. She works with ATLAS Labs on computational chemistry projects under Professor Tod Pascal. Emily is interested in the intersection of fundamental research and chemistry. When not researching, Emily dedicates time to her plants and her work as a lab assistant at the Altman Clinical and Translational Research Institute.
ORCID: 0000-0003-0315-7436

Snigdha Jagarlapudi

BIO: Snigdha is an incoming freshman at UC Berkeley and plans to major in Genetics and Plant Biology with a concentration in bioenergy/biotechnology. In high school, she completed research under Professor Goddard of Caltech investigating the thermodynamic properties of plasticizer additives when they are used in polyvinyl chloride in search of a sustainable alternative. Snigdha hopes to continue to explore the application of computational materials science in the field of energy science and, more broadly, sustainably.
ORCID: 0000-0002-4332-7332

Rishika Kulkarni

BIO: Rishika Kulkarni is a rising junior at Francis Parker High School (Class of 2024). She is extremely passionate about medicine and the applications of nanotechnology, particularly revolving around the neurovascular system and drug delivery. Additionally, she is also interested in physics, chemistry, bioengineering, and neurology. She is excited to further her interests in this field by participating in the 2022 RIMSE summer school on predictive assembly.
ORCID: 0000-0003-1752-660X

Michelle Luces

BIO: Michelle is an undergraduate student at University of Guam pursuing a degree in Chemistry and Mathematics. She is interested in exploring clean energy and sustainability, specifically in energy storage and CO2 conversion. She is excited to pursue her interests this summer by participating in UC San Diego MRSEC 2022 REU program and RIMSE summer school on Predictive Assembly.
ORCID: 0000-0001-5349-9149

Riksean Rosholt

BIO: Riksean is a senior at Scripps Ranch High School and will be participating in the UC San Diego MRSEC 2022 RIMSE Summer School for Predictive Assembly. He is interested in computational driven approaches to self-assembly modeling and predicting the properties of the resulting structures; he is motivated to discover the impact of atomic, nanoscale, and mesoscale materials on health enhancement.
ORCID: 0000-0002-0250-905X

Alejandro Shipley

BIO: Alejandro is currently enrolled in Ladue Horton High School in St. Louis, MO participating in UC San Diego MRSEC's 2022 RIMSE summer school on Predictive Assembly. His favorite subjects are math and chemistry and he is a member of three after school clubs: elements club, best buddies, and lifting club. His hobbies are playing soccer, hockey and golf.
ORCID: 0000-0002-1652-3493

 

James Young

BIO: James is an undergraduate student at UC San Diego (class of 2025), participating in the 2022 RIMSE summer school on Predictive Assembly. He currently majors in Mathematics - Computer Science and was first introduced to the program through Revelle College's honors seminar.
ORCID: 0000-0002-7250-0966